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Sample records for predictive control l-mpc

  1. Deadbeat Predictive Controllers

    NASA Technical Reports Server (NTRS)

    Juang, Jer-Nan; Phan, Minh

    1997-01-01

    Several new computational algorithms are presented to compute the deadbeat predictive control law. The first algorithm makes use of a multi-step-ahead output prediction to compute the control law without explicitly calculating the controllability matrix. The system identification must be performed first and then the predictive control law is designed. The second algorithm uses the input and output data directly to compute the feedback law. It combines the system identification and the predictive control law into one formulation. The third algorithm uses an observable-canonical form realization to design the predictive controller. The relationship between all three algorithms is established through the use of the state-space representation. All algorithms are applicable to multi-input, multi-output systems with disturbance inputs. In addition to the feedback terms, feed forward terms may also be added for disturbance inputs if they are measurable. Although the feedforward terms do not influence the stability of the closed-loop feedback law, they enhance the performance of the controlled system.

  2. Stable predictive control horizons

    NASA Astrophysics Data System (ADS)

    Estrada, Raúl; Favela, Antonio; Raimondi, Angelo; Nevado, Antonio; Requena, Ricardo; Beltrán-Carbajal, Francisco

    2012-04-01

    The stability theory of predictive and adaptive predictive control for processes of linear and stable nature is based on the hypothesis of a physically realisable driving desired trajectory (DDT). The formal theoretical verification of this hypothesis is trivial for processes with a stable inverse, but it is not for processes with an unstable inverse. The extended strategy of predictive control was developed with the purpose of overcoming methodologically this stability problem and it has delivered excellent performance and stability in its industrial applications given a suitable choice of the prediction horizon. From a theoretical point of view, the existence of a prediction horizon capable of ensuring stability for processes with an unstable inverse was proven in the literature. However, no analytical solution has been found for the determination of the prediction horizon values which guarantee stability, in spite of the theoretical and practical interest of this matter. This article presents a new method able to determine the set of prediction horizon values which ensure stability under the extended predictive control strategy formulation and a particular performance criterion for the design of the DDT generically used in many industrial applications. The practical application of this method is illustrated by means of simulation examples.

  3. On identified predictive control

    NASA Technical Reports Server (NTRS)

    Bialasiewicz, Jan T.

    1993-01-01

    Self-tuning control algorithms are potential successors to manually tuned PID controllers traditionally used in process control applications. A very attractive design method for self-tuning controllers, which has been developed over recent years, is the long-range predictive control (LRPC). The success of LRPC is due to its effectiveness with plants of unknown order and dead-time which may be simultaneously nonminimum phase and unstable or have multiple lightly damped poles (as in the case of flexible structures or flexible robot arms). LRPC is a receding horizon strategy and can be, in general terms, summarized as follows. Using assumed long-range (or multi-step) cost function the optimal control law is found in terms of unknown parameters of the predictor model of the process, current input-output sequence, and future reference signal sequence. The common approach is to assume that the input-output process model is known or separately identified and then to find the parameters of the predictor model. Once these are known, the optimal control law determines control signal at the current time t which is applied at the process input and the whole procedure is repeated at the next time instant. Most of the recent research in this field is apparently centered around the LRPC formulation developed by Clarke et al., known as generalized predictive control (GPC). GPC uses ARIMAX/CARIMA model of the process in its input-output formulation. In this paper, the GPC formulation is used but the process predictor model is derived from the state space formulation of the ARIMAX model and is directly identified over the receding horizon, i.e., using current input-output sequence. The underlying technique in the design of identified predictive control (IPC) algorithm is the identification algorithm of observer/Kalman filter Markov parameters developed by Juang et al. at NASA Langley Research Center and successfully applied to identification of flexible structures.

  4. Predictive fuzzy controller for robotic motion control

    SciTech Connect

    Huang, S.J.; Hu, C.F.

    1995-12-31

    A system output prediction strategy incorporated with a fuzzy controller is proposed to manipulate the robotic motion control. Usually, the current position and velocity errors are used to operate the fuzzy logic controller for picking out a corresponding rule. When the system has fast planning speed or time varying behavior, the required tracking accuracy is difficult to achieve by adjusting the fuzzy rules. In order to improve the position control accuracy and system robustness for the industrial application, the current position error in the fuzzy rules look-up table is substituted by the predictive position error of the next step by using the grey predictive algorithm. This idea is implemented on a five degrees of freedom robot. The experimental results show that this fuzzy controller has effectively improve the system performance and achieved the facilitation of fuzzy controller implementation.

  5. Inhibitory Control Predicts Grammatical Ability

    PubMed Central

    Ibbotson, Paul; Kearvell-White, Jennifer

    2015-01-01

    We present evidence that individual variation in grammatical ability can be predicted by individual variation in inhibitory control. We tested 81 5-year-olds using two classic tests from linguistics and psychology (Past Tense and the Stroop). Inhibitory control was a better predicator of grammatical ability than either vocabulary or age. Our explanation is that giving the correct response in both tests requires using a common cognitive capacity to inhibit unwanted competition. The implications are that understanding the developmental trajectory of language acquisition can benefit from integrating the developmental trajectory of non-linguistic faculties, such as executive control. PMID:26659926

  6. Adaptive, predictive controller for optimal process control

    SciTech Connect

    Brown, S.K.; Baum, C.C.; Bowling, P.S.; Buescher, K.L.; Hanagandi, V.M.; Hinde, R.F. Jr.; Jones, R.D.; Parkinson, W.J.

    1995-12-01

    One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from experimental data. Until recently, both methods failed for all but the simplest processes. First principles are almost always incomplete and fitting to experimental data fails for dimensions greater than one as well as for non-linear cases. Several authors have suggested the use of a neural network to fit the experimental data to a multi-dimensional and/or non-linear model. Most networks, however, use simple sigmoid functions and backpropagation for fitting. Training of these networks generally requires large amounts of data and, consequently, very long training times. In 1993 we reported on the tuning and optimization of a negative ion source using a special neural network[2]. One of the properties of this network (CNLSnet), a modified radial basis function network, is that it is able to fit data with few basis functions. Another is that its training is linear resulting in guaranteed convergence and rapid training. We found the training to be rapid enough to support real-time control. This work has been extended to incorporate this network into an MPC using the model built by the network for predictive control. This controller has shown some remarkable capabilities in such non-linear applications as continuous stirred exothermic tank reactors and high-purity fractional distillation columns[3]. The controller is able not only to build an appropriate model from operating data but also to thin the network continuously so that the model adapts to changing plant conditions. The controller is discussed as well as its possible use in various of the difficult control problems that face this community.

  7. Data-Based Predictive Control with Multirate Prediction Step

    NASA Technical Reports Server (NTRS)

    Barlow, Jonathan S.

    2010-01-01

    Data-based predictive control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. One challenge of MPC is computational requirements increasing with prediction horizon length. This paper develops a closed-loop dynamic output feedback controller that minimizes a multi-step-ahead receding-horizon cost function with multirate prediction step. One result is a reduced influence of prediction horizon and the number of system outputs on the computational requirements of the controller. Another result is an emphasis on portions of the prediction window that are sampled more frequently. A third result is the ability to include more outputs in the feedback path than in the cost function.

  8. Broadband Noise Control Using Predictive Techniques

    NASA Technical Reports Server (NTRS)

    Eure, Kenneth W.; Juang, Jer-Nan

    1997-01-01

    Predictive controllers have found applications in a wide range of industrial processes. Two types of such controllers are generalized predictive control and deadbeat control. Recently, deadbeat control has been augmented to include an extended horizon. This modification, named deadbeat predictive control, retains the advantage of guaranteed stability and offers a novel way of control weighting. This paper presents an application of both predictive control techniques to vibration suppression of plate modes. Several system identification routines are presented. Both algorithms are outlined and shown to be useful in the suppression of plate vibrations. Experimental results are given and the algorithms are shown to be applicable to non- minimal phase systems.

  9. Predictive Control of Speededness in Adaptive Testing

    ERIC Educational Resources Information Center

    van der Linden, Wim J.

    2009-01-01

    An adaptive testing method is presented that controls the speededness of a test using predictions of the test takers' response times on the candidate items in the pool. Two different types of predictions are investigated: posterior predictions given the actual response times on the items already administered and posterior predictions that use the…

  10. Generalized Predictive and Neural Generalized Predictive Control of Aerospace Systems

    NASA Technical Reports Server (NTRS)

    Kelkar, Atul G.

    2000-01-01

    The research work presented in this thesis addresses the problem of robust control of uncertain linear and nonlinear systems using Neural network-based Generalized Predictive Control (NGPC) methodology. A brief overview of predictive control and its comparison with Linear Quadratic (LQ) control is given to emphasize advantages and drawbacks of predictive control methods. It is shown that the Generalized Predictive Control (GPC) methodology overcomes the drawbacks associated with traditional LQ control as well as conventional predictive control methods. It is shown that in spite of the model-based nature of GPC it has good robustness properties being special case of receding horizon control. The conditions for choosing tuning parameters for GPC to ensure closed-loop stability are derived. A neural network-based GPC architecture is proposed for the control of linear and nonlinear uncertain systems. A methodology to account for parametric uncertainty in the system is proposed using on-line training capability of multi-layer neural network. Several simulation examples and results from real-time experiments are given to demonstrate the effectiveness of the proposed methodology.

  11. A Robustly Stabilizing Model Predictive Control Algorithm

    NASA Technical Reports Server (NTRS)

    Ackmece, A. Behcet; Carson, John M., III

    2007-01-01

    A model predictive control (MPC) algorithm that differs from prior MPC algorithms has been developed for controlling an uncertain nonlinear system. This algorithm guarantees the resolvability of an associated finite-horizon optimal-control problem in a receding-horizon implementation.

  12. Prediction, Control and the Challenge to Complexity

    ERIC Educational Resources Information Center

    Radford, Mike

    2008-01-01

    The dominant discourse in research, management and teaching is one that may loosely be characterised as that of prediction and control. The objective of research is to identify causal correlations within policy, management, teaching strategies and educational outcomes that are sufficiently robust as to be able to predict outcomes and make…

  13. A Course in... Model Predictive Control.

    ERIC Educational Resources Information Center

    Arkun, Yaman; And Others

    1988-01-01

    Describes a graduate engineering course which specializes in model predictive control. Lists course outline and scope. Discusses some specific topics and teaching methods. Suggests final projects for the students. (MVL)

  14. Model predictive control of constrained LPV systems

    NASA Astrophysics Data System (ADS)

    Yu, Shuyou; Böhm, Christoph; Chen, Hong; Allgöwer, Frank

    2012-06-01

    This article considers robust model predictive control (MPC) schemes for linear parameter varying (LPV) systems in which the time-varying parameter is assumed to be measured online and exploited for feedback. A closed-loop MPC with a parameter-dependent control law is proposed first. The parameter-dependent control law reduces conservativeness of the existing results with a static control law at the cost of higher computational burden. Furthermore, an MPC scheme with prediction horizon '1' is proposed to deal with the case of asymmetric constraints. Both approaches guarantee recursive feasibility and closed-loop stability if the considered optimisation problem is feasible at the initial time instant.

  15. Robust predictive cruise control for commercial vehicles

    NASA Astrophysics Data System (ADS)

    Junell, Jaime; Tumer, Kagan

    2013-10-01

    In this paper we explore learning-based predictive cruise control and the impact of this technology on increasing fuel efficiency for commercial trucks. Traditional cruise control is wasteful when maintaining a constant velocity over rolling hills. Predictive cruise control (PCC) is able to look ahead at future road conditions and solve for a cost-effective course of action. Model- based controllers have been implemented in this field but cannot accommodate many complexities of a dynamic environment which includes changing road and vehicle conditions. In this work, we focus on incorporating a learner into an already successful model- based predictive cruise controller in order to improve its performance. We explore back propagating neural networks to predict future errors then take actions to prevent said errors from occurring. The results show that this approach improves the model based PCC by up to 60% under certain conditions. In addition, we explore the benefits of classifier ensembles to further improve the gains due to intelligent cruise control.

  16. Controlling vibrations of a cutting process using predictive control

    NASA Astrophysics Data System (ADS)

    Fischer, Achim; Eberhard, Peter

    2014-07-01

    Unwanted vibrations in machining are detrimental to the equipment and the quality of the result. Notably chatter vibrations due to the regenerative effect are difficult to control and limit the achievable results. Typically, active and passive means are employed to prevent chatter from happening. This work proposes a predictive control strategy that actively uses information about the system past to predict future disturbances. Using those predicitions allows to counter the regenerative effect more effectively. The strategy is tested in simulation and improves the dynamic stability of the system greatly. It is robust with respect to quantitative errors in the disturbance predictions.

  17. Neural predictive control for active buffet alleviation

    NASA Astrophysics Data System (ADS)

    Pado, Lawrence E.; Lichtenwalner, Peter F.; Liguore, Salvatore L.; Drouin, Donald

    1998-06-01

    The adaptive neural control of aeroelastic response (ANCAR) and the affordable loads and dynamics independent research and development (IRAD) programs at the Boeing Company jointly examined using neural network based active control technology for alleviating undesirable vibration and aeroelastic response in a scale model aircraft vertical tail. The potential benefits of adaptive control includes reducing aeroelastic response associated with buffet and atmospheric turbulence, increasing flutter margins, and reducing response associated with nonlinear phenomenon like limit cycle oscillations. By reducing vibration levels and thus loads, aircraft structures can have lower acquisition cost, reduced maintenance, and extended lifetimes. Wind tunnel tests were undertaken on a rigid 15% scale aircraft in Boeing's mini-speed wind tunnel, which is used for testing at very low air speeds up to 80 mph. The model included a dynamically scaled flexible fail consisting of an aluminum spar with balsa wood cross sections with a hydraulically powered rudder. Neural predictive control was used to actuate the vertical tail rudder in response to strain gauge feedback to alleviate buffeting effects. First mode RMS strain reduction of 50% was achieved. The neural predictive control system was developed and implemented by the Boeing Company to provide an intelligent, adaptive control architecture for smart structures applications with automated synthesis, self-optimization, real-time adaptation, nonlinear control, and fault tolerance capabilities. It is designed to solve complex control problems though a process of automated synthesis, eliminating costly control design and surpassing it in many instances by accounting for real world non-linearities.

  18. Predictive Control of Large Complex Networks

    NASA Astrophysics Data System (ADS)

    Haber, Aleksandar; Motter, Adilson E.

    Networks of coupled dynamical subsystems are increasingly used to represent complex natural and engineered systems. While recent technological developments give us improved means to actively control the dynamics of individual subsystems in various domains, network control remains a challenging problem due to difficulties imposed by intrinsic nonlinearities, control constraints, and the large-scale nature of the systems. In this talk, we will present a model predictive control approach that is effective while accounting for these realistic properties of complex networks. Our method can systematically identify control interventions that steer the trajectory to a desired state, even in the presence of strong nonlinearities and constraints. Numerical tests show that the method is applicable to a variety of networks, ranging from power grids to chemical reaction systems.

  19. Wind farms production: Control and prediction

    NASA Astrophysics Data System (ADS)

    El-Fouly, Tarek Hussein Mostafa

    Wind energy resources, unlike dispatchable central station generation, produce power dependable on external irregular source and that is the incident wind speed which does not always blow when electricity is needed. This results in the variability, unpredictability, and uncertainty of wind resources. Therefore, the integration of wind facilities to utility electrical grid presents a major challenge to power system operator. Such integration has significant impact on the optimum power flow, transmission congestion, power quality issues, system stability, load dispatch, and economic analysis. Due to the irregular nature of wind power production, accurate prediction represents the major challenge to power system operators. Therefore, in this thesis two novel models are proposed for wind speed and wind power prediction. One proposed model is dedicated to short-term prediction (one-hour ahead) and the other involves medium term prediction (one-day ahead). The accuracy of the proposed models is revealed by comparing their results with the corresponding values of a reference prediction model referred to as the persistent model. Utility grid operation is not only impacted by the uncertainty of the future production of wind farms, but also by the variability of their current production and how the active and reactive power exchange with the grid is controlled. To address this particular task, a control technique for wind turbines, driven by doubly-fed induction generators (DFIGs), is developed to regulate the terminal voltage by equally sharing the generated/absorbed reactive power between the rotor-side and the gridside converters. To highlight the impact of the new developed technique in reducing the power loss in the generator set, an economic analysis is carried out. Moreover, a new aggregated model for wind farms is proposed that accounts for the irregularity of the incident wind distribution throughout the farm layout. Specifically, this model includes the wake effect

  20. Real-time Adaptive Control Using Neural Generalized Predictive Control

    NASA Technical Reports Server (NTRS)

    Haley, Pam; Soloway, Don; Gold, Brian

    1999-01-01

    The objective of this paper is to demonstrate the feasibility of a Nonlinear Generalized Predictive Control algorithm by showing real-time adaptive control on a plant with relatively fast time-constants. Generalized Predictive Control has classically been used in process control where linear control laws were formulated for plants with relatively slow time-constants. The plant of interest for this paper is a magnetic levitation device that is nonlinear and open-loop unstable. In this application, the reference model of the plant is a neural network that has an embedded nominal linear model in the network weights. The control based on the linear model provides initial stability at the beginning of network training. In using a neural network the control laws are nonlinear and online adaptation of the model is possible to capture unmodeled or time-varying dynamics. Newton-Raphson is the minimization algorithm. Newton-Raphson requires the calculation of the Hessian, but even with this computational expense the low iteration rate make this a viable algorithm for real-time control.

  1. Optimization approaches to nonlinear model predictive control

    SciTech Connect

    Biegler, L.T. . Dept. of Chemical Engineering); Rawlings, J.B. . Dept. of Chemical Engineering)

    1991-01-01

    With the development of sophisticated methods for nonlinear programming and powerful computer hardware, it now becomes useful and efficient to formulate and solve nonlinear process control problems through on-line optimization methods. This paper explores and reviews control techniques based on repeated solution of nonlinear programming (NLP) problems. Here several advantages present themselves. These include minimization of readily quantifiable objectives, coordinated and accurate handling of process nonlinearities and interactions, and systematic ways of dealing with process constraints. We motivate this NLP-based approach with small nonlinear examples and present a basic algorithm for optimization-based process control. As can be seen this approach is a straightforward extension of popular model-predictive controllers (MPCs) that are used for linear systems. The statement of the basic algorithm raises a number of questions regarding stability and robustness of the method, efficiency of the control calculations, incorporation of feedback into the controller and reliable ways of handling process constraints. Each of these will be treated through analysis and/or modification of the basic algorithm. To highlight and support this discussion, several examples are presented and key results are examined and further developed. 74 refs., 11 figs.

  2. Spacecraft Magnetic Cleanliness Prediction and Control

    NASA Astrophysics Data System (ADS)

    Weikert, S.; Mehlem, K.; Wiegand, A.

    2012-05-01

    The paper describes a sophisticated and realistic control and prediction method for the magnetic cleanliness of spacecraft, covering all phases of a project till the final system test. From the first establishment of the so-called magnetic moment allocation list the necessary boom length can be determined. The list is then continuously updated by real unit test results with the goal to ensure that the magnetic cleanliness budget is not exceeded at a given probability level. A complete example is described. The synthetic spacecraft modeling which predicts only quite late the final magnetic state of the spacecraft is also described. Finally, the most important cleanliness verification, the spacecraft system test, is described shortly with an example. The emphasis of the paper is put on the magnetic dipole moment allocation method.

  3. Constrained predictive control using orthogonal expansions

    SciTech Connect

    Finn, C.K. ); Wahlberg, B. . Dept. of Automatic Control); Ydstie, B.E. . Dept. of Chemical Engineering)

    1993-11-01

    Orthogonal expansion is routinely used for multivariable predictive control and optimization in the chemical and petrochemical manufacturing industries. In this article, the authors approximate bounded operators by orthogonal expansion. The rate of convergence depends on the choice of basis functions. Markov-Laguerre functions give rapid convergence for open-loop stable systems with long delay. The Markov-Kautz model can be used for lightly damped systems, and a more general orthogonal expansion is developed for modeling multivariable systems with widely scattered poles. The finite impulse response model is a special case of these models. A-priori knowledge about dominant time constants, time delay and oscillatory modes is used to reduce the model complexity and to improve conditioning of the parameter estimation algorithm. Algorithms for predictive control are developed, as well as conditions for constraint compatibility, closed-loop stability and constraint satisfaction for the ideal case. An H[infinity]--like design technique proposed guarantees robust stability in the presence of input constraints; output constraints may give chatter. A chatter-free algorithm is proposed.

  4. Optimal Control of Distributed Energy Resources using Model Predictive Control

    SciTech Connect

    Mayhorn, Ebony T.; Kalsi, Karanjit; Elizondo, Marcelo A.; Zhang, Wei; Lu, Shuai; Samaan, Nader A.; Butler-Purry, Karen

    2012-07-22

    In an isolated power system (rural microgrid), Distributed Energy Resources (DERs) such as renewable energy resources (wind, solar), energy storage and demand response can be used to complement fossil fueled generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation. The problem is formulated as a multi-objective optimization problem with the goals of minimizing fuel costs and changes in power output of diesel generators, minimizing costs associated with low battery life of energy storage and maintaining system frequency at the nominal operating value. Two control modes are considered for controlling the energy storage to compensate either net load variability or wind variability. Model predictive control (MPC) is used to solve the aforementioned problem and the performance is compared to an open-loop look-ahead dispatch problem. Simulation studies using high and low wind profiles, as well as, different MPC prediction horizons demonstrate the efficacy of the closed-loop MPC in compensating for uncertainties in wind and demand.

  5. Cascade generalized predictive control strategy for boiler drum level.

    PubMed

    Xu, Min; Li, Shaoyuan; Cai, Wenjian

    2005-07-01

    This paper proposes a cascade model predictive control scheme for boiler drum level control. By employing generalized predictive control structures for both inner and outer loops, measured and unmeasured disturbances can be effectively rejected, and drum level at constant load is maintained. In addition, nonminimum phase characteristic and system constraints in both loops can be handled effectively by generalized predictive control algorithms. Simulation results are provided to show that cascade generalized predictive control results in better performance than that of well tuned cascade proportional integral differential controllers. The algorithm has also been implemented to control a 75-MW boiler plant, and the results show an improvement over conventional control schemes. PMID:16082788

  6. Nonconvex model predictive control for commercial refrigeration

    NASA Astrophysics Data System (ADS)

    Gybel Hovgaard, Tobias; Boyd, Stephen; Larsen, Lars F. S.; Bagterp Jørgensen, John

    2013-08-01

    We consider the control of a commercial multi-zone refrigeration system, consisting of several cooling units that share a common compressor, and is used to cool multiple areas or rooms. In each time period we choose cooling capacity to each unit and a common evaporation temperature. The goal is to minimise the total energy cost, using real-time electricity prices, while obeying temperature constraints on the zones. We propose a variation on model predictive control to achieve this goal. When the right variables are used, the dynamics of the system are linear, and the constraints are convex. The cost function, however, is nonconvex due to the temperature dependence of thermodynamic efficiency. To handle this nonconvexity we propose a sequential convex optimisation method, which typically converges in fewer than 5 or so iterations. We employ a fast convex quadratic programming solver to carry out the iterations, which is more than fast enough to run in real time. We demonstrate our method on a realistic model, with a full year simulation and 15-minute time periods, using historical electricity prices and weather data, as well as random variations in thermal load. These simulations show substantial cost savings, on the order of 30%, compared to a standard thermostat-based control system. Perhaps more important, we see that the method exhibits sophisticated response to real-time variations in electricity prices. This demand response is critical to help balance real-time uncertainties in generation capacity associated with large penetration of intermittent renewable energy sources in a future smart grid.

  7. Predicting Loss-of-Control Boundaries Toward a Piloting Aid

    NASA Technical Reports Server (NTRS)

    Barlow, Jonathan; Stepanyan, Vahram; Krishnakumar, Kalmanje

    2012-01-01

    This work presents an approach to predicting loss-of-control with the goal of providing the pilot a decision aid focused on maintaining the pilot's control action within predicted loss-of-control boundaries. The predictive architecture combines quantitative loss-of-control boundaries, a data-based predictive control boundary estimation algorithm and an adaptive prediction method to estimate Markov model parameters in real-time. The data-based loss-of-control boundary estimation algorithm estimates the boundary of a safe set of control inputs that will keep the aircraft within the loss-of-control boundaries for a specified time horizon. The adaptive prediction model generates estimates of the system Markov Parameters, which are used by the data-based loss-of-control boundary estimation algorithm. The combined algorithm is applied to a nonlinear generic transport aircraft to illustrate the features of the architecture.

  8. Experimental results of a predictive neural network HVAC controller

    SciTech Connect

    Jeannette, E.; Assawamartbunlue, K.; Kreider, J.F.; Curtiss, P.S.

    1998-12-31

    Proportional, integral, and derivative (PID) control is widely used in many HVAC control processes and requires constant attention for optimal control. Artificial neural networks offer the potential for improved control of processes through predictive techniques. This paper introduces and shows experimental results of a predictive neural network (PNN) controller applied to an unstable hot water system in an air-handling unit. Actual laboratory testing of the PNN and PID controllers show favorable results for the PNN controller.

  9. Precise flight-path control using a predictive algorithm

    NASA Technical Reports Server (NTRS)

    Hess, R. A.; Jung, Y. C.

    1991-01-01

    Generalized predictive control describes an algorithm for the control of dynamic systems in which a control input is generated that minimizes a quadratic cost function consisting of a weighted sum of errors between desired and predicted future system output and future predicted control increments. The output predictions are obtained from an internal model of the plant dynamics. A design technique is discussed for applying the single-input/single-output generalized predictive control algorithm to a problem of longitudinal/vertical terrain-following flight of a rotorcraft. By using the generalized predictive control technique to provide inputs to a classically designed stability and control augmentation system, it is demonstrated that a robust flight-path control system can be created that exhibits excellent tracking performance.

  10. Predictive and Neural Predictive Control of Uncertain Systems

    NASA Technical Reports Server (NTRS)

    Kelkar, Atul G.

    2000-01-01

    Accomplishments and future work are:(1) Stability analysis: the work completed includes characterization of stability of receding horizon-based MPC in the setting of LQ paradigm. The current work-in-progress includes analyzing local as well as global stability of the closed-loop system under various nonlinearities; for example, actuator nonlinearities; sensor nonlinearities, and other plant nonlinearities. Actuator nonlinearities include three major types of nonlineaxities: saturation, dead-zone, and (0, 00) sector. (2) Robustness analysis: It is shown that receding horizon parameters such as input and output horizon lengths have direct effect on the robustness of the system. (3) Code development: A matlab code has been developed which can simulate various MPC formulations. The current effort is to generalize the code to include ability to handle all plant types and all MPC types. (4) Improved predictor: It is shown that MPC design using better predictors that can minimize prediction errors. It is shown analytically and numerically that Smith predictor can provide closed-loop stability under GPC operation for plants with dead times where standard optimal predictor fails. (5) Neural network predictors: When neural network is used as predictor it can be shown that neural network predicts the plant output within some finite error bound under certain conditions. Our preliminary study shows that with proper choice of update laws and network architectures such bound can be obtained. However, much work needs to be done to obtain a similar result in general case.

  11. Predictive Direct Torque Control for Induction Motor Drive

    NASA Astrophysics Data System (ADS)

    Benzaioua, A.; Ouhrouche, M.; Merabet, A.

    2008-06-01

    A predictive control combined with the direct torque control (DTC) to induction motor drive is presented. A new switching strategy is used in DTC, where the constant switching frequency is taken constant, and the speed tracking is done by a predictive controller. The scheme control is applied to induction motor drive in order to perform the dynamic responses of electromagnetic torque, stator flux and speed. A comparison between the PI controller and predictive controller for speed tracking is done. Results of simulation show that the performance of the proposed control scheme for induction motor drive is accurately achieved.

  12. Voltage control in pulsed system by predict-ahead control

    DOEpatents

    Payne, Anthony N.; Watson, James A.; Sampayan, Stephen E.

    1994-01-01

    A method and apparatus for predict-ahead pulse-to-pulse voltage control in a pulsed power supply system is disclosed. A DC power supply network is coupled to a resonant charging network via a first switch. The resonant charging network is coupled at a node to a storage capacitor. An output load is coupled to the storage capacitor via a second switch. A de-Q-ing network is coupled to the resonant charging network via a third switch. The trigger for the third switch is a derived function of the initial voltage of the power supply network, the initial voltage of the storage capacitor, and the present voltage of the storage capacitor. A first trigger closes the first switch and charges the capacitor. The third trigger is asserted according to the derived function to close the third switch. When the third switch is closed, the first switch opens and voltage on the node is regulated. The second trigger may be thereafter asserted to discharge the capacitor into the output load.

  13. Voltage control in pulsed system by predict-ahead control

    DOEpatents

    Payne, A.N.; Watson, J.A.; Sampayan, S.E.

    1994-09-13

    A method and apparatus for predict-ahead pulse-to-pulse voltage control in a pulsed power supply system is disclosed. A DC power supply network is coupled to a resonant charging network via a first switch. The resonant charging network is coupled at a node to a storage capacitor. An output load is coupled to the storage capacitor via a second switch. A de-Q-ing network is coupled to the resonant charging network via a third switch. The trigger for the third switch is a derived function of the initial voltage of the power supply network, the initial voltage of the storage capacitor, and the present voltage of the storage capacitor. A first trigger closes the first switch and charges the capacitor. The third trigger is asserted according to the derived function to close the third switch. When the third switch is closed, the first switch opens and voltage on the node is regulated. The second trigger may be thereafter asserted to discharge the capacitor into the output load. 4 figs.

  14. Comparison of Predictive Control Methods for High Consumption Industrial Furnace

    PubMed Central

    2013-01-01

    We describe several predictive control approaches for high consumption industrial furnace control. These furnaces are major consumers in production industries, and reducing their fuel consumption and optimizing the quality of the products is one of the most important engineer tasks. In order to demonstrate the benefits from implementation of the advanced predictive control algorithms, we have compared several major criteria for furnace control. On the basis of the analysis, some important conclusions have been drawn. PMID:24319354

  15. Multiplexed Predictive Control of a Large Commercial Turbofan Engine

    NASA Technical Reports Server (NTRS)

    Richter, hanz; Singaraju, Anil; Litt, Jonathan S.

    2008-01-01

    Model predictive control is a strategy well-suited to handle the highly complex, nonlinear, uncertain, and constrained dynamics involved in aircraft engine control problems. However, it has thus far been infeasible to implement model predictive control in engine control applications, because of the combination of model complexity and the time allotted for the control update calculation. In this paper, a multiplexed implementation is proposed that dramatically reduces the computational burden of the quadratic programming optimization that must be solved online as part of the model-predictive-control algorithm. Actuator updates are calculated sequentially and cyclically in a multiplexed implementation, as opposed to the simultaneous optimization taking place in conventional model predictive control. Theoretical aspects are discussed based on a nominal model, and actual computational savings are demonstrated using a realistic commercial engine model.

  16. Robot trajectory tracking with self-tuning predicted control

    NASA Technical Reports Server (NTRS)

    Cui, Xianzhong; Shin, Kang G.

    1988-01-01

    A controller that combines self-tuning prediction and control is proposed for robot trajectory tracking. The controller has two feedback loops: one is used to minimize the prediction error, and the other is designed to make the system output track the set point input. Because the velocity and position along the desired trajectory are given and the future output of the system is predictable, a feedforward loop can be designed for robot trajectory tracking with self-tuning predicted control (STPC). Parameters are estimated online to account for the model uncertainty and the time-varying property of the system. The authors describe the principle of STPC, analyze the system performance, and discuss the simplification of the robot dynamic equations. To demonstrate its utility and power, the controller is simulated for a Stanford arm.

  17. Pilots Rate Augmented Generalized Predictive Control for Reconfiguration

    NASA Technical Reports Server (NTRS)

    Soloway, Don; Haley, Pam

    2004-01-01

    The objective of this paper is to report the results from the research being conducted in reconfigurable fight controls at NASA Ames. A study was conducted with three NASA Dryden test pilots to evaluate two approaches of reconfiguring an aircraft's control system when failures occur in the control surfaces and engine. NASA Ames is investigating both a Neural Generalized Predictive Control scheme and a Neural Network based Dynamic Inverse controller. This paper highlights the Predictive Control scheme where a simple augmentation to reduce zero steady-state error led to the neural network predictor model becoming redundant for the task. Instead of using a neural network predictor model, a nominal single point linear model was used and then augmented with an error corrector. This paper shows that the Generalized Predictive Controller and the Dynamic Inverse Neural Network controller perform equally well at reconfiguration, but with less rate requirements from the actuators. Also presented are the pilot ratings for each controller for various failure scenarios and two samples of the required control actuation during reconfiguration. Finally, the paper concludes by stepping through the Generalized Predictive Control's reconfiguration process for an elevator failure.

  18. Rate-Based Model Predictive Control of Turbofan Engine Clearance

    NASA Technical Reports Server (NTRS)

    DeCastro, Jonathan A.

    2006-01-01

    An innovative model predictive control strategy is developed for control of nonlinear aircraft propulsion systems and sub-systems. At the heart of the controller is a rate-based linear parameter-varying model that propagates the state derivatives across the prediction horizon, extending prediction fidelity to transient regimes where conventional models begin to lose validity. The new control law is applied to a demanding active clearance control application, where the objectives are to tightly regulate blade tip clearances and also anticipate and avoid detrimental blade-shroud rub occurrences by optimally maintaining a predefined minimum clearance. Simulation results verify that the rate-based controller is capable of satisfying the objectives during realistic flight scenarios where both a conventional Jacobian-based model predictive control law and an unconstrained linear-quadratic optimal controller are incapable of doing so. The controller is evaluated using a variety of different actuators, illustrating the efficacy and versatility of the control approach. It is concluded that the new strategy has promise for this and other nonlinear aerospace applications that place high importance on the attainment of control objectives during transient regimes.

  19. Towards feasible and effective predictive wavefront control for adaptive optics

    SciTech Connect

    Poyneer, L A; Veran, J

    2008-06-04

    We have recently proposed Predictive Fourier Control, a computationally efficient and adaptive algorithm for predictive wavefront control that assumes frozen flow turbulence. We summarize refinements to the state-space model that allow operation with arbitrary computational delays and reduce the computational cost of solving for new control. We present initial atmospheric characterization using observations with Gemini North's Altair AO system. These observations, taken over 1 year, indicate that frozen flow is exists, contains substantial power, and is strongly detected 94% of the time.

  20. Predictive neuro-fuzzy controller for multilink robot manipulator

    NASA Astrophysics Data System (ADS)

    Kaymaz, Emre; Mitra, Sunanda

    1995-10-01

    A generalized controller based on fuzzy clustering and fuzzy generalized predictive control has been developed for nonlinear systems including multilink robot manipulators. The proposed controller is particularly useful when the dynamics of the nonlinear system to be controlled are difficult to yield exact solutions and the system specification can be obtained in terms of crisp input-output pairs. It inherits the advantages of both fuzzy logic and predictive control. The identification of the nonlinear mapping of the system to be controlled is realized by a three- layer feed-forward neural network model employing the input-output data obtained from the system. The speed of convergence of the neural network is improved by the introduction of a fuzzy logic controlled backpropagation learning algorithm. The neural network model is then used as a simulation tool to generate the input-output data for developing the predictive fuzzy logic controller for the chosen nonlinear system. The use of fuzzy clustering facilitates automatic generation of membership relations of the input-output data. Unlike the linguistic fuzzy logic controller which requires approximate knowledge of the shape and the numbers of the membership functions in the input and output universes of the discourse, this integrated neuro-fuzzy approach allows one to find the fuzzy relations and the membership functions more accurately. Furthermore, it is not necessary to tune the controller. For a two-link robot manipulator, the performance of this predictive fuzzy controller is shown to be superior to that of a conventional controller employing an ARMA model of the system in terms of accuracy and consumption of energy.

  1. Optimized continuous pharmaceutical manufacturing via model-predictive control.

    PubMed

    Rehrl, Jakob; Kruisz, Julia; Sacher, Stephan; Khinast, Johannes; Horn, Martin

    2016-08-20

    This paper demonstrates the application of model-predictive control to a feeding blending unit used in continuous pharmaceutical manufacturing. The goal of this contribution is, on the one hand, to highlight the advantages of the proposed concept compared to conventional PI-controllers, and, on the other hand, to present a step-by-step guide for controller synthesis. The derivation of the required mathematical plant model is given in detail and all the steps required to develop a model-predictive controller are shown. Compared to conventional concepts, the proposed approach allows to conveniently consider constraints (e.g. mass hold-up in the blender) and offers a straightforward, easy to tune controller setup. The concept is implemented in a simulation environment. In order to realize it on a real system, additional aspects (e.g., state estimation, measurement equipment) will have to be investigated. PMID:27317987

  2. Model predictive torque control with an extended prediction horizon for electrical drive systems

    NASA Astrophysics Data System (ADS)

    Wang, Fengxiang; Zhang, Zhenbin; Kennel, Ralph; Rodríguez, José

    2015-07-01

    This paper presents a model predictive torque control method for electrical drive systems. A two-step prediction horizon is achieved by considering the reduction of the torque ripples. The electromagnetic torque and the stator flux error between predicted values and the references, and an over-current protection are considered in the cost function design. The best voltage vector is selected by minimising the value of the cost function, which aims to achieve a low torque ripple in two intervals. The study is carried out experimentally. The results show that the proposed method achieves good performance in both steady and transient states.

  3. Predictive Feedback and Feedforward Control for Systems with Unknown Disturbances

    NASA Technical Reports Server (NTRS)

    Juang, Jer-Nan; Eure, Kenneth W.

    1998-01-01

    Predictive feedback control has been successfully used in the regulation of plate vibrations when no reference signal is available for feedforward control. However, if a reference signal is available it may be used to enhance regulation by incorporating a feedforward path in the feedback controller. Such a controller is known as a hybrid controller. This paper presents the theory and implementation of the hybrid controller for general linear systems, in particular for structural vibration induced by acoustic noise. The generalized predictive control is extended to include a feedforward path in the multi-input multi-output case and implemented on a single-input single-output test plant to achieve plate vibration regulation. There are cases in acoustic-induce vibration where the disturbance signal is not available to be used by the hybrid controller, but a disturbance model is available. In this case the disturbance model may be used in the feedback controller to enhance performance. In practice, however, neither the disturbance signal nor the disturbance model is available. This paper presents the theory of identifying and incorporating the noise model into the feedback controller. Implementations are performed on a test plant and regulation improvements over the case where no noise model is used are demonstrated.

  4. Self-Control Assessments and Implications for Predicting Adolescent Offending.

    PubMed

    Fine, Adam; Steinberg, Laurence; Frick, Paul J; Cauffman, Elizabeth

    2016-04-01

    Although low self-control is consistently related to adolescent offending, it is unknown whether self-report measures or laboratory behavior tasks yield better predictive utility, or if a combination yields incremental predictive power. This is particularly important because developmental theory indicates that self-control is related to adolescent offending and, consequently, risk assessments rely on self-control measures. The present study (a) examines relationships between self-reported self-control on the Weinberger Adjustment Inventory with Go/No-Go response inhibition, and (b) compares the predictive utility of both assessment strategies for short- and long-term adolescent reoffending. It uses longitudinal data from the Crossroads Study of male, first-time adolescent offenders ages 13-17 (N = 930; 46 % Hispanic/Latino, 37 % Black/African-American, 15 % non-Hispanic White, 2 % other race). The results of the study indicate that the measures are largely unrelated, and that the self-report measure is a better indicator of both short- and long-term reoffending. The laboratory task measure does not add value to what is already predicted by the self-report measure. Implications for assessing self-control during adolescence and consequences of assessment strategy are discussed. PMID:26792266

  5. Predicted torque equilibrium attitude utilization for Space Station attitude control

    NASA Technical Reports Server (NTRS)

    Kumar, Renjith R.; Heck, Michael L.; Robertson, Brent P.

    1990-01-01

    An approximate knowledge of the torque equilibrium attitude (TEA) is shown to improve the performance of a control moment gyroscope (CMG) momentum management/attitude control law for Space Station Freedom. The linearized equations of motion are used in conjunction with a state transformation to obtain a control law which uses full state feedback and the predicted TEA to minimize both attitude excursions and CMG peak and secular momentum. The TEA can be computationally determined either by observing the steady state attitude of a 'controlled' spacecraft using arbitrary initial attitude, or by simulating a fixed attitude spacecraft flying in desired orbit subject to realistic environmental disturbance models.

  6. Predicting psychological symptoms: the role of perceived thought control ability.

    PubMed

    Peterson, Rachel D; Klein, Jenny; Donnelly, Reesa; Renk, Kimberly

    2009-01-01

    The suppression of intrusive thoughts, which have been related significantly to depressive and anxious symptoms (Blumberg, 2000), has become an area of interest for those treating individuals with psychological disorders. The current study sought to extend the findings of Luciano, Algarabel, Tomas, and Martínez (2005), who developed the Thought Control Ability Questionnaire (TCAQ) and found that scores on this measure were predictive of psychopathology. In particular, this study examined the relationship between scores on the TCAQ and the Personality Assessment Inventory. Findings suggested that individuals' perceived thought control ability correlated significantly with several dimensions of commonly-occurring psychological symptoms (e.g. anxiety) and more severe and persistent psychological symptoms (e.g. schizophrenia). Regression analyses also showed that perceived thought control ability predicted significantly a range of psychological symptoms over and above individuals' sex and perceived stress. Findings suggested that thought control ability may be an important future research area in psychological assessment and intervention. PMID:19235599

  7. Neural Generalized Predictive Control: A Newton-Raphson Implementation

    NASA Technical Reports Server (NTRS)

    Soloway, Donald; Haley, Pamela J.

    1997-01-01

    An efficient implementation of Generalized Predictive Control using a multi-layer feedforward neural network as the plant's nonlinear model is presented. In using Newton-Raphson as the optimization algorithm, the number of iterations needed for convergence is significantly reduced from other techniques. The main cost of the Newton-Raphson algorithm is in the calculation of the Hessian, but even with this overhead the low iteration numbers make Newton-Raphson faster than other techniques and a viable algorithm for real-time control. This paper presents a detailed derivation of the Neural Generalized Predictive Control algorithm with Newton-Raphson as the minimization algorithm. Simulation results show convergence to a good solution within two iterations and timing data show that real-time control is possible. Comments about the algorithm's implementation are also included.

  8. Stabilisation of difference equations with noisy prediction-based control

    NASA Astrophysics Data System (ADS)

    Braverman, E.; Kelly, C.; Rodkina, A.

    2016-07-01

    We consider the influence of stochastic perturbations on stability of a unique positive equilibrium of a difference equation subject to prediction-based control. These perturbations may be multiplicative We begin by relaxing the control parameter in the deterministic equation, and deriving a range of values for the parameter over which all solutions eventually enter an invariant interval. Then, by allowing the variation to be stochastic, we derive sufficient conditions (less restrictive than known ones for the unperturbed equation) under which the positive equilibrium will be globally a.s. asymptotically stable: i.e. the presence of noise improves the known effectiveness of prediction-based control. Finally, we show that systemic noise has a "blurring" effect on the positive equilibrium, which can be made arbitrarily small by controlling the noise intensity. Numerical examples illustrate our results.

  9. Fuzzy Predictive Control Strategy in the Application of the Industrial Furnace Temperature Control

    NASA Astrophysics Data System (ADS)

    Dai, Luping; Chen, Xingliang; Chen, Liu; Liu, Xia

    Ceramic kiln with large heat capacity, big lag and nonlinear characteristic, this paper proposes a combining fuzzy control and predictive control of the control algorithm, to enhance the tracking and anti-interference ability of the algorithm. The simulation results show, this method compared with the control of PID has the high steady precision and dynamic characteristic.

  10. Predicting worsening asthma control following the common cold

    PubMed Central

    Walter, Michael J.; Castro, Mario; Kunselman, Susan J.; Chinchilli, Vernon M; Reno, Melissa; Ramkumar, Thiruvamoor P.; Avila, Pedro C.; Boushey, Homer A.; Ameredes, Bill T.; Bleecker, Eugene R.; Calhoun, William J.; Cherniack, Reuben M.; Craig, Timothy J.; Denlinger, Loren C.; Israel, Elliot; Fahy, John V.; Jarjour, Nizar N.; Kraft, Monica; Lazarus, Stephen C.; Lemanske, Robert F.; Martin, Richard J.; Peters, Stephen P.; Ramsdell, Joe W.; Sorkness, Christine A.; Rand Sutherland, E.; Szefler, Stanley J.; Wasserman, Stephen I.; Wechsler, Michael E.

    2008-01-01

    The asthmatic response to the common cold is highly variable and early characteristics that predict worsening of asthma control following a cold have not been identified. In this prospective multi-center cohort study of 413 adult subjects with asthma, we used the mini-Asthma Control Questionnaire (mini-ACQ) to quantify changes in asthma control and the Wisconsin Upper Respiratory Symptom Survey-21 (WURSS-21) to measure cold severity. Univariate and multivariable models examined demographic, physiologic, serologic, and cold-related characteristics for their relationship to changes in asthma control following a cold. We observed a clinically significant worsening of asthma control following a cold (increase in mini-ACQ of 0.69 ± 0.93). Univariate analysis demonstrated season, center location, cold length, and cold severity measurements all associated with a change in asthma control. Multivariable analysis of the covariates available within the first 2 days of cold onset revealed the day 2 and the cumulative sum of the day 1 and 2 WURSS-21 scores were significant predictors for the subsequent changes in asthma control. In asthmatic subjects the cold severity measured within the first 2 days can be used to predict subsequent changes in asthma control. This information may help clinicians prevent deterioration in asthma control following a cold. PMID:18768579

  11. Prediction of active control of subsonic centrifugal compressor rotating stall

    NASA Technical Reports Server (NTRS)

    Lawless, Patrick B.; Fleeter, Sanford

    1993-01-01

    A mathematical model is developed to predict the suppression of rotating stall in a centrifugal compressor with a vaned diffuser. This model is based on the employment of a control vortical waveform generated upstream of the impeller inlet to damp weak potential disturbances that are the early stages of rotating stall. The control system is analyzed by matching the perturbation pressure in the compressor inlet and exit flow fields with a model for the unsteady behavior of the compressor. The model was effective at predicting the stalling behavior of the Purdue Low Speed Centrifugal Compressor for two distinctly different stall patterns. Predictions made for the effect of a controlled inlet vorticity wave on the stability of the compressor show that for minimum control wave magnitudes, on the order of the total inlet disturbance magnitude, significant damping of the instability can be achieved. For control waves of sufficient amplitude, the control phase angle appears to be the most important factor in maintaining a stable condition in the compressor.

  12. The predictive protective control of the heat exchanger

    NASA Astrophysics Data System (ADS)

    Nevriva, Pavel; Filipova, Blanka; Vilimec, Ladislav

    2016-06-01

    The paper deals with the predictive control applied to flexible cogeneration energy system FES. FES was designed and developed by the VITKOVICE POWER ENGINEERING joint-stock company and represents a new solution of decentralized cogeneration energy sources. In FES, the heating medium is flue gas generated by combustion of a solid fuel. The heated medium is power gas, which is a gas mixture of air and water steam. Power gas is superheated in the main heat exchanger and led to gas turbines. To protect the main heat exchanger against damage by overheating, the novel predictive protective control based on the mathematical model of exchanger was developed. The paper describes the principle, the design and the simulation of the predictive protective method applied to main heat exchanger of FES.

  13. Model-predictive control of polymer composite manufacturing processes

    NASA Astrophysics Data System (ADS)

    Voorakaranam, Srikanth

    Quality control is crucial for reducing costs and enabling a more widespread use of fiber-resin composites. This research focuses on development of model-based control strategies for controlling product quality in continuous processes for manufacturing polymer composites with injected pultrusion as a prototype. The control objective is to maximize production rates, meeting quality criteria such as eliminating voids, achieving desired degree of cure and preventing backflow of resin from the die entrance. A 2-D mathematical model of IP developed by Kommu is extended to incorporate die dynamics. Exercising the model over a range of operating conditions, the requirements for a control system are formulated. Simultaneous requirements of optimization and control are met by using a cascade strategy consisting of supervisory and regulatory layers. The supervisory layer consists of an optimizer in conjunction with a steady-state cure model and an injection pressure model. The cure model is linear in important process variables. The injection pressure model is also linear in pullspeed. A linear program generates setpoints for pullspeed, injection pressure and temperatures in the three zones of the die which are implemented by the regulatory layer using multiple PID controllers. This formulation operates the process optimally. A major problem in feedback control of the IP process is the inability to measure quality variables on-line. An inferential control strategy is proposed to tackle this. It is then extended so that it can be implemented in a model predictive control formulation. This novel strategy called model predictive inferential control is general enough to accommodate multiple secondary measurements as well as nonlinear estimators and controllers. Collinearity among multiple measurements is addressed through principal component regression. The estimator uses frequent secondary measurements to estimate the effect of the disturbances on the primary variable which are

  14. Adaptive model predictive process control using neural networks

    DOEpatents

    Buescher, K.L.; Baum, C.C.; Jones, R.D.

    1997-08-19

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data. 46 figs.

  15. Adaptive model predictive process control using neural networks

    DOEpatents

    Buescher, Kevin L.; Baum, Christopher C.; Jones, Roger D.

    1997-01-01

    A control system for controlling the output of at least one plant process output parameter is implemented by adaptive model predictive control using a neural network. An improved method and apparatus provides for sampling plant output and control input at a first sampling rate to provide control inputs at the fast rate. The MPC system is, however, provided with a network state vector that is constructed at a second, slower rate so that the input control values used by the MPC system are averaged over a gapped time period. Another improvement is a provision for on-line training that may include difference training, curvature training, and basis center adjustment to maintain the weights and basis centers of the neural in an updated state that can follow changes in the plant operation apart from initial off-line training data.

  16. Implementation of model predictive control on a hydrothermal oxidation reactor

    SciTech Connect

    Muske, K.R.; Dell`Orco, P.C.; Le, L.A.; Flesner, R.L.

    1998-12-31

    This paper describes the model-based control algorithm developed for a hydrothermal oxidation reactor at the Pantex Department of Energy facility in Amarillo, Texas. The combination of base hydrolysis and hydrothermal oxidation is used for the disposal of PBX 9404 high explosive at Pantex. The reactor oxidizes the organic compounds in the hydrolysate solutions obtained from the base hydrolysis process. The objective of the model predictive controller is to minimize the total aqueous nitrogen compounds in the effluent of the reactor. The controller also maintains a desired excess oxygen concentration in the reactor effluent to ensure the complete destruction of the organic carbon compounds in the hydrolysate.

  17. Motivation to control prejudice predicts categorization of multiracials.

    PubMed

    Chen, Jacqueline M; Moons, Wesley G; Gaither, Sarah E; Hamilton, David L; Sherman, Jeffrey W

    2014-05-01

    Multiracial individuals often do not easily fit into existing racial categories. Perceivers may adopt a novel racial category to categorize multiracial targets, but their willingness to do so may depend on their motivations. We investigated whether perceivers' levels of internal motivation to control prejudice (IMS) and external motivation to control prejudice (EMS) predicted their likelihood of categorizing Black-White multiracial faces as Multiracial. Across four studies, IMS positively predicted perceivers' categorizations of multiracial faces as Multiracial. The association between IMS and Multiracial categorizations was strongest when faces were most racially ambiguous. Explicit prejudice, implicit prejudice, and interracial contact were ruled out as explanations for the relationship between IMS and Multiracial categorizations. EMS may be negatively associated with the use of the Multiracial category. Therefore, perceivers' motivations to control prejudice have important implications for racial categorization processes. PMID:24458216

  18. Nonlinear Dynamic Inversion Baseline Control Law: Architecture and Performance Predictions

    NASA Technical Reports Server (NTRS)

    Miller, Christopher J.

    2011-01-01

    A model reference dynamic inversion control law has been developed to provide a baseline control law for research into adaptive elements and other advanced flight control law components. This controller has been implemented and tested in a hardware-in-the-loop simulation; the simulation results show excellent handling qualities throughout the limited flight envelope. A simple angular momentum formulation was chosen because it can be included in the stability proofs for many basic adaptive theories, such as model reference adaptive control. Many design choices and implementation details reflect the requirements placed on the system by the nonlinear flight environment and the desire to keep the system as basic as possible to simplify the addition of the adaptive elements. Those design choices are explained, along with their predicted impact on the handling qualities.

  19. Decentralized robust nonlinear model predictive controller for unmanned aerial systems

    NASA Astrophysics Data System (ADS)

    Garcia Garreton, Gonzalo A.

    The nonlinear and unsteady nature of aircraft aerodynamics together with limited practical range of controls and state variables make the use of the linear control theory inadequate especially in the presence of external disturbances, such as wind. In the classical approach, aircraft are controlled by multiple inner and outer loops, designed separately and sequentially. For unmanned aerial systems in particular, control technology must evolve to a point where autonomy is extended to the entire mission flight envelope. This requires advanced controllers that have sufficient robustness, track complex trajectories, and use all the vehicles control capabilities at higher levels of accuracy. In this work, a robust nonlinear model predictive controller is designed to command and control an unmanned aerial system to track complex tight trajectories in the presence of internal and external perturbance. The Flight System developed in this work achieves the above performance by using: 1. A nonlinear guidance algorithm that enables the vehicle to follow an arbitrary trajectory shaped by moving points; 2. A formulation that embeds the guidance logic and trajectory information in the aircraft model, avoiding cross coupling and control degradation; 3. An artificial neural network, designed to adaptively estimate and provide aerodynamic and propulsive forces in real-time; and 4. A mixed sensitivity approach that enhances the robustness for a nonlinear model predictive controller overcoming the effect of un-modeled dynamics, external disturbances such as wind, and measurement additive perturbations, such as noise and biases. These elements have been integrated and tested in simulation and with previously stored flight test data and shown to be feasible.

  20. Model Predictive Control of Integrated Gasification Combined Cycle Power Plants

    SciTech Connect

    B. Wayne Bequette; Priyadarshi Mahapatra

    2010-08-31

    The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.

  1. Predictive onboard flow control for packet switching satellites

    NASA Technical Reports Server (NTRS)

    Bobinsky, Eric A.

    1992-01-01

    We outline two alternate approaches to predicting the onset of congestion in a packet switching satellite, and argue that predictive, rather than reactive, flow control is necessary for the efficient operation of such a system. The first method discussed is based on standard, statistical techniques which are used to periodically calculate a probability of near-term congestion based on arrival rate statistics. If this probability exceeds a present threshold, the satellite would transmit a rate-reduction signal to all active ground stations. The second method discussed would utilize a neural network to periodically predict the occurrence of buffer overflow based on input data which would include, in addition to arrival rates, the distributions of packet lengths, source addresses, and destination addresses.

  2. Model predictive control of a wind turbine modelled in Simpack

    NASA Astrophysics Data System (ADS)

    Jassmann, U.; Berroth, J.; Matzke, D.; Schelenz, R.; Reiter, M.; Jacobs, G.; Abel, D.

    2014-06-01

    Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine to

  3. Prediction as Persuasion and Threat: Interaction of Locus of Control and Locus of Prediction on Compliance and Reactance.

    ERIC Educational Resources Information Center

    Goggin, William C.

    A model of persuasion suggests that individuals comply with a prediction of their behavior because they are persuaded by that prediction; a model of threat suggests that they defy prediction because of its threat of control. College students with either internal (N=20) or external (N=20) loci of control were informed of the accuracy of the…

  4. Flutter prediction for a wing with active aileron control

    NASA Technical Reports Server (NTRS)

    Penning, K.; Sandlin, D. R.

    1983-01-01

    A method for predicting the vibrational stability of an aircraft with an analog active aileron flutter suppression system (FSS) is expained. Active aileron refers to the use of an active control system connected to the aileron to damp vibrations. Wing vibrations are sensed by accelerometers and the information is used to deflect the aileron. Aerodynamic force caused by the aileron deflection oppose wing vibrations and effectively add additional damping to the system.

  5. Punishment Sensitivity Predicts the Impact of Punishment on Cognitive Control

    PubMed Central

    Braem, Senne; Duthoo, Wout; Notebaert, Wim

    2013-01-01

    Cognitive control theories predict enhanced conflict adaptation after punishment. However, no such effect was found in previous work. In the present study, we demonstrate in a flanker task how behavioural adjustments following punishment signals are highly dependent on punishment sensitivity (as measured by the Behavioural Inhibition System (BIS) scale): Whereas low punishment-sensitive participants do show increased conflict adaptation after punishment, high punishment-sensitive participants show no such modulation. Interestingly, participants with a high punishment-sensitivity showed an overall reaction time increase after punishments. Our results stress the role of individual differences in explaining motivational modulations of cognitive control. PMID:24058520

  6. Prediction and control of chaotic processes using nonlinear adaptive networks

    SciTech Connect

    Jones, R.D.; Barnes, C.W.; Flake, G.W.; Lee, K.; Lewis, P.S.; O'Rouke, M.K.; Qian, S.

    1990-01-01

    We present the theory of nonlinear adaptive networks and discuss a few applications. In particular, we review the theory of feedforward backpropagation networks. We then present the theory of the Connectionist Normalized Linear Spline network in both its feedforward and iterated modes. Also, we briefly discuss the theory of stochastic cellular automata. We then discuss applications to chaotic time series, tidal prediction in Venice lagoon, finite differencing, sonar transient detection, control of nonlinear processes, control of a negative ion source, balancing a double inverted pendulum and design advice for free electron lasers and laser fusion targets.

  7. Experimental Investigations of Generalized Predictive Control for Tiltrotor Stability Augmentation

    NASA Technical Reports Server (NTRS)

    Nixon, Mark W.; Langston, Chester W.; Singleton, Jeffrey D.; Piatak, David J.; Kvaternik, Raymond G.; Bennett, Richard L.; Brown, Ross K.

    2001-01-01

    A team of researchers from the Army Research Laboratory, NASA Langley Research Center (LaRC), and Bell Helicopter-Textron, Inc. have completed hover-cell and wind-tunnel testing of a 1/5-size aeroelastically-scaled tiltrotor model using a new active control system for stability augmentation. The active system is based on a generalized predictive control (GPC) algorithm originally developed at NASA LaRC in 1997 for un-known disturbance rejection. Results of these investigations show that GPC combined with an active swashplate can significantly augment the damping and stability of tiltrotors in both hover and high-speed flight.

  8. Applying new optimization algorithms to more predictive control

    SciTech Connect

    Wright, S.J.

    1996-03-01

    The connections between optimization and control theory have been explored by many researchers and optimization algorithms have been applied with success to optimal control. The rapid pace of developments in model predictive control has given rise to a host of new problems to which optimization has yet to be applied. Concurrently, developments in optimization, and especially in interior-point methods, have produced a new set of algorithms that may be especially helpful in this context. In this paper, we reexamine the relatively simple problem of control of linear processes subject to quadratic objectives and general linear constraints. We show how new algorithms for quadratic programming can be applied efficiently to this problem. The approach extends to several more general problems in straightforward ways.

  9. Multiplexed model predictive control for active vehicle suspensions

    NASA Astrophysics Data System (ADS)

    Hu, Yinlong; Chen, Michael Z. Q.; Hou, Zhongsheng

    2015-02-01

    Multiplexed model predictive control (MMPC) is a recently proposed efficient model predictive control (MPC) algorithm, which can effectively reduce the computational burden of the online optimisation in MPC implementation by updating the control inputs in an asynchronous manner. This paper investigates the application of MMPC in active vehicle suspension design. An MMPC controller integrated with soft constraints and a Kalman filter is proposed based on a full-car model. Ride comfort, roadholding and suspension deflection are considered in this paper, where ride comfort and roadholding are formulated as a quadratic cost function in terms of sprung mass accelerations and tyre deflections, while suspension deflection performance is formulated as a hard constraint. The saturation of the actuator force is also considered and formulated as a hard constraint as well. Numerical simulation is performed with respect to different choices of weighting factors, vehicle speeds and control horizons. The results show that the overall performance of ride comfort and roadholding can be improved significantly by employing MMPC and the average time taken by MMPC to solve the individual quadratic programming problem is considerably smaller than that of the conventional MPC, which effectively demonstrate the effectiveness of the proposed method.

  10. A novel trajectory prediction control for proximate time-optimal digital control DC—DC converters

    NASA Astrophysics Data System (ADS)

    Qing, Wang; Ning, Chen; Shen, Xu; Weifeng, Sun; Longxing, Shi

    2014-09-01

    The purpose of this paper is to present a novel trajectory prediction method for proximate time-optimal digital control DC—DC converters. The control method provides pre-estimations of the duty ratio in the next several switching cycles, so as to compensate the computational time delay of the control loop and increase the control loop bandwidth, thereby improving the response speed. The experiment results show that the fastest transient response time of the digital DC—DC with the proposed prediction is about 8 μs when the load current changes from 0.6 to 0.1 A.

  11. An insula-frontostriatal network mediates flexible cognitive control by adaptively predicting changing control demands

    PubMed Central

    Jiang, Jiefeng; Beck, Jeffrey; Heller, Katherine; Egner, Tobias

    2015-01-01

    The anterior cingulate and lateral prefrontal cortices have been implicated in implementing context-appropriate attentional control, but the learning mechanisms underlying our ability to flexibly adapt the control settings to changing environments remain poorly understood. Here we show that human adjustments to varying control demands are captured by a reinforcement learner with a flexible, volatility-driven learning rate. Using model-based functional magnetic resonance imaging, we demonstrate that volatility of control demand is estimated by the anterior insula, which in turn optimizes the prediction of forthcoming demand in the caudate nucleus. The caudate's prediction of control demand subsequently guides the implementation of proactive and reactive attentional control in dorsal anterior cingulate and dorsolateral prefrontal cortices. These data enhance our understanding of the neuro-computational mechanisms of adaptive behaviour by connecting the classic cingulate-prefrontal cognitive control network to a subcortical control-learning mechanism that infers future demands by flexibly integrating remote and recent past experiences. PMID:26391305

  12. Control of nonlinear processes by using linear model predictive control algorithms.

    PubMed

    Gu, Bingfeng; Gupta, Yash P

    2008-04-01

    Most chemical processes are inherently nonlinear. However, because of their simplicity, linear control algorithms have been used for the control of nonlinear processes. In this study, the use of the dynamic matrix control algorithm and a simplified model predictive control algorithm for control of a bench-scale pH neutralization process is investigated. The nonlinearity is handled by dividing the operating region into sub-regions and by switching the controller model as the process moves from one sub-region to another. A simple modification for model predictive control algorithms is presented to handle the switching. The simulation and experimental results show that the modification can provide a significant improvement in the control of nonlinear processes. PMID:18255068

  13. Constrained model predictive control, state estimation and coordination

    NASA Astrophysics Data System (ADS)

    Yan, Jun

    In this dissertation, we study the interaction between the control performance and the quality of the state estimation in a constrained Model Predictive Control (MPC) framework for systems with stochastic disturbances. This consists of three parts: (i) the development of a constrained MPC formulation that adapts to the quality of the state estimation via constraints; (ii) the application of such a control law in a multi-vehicle formation coordinated control problem in which each vehicle operates subject to a no-collision constraint posed by others' imperfect prediction computed from finite bit-rate, communicated data; (iii) the design of the predictors and the communication resource assignment problem that satisfy the performance requirement from Part (ii). Model Predictive Control (MPC) is of interest because it is one of the few control design methods which preserves standard design variables and yet handles constraints. MPC is normally posed as a full-state feedback control and is implemented in a certainty-equivalence fashion with best estimates of the states being used in place of the exact state. However, if the state constraints were handled in the same certainty-equivalence fashion, the resulting control law could drive the real state to violate the constraints frequently. Part (i) focuses on exploring the inclusion of state estimates into the constraints. It does this by applying constrained MPC to a system with stochastic disturbances. The stochastic nature of the problem requires re-posing the constraints in a probabilistic form. In Part (ii), we consider applying constrained MPC as a local control law in a coordinated control problem of a group of distributed autonomous systems. Interactions between the systems are captured via constraints. First, we inspect the application of constrained MPC to a completely deterministic case. Formation stability theorems are derived for the subsystems and conditions on the local constraint set are derived in order to

  14. Cognitive control predicts use of model-based reinforcement learning.

    PubMed

    Otto, A Ross; Skatova, Anya; Madlon-Kay, Seth; Daw, Nathaniel D

    2015-02-01

    Accounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information--in the service of overcoming habitual, stimulus-driven responses--in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior. PMID:25170791

  15. Predictive maintenance now available for controls and instrumentation

    SciTech Connect

    Frerichs, D.K.

    1999-11-01

    Predictive maintenance (PdM) methods now abound in all areas of the powerhouse. Vibration analysis methods for all rotating machinery, oil analysis for both lubricated parts and transformers, wear particle analysis, acoustic leak detection, and loose parts monitoring are commonplace. But what about the controls and instrumentation arena? Smart positioners/actuators are part of the answer. They can tell us that stroke times are different or something is sticking, and therefore some level of maintenance is in order. Smart transmitters and new sensing technologies allow those devices to hold their calibration longer. But how does one know when it is time to re-calibrate the sensor? When does an RTD or thermocouple and/or it`s signal converter begin to drift? When did the steam temperature controls start to behave sub-optimally? If you perform the maintenance too early, you waste maintenance dollars. If you do it too late, you could be running off normal and not realize it, which in turn wastes operation dollars. There are hundreds of controllers and sensors to be maintained (thousands in a large facility), so guessing wrong can waste a lot of O and M dollars. This paper will explore new technology that finally allows the science of predictive maintenance to lend its benefits to the field of controls and instrumentation.

  16. Robust model predictive control for optimal continuous drug administration.

    PubMed

    Sopasakis, Pantelis; Patrinos, Panagiotis; Sarimveis, Haralambos

    2014-10-01

    In this paper the model predictive control (MPC) technology is used for tackling the optimal drug administration problem. The important advantage of MPC compared to other control technologies is that it explicitly takes into account the constraints of the system. In particular, for drug treatments of living organisms, MPC can guarantee satisfaction of the minimum toxic concentration (MTC) constraints. A whole-body physiologically-based pharmacokinetic (PBPK) model serves as the dynamic prediction model of the system after it is formulated as a discrete-time state-space model. Only plasma measurements are assumed to be measured on-line. The rest of the states (drug concentrations in other organs and tissues) are estimated in real time by designing an artificial observer. The complete system (observer and MPC controller) is able to drive the drug concentration to the desired levels at the organs of interest, while satisfying the imposed constraints, even in the presence of modelling errors, disturbances and noise. A case study on a PBPK model with 7 compartments, constraints on 5 tissues and a variable drug concentration set-point illustrates the efficiency of the methodology in drug dosing control applications. The proposed methodology is also tested in an uncertain setting and proves successful in presence of modelling errors and inaccurate measurements. PMID:24986530

  17. Vehicle yaw stability control using active limited-slip differential via model predictive control methods

    NASA Astrophysics Data System (ADS)

    Rubin, Daniel; Arogeti, Shai A.

    2015-09-01

    In this paper, the problem of vehicle yaw control using an active limited-slip differential (ALSD) applied on the rear axle is addressed. The controller objective is to minimise yaw-rate and body slip-angle errors, with respect to target values. A novel model predictive controller is designed, using a linear parameter-varying (LPV) vehicle model, which takes into account the ALSD dynamics and its constraints. The controller is simulated using a 10DOF Matlab/Simulink simulation model and a CarSim model. These simulations exemplify the controller yaw-rate and slip-angle tracking performances, under challenging manoeuvres and road conditions. The model predictive controller performances surpass those of a reference sliding mode controller, and can narrow the loss of performances due to the ALSD's inability to transfer torque regardless of driving conditions.

  18. Self-Tuning of Design Variables for Generalized Predictive Control

    NASA Technical Reports Server (NTRS)

    Lin, Chaung; Juang, Jer-Nan

    2000-01-01

    Three techniques are introduced to determine the order and control weighting for the design of a generalized predictive controller. These techniques are based on the application of fuzzy logic, genetic algorithms, and simulated annealing to conduct an optimal search on specific performance indexes or objective functions. Fuzzy logic is found to be feasible for real-time and on-line implementation due to its smooth and quick convergence. On the other hand, genetic algorithms and simulated annealing are applicable for initial estimation of the model order and control weighting, and final fine-tuning within a small region of the solution space, Several numerical simulations for a multiple-input and multiple-output system are given to illustrate the techniques developed in this paper.

  19. Prediction in the Vestibular Control of Arm Movements.

    PubMed

    Blouin, Jean; Bresciani, Jean-Pierre; Guillaud, Etienne; Simoneau, Martin

    2015-01-01

    The contribution of vestibular signals to motor control has been evidenced in postural, locomotor, and oculomotor studies. Here, we review studies showing that vestibular information also contributes to the control of arm movements during whole-body motion. The data reviewed suggest that vestibular information is used by the arm motor system to maintain the initial hand position or the planned hand trajectory unaltered during body motion. This requires integration of vestibular and cervical inputs to determine the trunk motion dynamics. These studies further suggest that the vestibular control of arm movement relies on rapid and efficient vestibulomotor transformations that cannot be considered automatic. We also reviewed evidence suggesting that the vestibular afferents can be used by the brain to predict and counteract body-rotation-induced torques (e.g., Coriolis) acting on the arm when reaching for a target while turning the trunk. PMID:26595953

  20. Structural Acoustic Prediction and Interior Noise Control Technology

    NASA Technical Reports Server (NTRS)

    Mathur, G. P.; Chin, C. L.; Simpson, M. A.; Lee, J. T.; Palumbo, Daniel L. (Technical Monitor)

    2001-01-01

    This report documents the results of Task 14, "Structural Acoustic Prediction and Interior Noise Control Technology". The task was to evaluate the performance of tuned foam elements (termed Smart Foam) both analytically and experimentally. Results taken from a three-dimensional finite element model of an active, tuned foam element are presented. Measurements of sound absorption and sound transmission loss were taken using the model. These results agree well with published data. Experimental performance data were taken in Boeing's Interior Noise Test Facility where 12 smart foam elements were applied to a 757 sidewall. Several configurations were tested. Noise reductions of 5-10 dB were achieved over the 200-800 Hz bandwidth of the controller. Accelerometers mounted on the panel provided a good reference for the controller. Configurations with far-field error microphones outperformed near-field cases.

  1. Prediction and control of neural responses to pulsatile electrical stimulation

    NASA Astrophysics Data System (ADS)

    Campbell, Luke J.; Sly, David James; O'Leary, Stephen John

    2012-04-01

    This paper aims to predict and control the probability of firing of a neuron in response to pulsatile electrical stimulation of the type delivered by neural prostheses such as the cochlear implant, bionic eye or in deep brain stimulation. Using the cochlear implant as a model, we developed an efficient computational model that predicts the responses of auditory nerve fibers to electrical stimulation and evaluated the model's accuracy by comparing the model output with pooled responses from a group of guinea pig auditory nerve fibers. It was found that the model accurately predicted the changes in neural firing probability over time to constant and variable amplitude electrical pulse trains, including speech-derived signals, delivered at rates up to 889 pulses s-1. A simplified version of the model that did not incorporate adaptation was used to adaptively predict, within its limitations, the pulsatile electrical stimulus required to cause a desired response from neurons up to 250 pulses s-1. Future stimulation strategies for cochlear implants and other neural prostheses may be enhanced using similar models that account for the way that neural responses are altered by previous stimulation.

  2. Dinucleotide controlled null models for comparative RNA gene prediction

    PubMed Central

    Gesell, Tanja; Washietl, Stefan

    2008-01-01

    Background Comparative prediction of RNA structures can be used to identify functional noncoding RNAs in genomic screens. It was shown recently by Babak et al. [BMC Bioinformatics. 8:33] that RNA gene prediction programs can be biased by the genomic dinucleotide content, in particular those programs using a thermodynamic folding model including stacking energies. As a consequence, there is need for dinucleotide-preserving control strategies to assess the significance of such predictions. While there have been randomization algorithms for single sequences for many years, the problem has remained challenging for multiple alignments and there is currently no algorithm available. Results We present a program called SISSIz that simulates multiple alignments of a given average dinucleotide content. Meeting additional requirements of an accurate null model, the randomized alignments are on average of the same sequence diversity and preserve local conservation and gap patterns. We make use of a phylogenetic substitution model that includes overlapping dependencies and site-specific rates. Using fast heuristics and a distance based approach, a tree is estimated under this model which is used to guide the simulations. The new algorithm is tested on vertebrate genomic alignments and the effect on RNA structure predictions is studied. In addition, we directly combined the new null model with the RNAalifold consensus folding algorithm giving a new variant of a thermodynamic structure based RNA gene finding program that is not biased by the dinucleotide content. Conclusion SISSIz implements an efficient algorithm to randomize multiple alignments preserving dinucleotide content. It can be used to get more accurate estimates of false positive rates of existing programs, to produce negative controls for the training of machine learning based programs, or as standalone RNA gene finding program. Other applications in comparative genomics that require randomization of multiple

  3. Programmable logic controller implementation of an auto-tuned predictive control based on minimal plant information.

    PubMed

    Valencia-Palomo, G; Rossiter, J A

    2011-01-01

    This paper makes two key contributions. First, it tackles the issue of the availability of constrained predictive control for low-level control loops. Hence, it describes how the constrained control algorithm is embedded in an industrial programmable logic controller (PLC) using the IEC 61131-3 programming standard. Second, there is a definition and implementation of a novel auto-tuned predictive controller; the key novelty is that the modelling is based on relatively crude but pragmatic plant information. Laboratory experiment tests were carried out in two bench-scale laboratory systems to prove the effectiveness of the combined algorithm and hardware solution. For completeness, the results are compared with a commercial proportional-integral-derivative (PID) controller (also embedded in the PLC) using the most up to date auto-tuning rules. PMID:21056412

  4. Predictive control and estimation algorithms for the NASA/JPL 70-meter antennas

    NASA Technical Reports Server (NTRS)

    Gawronski, W.

    1991-01-01

    A modified output prediction procedure and a new controller design is presented based on the predictive control law. Also, a new predictive estimator is developed to complement the controller and to enhance system performance. The predictive controller is designed and applied to the tracking control of the Deep Space Network 70 m antennas. Simulation results show significant improvement in tracking performance over the linear quadratic controller and estimator presently in use.

  5. [The quality control based on the predictable performance].

    PubMed

    Zheng, D X

    2016-09-01

    The clinical performance can only be evaluated when it comes to the last step in the conventional way of prosthesis. However, it often causes the failure because of the unconformity between the expectation and final performance. Resulting from this kind of situation, quality control based on the predictable results has been suggested. It is a new idea based on the way of reverse thinking, and focuses on the need of patient and puts the final performance of the prosthesis to the first place. With the prosthodontically driven prodedure, dentists can complete the unification with the expectation and the final performance. PMID:27596338

  6. Model Predictive Control for the Operation of Building Cooling Systems

    SciTech Connect

    Ma, Yudong; Borrelli, Francesco; Hencey, Brandon; Coffey, Brian; Bengea, Sorin; Haves, Philip

    2010-06-29

    A model-based predictive control (MPC) is designed for optimal thermal energy storage in building cooling systems. We focus on buildings equipped with a water tank used for actively storing cold water produced by a series of chillers. Typically the chillers are operated at night to recharge the storage tank in order to meet the building demands on the following day. In this paper, we build on our previous work, improve the building load model, and present experimental results. The experiments show that MPC can achieve reduction in the central plant electricity cost and improvement of its efficiency.

  7. Tuning the Model Predictive Control of a Crude Distillation Unit.

    PubMed

    Yamashita, André Shigueo; Zanin, Antonio Carlos; Odloak, Darci

    2016-01-01

    Tuning the parameters of the Model Predictive Control (MPC) of an industrial Crude Distillation Unit (CDU) is considered here. A realistic scenario is depicted where the inputs of the CDU system have optimizing targets, which are provided by the Real Time Optimization layer of the control structure. It is considered the nominal case, in which both the CDU model and the MPC model are the same. The process outputs are controlled inside zones instead of at fixed set points. Then, the tuning procedure has to define the weights that penalize the output error with respect to the control zone, the weights that penalize the deviation of the inputs from their targets, as well as the weights that penalize the input moves. A tuning approach based on multi-objective optimization is proposed and applied to the MPC of the CDU system. The performance of the controller tuned with the proposed approach is compared through simulation with the results of an existing approach also based on multi-objective optimization. The simulation results are similar, but the proposed approach has a computational load significantly lower than the existing method. The tuning effort is also much lower than in the conventional practical approaches that are usually based on ad-hoc procedures. PMID:26549567

  8. What`s new in multivariable predictive control

    SciTech Connect

    Colwell, L.W.; Poe, W.A.; Papadopoulos, M.N.; Gamez, J.P.

    1995-11-01

    Multivariable control techniques have been successfully applied to a variety of gas processing operations. The technology has been applied to CO{sub 2} recovery towers, cryogenic demethanizers, lean oil absorbers, rich oil demethanizers, rich oil stills, deethanizers, depropanizers, deisobutanizers, amine treaters, sulfur recovery units, nitrogen rejection units and compressors. The system has been developed with a modular structure and employs process model based predictions of key plant variables. Modules for each type of operation are available and, with minimal modification, can be applied to a specific unit since the key plant variables are usually common between plants and are affected by similar disturbances. Adaptive nonlinear multivariable control models allow continuous operation at optimum conditions within plant constraints. In most applications a personal computer (PC) containing the control software dan supervisory control and data acquisition (SCADA) system operates under a UNIX operating system and interfaces with the plant`s existing control system. The PC-based system dispatches setpoints that have been calculated to optimize on-line the profitability of the plant. A typical project can be implemented in 4-6 months with a payout of less than a year by increasing natural gas liquids (NGL) revenues and decreasing plant operating costs. This paper describes the technology and the initial installation results.

  9. Low inhibitory control and restrictive feeding practices predict weight outcomes

    PubMed Central

    Anzman, Stephanie L.; Birch, Leann L.

    2009-01-01

    Objective A priority for research is to identify individuals early in development who are particularly susceptible to weight gain in the current, obesogenic environment. This longitudinal study investigated whether early individual differences in inhibitory control, an aspect of temperament, predicted weight outcomes and whether parents’ restrictive feeding practices moderated this relation. Study design Participants included 197 non-Hispanic White girls and their parents; families were assessed when girls were 5, 7, 9, 11, 13, and 15 years old. Measures included mothers’ reports of girls’ inhibitory control levels, girls’ reports of parental restriction in feeding, girls’ body mass indexes (BMIs), and parents’ BMIs, education, and income. Results Girls with lower inhibitory control at age 7 had higher concurrent BMIs, greater weight gain, higher BMIs at all subsequent time points, and were 1.95 times more likely to be overweight at age 15. Girls who perceived higher parental restriction exhibited the strongest inverse relation between inhibitory control and weight status. Conclusion Variability in inhibitory control could help identify individuals who are predisposed to obesity risk; the current findings also highlight the importance of parenting practices as potentially modifiable factors which exacerbate or attenuate this risk. PMID:19595373

  10. Preview Scheduled Model Predictive Control For Horizontal Axis Wind Turbines

    NASA Astrophysics Data System (ADS)

    Laks, Jason H.

    This research investigates the use of model predictive control (MPC) in application to wind turbine operation from start-up to cut-out. The studies conducted are focused on the design of an MPC controller for a 650˜KW, three-bladed horizontal axis turbine that is in operation at the National Renewable Energy Laboratory's National Wind Technology Center outside of Golden, Colorado. This turbine is at the small end of utility scale turbines, but it provides advanced instrumentation and control capabilities, and there is a good probability that the approach developed in simulation for this thesis, will be field tested on the actual turbine. A contribution of this thesis is a method to combine the use of preview measurements with MPC while also providing regulation of turbine speed and cyclic blade loading. A common MPC technique provides integral-like control to achieve offset-free operation. At the same time in wind turbine applications, multiple studies have developed "feed-forward" controls based on applying a gain to an estimate of the wind speed changes obtained from an observer incorporating a disturbance model. These approaches are based on a technique that can be referred to as disturbance accommodating control (DAC). In this thesis, it is shown that offset-free tracking MPC is equivalent to a DAC approach when the disturbance gain is computed to satisfy a regulator equation. Although the MPC literature has recognized that this approach provides "structurally stable" disturbance rejection and tracking, this step is not typically divorced from the MPC computations repeated each sample hit. The DAC formulation is conceptually simpler, and essentially uncouples regulation considerations from MPC related issues. This thesis provides a self contained proof that the DAC formulation (an observer-controller and appropriate disturbance gain) provides structurally stable regulation.

  11. Predictive mechanisms in the control of contour following

    PubMed Central

    Tramper, Julian J.; Flanders, Martha

    2013-01-01

    In haptic exploration, when running a fingertip along a surface, the control system may attempt to anticipate upcoming changes in curvature in order to maintain a consistent level of contact force. Such predictive mechanisms are well known in the visual system, but have yet to be studied in the somatosensory system. Thus the present experiment was designed to reveal human capabilities for different types of haptic prediction. A robot arm with a large 3D workspace was attached to the index fingertip and was programmed to produce virtual surfaces with curvatures that varied within and across trials. With eyes closed, subjects moved the fingertip around elliptical hoops with flattened regions or Limaçon shapes, where the curvature varied continuously. Subjects anticipated the corner of the flattened region rather poorly, but for the Limaçon shapes they varied finger speed with upcoming curvature according to the two-thirds power law. Furthermore, although the Limaçon shapes were randomly presented in various 3D orientations, modulation of contact force also indicated good anticipation of upcoming changes in curvature. The results demonstrate that it is difficult to haptically anticipate the spatial location of an abrupt change in curvature, but smooth changes in curvature may be facilitated by anticipatory predictions. PMID:23649968

  12. Evidence for predictive control in lifting series of virtual objects.

    PubMed

    Mawase, Firas; Karniel, Amir

    2010-06-01

    The human motor control system gracefully behaves in a dynamic and time varying environment. Here, we explored the predictive capabilities of the motor system in a simple motor task of lifting a series of virtual objects. When a subject lifts an object, she/he uses an expectation of the weight of the object to generate a motor command. All models of motor learning employ learning algorithms that essentially expect the future to be similar to the previously experienced environment. In this study, we asked subjects to lift a series of increasing weights and determined whether they extrapolated from past experience and predicted the next weight in the series even though that weight had never been experienced. The grip force at the beginning of the lifting task is a clean indication of the motor expectation. In contrast to the motor learning literature asserting adaptation by means of expecting a weighted average based on past experience, our results suggest that the motor system is able to predict the subsequent weight that follows a series of increasing weights. PMID:20428856

  13. Predictive models of procedural human supervisory control behavior

    NASA Astrophysics Data System (ADS)

    Boussemart, Yves

    Human supervisory control systems are characterized by the computer-mediated nature of the interactions between one or more operators and a given task. Nuclear power plants, air traffic management and unmanned vehicles operations are examples of such systems. In this context, the role of the operators is typically highly proceduralized due to the time and mission-critical nature of the tasks. Therefore, the ability to continuously monitor operator behavior so as to detect and predict anomalous situations is a critical safeguard for proper system operation. In particular, such models can help support the decision J]l8king process of a supervisor of a team of operators by providing alerts when likely anomalous behaviors are detected By exploiting the operator behavioral patterns which are typically reinforced through standard operating procedures, this thesis proposes a methodology that uses statistical learning techniques in order to detect and predict anomalous operator conditions. More specifically, the proposed methodology relies on hidden Markov models (HMMs) and hidden semi-Markov models (HSMMs) to generate predictive models of unmanned vehicle systems operators. Through the exploration of the resulting HMMs in two distinct single operator scenarios, the methodology presented in this thesis is validated and shown to provide models capable of reliably predicting operator behavior. In addition, the use of HSMMs on the same data scenarios provides the temporal component of the predictions missing from the HMMs. The final step of this work is to examine how the proposed methodology scales to more complex scenarios involving teams of operators. Adopting a holistic team modeling approach, both HMMs and HSMMs are learned based on two team-based data sets. The results show that the HSMMs can provide valuable timing information in the single operator case, whereas HMMs tend to be more robust to increased team complexity. In addition, this thesis discusses the

  14. Design and Performance Analysis of Incremental Networked Predictive Control Systems.

    PubMed

    Pang, Zhong-Hua; Liu, Guo-Ping; Zhou, Donghua

    2016-06-01

    This paper is concerned with the design and performance analysis of networked control systems with network-induced delay, packet disorder, and packet dropout. Based on the incremental form of the plant input-output model and an incremental error feedback control strategy, an incremental networked predictive control (INPC) scheme is proposed to actively compensate for the round-trip time delay resulting from the above communication constraints. The output tracking performance and closed-loop stability of the resulting INPC system are considered for two cases: 1) plant-model match case and 2) plant-model mismatch case. For the former case, the INPC system can achieve the same output tracking performance and closed-loop stability as those of the corresponding local control system. For the latter case, a sufficient condition for the stability of the closed-loop INPC system is derived using the switched system theory. Furthermore, for both cases, the INPC system can achieve a zero steady-state output tracking error for step commands. Finally, both numerical simulations and practical experiments on an Internet-based servo motor system illustrate the effectiveness of the proposed method. PMID:26186798

  15. Study on Noise Prediction Model and Control Schemes for Substation

    PubMed Central

    Gao, Yang; Liu, Songtao

    2014-01-01

    With the government's emphasis on environmental issues of power transmission and transformation project, noise pollution has become a prominent problem now. The noise from the working transformer, reactor, and other electrical equipment in the substation will bring negative effect to the ambient environment. This paper focuses on using acoustic software for the simulation and calculation method to control substation noise. According to the characteristics of the substation noise and the techniques of noise reduction, a substation's acoustic field model was established with the SoundPLAN software to predict the scope of substation noise. On this basis, 4 reasonable noise control schemes were advanced to provide some helpful references for noise control during the new substation's design and construction process. And the feasibility and application effect of these control schemes can be verified by using the method of simulation modeling. The simulation results show that the substation always has the problem of excessive noise at boundary under the conventional measures. The excess noise can be efficiently reduced by taking the corresponding noise reduction methods. PMID:24672356

  16. Study on noise prediction model and control schemes for substation.

    PubMed

    Chen, Chuanmin; Gao, Yang; Liu, Songtao

    2014-01-01

    With the government's emphasis on environmental issues of power transmission and transformation project, noise pollution has become a prominent problem now. The noise from the working transformer, reactor, and other electrical equipment in the substation will bring negative effect to the ambient environment. This paper focuses on using acoustic software for the simulation and calculation method to control substation noise. According to the characteristics of the substation noise and the techniques of noise reduction, a substation's acoustic field model was established with the SoundPLAN software to predict the scope of substation noise. On this basis, 4 reasonable noise control schemes were advanced to provide some helpful references for noise control during the new substation's design and construction process. And the feasibility and application effect of these control schemes can be verified by using the method of simulation modeling. The simulation results show that the substation always has the problem of excessive noise at boundary under the conventional measures. The excess noise can be efficiently reduced by taking the corresponding noise reduction methods. PMID:24672356

  17. Humans are sensitive to attention control when predicting others' actions.

    PubMed

    Pesquita, Ana; Chapman, Craig S; Enns, James T

    2016-08-01

    Studies of social perception report acute human sensitivity to where another's attention is aimed. Here we ask whether humans are also sensitive to how the other's attention is deployed. Observers viewed videos of actors reaching to targets without knowing that those actors were sometimes choosing to reach to one of the targets (endogenous control) and sometimes being directed to reach to one of the targets (exogenous control). Experiments 1 and 2 showed that observers could respond more rapidly when actors chose where to reach, yet were at chance when guessing whether the reach was chosen or directed. This implicit sensitivity to attention control held when either actor's faces or limbs were masked (experiment 3) and when only the earliest actor's movements were visible (experiment 4). Individual differences in sensitivity to choice correlated with an independent measure of social aptitude. We conclude that humans are sensitive to attention control through an implicit kinematic process linked to empathy. The findings support the hypothesis that social cognition involves the predictive modeling of others' attentional states. PMID:27436897

  18. Control when it counts: Change in executive control under stress predicts depression symptoms.

    PubMed

    Quinn, Meghan E; Joormann, Jutta

    2015-08-01

    Individual differences in the ability to regulate affect following stressful life events have been associated with an increased risk for experiencing depression symptoms. Research further suggests that emotion regulation may depend on executive control which, in turn, has been shown to decline following stress exposure. Whether individual differences in stress-induced change in executive control predict depression symptoms, however, remains unknown. The current study examined whether trait executive control as well as stress-induced change in executive control predicts depression symptoms during a stressful time of life. The current study recruited 43 individuals during their first year of college. Participants completed an executive control task before and after a laboratory stress induction. Participants reported baseline depression symptoms during the laboratory session and follow-up depression symptoms during the final weeks of the semester. Results demonstrate that stress-induced change in executive control predicted an increase in depression symptoms at the end of the semester. The findings suggest that individual differences in the degree of decline in executive control following stress exposure may be a key factor in explaining why some individuals are vulnerable to depression during a stressful time of life. PMID:26098731

  19. Cognitive control predicted by color vision, and vice versa.

    PubMed

    Colzato, Lorenza S; Sellaro, Roberta; Hulka, Lea M; Quednow, Boris B; Hommel, Bernhard

    2014-09-01

    One of the most important functions of cognitive control is to continuously adapt cognitive processes to changing and often conflicting demands of the environment. Dopamine (DA) has been suggested to play a key role in the signaling and resolution of such response conflict. Given that DA is found in high concentration in the retina, color vision discrimination has been suggested as an index of DA functioning and in particular blue-yellow color vision impairment (CVI) has been used to indicate a central hypodopaminergic state. We used color discrimination (indexed by the total color distance score; TCDS) to predict individual differences in the cognitive control of response conflict, as reflected by conflict-resolution efficiency in an auditory Simon task. As expected, participants showing better color discrimination were more efficient in resolving response conflict. Interestingly, participants showing a blue-yellow CVI were associated with less efficiency in handling response conflict. Our findings indicate that color vision discrimination might represent a promising predictor of cognitive controlability in healthy individuals. PMID:25058057

  20. Inlet Flow Control and Prediction Technologies for Embedded Propulsion Systems

    NASA Technical Reports Server (NTRS)

    McMillan, Michelle L.; Mackie, Scott A.; Gissen, Abe; Vukasinovic, Bojan; Lakebrink, Matthew T.; Glezer, Ari; Mani, Mori; Mace, James L.

    2011-01-01

    Fail-safe, hybrid, flow control (HFC) is a promising technology for meeting high-speed cruise efficiency, low-noise signature, and reduced fuel-burn goals for future, Hybrid-Wing-Body (HWB) aircraft with embedded engines. This report details the development of HFC technology that enables improved inlet performance in HWB vehicles with highly integrated inlets and embedded engines without adversely affecting vehicle performance. In addition, new test techniques for evaluating Boundary-Layer-Ingesting (BLI)-inlet flow-control technologies developed and demonstrated through this program are documented, including the ability to generate a BLI-like inlet-entrance flow in a direct-connect, wind-tunnel facility, as well as, the use of D-optimal, statistically designed experiments to optimize test efficiency and enable interpretation of results. Validated improvements in numerical analysis tools and methods accomplished through this program are also documented, including Reynolds-Averaged Navier-Stokes CFD simulations of steady-state flow physics for baseline, BLI-inlet diffuser flow, as well as, that created by flow-control devices. Finally, numerical methods were employed in a ground-breaking attempt to directly simulate dynamic distortion. The advances in inlet technologies and prediction tools will help to meet and exceed "N+2" project goals for future HWB aircraft.

  1. Inlet Flow Control and Prediction Technologies for Embedded Propulsion Systems

    NASA Technical Reports Server (NTRS)

    McMillan, Michelle L.; Gissen, Abe; Vukasinovic, Bojan; Lakebrink, Matthew T.; Glezer, Ari; Mani, Mori; Mace, James

    2010-01-01

    Fail-safe inlet flow control may enable high-speed cruise efficiency, low noise signature, and reduced fuel-burn goals for hybrid wing-body aircraft. The objectives of this program are to develop flow control and prediction methodologies for boundary-layer ingesting (BLI) inlets used in these aircraft. This report covers the second of a three year program. The approach integrates experiments and numerical simulations. Both passive and active flow-control devices were tested in a small-scale wind tunnel. Hybrid actuation approaches, combining a passive microvane and active synthetic jet, were tested in various geometric arrangements. Detailed flow measurements were taken to provide insight into the flow physics. Results of the numerical simulations were correlated against experimental data. The sensitivity of results to grid resolution and turbulence models was examined. Aerodynamic benefits from microvanes and microramps were assessed when installed in an offset BLI inlet. Benefits were quantified in terms of recovery and distortion changes. Microvanes were more effective than microramps at improving recovery and distortion.

  2. Nonlinear model predictive control based on collective neurodynamic optimization.

    PubMed

    Yan, Zheng; Wang, Jun

    2015-04-01

    In general, nonlinear model predictive control (NMPC) entails solving a sequential global optimization problem with a nonconvex cost function or constraints. This paper presents a novel collective neurodynamic optimization approach to NMPC without linearization. Utilizing a group of recurrent neural networks (RNNs), the proposed collective neurodynamic optimization approach searches for optimal solutions to global optimization problems by emulating brainstorming. Each RNN is guaranteed to converge to a candidate solution by performing constrained local search. By exchanging information and iteratively improving the starting and restarting points of each RNN using the information of local and global best known solutions in a framework of particle swarm optimization, the group of RNNs is able to reach global optimal solutions to global optimization problems. The essence of the proposed collective neurodynamic optimization approach lies in the integration of capabilities of global search and precise local search. The simulation results of many cases are discussed to substantiate the effectiveness and the characteristics of the proposed approach. PMID:25608315

  3. Predictive wavefront control for Adaptive Optics with arbitrary control loop delays

    SciTech Connect

    Poyneer, L A; Veran, J

    2007-10-30

    We present a modification of the closed-loop state space model for AO control which allows delays that are a non-integer multiple of the system frame rate. We derive the new forms of the Predictive Fourier Control Kalman filters for arbitrary delays and show that they are linear combinations of the whole-frame delay terms. This structure of the controller is independent of the delay. System stability margins and residual error variance both transition gracefully between integer-frame delays.

  4. Predictive active disturbance rejection control for processes with time delay.

    PubMed

    Zheng, Qinling; Gao, Zhiqiang

    2014-07-01

    Active disturbance rejection control (ADRC) has been shown to be an effective tool in dealing with real world problems of dynamic uncertainties, disturbances, nonlinearities, etc. This paper addresses its existing limitations with plants that have a large transport delay. In particular, to overcome the delay, the extended state observer (ESO) in ADRC is modified to form a predictive ADRC, leading to significant improvements in the transient response and stability characteristics, as shown in extensive simulation studies and hardware-in-the-loop tests, as well as in the frequency response analysis. In this research, it is assumed that the amount of delay is approximately known, as is the approximated model of the plant. Even with such uncharacteristic assumptions for ADRC, the proposed method still exhibits significant improvements in both performance and robustness over the existing methods such as the dead-time compensator based on disturbance observer and the Filtered Smith Predictor, in the context of some well-known problems of chemical reactor and boiler control problems. PMID:24182516

  5. Factors Predicting Atypical Development of Nighttime Bladder Control

    PubMed Central

    Sullivan, Sarah; Heron, Jon

    2015-01-01

    ABSTRACT: Objective: To derive latent classes (longitudinal “phenotypes”) of frequency of bedwetting from 4 to 9 years and to examine their association with developmental delay, parental history of bedwetting, length of gestation and birth weight. Method: The authors used data from 8,769 children from the UK Avon Longitudinal Study of Parents and Children cohort. Mothers provided repeated reports on their child's frequency of bedwetting from 4 to 9 years. The authors used longitudinal latent class analysis to derive latent classes of bedwetting and examined their association with sex, developmental level at 18 months, parental history of wetting, birth weight, and gestational length. Results: The authors identified 5 latent classes: (1) “normative”—low probability of bedwetting; (2) “infrequent delayed”—delayed attainment of nighttime bladder control with bedwetting control with bedwetting ≥ twice a week; (4) “infrequent persistent”—persistent bedwetting < twice a week; and (5) “frequent persistent”—persistent bedwetting ≥ twice a week. Male gender (odds ratio = 3.20 [95% confidence interval = 2.36–4.34]), developmental delay, for example, delayed social skills (1.33 [1.11–1.58]), and maternal history of wetting (3.91 [2.60–5.88]) were associated with an increase in the odds of bedwetting at 4 to 9 years. There was little evidence that low birth weight and shorter gestation period were associated with bedwetting. Conclusion: The authors described patterns of development of nighttime bladder control and found evidence for factors that predict continuation of bedwetting at school age. Increased knowledge of risk factors for bedwetting is needed to identify children at risk of future problems attaining and maintaining continence. PMID:26468941

  6. Neural network-based nonlinear model predictive control vs. linear quadratic gaussian control

    USGS Publications Warehouse

    Cho, C.; Vance, R.; Mardi, N.; Qian, Z.; Prisbrey, K.

    1997-01-01

    One problem with the application of neural networks to the multivariable control of mineral and extractive processes is determining whether and how to use them. The objective of this investigation was to compare neural network control to more conventional strategies and to determine if there are any advantages in using neural network control in terms of set-point tracking, rise time, settling time, disturbance rejection and other criteria. The procedure involved developing neural network controllers using both historical plant data and simulation models. Various control patterns were tried, including both inverse and direct neural network plant models. These were compared to state space controllers that are, by nature, linear. For grinding and leaching circuits, a nonlinear neural network-based model predictive control strategy was superior to a state space-based linear quadratic gaussian controller. The investigation pointed out the importance of incorporating state space into neural networks by making them recurrent, i.e., feeding certain output state variables into input nodes in the neural network. It was concluded that neural network controllers can have better disturbance rejection, set-point tracking, rise time, settling time and lower set-point overshoot, and it was also concluded that neural network controllers can be more reliable and easy to implement in complex, multivariable plants.

  7. Predictive powertrain control using powertrain history and GPS data

    DOEpatents

    Weslati, Feisel; Krupadanam, Ashish A

    2015-03-03

    A method and powertrain apparatus that predicts a route of travel for a vehicle and uses historical powertrain loads and speeds for the predicted route of travel to optimize at least one powertrain operation for the vehicle.

  8. Autonomous formation flight of helicopters: Model predictive control approach

    NASA Astrophysics Data System (ADS)

    Chung, Hoam

    Formation flight is the primary movement technique for teams of helicopters. However, the potential for accidents is greatly increased when helicopter teams are required to fly in tight formations and under harsh conditions. This dissertation proposes that the automation of helicopter formations is a realistic solution capable of alleviating risks. Helicopter formation flight operations in battlefield situations are highly dynamic and dangerous, and, therefore, we maintain that both a high-level formation management system and a distributed coordinated control algorithm should be implemented to help ensure safe formations. The starting point for safe autonomous formation flights is to design a distributed control law attenuating external disturbances coming into a formation, so that each vehicle can safely maintain sufficient clearance between it and all other vehicles. While conventional methods are limited to homogeneous formations, our decentralized model predictive control (MPC) approach allows for heterogeneity in a formation. In order to avoid the conservative nature inherent in distributed MPC algorithms, we begin by designing a stable MPC for individual vehicles, and then introducing carefully designed inter-agent coupling terms in a performance index. Thus the proposed algorithm works in a decentralized manner, and can be applied to the problem of helicopter formations comprised of heterogenous vehicles. Individual vehicles in a team may be confronted by various emerging situations that will require the capability for in-flight reconfiguration. We propose the concept of a formation manager to manage separation, join, and synchronization of flight course changes. The formation manager accepts an operator's commands, information from neighboring vehicles, and its own vehicle states. Inside the formation manager, there are multiple modes and complex mode switchings represented as a finite state machine (FSM). Based on the current mode and collected

  9. Predictable SCR co-benefits for mercury control

    SciTech Connect

    Pritchard, S.

    2009-01-15

    A test program, performed in cooperation with Dominion Power and the Babcock and Wilcox Co., was executed at Dominion Power's Mount Storm power plant in Grant County, W. Va. The program was focused on both the selective catalytic reduction (SCR) catalyst capability to oxide mercury as well as the scrubber's capability to capture and retain the oxidized mercury. This article focuses on the SCR catalyst performance aspects. The Mount Storm site consists of three units totaling approximately 1,660 MW. All units are equipped with SCR systems for NOx control. A full-scale test to evaluate the effect of the SCR was performed on Unit 2, a 550 MWT-fired boiler firing a medium sulfur bituminous coal. This test program demonstrated that the presence of an SCR catalyst can significantly affect the mercury speciation profile. Observation showed that in the absence of an SCR catalyst, the extent of oxidation of element a mercury at the inlet of the flue gas desulfurization system was about 64%. The presence of a Cornertech SCR catalyst improved this oxidation to levels greater than 95% almost all of which was captured by the downstream wet FGD system. Cornertech's proprietary SCR Hg oxidation model was used to accurately predict the field results. 1 ref., 2 figs., 1 tab.

  10. Exploratory Studies in Generalized Predictive Control for Active Aeroelastic Control of Tiltrotor Aircraft

    NASA Technical Reports Server (NTRS)

    Kvaternik, Raymond G.; Juang, Jer-Nan; Bennett, Richard L.

    2000-01-01

    The Aeroelasticity Branch at NASA Langley Research Center has a long and substantive history of tiltrotor aeroelastic research. That research has included a broad range of experimental investigations in the Langley Transonic Dynamics Tunnel (TDT) using a variety of scale models and the development of essential analyses. Since 1994, the tiltrotor research program has been using a 1/5-scale, semispan aeroelastic model of the V-22 designed and built by Bell Helicopter Textron Inc. (BHTI) in 1981. That model has been refurbished to form a tiltrotor research testbed called the Wing and Rotor Aeroelastic Test System (WRATS) for use in the TDT. In collaboration with BHTI, studies under the current tiltrotor research program are focused on aeroelastic technology areas having the potential for enhancing the commercial and military viability of tiltrotor aircraft. Among the areas being addressed, considerable emphasis is being directed to the evaluation of modern adaptive multi-input multi- output (MIMO) control techniques for active stability augmentation and vibration control of tiltrotor aircraft. As part of this investigation, a predictive control technique known as Generalized Predictive Control (GPC) is being studied to assess its potential for actively controlling the swashplate of tiltrotor aircraft to enhance aeroelastic stability in both helicopter and airplane modes of flight. This paper summarizes the exploratory numerical and experimental studies that were conducted as part of that investigation.

  11. Multivariate Prediction of College Grades for Disadvantaged and Control Students

    ERIC Educational Resources Information Center

    Pedrini, Bonnie; Pedrini, D. T.

    1977-01-01

    Shows that attrition/persistence (dropouts or students not continuously enrolled versus students continuously enrolled) is the primary, significant, single variate in the prediction of grades, and that attrition/persistence and American College Test (ACT) scores are the significant multiple variates in the prediction of grade point average. (RL)

  12. Analysis, prediction and control of radio frequency interference with respect to DSN

    NASA Technical Reports Server (NTRS)

    Degroot, N. F.

    1982-01-01

    Susceptibility modeling, prediction of radio frequency interference from satellites, operational radio frequency interference control, and international regulations are considered. The existing satellite interference prediction program DSIP2 is emphasized. A summary status evaluation and recommendations for future work are given.

  13. Predictive Techniques for Spacecraft Cabin Air Quality Control

    NASA Technical Reports Server (NTRS)

    Perry, J. L.; Cromes, Scott D. (Technical Monitor)

    2001-01-01

    As assembly of the International Space Station (ISS) proceeds, predictive techniques are used to determine the best approach for handling a variety of cabin air quality challenges. These techniques use equipment offgassing data collected from each ISS module before flight to characterize the trace chemical contaminant load. Combined with crew metabolic loads, these data serve as input to a predictive model for assessing the capability of the onboard atmosphere revitalization systems to handle the overall trace contaminant load as station assembly progresses. The techniques for predicting in-flight air quality are summarized along with results from early ISS mission analyses. Results from groundbased analyses of in-flight air quality samples are compared to the predictions to demonstrate the technique's relative conservatism.

  14. Predictive motor control of sensory dynamics in auditory active sensing.

    PubMed

    Morillon, Benjamin; Hackett, Troy A; Kajikawa, Yoshinao; Schroeder, Charles E

    2015-04-01

    Neuronal oscillations present potential physiological substrates for brain operations that require temporal prediction. We review this idea in the context of auditory perception. Using speech as an exemplar, we illustrate how hierarchically organized oscillations can be used to parse and encode complex input streams. We then consider the motor system as a major source of rhythms (temporal priors) in auditory processing, that act in concert with attention to sharpen sensory representations and link them across areas. We discuss the circuits that could mediate this audio-motor interaction, notably the potential role of the somatosensory system. Finally, we reposition temporal predictions in the context of internal models, discussing how they interact with feature-based or spatial predictions. We argue that complementary predictions interact synergistically according to the organizational principles of each sensory system, forming multidimensional filters crucial to perception. PMID:25594376

  15. Prediction of forces and moments for flight vehicle control effectors. Part 1: Validation of methods for predicting hypersonic vehicle controls forces and moments

    NASA Technical Reports Server (NTRS)

    Maughmer, Mark D.; Ozoroski, L.; Ozoroski, T.; Straussfogel, D.

    1990-01-01

    Many types of hypersonic aircraft configurations are currently being studied for feasibility of future development. Since the control of the hypersonic configurations throughout the speed range has a major impact on acceptable designs, it must be considered in the conceptual design stage. The ability of the aerodynamic analysis methods contained in an industry standard conceptual design system, APAS II, to estimate the forces and moments generated through control surface deflections from low subsonic to high hypersonic speeds is considered. Predicted control forces and moments generated by various control effectors are compared with previously published wind tunnel and flight test data for three configurations: the North American X-15, the Space Shuttle Orbiter, and a hypersonic research airplane concept. Qualitative summaries of the results are given for each longitudinal force and moment and each control derivative in the various speed ranges. Results show that all predictions of longitudinal stability and control derivatives are acceptable for use at the conceptual design stage. Results for most lateral/directional control derivatives are acceptable for conceptual design purposes; however, predictions at supersonic Mach numbers for the change in yawing moment due to aileron deflection and the change in rolling moment due to rudder deflection are found to be unacceptable. Including shielding effects in the analysis is shown to have little effect on lift and pitching moment predictions while improving drag predictions.

  16. Mechanisms of Intentional Binding and Sensory Attenuation: The Role of Temporal Prediction, Temporal Control, Identity Prediction, and Motor Prediction

    ERIC Educational Resources Information Center

    Hughes, Gethin; Desantis, Andrea; Waszak, Florian

    2013-01-01

    Sensory processing of action effects has been shown to differ from that of externally triggered stimuli, with respect both to the perceived timing of their occurrence (intentional binding) and to their intensity (sensory attenuation). These phenomena are normally attributed to forward action models, such that when action prediction is consistent…

  17. Adaptive Data-based Predictive Control for Short Take-off and Landing (STOL) Aircraft

    NASA Technical Reports Server (NTRS)

    Barlow, Jonathan Spencer; Acosta, Diana Michelle; Phan, Minh Q.

    2010-01-01

    Data-based Predictive Control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. The characteristics of adaptive data-based predictive control are particularly appropriate for the control of nonlinear and time-varying systems, such as Short Take-off and Landing (STOL) aircraft. STOL is a capability of interest to NASA because conceptual Cruise Efficient Short Take-off and Landing (CESTOL) transport aircraft offer the ability to reduce congestion in the terminal area by utilizing existing shorter runways at airports, as well as to lower community noise by flying steep approach and climb-out patterns that reduce the noise footprint of the aircraft. In this study, adaptive data-based predictive control is implemented as an integrated flight-propulsion controller for the outer-loop control of a CESTOL-type aircraft. Results show that the controller successfully tracks velocity while attempting to maintain a constant flight path angle, using longitudinal command, thrust and flap setting as the control inputs.

  18. Implementation of a model for census prediction and control.

    PubMed Central

    Swain, R W; Kilpatrick, K E; Marsh, J J

    1977-01-01

    A model is described that predicts hospital census and computes, for each day, the number of elective admissions that will maximize the census over the short run, subject to constraints on the probability of overflow. Where a computer is available the model provides detailed predictions of census in units as small as 10 beds; used with manual computation the model allows production of tables of the recommended numbers of elective admissions to the hospital as a whole. The model has been tested in five hospitals and is part of the admissions system in two of them; implementation is described, and the results obtained are discussed. PMID:591350

  19. An application of generalized predictive control to rotorcraft terrain-following flight

    NASA Technical Reports Server (NTRS)

    Hess, Ronald A.; Jung, Yoon C.

    1989-01-01

    Generalized predictive control (GPC) describes an algorithm for the control of dynamic systems in which a control input is generated which minimizes a quadratic cost function consisting of a weighted sum of errors between desired and predicted future system output and future predicted control increments. The output predictions are obtained from an internal model of the plant dynamics. The GPC algorithm is first applied to a simplified rotorcraft terrain-following problem, and GPC performance is compared to that of a conventional compensatory automatic system in terms of flight-path following, control activity, and control law implementation. Next, more realistic vehicle dynamics are utilized, and the GPC algorithm is applied to simultaneous terrain following and velocity control in the presence of atmospheric disturbances and errors in the internal model of the vehicle. The online computational and sensing requirements for implementing the GPC algorithm are minimal. Its use for manual control models appears promising.

  20. Self-tuning Generalized Predictive Control applied to terrain following flight

    NASA Technical Reports Server (NTRS)

    Hess, R. A.; Jung, Y. C.

    1989-01-01

    Generalized Predictive Control (GPC) describes an algorithm for the control of dynamic systems in which a control input is generated which minimizes a quadratic cost function consisting of a weighted sum of errors between desired and predicted future system output and future predicted control increments. The output predictions are obtained from an internal model of the plant dynamics. Self-tuning GPC refers to an implementation of the GPC algorithm in which the parameters of the internal model(s) are estimated on-line and the predictive control law tuned to the parameters so identified. The self-tuning GPC algorithm is applied to a problem of rotorcraft longitudinal/vertical terrain-following flight. The ability of the algorithm to tune to the initial vehicle parameters and to successfully adapt to a stability augmentation failure is demonstrated. Flight path performance is compared to a conventional, classically designed flight path control system.

  1. Predicting Changes in Older Adults' Interpersonal Control Strivings

    ERIC Educational Resources Information Center

    Sorkin, Dara H.; Rook, Karen S.; Heckhausen, Jutta; Billimek, John

    2009-01-01

    People vary in the importance they ascribe to, and efforts they invest in, maintaining positive relationships with others. Research has linked such variation in interpersonal control strivings to the quality of social exchanges experienced, but little work has examined the predictors of interpersonal control strivings. Given the importance of…

  2. A Computerized Test of Self-Control Predicts Classroom Behavior

    ERIC Educational Resources Information Center

    Hoerger, Marguerite L.; Mace, F. Charles

    2006-01-01

    We assessed choices on a computerized test of self-control (CTSC) for a group of children with features of attention deficit hyperactivity disorder (ADHD) and a group of controls. Thirty boys participated in the study. Fifteen of the children had been rated by their parents as hyperactive and inattentive, and 15 were age- and gender-matched…

  3. Inhibitory Control Predicts Language Switching Performance in Trilingual Speech Production

    ERIC Educational Resources Information Center

    Linck, Jared A.; Schwieter, John W.; Sunderman, Gretchen

    2012-01-01

    This study investigated the role of domain-general inhibitory control in trilingual speech production. Taking an individual differences approach, we examined the relationship between performance on a non-linguistic measure of inhibitory control (the Simon task) and a multilingual language switching task for a group of fifty-six native English (L1)…

  4. Predicting preschool effortful control from toddler temperament and parenting behavior

    PubMed Central

    Cipriano, Elizabeth A.; Stifter, Cynthia A.

    2010-01-01

    This longitudinal study assessed whether maternal behavior and emotional tone moderated the relationship between toddler temperament and preschooler's effortful control. Maternal behavior and emotional tone were observed during a parent-child competing demands task when children were 2 years of age. Child temperament was also assessed at 2 years of age, and three temperament groups were formed: inhibited, exuberant, and low reactive. At 4.5 years of age, children's effortful control was measured from parent-report and observational measures. Results indicated that parental behavior and emotional tone appear to be especially influential on exuberant children's effortful control development. Exuberant children whose mothers used commands and prohibitive statements with a positive emotional tone were more likely to be rated higher on parent-reported effortful control 2.5 years later. When mothers conveyed redirections and reasoning-explanations in a neutral tone, their exuberant children showed poorer effortful control at 4.5 years. PMID:23814350

  5. A predictive and feedback control algorithm maintains a constant glucose concentration in fed-batch fermentations.

    PubMed

    Kleman, G L; Chalmers, J J; Luli, G W; Strohl, W R

    1991-04-01

    A combined predictive and feedback control algorithm based on measurements of the concentration of glucose on-line has been developed to control fed-batch fermentations of Escherichia coli. The predictive control algorithm was based on the on-line calculation of glucose demand by the culture and plotting a linear regression to the next datum point to obtain a predicted glucose demand. This provided a predictive "coarse" control for the glucose-based nutrient feed. A direct feedback control using a proportional controller, based on glucose measurements every 2 min, fine-tuned the feed rate. These combined control schemes were used to maintain glucose concentrations in fed-batch fermentations as tight as 0.49 +/- 0.04 g/liter during growth of E. coli to high cell densities. PMID:2059049

  6. A predictive and feedback control algorithm maintains a constant glucose concentration in fed-batch fermentations.

    PubMed Central

    Kleman, G L; Chalmers, J J; Luli, G W; Strohl, W R

    1991-01-01

    A combined predictive and feedback control algorithm based on measurements of the concentration of glucose on-line has been developed to control fed-batch fermentations of Escherichia coli. The predictive control algorithm was based on the on-line calculation of glucose demand by the culture and plotting a linear regression to the next datum point to obtain a predicted glucose demand. This provided a predictive "coarse" control for the glucose-based nutrient feed. A direct feedback control using a proportional controller, based on glucose measurements every 2 min, fine-tuned the feed rate. These combined control schemes were used to maintain glucose concentrations in fed-batch fermentations as tight as 0.49 +/- 0.04 g/liter during growth of E. coli to high cell densities. PMID:2059049

  7. The Interplay of Maternal Sensitivity and Gentle Control When Predicting Children's Subsequent Academic Functioning: Evidence of Mediation by Effortful Control

    ERIC Educational Resources Information Center

    Kopystynska, Olena; Spinrad, Tracy L.; Seay, Danielle M.; Eisenberg, Nancy

    2016-01-01

    The goal of this work was to examine the complex interrelation of mothers' early gentle control and sensitivity in predicting children's effortful control (EC) and academic functioning. Maternal gentle control, maternal sensitivity, and children's EC were measured when children were 18, 30, and 42 months of age (T1, T2, and T3, respectively), and…

  8. Investigation of energy management strategies for photovoltaic systems - A predictive control algorithm

    NASA Technical Reports Server (NTRS)

    Cull, R. C.; Eltimsahy, A. H.

    1983-01-01

    The present investigation is concerned with the formulation of energy management strategies for stand-alone photovoltaic (PV) systems, taking into account a basic control algorithm for a possible predictive, (and adaptive) controller. The control system controls the flow of energy in the system according to the amount of energy available, and predicts the appropriate control set-points based on the energy (insolation) available by using an appropriate system model. Aspects of adaptation to the conditions of the system are also considered. Attention is given to a statistical analysis technique, the analysis inputs, the analysis procedure, and details regarding the basic control algorithm.

  9. Noise prediction and control of Pudong International Airport expansion project.

    PubMed

    Lei, Bin; Yang, Xin; Yang, Jianguo

    2009-04-01

    The Environmental Impact Assessment (EIA) process of the third runway building project of Pudong International Airport is briefly introduced in the paper. The basic principle, the features, and the operation steps of newly imported FAA's Integrated Noise Model (INM) are discussed for evaluating the aircraft noise impacts. The prediction of the aircraft noise and the countermeasures for the noise mitigation are developed, which includes the reasonable runway location, the optimized land use, the selection of low noise aircrafts, the Fly Quit Program, the relocation of sensitive receptors and the noise insulation of sensitive buildings. Finally, the expansion project is justified and its feasibility is confirmed. PMID:18373206

  10. Meditation-induced states predict attentional control over time.

    PubMed

    Colzato, Lorenza S; Sellaro, Roberta; Samara, Iliana; Baas, Matthijs; Hommel, Bernhard

    2015-12-01

    Meditation is becoming an increasingly popular topic for scientific research and various effects of extensive meditation practice (ranging from weeks to several years) on cognitive processes have been demonstrated. Here we show that extensive practice may not be necessary to achieve those effects. Healthy adult non-meditators underwent a brief single session of either focused attention meditation (FAM), which is assumed to increase top-down control, or open monitoring meditation (OMM), which is assumed to weaken top-down control, before performing an Attentional Blink (AB) task - which assesses the efficiency of allocating attention over time. The size of the AB was considerably smaller after OMM than after FAM, which suggests that engaging in meditation immediately creates a cognitive-control state that has a specific impact on how people allocate their attention over time. PMID:26320866

  11. Transition prediction and control in subsonic flow over a hump

    NASA Technical Reports Server (NTRS)

    Masad, Jamal A.; Iyer, Venkit

    1993-01-01

    The influence of a surface roughness element in the form of a two-dimensional hump on the transition location in a two-dimensional subsonic flow with a free-stream Mach number up to 0.8 is evaluated. Linear stability theory, coupled with the N-factor transition criterion, is used in the evaluation. The mean flow over the hump is calculated by solving the interacting boundary-layer equations; the viscous-inviscid coupling is taken into consideration, and the flow is solved within the separation bubble. The effects of hump height, length, location, and shape; unit Reynolds number; free-stream Mach number, continuous suction level; location of a suction strip; continuous cooling level; and location of a heating strip on the transition location are evaluated. The N-factor criterion predictions agree well with the experimental correlation of Fage; in addition, the N-factor criterion is more general and powerful than experimental correlations. The theoretically predicted effects of the hump's parameters and flow conditions on transition location are consistent and in agreement with both wind-tunnel and flight observations.

  12. Cognitive Control Predicts Academic Achievement in Kindergarten Children

    ERIC Educational Resources Information Center

    Coldren, Jeffrey T.

    2013-01-01

    Children's ability to shift behavior in response to changing environmental demands is critical for successful intellectual functioning. While the processes underlying the development of cognitive control have been thoroughly investigated, its functioning in an ecologically relevant setting such as school is less well understood. Given the alarming…

  13. Sustained Attention and Age Predict Inhibitory Control during Early Childhood

    ERIC Educational Resources Information Center

    Reck, Sarah G.; Hund, Alycia M.

    2011-01-01

    Executive functioning skills develop rapidly during early childhood. Recent research has focused on specifying this development, particularly predictors of executive functioning skills. Here we focus on sustained attention as a predictor of inhibitory control, one key executive functioning component. Although sustained attention and inhibitory…

  14. Predicting Preschool Effortful Control from Toddler Temperament and Parenting Behavior

    ERIC Educational Resources Information Center

    Cipriano, Elizabeth A.; Stifter, Cynthia A.

    2010-01-01

    This longitudinal study assessed whether maternal behavior and emotional tone moderated the relationship between toddler temperament and preschooler's effortful control. Maternal behavior and emotional tone were observed during a parent-child competing demands task when children were 2 years of age. Child temperament was also assessed at 2 years…

  15. Adaptive and predictive control of a simulated robot arm.

    PubMed

    Tolu, Silvia; Vanegas, Mauricio; Garrido, Jesús A; Luque, Niceto R; Ros, Eduardo

    2013-06-01

    In this work, a basic cerebellar neural layer and a machine learning engine are embedded in a recurrent loop which avoids dealing with the motor error or distal error problem. The presented approach learns the motor control based on available sensor error estimates (position, velocity, and acceleration) without explicitly knowing the motor errors. The paper focuses on how to decompose the input into different components in order to facilitate the learning process using an automatic incremental learning model (locally weighted projection regression (LWPR) algorithm). LWPR incrementally learns the forward model of the robot arm and provides the cerebellar module with optimal pre-processed signals. We present a recurrent adaptive control architecture in which an adaptive feedback (AF) controller guarantees a precise, compliant, and stable control during the manipulation of objects. Therefore, this approach efficiently integrates a bio-inspired module (cerebellar circuitry) with a machine learning component (LWPR). The cerebellar-LWPR synergy makes the robot adaptable to changing conditions. We evaluate how this scheme scales for robot-arms of a high number of degrees of freedom (DOFs) using a simulated model of a robot arm of the new generation of light weight robots (LWRs). PMID:23627657

  16. New technologies in predicting, preventing and controlling emerging infectious diseases

    PubMed Central

    Christaki, Eirini

    2015-01-01

    Surveillance of emerging infectious diseases is vital for the early identification of public health threats. Emergence of novel infections is linked to human factors such as population density, travel and trade and ecological factors like climate change and agricultural practices. A wealth of new technologies is becoming increasingly available for the rapid molecular identification of pathogens but also for the more accurate monitoring of infectious disease activity. Web-based surveillance tools and epidemic intelligence methods, used by all major public health institutions, are intended to facilitate risk assessment and timely outbreak detection. In this review, we present new methods for regional and global infectious disease surveillance and advances in epidemic modeling aimed to predict and prevent future infectious diseases threats. PMID:26068569

  17. Prediction and control of slender-wing rock

    NASA Technical Reports Server (NTRS)

    Kandil, Osama A.; Salman, Ahmed A.

    1992-01-01

    The unsteady Euler equations and the Euler equations of rigid-body dynamics, both written in the moving frame of reference, are sequentially solved to simulate the limit-cycle rock motion of slender delta wings. The governing equations of the fluid flow and the dynamics of the present multidisciplinary problem are solved using an implicit, approximately-factored, central-difference-like, finite-volume scheme and a four-stage Runge-Kutta scheme, respectively. For the control of wing-rock motion, leading-edge flaps are forced to oscillate anti-symmetrically at prescribed frequency and amplitude, which are tuned in order to suppress the rock motion. Since the computational grid deforms due to the leading-edge flaps motion, the grid is dynamically deformed using the Navier-displacement equations. Computational applications cover locally-conical and three-dimensional solutions for the wing-rock simulation and its control.

  18. Predictive Multiple Model Switching Control with the Self-Organizing Map

    NASA Technical Reports Server (NTRS)

    Motter, Mark A.

    2000-01-01

    A predictive, multiple model control strategy is developed by extension of self-organizing map (SOM) local dynamic modeling of nonlinear autonomous systems to a control framework. Multiple SOMs collectively model the global response of a nonautonomous system to a finite set of representative prototype controls. Each SOM provides a codebook representation of the dynamics corresponding to a prototype control. Different dynamic regimes are organized into topological neighborhoods where the adjacent entries in the codebook represent the global minimization of a similarity metric. The SOM is additionally employed to identify the local dynamical regime, and consequently implements a switching scheme that selects the best available model for the applied control. SOM based linear models are used to predict the response to a larger family of control sequences which are clustered on the representative prototypes. The control sequence which corresponds to the prediction that best satisfies the requirements on the system output is applied as the external driving signal.

  19. Asynchronous update based networked predictive control system using a novel proactive compensation strategy.

    PubMed

    Duan, Yingyao; Zuo, Xin; Liu, Jianwei

    2016-01-01

    Networked predictive control system (NPCS) has been proposed to address random delays and data dropouts in networked control systems (NCSs). A remaining challenge of this approach is that the controller has uncertain information about the actual control inputs, which leads to the predicted control input errors. The main contribution of this paper is to develop an explicit mechanism running in the distributed network nodes asynchronously, which enables the controller node to keep informed of the states of the actuator node without a priori knowledge about the network. Based on this mechanism, a novel proactive compensation strategy is proposed to develop asynchronous update based networked predictive control system (AUBNPCS). The stability criterion of AUBNPCS is derived analytically. A simulation experiment based on Truetime demonstrates the effectiveness of the scheme. PMID:26582090

  20. Nonlinear model identification and adaptive model predictive control using neural networks.

    PubMed

    Akpan, Vincent A; Hassapis, George D

    2011-04-01

    This paper presents two new adaptive model predictive control algorithms, both consisting of an on-line process identification part and a predictive control part. Both parts are executed at each sampling instant. The predictive control part of the first algorithm is the Nonlinear Model Predictive Control strategy and the control part of the second algorithm is the Generalized Predictive Control strategy. In the identification parts of both algorithms the process model is approximated by a series-parallel neural network structure which is trained by a recursive least squares (ARLS) method. The two control algorithms have been applied to: 1) the temperature control of a fluidized bed furnace reactor (FBFR) of a pilot plant and 2) the auto-pilot control of an F-16 aircraft. The training and validation data of the neural network are obtained from the open-loop simulation of the FBFR and the nonlinear F-16 aircraft models. The identification and control simulation results show that the first algorithm outperforms the second one at the expense of extra computation time. PMID:21281932

  1. Predictive optimal control of sewer networks using CORAL tool: application to Riera Blanca catchment in Barcelona.

    PubMed

    Puig, V; Cembrano, G; Romera, J; Quevedo, J; Aznar, B; Ramón, G; Cabot, J

    2009-01-01

    This paper deals with the global control of the Riera Blanca catchment in the Barcelona sewer network using a predictive optimal control approach. This catchment has been modelled using a conceptual modelling approach based on decomposing the catchments in subcatchments and representing them as virtual tanks. This conceptual modelling approach allows real-time model calibration and control of the sewer network. The global control problem of the Riera Blanca catchment is solved using a optimal/predictive control algorithm. To implement the predictive optimal control of the Riera Blanca catchment, a software tool named CORAL is used. The on-line control is simulated by interfacing CORAL with a high fidelity simulator of sewer networks (MOUSE). CORAL interchanges readings from the limnimeters and gate commands with MOUSE as if it was connected with the real SCADA system. Finally, the global control results obtained using the predictive optimal control are presented and compared against the results obtained using current local control system. The results obtained using the global control are very satisfactory compared to those obtained using the local control. PMID:19700825

  2. Non linear predictive control of a LEGO mobile robot

    NASA Astrophysics Data System (ADS)

    Merabti, H.; Bouchemal, B.; Belarbi, K.; Boucherma, D.; Amouri, A.

    2014-10-01

    Metaheuristics are general purpose heuristics which have shown a great potential for the solution of difficult optimization problems. In this work, we apply the meta heuristic, namely particle swarm optimization, PSO, for the solution of the optimization problem arising in NLMPC. This algorithm is easy to code and may be considered as alternatives for the more classical solution procedures. The PSO- NLMPC is applied to control a mobile robot for the tracking trajectory and obstacles avoidance. Experimental results show the strength of this approach.

  3. Model analysis of remotely controlled rendezvous and docking with display prediction

    NASA Technical Reports Server (NTRS)

    Milgram, P.; Wewerinke, P. H.

    1986-01-01

    Manual control of rendezvous and docking (RVD) of two spacecraft in low earth orbit by a remote human operator is discussed. Experimental evidence has shown that control performance degradation for large transmission delays (between spacecraft and operations control center) can be substantially improved by the introduction of predictor displays. An intial Optimal Control Model (OCM) analysis of RVD translational and rotational perturbation control was performed, with emphasis placed on the predictive capabilities of the combined Kalman estimator/optimal predictor with respect to control performance, for a range of time delays, motor noise levels and tracking axes. OCM predictions are then used as a reference for comparing tracking performance with a simple predictor display, as well as with no display prediction at all. Use is made here of an imperfect internal model formulation, whereby it is assumed that the human operator has no knowledge of the system transmission delay.

  4. Predicting methyl iodide emission, soil concentration, and pest control in a two-dimensional chamber system

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Due to ever increasing state and federal regulations, the future use of fumigants is predicted on negative environmental impacts while offering sufficient pest control efficacy. To foster the development of the best management practice (BMP), an integrated tool is needed to simultaneously predict fu...

  5. Jet Engine Noise Generation, Prediction and Control. Chapter 86

    NASA Technical Reports Server (NTRS)

    Huff, Dennis L.; Envia, Edmane

    2004-01-01

    . An example of this type of engine is shown in Figure IC, which is a schematic of the Honeywell T55 engine that powers the CH-47 Chinook helicopter. Since the noise from the propellers or helicopter rotors is usually dominant for turbo-shaft engines, less attention has been paid to these engines in so far as community noise considerations are concerned. This chapter will concentrate mostly on turbofan engine noise and will highlight common methods for their noise prediction and reduction.

  6. Prediction and Control of Vortex Dominated and Vortex-wake Flows

    NASA Technical Reports Server (NTRS)

    Kandil, Osama

    1996-01-01

    This report describes the activities and accomplishments under this research grant, including a list of publications and dissertations, produced in the field of prediction and control of vortex dominated and vortex wake flows.

  7. Identification-free adaptive optimal control based on switching predictive models

    NASA Astrophysics Data System (ADS)

    Luo, Wenguang; Pan, Shenghui; Ma, Zhaomin; Lan, Hongli

    2008-10-01

    An identification-free adaptive optimal control based on switching predictive models is proposed for the systems with big inertia, long time delay and multi models. Multi predictive models are set in the identification-free adaptive predictive control, and switched according to the optimal switching instants in control of the switching law along with the system running situations in real time. The switching law is designed based on the most important character parameter of the systems, and the optimal switching instants are computed out with the optimal theory for switched systems. The simulation test results show the proposed method is suitable to the systems, such as superheated steam temperature systems of electric power plants, can provide excellent control performance, improve rejecting disturbance ability and self-adaptability, and has lower demand on the predictive model precision.

  8. Constrained off-line synthesis approach of model predictive control for networked control systems with network-induced delays.

    PubMed

    Tang, Xiaoming; Qu, Hongchun; Wang, Ping; Zhao, Meng

    2015-03-01

    This paper investigates the off-line synthesis approach of model predictive control (MPC) for a class of networked control systems (NCSs) with network-induced delays. A new augmented model which can be readily applied to time-varying control law, is proposed to describe the NCS where bounded deterministic network-induced delays may occur in both sensor to controller (S-A) and controller to actuator (C-A) links. Based on this augmented model, a sufficient condition of the closed-loop stability is derived by applying the Lyapunov method. The off-line synthesis approach of model predictive control is addressed using the stability results of the system, which explicitly considers the satisfaction of input and state constraints. Numerical example is given to illustrate the effectiveness of the proposed method. PMID:25538025

  9. Scenario-based, closed-loop model predictive control with application to emergency vehicle scheduling

    NASA Astrophysics Data System (ADS)

    Goodwin, Graham. C.; Medioli, Adrian. M.

    2013-08-01

    Model predictive control has been a major success story in process control. More recently, the methodology has been used in other contexts, including automotive engine control, power electronics and telecommunications. Most applications focus on set-point tracking and use single-sequence optimisation. Here we consider an alternative class of problems motivated by the scheduling of emergency vehicles. Here disturbances are the dominant feature. We develop a novel closed-loop model predictive control strategy aimed at this class of problems. We motivate, and illustrate, the ideas via the problem of fluid deployment of ambulance resources.

  10. Auxiliary particle filter-model predictive control of the vacuum arc remelting process

    NASA Astrophysics Data System (ADS)

    Lopez, F.; Beaman, J.; Williamson, R.

    2016-07-01

    Solidification control is required for the suppression of segregation defects in vacuum arc remelting of superalloys. In recent years, process controllers for the VAR process have been proposed based on linear models, which are known to be inaccurate in highly-dynamic conditions, e.g. start-up, hot-top and melt rate perturbations. A novel controller is proposed using auxiliary particle filter-model predictive control based on a nonlinear stochastic model. The auxiliary particle filter approximates the probability of the state, which is fed to a model predictive controller that returns an optimal control signal. For simplicity, the estimation and control problems are solved using Sequential Monte Carlo (SMC) methods. The validity of this approach is verified for a 430 mm (17 in) diameter Alloy 718 electrode melted into a 510 mm (20 in) diameter ingot. Simulation shows a more accurate and smoother performance than the one obtained with an earlier version of the controller.

  11. The role of action prediction and inhibitory control for joint action coordination in toddlers.

    PubMed

    Meyer, M; Bekkering, H; Haartsen, R; Stapel, J C; Hunnius, S

    2015-11-01

    From early in life, young children eagerly engage in social interactions. Yet, they still have difficulties in performing well-coordinated joint actions with others. Adult literature suggests that two processes are important for smooth joint action coordination: action prediction and inhibitory control. The aim of the current study was to disentangle the potential role of these processes in the early development of joint action coordination. Using a simple turn-taking game, we assessed 2½-year-old toddlers' joint action coordination, focusing on timing variability and turn-taking accuracy. In two additional tasks, we examined their action prediction capabilities with an eye-tracking paradigm and examined their inhibitory control capabilities with a classic executive functioning task (gift delay task). We found that individual differences in action prediction and inhibitory action control were distinctly related to the two aspects of joint action coordination. Toddlers who showed more precision in their action predictions were less variable in their action timing during the joint play. Furthermore, toddlers who showed more inhibitory control in an individual context were more accurate in their turn-taking performance during the joint action. On the other hand, no relation between timing variability and inhibitory control or between turn-taking accuracy and action prediction was found. The current results highlight the distinct role of action prediction and inhibitory action control for the quality of joint action coordination in toddlers. Underlying neurocognitive mechanisms and implications for processes involved in joint action coordination in general are discussed. PMID:26150055

  12. Is It Really Self-Control? Examining the Predictive Power of the Delay of Gratification Task

    PubMed Central

    Duckworth, Angela L.; Tsukayama, Eli; Kirby, Teri A.

    2013-01-01

    This investigation tests whether the predictive power of the delay of gratification task (colloquially known as the “marshmallow test”) derives from its assessment of self-control or of theoretically unrelated traits. Among 56 school-age children in Study 1, delay time was associated with concurrent teacher ratings of self-control and Big Five conscientiousness—but not with other personality traits, intelligence, or reward-related impulses. Likewise, among 966 preschool children in Study 2, delay time was consistently associated with concurrent parent and caregiver ratings of self-control but not with reward-related impulses. While delay time in Study 2 was also related to concurrently measured intelligence, predictive relations with academic, health, and social outcomes in adolescence were more consistently explained by ratings of effortful control. Collectively, these findings suggest that delay task performance may be influenced by extraneous traits, but its predictive power derives primarily from its assessment of self-control. PMID:23813422

  13. The Impact of Trajectory Prediction Uncertainty on Air Traffic Controller Performance and Acceptability

    NASA Technical Reports Server (NTRS)

    Mercer, Joey S.; Bienert, Nancy; Gomez, Ashley; Hunt, Sarah; Kraut, Joshua; Martin, Lynne; Morey, Susan; Green, Steven M.; Prevot, Thomas; Wu, Minghong G.

    2013-01-01

    A Human-In-The-Loop air traffic control simulation investigated the impact of uncertainties in trajectory predictions on NextGen Trajectory-Based Operations concepts, seeking to understand when the automation would become unacceptable to controllers or when performance targets could no longer be met. Retired air traffic controllers staffed two en route transition sectors, delivering arrival traffic to the northwest corner-post of Atlanta approach control under time-based metering operations. Using trajectory-based decision-support tools, the participants worked the traffic under varying levels of wind forecast error and aircraft performance model error, impacting the ground automations ability to make accurate predictions. Results suggest that the controllers were able to maintain high levels of performance, despite even the highest levels of trajectory prediction errors.

  14. Predictive control strategies for wind turbine system based on permanent magnet synchronous generator.

    PubMed

    Maaoui-Ben Hassine, Ikram; Naouar, Mohamed Wissem; Mrabet-Bellaaj, Najiba

    2016-05-01

    In this paper, Model Predictive Control and Dead-beat predictive control strategies are proposed for the control of a PMSG based wind energy system. The proposed MPC considers the model of the converter-based system to forecast the possible future behavior of the controlled variables. It allows selecting the voltage vector to be applied that leads to a minimum error by minimizing a predefined cost function. The main features of the MPC are low current THD and robustness against parameters variations. The Dead-beat predictive control is based on the system model to compute the optimum voltage vector that ensures zero-steady state error. The optimum voltage vector is then applied through Space Vector Modulation (SVM) technique. The main advantages of the Dead-beat predictive control are low current THD and constant switching frequency. The proposed control techniques are presented and detailed for the control of back-to-back converter in a wind turbine system based on PMSG. Simulation results (under Matlab-Simulink software environment tool) and experimental results (under developed prototyping platform) are presented in order to show the performances of the considered control strategies. PMID:26725504

  15. Model predictive control system and method for integrated gasification combined cycle power generation

    DOEpatents

    Kumar, Aditya; Shi, Ruijie; Kumar, Rajeeva; Dokucu, Mustafa

    2013-04-09

    Control system and method for controlling an integrated gasification combined cycle (IGCC) plant are provided. The system may include a controller coupled to a dynamic model of the plant to process a prediction of plant performance and determine a control strategy for the IGCC plant over a time horizon subject to plant constraints. The control strategy may include control functionality to meet a tracking objective and control functionality to meet an optimization objective. The control strategy may be configured to prioritize the tracking objective over the optimization objective based on a coordinate transformation, such as an orthogonal or quasi-orthogonal projection. A plurality of plant control knobs may be set in accordance with the control strategy to generate a sequence of coordinated multivariable control inputs to meet the tracking objective and the optimization objective subject to the prioritization resulting from the coordinate transformation.

  16. Factors predictive of adolescents' intentions to use birth control pills, condoms, and birth control pills in combination with condoms.

    PubMed

    Craig, D M; Wade, K E; Allison, K R; Irving, H M; Williams, J I; Hlibka, C M

    2000-01-01

    Using the Theory of Planned Behaviour (Ajzen, 1988) as a conceptual framework, 705 secondary school students were surveyed to identify their intentions to use birth control pills, condoms, and birth control pills in combination with condoms. Hierarchical multiple regression revealed that the theory explained between 23.5% and 45.8% of the variance in intentions. Variables external to the model such as past use, age, and ethnicity exhibited some independent effects. Attitudes were consistently predictive of intentions to use condoms, pills, and condoms in combination with pills for both male and female students. However, there were differences by gender in the degree to which subjective norms and perceived behavioural control predicted intentions. The findings suggest that programs should focus on: creation of positive attitudes regarding birth control pills and condoms; targeting important social influences, particularly regarding males' use of condoms; and developing strategies to increase students' control over the use of condoms. PMID:11089290

  17. Controllability modulates the neural response to predictable but not unpredictable threat in humans.

    PubMed

    Wood, Kimberly H; Wheelock, Muriah D; Shumen, Joshua R; Bowen, Kenton H; Ver Hoef, Lawrence W; Knight, David C

    2015-10-01

    Stress resilience is mediated, in part, by our ability to predict and control threats within our environment. Therefore, determining the neural mechanisms that regulate the emotional response to predictable and controllable threats may provide important new insight into the processes that mediate resilience to emotional dysfunction and guide the future development of interventions for anxiety disorders. To better understand the effect of predictability and controllability on threat-related brain activity in humans, two groups of healthy volunteers participated in a yoked Pavlovian fear conditioning study during functional magnetic resonance imaging (fMRI). Threat predictability was manipulated by presenting an aversive unconditioned stimulus (UCS) that was either preceded by a conditioned stimulus (i.e., predictable) or by presenting the UCS alone (i.e., unpredictable). Similar to animal model research that has employed yoked fear conditioning procedures, one group (controllable condition; CC), but not the other group (uncontrollable condition; UC) was able to terminate the UCS. The fMRI signal response within the dorsolateral prefrontal cortex (PFC), dorsomedial PFC, ventromedial PFC, and posterior cingulate was diminished during predictable compared to unpredictable threat (i.e., UCS). In addition, threat-related activity within the ventromedial PFC and bilateral hippocampus was diminished only to threats that were both predictable and controllable. These findings provide insight into how threat predictability and controllability affects the activity of brain regions (i.e., ventromedial PFC and hippocampus) involved in emotion regulation, and may have important implications for better understanding neural processes that mediate emotional resilience to stress. PMID:26149610

  18. Water Prediction and Control Technologies for Large-scale Water Systems

    NASA Astrophysics Data System (ADS)

    Tian, Xin; van de Giesen, Nick; van Overloop, Peter-Jules

    2014-05-01

    A number of control techniques have been used in the field of operational water management over recent decades. Among these techniques, the ones that utilize prediction to anticipate near-future problems, such as Model Predictive Control (MPC), have shown the most promising results. Constraints handling and multi-objective management can be explicitly taken into account in MPC. To control large-scale systems, several extensions to standard MPC have been proposed. Firstly, Proper Orthogonal Decomposition (POD-MPC) has been applied to reduce the order the states and computational time. Secondly, a tree-based scheme (TB-MPC) has been proposed to cope with uncertainties of the prediction that are inherently parts of large scale systems. Thirdly, a distributed scheme (DMPC) has been proposed to deal with multiple regions and multiple goals in a computationally tractable way. Simulation experiments on the Dutch water system illustrate that tree-based distributed MPC outperforms feedback control, feedforward control and conventional MPC. Keywords: Model Predictive Control; Proper Orthogonal Decomposition; tree-based control; distributed control; Large Scale Systems;

  19. Model Predictive Control for Automobile Ecological Driving Using Traffic Signal Information

    NASA Astrophysics Data System (ADS)

    Yamaguchi, Daisuke; Kamal, M. A. S.; Mukai, Masakazu; Kawabe, Taketoshi

    This paper presents development of a control system for ecological driving of an automobile. Prediction using traffic signal information is considered to improve the fuel economy. It is assumed that the automobile receives traffic signal information from Intelligent Transportation Systems (ITS). Model predictive control is used to calculate optimal vehicle control inputs using traffic signal information. The performance of the proposed method was analyzed through computer simulation results. It was observed that fuel economy was improved compared with driving of a typical human driving model.

  20. Feasibility study on a perceived fatigue prediction dependent power control for an electrically assisted bicycle.

    PubMed

    Kiryu, T; Minagawa, H

    2013-01-01

    Several types of electric motor assists have been developed, as a result, it is important to control muscular fatigue on-site in terms of health promotion and motor rehabilitation. Predicting the perceived fatigue by several biosignal-related variables with the multiple regression model and polynomial approximation, we try to propose a self control design for the electrically assisted bicycle (EAB). We also determine the meaningful muscles during pedaling by muscle synergies in relation to the motion maturity. In field experiments, prediction of ongoing perceived physical fatigue could have the potential of suitable control of EAB. PMID:24110131

  1. Artificial neural network implementation of a near-ideal error prediction controller

    NASA Technical Reports Server (NTRS)

    Mcvey, Eugene S.; Taylor, Lynore Denise

    1992-01-01

    A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error

  2. Nonlinear Predictive Control of Wind Energy Conversion System Using Dfig with Aerodynamic Torque Observer

    NASA Astrophysics Data System (ADS)

    Kamel, Ouari; Mohand, Ouhrouche; Toufik, Rekioua; Taib, Nabil

    2015-01-01

    In order to improvement of the performances for wind energy conversions systems (WECS), an advanced control techniques must be used. In this paper, as an alternative to conventional PI-type control methods, a nonlinear predictive control (NPC) approach is developed for DFIG-based wind turbine. To enhance the robustness of the controller, a disturbance observer is designed to estimate the aerodynamic torque which is considered as an unknown perturbation. An explicitly analytical form of the optimal predictive controller is given consequently on-line optimization is not necessary The DFIG is fed through the rotor windings by a back-to-back converter controlled by Pulse Width Modulation (PWM), where the stator winding is directly connected to the grid. The presented simulation results show a good performance in trajectory tracking of the proposed strategy and rejection of disturbances is successfully achieved.

  3. Machine learning and predictive data analytics enabling metrology and process control in IC fabrication

    NASA Astrophysics Data System (ADS)

    Rana, Narender; Zhang, Yunlin; Wall, Donald; Dirahoui, Bachir; Bailey, Todd C.

    2015-03-01

    Integrate circuit (IC) technology is going through multiple changes in terms of patterning techniques (multiple patterning, EUV and DSA), device architectures (FinFET, nanowire, graphene) and patterning scale (few nanometers). These changes require tight controls on processes and measurements to achieve the required device performance, and challenge the metrology and process control in terms of capability and quality. Multivariate data with complex nonlinear trends and correlations generally cannot be described well by mathematical or parametric models but can be relatively easily learned by computing machines and used to predict or extrapolate. This paper introduces the predictive metrology approach which has been applied to three different applications. Machine learning and predictive analytics have been leveraged to accurately predict dimensions of EUV resist patterns down to 18 nm half pitch leveraging resist shrinkage patterns. These patterns could not be directly and accurately measured due to metrology tool limitations. Machine learning has also been applied to predict the electrical performance early in the process pipeline for deep trench capacitance and metal line resistance. As the wafer goes through various processes its associated cost multiplies. It may take days to weeks to get the electrical performance readout. Predicting the electrical performance early on can be very valuable in enabling timely actionable decision such as rework, scrap, feedforward, feedback predicted information or information derived from prediction to improve or monitor processes. This paper provides a general overview of machine learning and advanced analytics application in the advanced semiconductor development and manufacturing.

  4. Operational flood control of a low-lying delta system using large time step Model Predictive Control

    NASA Astrophysics Data System (ADS)

    Tian, Xin; van Overloop, Peter-Jules; Negenborn, Rudy R.; van de Giesen, Nick

    2015-01-01

    The safety of low-lying deltas is threatened not only by riverine flooding but by storm-induced coastal flooding as well. For the purpose of flood control, these deltas are mostly protected in a man-made environment, where dikes, dams and other adjustable infrastructures, such as gates, barriers and pumps are widely constructed. Instead of always reinforcing and heightening these structures, it is worth considering making the most of the existing infrastructure to reduce the damage and manage the delta in an operational and overall way. In this study, an advanced real-time control approach, Model Predictive Control, is proposed to operate these structures in the Dutch delta system (the Rhine-Meuse delta). The application covers non-linearity in the dynamic behavior of the water system and the structures. To deal with the non-linearity, a linearization scheme is applied which directly uses the gate height instead of the structure flow as the control variable. Given the fact that MPC needs to compute control actions in real-time, we address issues regarding computational time. A new large time step scheme is proposed in order to save computation time, in which different control variables can have different control time steps. Simulation experiments demonstrate that Model Predictive Control with the large time step setting is able to control a delta system better and much more efficiently than the conventional operational schemes.

  5. Small Body GN&C Research Report: A Robust Model Predictive Control Algorithm with Guaranteed Resolvability

    NASA Technical Reports Server (NTRS)

    Acikmese, Behcet A.; Carson, John M., III

    2005-01-01

    A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees the resolvability of the associated finite-horizon optimal control problem in a receding-horizon implementation. The control consists of two components; (i) feedforward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives, and derivatives in polytopes. An illustrative numerical example is also provided.

  6. A robust model predictive control algorithm for uncertain nonlinear systems that guarantees resolvability

    NASA Technical Reports Server (NTRS)

    Acikmese, Ahmet Behcet; Carson, John M., III

    2006-01-01

    A robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems is developed that guarantees resolvability. With resolvability, initial feasibility of the finite-horizon optimal control problem implies future feasibility in a receding-horizon framework. The control consists of two components; (i) feed-forward, and (ii) feedback part. Feed-forward control is obtained by online solution of a finite-horizon optimal control problem for the nominal system dynamics. The feedback control policy is designed off-line based on a bound on the uncertainty in the system model. The entire controller is shown to be robustly stabilizing with a region of attraction composed of initial states for which the finite-horizon optimal control problem is feasible. The controller design for this algorithm is demonstrated on a class of systems with uncertain nonlinear terms that have norm-bounded derivatives and derivatives in polytopes. An illustrative numerical example is also provided.

  7. PLIO: a generic tool for real-time operational predictive optimal control of water networks.

    PubMed

    Cembrano, G; Quevedo, J; Puig, V; Pérez, R; Figueras, J; Verdejo, J M; Escaler, I; Ramón, G; Barnet, G; Rodríguez, P; Casas, M

    2011-01-01

    This paper presents a generic tool, named PLIO, that allows to implement the real-time operational control of water networks. Control strategies are generated using predictive optimal control techniques. This tool allows the flow management in a large water supply and distribution system including reservoirs, open-flow channels for water transport, water treatment plants, pressurized water pipe networks, tanks, flow/pressure control elements and a telemetry/telecontrol system. Predictive optimal control is used to generate flow control strategies from the sources to the consumer areas to meet future demands with appropriate pressure levels, optimizing operational goals such as network safety volumes and flow control stability. PLIO allows to build the network model graphically and then to automatically generate the model equations used by the predictive optimal controller. Additionally, PLIO can work off-line (in simulation) and on-line (in real-time mode). The case study of Santiago-Chile is presented to exemplify the control results obtained using PLIO off-line (in simulation). PMID:22097020

  8. Predictive-model-based dynamic coordination control strategy for power-split hybrid electric bus

    NASA Astrophysics Data System (ADS)

    Zeng, Xiaohua; Yang, Nannan; Wang, Junnian; Song, Dafeng; Zhang, Nong; Shang, Mingli; Liu, Jianxin

    2015-08-01

    Parameter-matching methods and optimal control strategies of the top-selling hybrid electric vehicle (HEV), namely, power-split HEV, are widely studied. In particular, extant research on control strategy focuses on the steady-state energy management strategy to obtain better fuel economy. However, given that multi-power sources are highly coupled in power-split HEVs and influence one another during mode shifting, conducting research on dynamic coordination control strategy (DCCS) to achieve riding comfort is also important. This paper proposes a predictive-model-based DCCS. First, the dynamic model of the objective power-split HEV is built and the mode shifting process is analyzed based on the developed model to determine the reason for the system shock generated. Engine torque estimation algorithm is then designed according to the principle of the nonlinear observer, and the prediction model of the degree of shock is established based on the theory of model predictive control. Finally, the DCCS with adaptation for a complex driving cycle is realized by combining the feedback control and the predictive model. The presented DCCS is validated on the co-simulation platform of AMESim and Simulink. Results show that the shock during mode shifting is well controlled, thereby improving riding comfort.

  9. Model predictive control of bidirectional isolated DC-DC converter for energy conversion system

    NASA Astrophysics Data System (ADS)

    Akter, Parvez; Uddin, Muslem; Mekhilef, Saad; Tan, Nadia Mei Lin; Akagi, Hirofumi

    2015-08-01

    Model predictive control (MPC) is a powerful and emerging control algorithm in the field of power converters and energy conversion systems. This paper proposes a model predictive algorithm to control the power flow between the high-voltage and low-voltage DC buses of a bidirectional isolated full-bridge DC-DC converter. The predictive control algorithm utilises the discrete nature of the power converters and predicts the future nature of the system, which are compared with the references to calculate the cost function. The switching state that minimises the cost function is selected for firing the converter in the next sampling time period. The proposed MPC bidirectional DC-DC converter is simulated with MATLAB/Simulink and further verified with a 2.5 kW experimental configuration. Both the simulation and experimental results confirm that the proposed MPC algorithm of the DC-DC converter reduces reactive power by avoiding the phase shift between primary and secondary sides of the high-frequency transformer and allow power transfer with unity power factor. Finally, an efficiency comparison is performed between the MPC and dual-phase-shift-based pulse-width modulation controlled DC-DC converter which ensures the effectiveness of the MPC controller.

  10. Implicit theories about willpower predict the activation of a rest goal following self-control exertion.

    PubMed

    Job, Veronika; Bernecker, Katharina; Miketta, Stefanie; Friese, Malte

    2015-10-01

    Past research indicates that peoples' implicit theories about the nature of willpower moderate the ego-depletion effect. Only people who believe or were led to believe that willpower is a limited resource (limited-resource theory) showed lower self-control performance after an initial demanding task. As of yet, the underlying processes explaining this moderating effect by theories about willpower remain unknown. Here, we propose that the exertion of self-control activates the goal to preserve and replenish mental resources (rest goal) in people with a limited-resource theory. Five studies tested this hypothesis. In Study 1, individual differences in implicit theories about willpower predicted increased accessibility of a rest goal after self-control exertion. Furthermore, measured (Study 2) and manipulated (Study 3) willpower theories predicted an increased preference for rest-conducive objects. Finally, Studies 4 and 5 provide evidence that theories about willpower predict actual resting behavior: In Study 4, participants who held a limited-resource theory took a longer break following self-control exertion than participants with a nonlimited-resource theory. Longer resting time predicted decreased rest goal accessibility afterward. In Study 5, participants with an induced limited-resource theory sat longer on chairs in an ostensible product-testing task when they had engaged in a task requiring self-control beforehand. This research provides consistent support for a motivational shift toward rest after self-control exertion in people holding a limited-resource theory about willpower. PMID:26075793

  11. Emotional attentional control predicts changes in diurnal cortisol secretion following exposure to a prolonged psychosocial stressor.

    PubMed

    Lenaert, Bert; Barry, Tom J; Schruers, Koen; Vervliet, Bram; Hermans, Dirk

    2016-01-01

    Hypothalamic-pituitary-adrenal (HPA) axis irregularities have been associated with several psychological disorders. Hence, the identification of individual difference variables that predict variations in HPA-axis activity represents an important challenge for psychiatric research. We investigated whether self-reported attentional control in emotionally demanding situations prospectively predicted changes in diurnal salivary cortisol secretion following exposure to a prolonged psychosocial stressor. Low ability to voluntarily control attention has previously been associated with anxiety and depressive symptomatology. Attentional control was assessed using the Emotional Attentional Control Scale. In students who were preparing for academic examination, salivary cortisol was assessed before (time 1) and after (time 2) examination. Results showed that lower levels of self-reported emotional attentional control at time 1 (N=90) predicted higher absolute diurnal cortisol secretion and a slower decline in cortisol throughout the day at time 2 (N=71). Difficulty controlling attention during emotional experiences may lead to chronic HPA-axis hyperactivity after prolonged exposure to stress. These results indicate that screening for individual differences may foster prediction of HPA-axis disturbances, paving the way for targeted disorder prevention. PMID:26539967

  12. Nonlinear modeling and predictive functional control of Hammerstein system with application to the turntable servo system

    NASA Astrophysics Data System (ADS)

    Zhang, Qian; Wang, Qunjing; Li, Guoli

    2016-05-01

    This article deals with the identification of nonlinear model and Nonlinear Predictive Functional Controller (NPFC) design based on the Hammerstein structure for the turntable servo system. As a mechanism with multi-mass rotational system, nonlinearities significantly influence the system operation, especially when the turntable is in the states of zero-crossing distortion or rapid acceleration/deceleration, etc. The field data from identification experiments are processed by Comprehensive Learning Particle Swarm Optimization (CLPSO). As a result, Hammerstein model can be derived to describe the input-output relationship globally, considering all the linear and nonlinear factors of the turntable system. Cross validation results demonstrate good correspondence between the real equipment and the identified model. In the second part of this manuscript, a nonlinear control strategy based on the genetic algorithm and predictive control is developed. The global nonlinear predictive controller is carried out by two steps: (i) build the linear predictive functional controller with state space equations for the linear subsystem of Hammerstein model, and (ii) optimize the global control variable by minimizing the cost function through genetic algorithm. On the basis of distinguish model for turntable and the effectiveness of NPFC, the good performance of tracking ability is achieved in the simulation results.

  13. Model Predictive Control application for real time operation of controlled structures for the Water Authority Noorderzijlvest, The Netherlands

    NASA Astrophysics Data System (ADS)

    van Heeringen, Klaas-Jan; Gooijer, Jan; Knot, Floris; Talsma, Jan

    2015-04-01

    In the Netherlands, flood protection has always been a key issue to protect settlements against storm surges and riverine floods. Whereas flood protection traditionally focused on structural measures, nowadays the availability of meteorological and hydrological forecasts enable the application of more advanced real-time control techniques for operating the existing hydraulic infrastructure in an anticipatory and more efficient way. Model Predictive Control (MPC) is a powerful technique to derive optimal control variables with the help of model based predictions evaluated against a control objective. In a project for the regional water authority Noorderzijlvest in the north of the Netherlands, it has been shown that MPC can increase the safety level of the system during flood events by an anticipatory pre-release of water. Furthermore, energy costs of pumps can be reduced by making tactical use of the water storage and shifting pump activities during normal operating conditions to off-peak hours. In this way cheap energy is used in combination of gravity flow through gates during low tide periods. MPC has now been implemented for daily operational use of the whole water system of the water authority Noorderzijlvest. The system developed to a real time decision support system which not only supports the daily operation but is able to directly implement the optimal control settings at the structures. We explain how we set-up and calibrated a prediction model (RTC-Tools) that is accurate and fast enough for optimization purposes, and how we integrated it in the operational flood early warning system (Delft-FEWS). Beside the prediction model, the weights and the factors of the objective function are an important element of MPC, since they shape the control objective. We developed special features in Delft-FEWS to allow the operators to adjust the objective function in order to meet changing requirements and to evaluate different control strategies.

  14. Model predictive control of non-linear systems over networks with data quantization and packet loss.

    PubMed

    Yu, Jimin; Nan, Liangsheng; Tang, Xiaoming; Wang, Ping

    2015-11-01

    This paper studies the approach of model predictive control (MPC) for the non-linear systems under networked environment where both data quantization and packet loss may occur. The non-linear controlled plant in the networked control system (NCS) is represented by a Tagaki-Sugeno (T-S) model. The sensed data and control signal are quantized in both links and described as sector bound uncertainties by applying sector bound approach. Then, the quantized data are transmitted in the communication networks and may suffer from the effect of packet losses, which are modeled as Bernoulli process. A fuzzy predictive controller which guarantees the stability of the closed-loop system is obtained by solving a set of linear matrix inequalities (LMIs). A numerical example is given to illustrate the effectiveness of the proposed method. PMID:26341070

  15. LMI-Based Generation of Feedback Laws for a Robust Model Predictive Control Algorithm

    NASA Technical Reports Server (NTRS)

    Acikmese, Behcet; Carson, John M., III

    2007-01-01

    This technical note provides a mathematical proof of Corollary 1 from the paper 'A Nonlinear Model Predictive Control Algorithm with Proven Robustness and Resolvability' that appeared in the 2006 Proceedings of the American Control Conference. The proof was omitted for brevity in the publication. The paper was based on algorithms developed for the FY2005 R&TD (Research and Technology Development) project for Small-body Guidance, Navigation, and Control [2].The framework established by the Corollary is for a robustly stabilizing MPC (model predictive control) algorithm for uncertain nonlinear systems that guarantees the resolvability of the associated nite-horizon optimal control problem in a receding-horizon implementation. Additional details of the framework are available in the publication.

  16. Validation of engineering methods for predicting hypersonic vehicle controls forces and moments

    NASA Technical Reports Server (NTRS)

    Maughmer, M.; Straussfogel, D.; Long, L.; Ozoroski, L.

    1991-01-01

    This work examines the ability of the aerodynamic analysis methods contained in an industry standard conceptual design code, the Aerodynamic Preliminary Analysis System (APAS II), to estimate the forces and moments generated through control surface deflections from low subsonic to high hypersonic speeds. Predicted control forces and moments generated by various control effectors are compared with previously published wind-tunnel and flight-test data for three vehicles: the North American X-15, a hypersonic research airplane concept, and the Space Shuttle Orbiter. Qualitative summaries of the results are given for each force and moment coefficient and each control derivative in the various speed ranges. Results show that all predictions of longitudinal stability and control derivatives are acceptable for use at the conceptual design stage.

  17. Predicting Time Series Outputs and Time-to-Failure for an Aircraft Controller Using Bayesian Modeling

    NASA Technical Reports Server (NTRS)

    He, Yuning

    2015-01-01

    Safety of unmanned aerial systems (UAS) is paramount, but the large number of dynamically changing controller parameters makes it hard to determine if the system is currently stable, and the time before loss of control if not. We propose a hierarchical statistical model using Treed Gaussian Processes to predict (i) whether a flight will be stable (success) or become unstable (failure), (ii) the time-to-failure if unstable, and (iii) time series outputs for flight variables. We first classify the current flight input into success or failure types, and then use separate models for each class to predict the time-to-failure and time series outputs. As different inputs may cause failures at different times, we have to model variable length output curves. We use a basis representation for curves and learn the mappings from input to basis coefficients. We demonstrate the effectiveness of our prediction methods on a NASA neuro-adaptive flight control system.

  18. Generalized minimum variance control under long-range prediction horizon setups.

    PubMed

    Silveira, Antonio; Trentini, Rodrigo; Coelho, Antonio; Kutzner, Rüdiger; Hofmann, Lutz

    2016-05-01

    This paper presents the design and evaluation of a minimal order Generalized Minimum Variance controller with long-range prediction horizon and how it affects the controller and plant output variances. This study investigates how the increased prediction horizon can contribute to mitigate stochastic disturbances and attenuate oscillations. In order to design high order prediction minimum variance filters, a design procedure independent of the Diophantine Equation solution is used. The evaluation is conducted through simulations and practical essays with two different plants: a first order water flow rate problem and a second order under-damped electronic circuit. Both problems are assessed under an incremental control scheme and based on identified stochastic models. Also, two optimal tuning procedures for the algorithm are proposed. PMID:26899555

  19. Multi input single output model predictive control of non-linear bio-polymerization process

    NASA Astrophysics Data System (ADS)

    Arumugasamy, Senthil Kumar; Ahmad, Z.

    2015-05-01

    This paper focuses on Multi Input Single Output (MISO) Model Predictive Control of bio-polymerization process in which mechanistic model is developed and linked with the feedforward neural network model to obtain a hybrid model (Mechanistic-FANN) of lipase-catalyzed ring-opening polymerization of ɛ-caprolactone (ɛ-CL) for Poly (ɛ-caprolactone) production. In this research, state space model was used, in which the input to the model were the reactor temperatures and reactor impeller speeds and the output were the molecular weight of polymer (Mn) and polymer polydispersity index. State space model for MISO created using System identification tool box of Matlab™. This state space model is used in MISO MPC. Model predictive control (MPC) has been applied to predict the molecular weight of the biopolymer and consequently control the molecular weight of biopolymer. The result shows that MPC is able to track reference trajectory and give optimum movement of manipulated variable.

  20. Multi input single output model predictive control of non-linear bio-polymerization process

    SciTech Connect

    Arumugasamy, Senthil Kumar; Ahmad, Z.

    2015-05-15

    This paper focuses on Multi Input Single Output (MISO) Model Predictive Control of bio-polymerization process in which mechanistic model is developed and linked with the feedforward neural network model to obtain a hybrid model (Mechanistic-FANN) of lipase-catalyzed ring-opening polymerization of ε-caprolactone (ε-CL) for Poly (ε-caprolactone) production. In this research, state space model was used, in which the input to the model were the reactor temperatures and reactor impeller speeds and the output were the molecular weight of polymer (M{sub n}) and polymer polydispersity index. State space model for MISO created using System identification tool box of Matlab™. This state space model is used in MISO MPC. Model predictive control (MPC) has been applied to predict the molecular weight of the biopolymer and consequently control the molecular weight of biopolymer. The result shows that MPC is able to track reference trajectory and give optimum movement of manipulated variable.

  1. Real time simulation of nonlinear generalized predictive control for wind energy conversion system with nonlinear observer.

    PubMed

    Ouari, Kamel; Rekioua, Toufik; Ouhrouche, Mohand

    2014-01-01

    In order to make a wind power generation truly cost-effective and reliable, an advanced control techniques must be used. In this paper, we develop a new control strategy, using nonlinear generalized predictive control (NGPC) approach, for DFIG-based wind turbine. The proposed control law is based on two points: NGPC-based torque-current control loop generating the rotor reference voltage and NGPC-based speed control loop that provides the torque reference. In order to enhance the robustness of the controller, a disturbance observer is designed to estimate the aerodynamic torque which is considered as an unknown perturbation. Finally, a real-time simulation is carried out to illustrate the performance of the proposed controller. PMID:24021543

  2. Can the annual flood control volume at Three Gorges Dam be predicted to size a variable flood control pool?

    NASA Astrophysics Data System (ADS)

    DONG, Q.; Lall, U.

    2014-12-01

    We consider the empirical prediction of the peak flood volume on the Yangtze River at the Three Gorges Dam. The dam is operated for flood control, hydropower production and irrigation. The flood control space reserved in the reservoir each year during the monsoon season limits the ability to supply hydropower and irrigation services. Allocating a variable amount of flood control space based on a pre-season forecast of the peak event flood volume, or of the flood volume over a specific duration is consequently, more useful than a prediction of the annual maximum peak flow for this dam and for other flood control dams. The joint distribution of annual peak flow, the corresponding flood volume, and the event duration is investigated based on the copula theory. A statistical model is developed for the conditional prediction of this joint distribution using pre-season climate indicators. The potential for the guidance for water management in the Yangtze River basin and for insights to the design of the large flood control reservoirs in the future is illustrated.

  3. Predicting Human Error in Air Traffic Control Decision Support Tools and Free Flight Concepts

    NASA Technical Reports Server (NTRS)

    Mogford, Richard; Kopardekar, Parimal

    2001-01-01

    The document is a set of briefing slides summarizing the work the Advanced Air Transportation Technologies (AATT) Project is doing on predicting air traffic controller and airline pilot human error when using new decision support software tools and when involved in testing new air traffic control concepts. Previous work in this area is reviewed as well as research being done jointly with the FAA. Plans for error prediction work in the AATT Project are discussed. The audience is human factors researchers and aviation psychologists from government and industry.

  4. Optimized Treatment of Fibromyalgia Using System Identification and Hybrid Model Predictive Control

    PubMed Central

    Deshpande, Sunil; Nandola, Naresh N.; Rivera, Daniel E.; Younger, Jarred W.

    2014-01-01

    The term adaptive intervention is used in behavioral health to describe individually-tailored strategies for preventing and treating chronic, relapsing disorders. This paper describes a system identification approach for developing dynamical models from clinical data, and subsequently, a hybrid model predictive control scheme for assigning dosages of naltrexone as treatment for fibromyalgia, a chronic pain condition. A simulation study that includes conditions of significant plant-model mismatch demonstrates the benefits of hybrid predictive control as a decision framework for optimized adaptive interventions. This work provides insights on the design of novel personalized interventions for chronic pain and related conditions in behavioral health. PMID:25506132

  5. The interplay of maternal sensitivity and gentle control when predicting children's subsequent academic functioning: Evidence of mediation by effortful control.

    PubMed

    Kopystynska, Olena; Spinrad, Tracy L; Seay, Danielle M; Eisenberg, Nancy

    2016-06-01

    The goal of this work was to examine the complex interrelation of mothers' early gentle control and sensitivity in predicting children's effortful control (EC) and academic functioning. Maternal gentle control, maternal sensitivity, and children's EC were measured when children were 18, 30, and 42 months of age (T1, T2, and T3, respectively), and measures of children's academic functioning were combined across 72 and 84 months (T5/T6; Ns = 255, 222, 200, 162, and 143). Using structural equation modeling, results demonstrated that T1 maternal sensitivity moderated the relation between T1 maternal gentle control and T2 EC, and T3 EC predicted children's later academic functioning. There was evidence for moderated mediation, such that when maternal sensitivity was high, children's EC mediated the relation between T1 maternal gentle control and children's academic functioning, even after controlling for stability of the constructs. The relation between maternal gentle control and children's EC was not significant under conditions of low maternal sensitivity. Implications for parenting programs are offered and future research directions are discussed. (PsycINFO Database Record PMID:27228451

  6. Offset-Free Model Predictive Control of Open Water Channel Based on Moving Horizon Estimation

    NASA Astrophysics Data System (ADS)

    Ekin Aydin, Boran; Rutten, Martine

    2016-04-01

    Model predictive control (MPC) is a powerful control option which is increasingly used by operational water managers for managing water systems. The explicit consideration of constraints and multi-objective management are important features of MPC. However, due to the water loss in open water systems by seepage, leakage and evaporation a mismatch between the model and the real system will be created. These mismatch affects the performance of MPC and creates an offset from the reference set point of the water level. We present model predictive control based on moving horizon estimation (MHE-MPC) to achieve offset free control of water level for open water canals. MHE-MPC uses the past predictions of the model and the past measurements of the system to estimate unknown disturbances and the offset in the controlled water level is systematically removed. We numerically tested MHE-MPC on an accurate hydro-dynamic model of the laboratory canal UPC-PAC located in Barcelona. In addition, we also used well known disturbance modeling offset free control scheme for the same test case. Simulation experiments on a single canal reach show that MHE-MPC outperforms disturbance modeling offset free control scheme.

  7. Urinary Bromotyrosine Measures Asthma Control and Predicts Asthma Exacerbations in Children

    PubMed Central

    Wedes, Samuel H.; Wu, Weijia; Comhair, Suzy A. A.; McDowell, Karen M.; DiDonato, Joseph A.; Erzurum, Serpil C.; Hazen, Stanley L.

    2012-01-01

    Objectives To determine the usefulness of urinary bromotyrosine, a noninvasive marker of eosinophil-catalyzed protein oxidation, in tracking with indexes of asthma control and in predicting future asthma exacerbations in children. Study design Children with asthma were recruited consecutively at the time of clinic visit. Urine was obtained, along with spirometry, exhaled nitric oxide, and Asthma Control Questionnaire data. Follow-up phone calls were made 6 weeks after enrollment. Results Fifty-seven participants were enrolled. Urinary bromotyrosine levels tracked significantly with indexes of asthma control as assessed by Asthma Control Questionnaire scores at baseline (R = 0.38, P = .004) and follow-up (R = 0.39, P = .008). Participants with high baseline levels of bromotyrosine were 18.1-fold (95% CI 2.1–153.1, P = .0004) more likely to have inadequately controlled asthma and 4.0-fold more likely (95% CI 1.1–14.7, P = .03) to have an asthma exacerbation (unexpected emergency department visit; doctor’s appointment or phone call; oral or parenteral corticosteroid burst; acute asthma-related respiratory symptoms) over the ensuing 6 weeks. Exhaled nitric oxide levels did not track with Asthma Control Questionnaire data; and immunoglobulin E, eosinophil count, spirometry, and exhaled nitric oxide levels failed to predict asthma exacerbations. Conclusions Urinary bromotyrosine tracks with asthma control and predicts the risk of future asthma exacerbations in children. PMID:21392781

  8. A gradient of childhood self-control predicts health, wealth, and public safety

    PubMed Central

    Moffitt, Terrie E.; Arseneault, Louise; Belsky, Daniel; Dickson, Nigel; Hancox, Robert J.; Harrington, HonaLee; Houts, Renate; Poulton, Richie; Roberts, Brent W.; Ross, Stephen; Sears, Malcolm R.; Thomson, W. Murray; Caspi, Avshalom

    2011-01-01

    Policy-makers are considering large-scale programs aimed at self-control to improve citizens’ health and wealth and reduce crime. Experimental and economic studies suggest such programs could reap benefits. Yet, is self-control important for the health, wealth, and public safety of the population? Following a cohort of 1,000 children from birth to the age of 32 y, we show that childhood self-control predicts physical health, substance dependence, personal finances, and criminal offending outcomes, following a gradient of self-control. Effects of children's self-control could be disentangled from their intelligence and social class as well as from mistakes they made as adolescents. In another cohort of 500 sibling-pairs, the sibling with lower self-control had poorer outcomes, despite shared family background. Interventions addressing self-control might reduce a panoply of societal costs, save taxpayers money, and promote prosperity. PMID:21262822

  9. Neural Network-Based Resistance Spot Welding Control and Quality Prediction

    SciTech Connect

    Allen, J.D., Jr.; Ivezic, N.D.; Zacharia, T.

    1999-07-10

    This paper describes the development and evaluation of neural network-based systems for industrial resistance spot welding process control and weld quality assessment. The developed systems utilize recurrent neural networks for process control and both recurrent networks and static networks for quality prediction. The first section describes a system capable of both welding process control and real-time weld quality assessment, The second describes the development and evaluation of a static neural network-based weld quality assessment system that relied on experimental design to limit the influence of environmental variability. Relevant data analysis methods are also discussed. The weld classifier resulting from the analysis successfldly balances predictive power and simplicity of interpretation. The results presented for both systems demonstrate clearly that neural networks can be employed to address two significant problems common to the resistance spot welding industry, control of the process itself, and non-destructive determination of resulting weld quality.

  10. Toddler Inhibitory Control, Bold Response to Novelty, and Positive Affect Predict Externalizing Symptoms in Kindergarten

    PubMed Central

    Buss, Kristin A.; Kiel, Elizabeth J.; Morales, Santiago; Robinson, Emily

    2013-01-01

    Poor inhibitory control and bold-approach have been found to predict the development of externalizing behavior problems in young children. Less research has examined how positive affect may influence the development of externalizing behavior in the context of low inhibitory control and high approach. We used a multimethod approach to examine how observed toddler inhibitory control, bold-approach, and positive affect predicted externalizing outcomes (observed, adult- and self-reported) in additive and interactive ways at the beginning of kindergarten. 24-month-olds (N = 110) participated in a laboratory visit and 84 were followed up in kindergarten for externalizing behaviors. Overall, children who were low in inhibitory control, high in bold-approach, and low in positive affect at 24-months of age were at greater risk for externalizing behaviors during kindergarten. PMID:25018589

  11. Nonlinear Recurrent Neural Network Predictive Control for Energy Distribution of a Fuel Cell Powered Robot

    PubMed Central

    Chen, Qihong; Long, Rong; Quan, Shuhai

    2014-01-01

    This paper presents a neural network predictive control strategy to optimize power distribution for a fuel cell/ultracapacitor hybrid power system of a robot. We model the nonlinear power system by employing time variant auto-regressive moving average with exogenous (ARMAX), and using recurrent neural network to represent the complicated coefficients of the ARMAX model. Because the dynamic of the system is viewed as operating- state- dependent time varying local linear behavior in this frame, a linear constrained model predictive control algorithm is developed to optimize the power splitting between the fuel cell and ultracapacitor. The proposed algorithm significantly simplifies implementation of the controller and can handle multiple constraints, such as limiting substantial fluctuation of fuel cell current. Experiment and simulation results demonstrate that the control strategy can optimally split power between the fuel cell and ultracapacitor, limit the change rate of the fuel cell current, and so as to extend the lifetime of the fuel cell. PMID:24707206

  12. Predictive and reinforcement learning for magneto-hydrodynamic control of hypersonic flows

    NASA Astrophysics Data System (ADS)

    Kulkarni, Nilesh Vijay

    Increasing needs for autonomy in future aerospace systems and immense progress in computing technology have motivated the development of on-line adaptive control techniques to account for modeling errors, changes in system dynamics, and faults occurring during system operation. After extensive treatment of the inner-loop adaptive control dealing mainly with stable adaptation towards desired transient behavior, adaptive optimal control has started receiving attention in literature. Motivated by the problem of optimal control of the magneto-hydrodynamic (MHD) generator at the inlet of the scramjet engine of a hypersonic flight vehicle, this thesis treats the general problem of efficiently combining off-line and on-line optimal control methods. The predictive control approach is chosen as the off-line method for designing optimal controllers using all the existing system knowledge. This controller is then adapted on-line using policy-iteration-based Q-learning, which is a stable model-free reinforcement learning approach. The combined approach is first illustrated in the optimal control of linear systems, which helps in the analysis as well as the validation of the method. A novel neural-networks-based parametric predictive control approach is then designed for the off-line optimal control of non-linear systems. The off-line approach is illustrated by applications to aircraft and spacecraft systems. This is followed by an extensive treatment of the off-line optimal control of the MHD generator using this neuro-control approach. On-line adaptation of the controller is implemented using several novel schemes derived from the policy-iteration-based Q-learning. The implementation results demonstrate the success of these on-line algorithms for adapting towards modeling errors in the off-line design.

  13. A new methane control and prediction software suite for longwall mines

    NASA Astrophysics Data System (ADS)

    Dougherty, Heather N.; Özgen Karacan, C.

    2011-09-01

    This paper presents technical and application aspects of a new software suite, MCP (Methane Control and Prediction), developed for addressing some of the methane and methane control issues in longwall coal mines. The software suite consists of dynamic link library (DLL) extensions to MS-Access TM, written in C++. In order to create the DLLs, various statistical, mathematical approaches, prediction and classification artificial neural network (ANN) methods were used. The current version of MCP suite (version 1.3) discussed in this paper has four separate modules that (a) predict the dynamic elastic properties of coal-measure rocks, (b) predict ventilation emissions from longwall mines, (c) determine the type of degasification system that needs to be utilized for given situations and (d) assess the production performance of gob gas ventholes that are used to extract methane from longwall gobs. These modules can be used with the data from basic logs, mining, longwall panel, productivity, and coal bed characteristics. The applications of these modules separately or in combination for methane capture and control related problems will help improve the safety of mines. The software suite's version 1.3 is discussed in this paper. Currently, it's new version 2.0 is available and can be downloaded from http://www.cdc.gov/niosh/mining/products/product180.htm free of charge. The models discussed in this paper can be found under "ancillary models" and under "methane prediction models" for specific U.S. conditions in the new version.

  14. An efficient artificial bee colony algorithm with application to nonlinear predictive control

    NASA Astrophysics Data System (ADS)

    Ait Sahed, Oussama; Kara, Kamel; Benyoucef, Abousoufyane; Laid Hadjili, Mohamed

    2016-05-01

    In this paper a constrained nonlinear predictive control algorithm, that uses the artificial bee colony (ABC) algorithm to solve the optimization problem, is proposed. The main objective is to derive a simple and efficient control algorithm that can solve the nonlinear constrained optimization problem with minimal computational time. Indeed, a modified version, enhancing the exploring and the exploitation capabilities, of the ABC algorithm is proposed and used to design a nonlinear constrained predictive controller. This version allows addressing the premature and the slow convergence drawbacks of the standard ABC algorithm, using a modified search equation, a well-known organized distribution mechanism for the initial population and a new equation for the limit parameter. A convergence statistical analysis of the proposed algorithm, using some well-known benchmark functions is presented and compared with several other variants of the ABC algorithm. To demonstrate the efficiency of the proposed algorithm in solving engineering problems, the constrained nonlinear predictive control of the model of a Multi-Input Multi-Output industrial boiler is considered. The control performances of the proposed ABC algorithm-based controller are also compared to those obtained using some variants of the ABC algorithms.

  15. Lateral prefrontal cortex activity during cognitive control of emotion predicts response to social stress in schizophrenia

    PubMed Central

    Tully, Laura M.; Lincoln, Sarah Hope; Hooker, Christine I.

    2014-01-01

    LPFC dysfunction is a well-established neural impairment in schizophrenia and is associated with worse symptoms. However, how LPFC activation influences symptoms is unclear. Previous findings in healthy individuals demonstrate that lateral prefrontal cortex (LPFC) activation during cognitive control of emotional information predicts mood and behavior in response to interpersonal conflict, thus impairments in these processes may contribute to symptom exacerbation in schizophrenia. We investigated whether schizophrenia participants show LPFC deficits during cognitive control of emotional information, and whether these LPFC deficits prospectively predict changes in mood and symptoms following real-world interpersonal conflict. During fMRI, 23 individuals with schizophrenia or schizoaffective disorder and 24 healthy controls completed the Multi-Source Interference Task superimposed on neutral and negative pictures. Afterwards, schizophrenia participants completed a 21-day online daily-diary in which they rated the extent to which they experienced mood and schizophrenia-spectrum symptoms, as well as the occurrence and response to interpersonal conflict. Schizophrenia participants had lower dorsal LPFC activity (BA9) during cognitive control of task-irrelevant negative emotional information. Within schizophrenia participants, DLPFC activity during cognitive control of emotional information predicted changes in positive and negative mood on days following highly distressing interpersonal conflicts. Results have implications for understanding the specific role of LPFC in response to social stress in schizophrenia, and suggest that treatments targeting LPFC-mediated cognitive control of emotion could promote adaptive response to social stress in schizophrenia. PMID:25379415

  16. Online elicitation of Mamdani-type fuzzy rules via TSK-based generalized predictive control.

    PubMed

    Mahfouf, M; Abbod, M F; Linkens, D A

    2003-01-01

    Many synergies have been proposed between soft-computing techniques, such as neural networks (NNs), fuzzy logic (FL), and genetic algorithms (GAs), which have shown that such hybrid structures can work well and also add more robustness to the control system design. In this paper, a new control architecture is proposed whereby the on-line generated fuzzy rules relating to the self-organizing fuzzy logic controller (SOFLC) are obtained via integration with the popular generalized predictive control (GPC) algorithm using a Takagi-Sugeno-Kang (TSK)-based controlled autoregressive integrated moving average (CARIMA) model structure. In this approach, GPC replaces the performance index (PI) table which, as an incremental model, is traditionally used to discover, amend, and delete the rules. Because the GPC sequence is computed using predicted future outputs, the new hybrid approach rewards the time-delay very well. The new generic approach, named generalized predictive self-organizing fuzzy logic control (GPSOFLC), is simulated on a well-known nonlinear chemical process, the distillation column, and is shown to produce an effective fuzzy rule-base in both qualitative (minimum number of generated rules) and quantitative (good rules) terms. PMID:18238192

  17. Effective variable switching point predictive current control for ac low-voltage drives

    NASA Astrophysics Data System (ADS)

    Stolze, Peter; Karamanakos, Petros; Kennel, Ralph; Manias, Stefanos; Endisch, Christian

    2015-07-01

    This paper presents an effective model predictive current control scheme for induction machines driven by a three-level neutral point clamped inverter, called variable switching point predictive current control. Despite the fact that direct, enumeration-based model predictive control (MPC) strategies are very popular in the field of power electronics due to their numerous advantages such as design simplicity and straightforward implementation procedure, they carry two major drawbacks. These are the increased computational effort and the high ripples on the controlled variables, resulting in a limited applicability of such methods. The high ripples occur because in direct MPC algorithms the actuating variable can only be changed at the beginning of a sampling interval. A possible remedy for this would be to change the applied control input within the sampling interval, and thus to apply it for a shorter time than one sample. However, since such a solution would lead to an additional overhead which is crucial especially for multilevel inverters, a heuristic preselection of the optimal control action is adopted to keep the computational complexity at bay. Experimental results are provided to verify the potential advantages of the proposed strategy.

  18. Prediction of force and acceleration control spectra for Space Shuttle orbiter sidewall-mounted payloads

    NASA Technical Reports Server (NTRS)

    Hipol, Philip J.

    1990-01-01

    The development of force and acceleration control spectra for vibration testing of Space Shuttle (STS) orbiter sidewall-mounted payloads requiresreliable estimates of the sidewall apparent weight and free (i.e. unloaded) vibration during lift-off. The feasibility of analytically predicting these quantities has been investigated through the development and analysis of a finite element model of the STS cargo bay. Analytical predictions of the sidewall apparent weight were compared with apparent weight measurements made on OV-101, and analytical predictions of the sidewall free vibration response during lift-off were compared with flight measurements obtained from STS-3 and STS-4. These analysis suggest that the cargo bay finite element model has potential application for the estimation of force and acceleration control spectra for STS sidewall-mounted payloads.

  19. Adaptive Control of the Packet Transmission Period with Solar Energy Harvesting Prediction in Wireless Sensor Networks

    PubMed Central

    Kwon, Kideok; Yang, Jihoon; Yoo, Younghwan

    2015-01-01

    A number of research works has studied packet scheduling policies in energy scavenging wireless sensor networks, based on the predicted amount of harvested energy. Most of them aim to achieve energy neutrality, which means that an embedded system can operate perpetually while meeting application requirements. Unlike other renewable energy sources, solar energy has the feature of distinct periodicity in the amount of harvested energy over a day. Using this feature, this paper proposes a packet transmission control policy that can enhance the network performance while keeping sensor nodes alive. Furthermore, this paper suggests a novel solar energy prediction method that exploits the relation between cloudiness and solar radiation. The experimental results and analyses show that the proposed packet transmission policy outperforms others in terms of the deadline miss rate and data throughput. Furthermore, the proposed solar energy prediction method can predict more accurately than others by 6.92%. PMID:25919372

  20. Adaptive control of the packet transmission period with solar energy harvesting prediction in wireless sensor networks.

    PubMed

    Kwon, Kideok; Yang, Jihoon; Yoo, Younghwan

    2015-01-01

    A number of research works has studied packet scheduling policies in energy scavenging wireless sensor networks, based on the predicted amount of harvested energy. Most of them aim to achieve energy neutrality, which means that an embedded system can operate perpetually while meeting application requirements. Unlike other renewable energy sources, solar energy has the feature of distinct periodicity in the amount of harvested energy over a day. Using this feature, this paper proposes a packet transmission control policy that can enhance the network performance while keeping sensor nodes alive. Furthermore, this paper suggests a novel solar energy prediction method that exploits the relation between cloudiness and solar radiation. The experimental results and analyses show that the proposed packet transmission policy outperforms others in terms of the deadline miss rate and data throughput. Furthermore, the proposed solar energy prediction method can predict more accurately than others by 6.92%. PMID:25919372

  1. Development of advanced stability theory suction prediction techniques for laminar flow control. [on swept wings

    NASA Technical Reports Server (NTRS)

    Srokowski, A. J.

    1978-01-01

    The problem of obtaining accurate estimates of suction requirements on swept laminar flow control wings was discussed. A fast accurate computer code developed to predict suction requirements by integrating disturbance amplification rates was described. Assumptions and approximations used in the present computer code are examined in light of flow conditions on the swept wing which may limit their validity.

  2. The Ability of Psychological Flexibility and Job Control to Predict Learning, Job Performance, and Mental Health

    ERIC Educational Resources Information Center

    Bond, Frank W.; Flaxman, Paul E.

    2006-01-01

    This longitudinal study tested the degree to which an individual characteristic, psychological flexibility, and a work organization variable, job control, predicted ability to learn new skills at work, job performance, and mental health, amongst call center workers in the United Kingdom (N = 448). As hypothesized, results indicated that job…

  3. How Minimal Grade Goals and Self-Control Capacity Interact in Predicting Test Grades

    ERIC Educational Resources Information Center

    Bertrams, Alex

    2012-01-01

    The present research examined the prediction of school students' grades in an upcoming math test via their minimal grade goals (i.e., the minimum grade in an upcoming test one would be satisfied with). Due to its significance for initiating and maintaining goal-directed behavior, self-control capacity was expected to moderate the relation between…

  4. Demonstration of leapfrogging for implementing nonlinear model predictive control on a heat exchanger.

    PubMed

    Sridhar, Upasana Manimegalai; Govindarajan, Anand; Rhinehart, R Russell

    2016-01-01

    This work reveals the applicability of a relatively new optimization technique, Leapfrogging, for both nonlinear regression modeling and a methodology for nonlinear model-predictive control. Both are relatively simple, yet effective. The application on a nonlinear, pilot-scale, shell-and-tube heat exchanger reveals practicability of the techniques. PMID:26606850

  5. Parenting and Child "DRD4" Genotype Interact to Predict Children's Early Emerging Effortful Control

    ERIC Educational Resources Information Center

    Smith, Heather J.; Sheikh, Haroon I.; Dyson, Margaret W.; Olino, Thomas M.; Laptook, Rebecca S.; Durbin, C. Emily; Hayden, Elizabeth P.; Singh, Shiva M.; Klein, Daniel N.

    2012-01-01

    Effortful control (EC), or the trait-like capacity to regulate dominant responses, has important implications for children's development. Although genetic factors and parenting likely influence EC, few studies have examined whether they interact to predict its development. This study examined whether the "DRD4" exon III variable number tandem…

  6. Predicting Young Children's Externalizing Problems: Interactions among Effortful Control, Parenting, and Child Gender

    ERIC Educational Resources Information Center

    Karreman, Annemiek; van Tuijl, Cathy; van Aken, Marcel A. G.; Dekovi, Maja

    2009-01-01

    This study investigated interactions between observed temperamental effortful control and observed parenting in the prediction of externalizing problems. Child gender effects on these relations were examined. The relations were examined concurrently when the child was 3 years old and longitudinally at 4.5 years. The sample included 89 two-parent…

  7. Predictive Value of Morphological Features in Patients with Autism versus Normal Controls

    ERIC Educational Resources Information Center

    Ozgen, H.; Hellemann, G. S.; de Jonge, M. V.; Beemer, F. A.; van Engeland, H.

    2013-01-01

    We investigated the predictive power of morphological features in 224 autistic patients and 224 matched-pairs controls. To assess the relationship between the morphological features and autism, we used the receiver operator curves (ROC). In addition, we used recursive partitioning (RP) to determine a specific pattern of abnormalities that is…

  8. Adaptive cruise control with stop&go function using the state-dependent nonlinear model predictive control approach.

    PubMed

    Shakouri, Payman; Ordys, Andrzej; Askari, Mohamad R

    2012-09-01

    In the design of adaptive cruise control (ACC) system two separate control loops - an outer loop to maintain the safe distance from the vehicle traveling in front and an inner loop to control the brake pedal and throttle opening position - are commonly used. In this paper a different approach is proposed in which a single control loop is utilized. The objective of the distance tracking is incorporated into the single nonlinear model predictive control (NMPC) by extending the original linear time invariant (LTI) models obtained by linearizing the nonlinear dynamic model of the vehicle. This is achieved by introducing the additional states corresponding to the relative distance between leading and following vehicles, and also the velocity of the leading vehicle. Control of the brake and throttle position is implemented by taking the state-dependent approach. The model demonstrates to be more effective in tracking the speed and distance by eliminating the necessity of switching between the two controllers. It also offers smooth variation in brake and throttle controlling signal which subsequently results in a more uniform acceleration of the vehicle. The results of proposed method are compared with other ACC systems using two separate control loops. Furthermore, an ACC simulation results using a stop&go scenario are shown, demonstrating a better fulfillment of the design requirements. PMID:22704362

  9. Higher Self-Control Capacity Predicts Lower Anxiety-Impaired Cognition during Math Examinations

    PubMed Central

    Bertrams, Alex; Baumeister, Roy F.; Englert, Chris

    2016-01-01

    We assumed that self-control capacity, self-efficacy, and self-esteem would enable students to keep attentional control during tests. Therefore, we hypothesized that the three personality traits would be negatively related to anxiety-impaired cognition during math examinations. Secondary school students (N = 158) completed measures of self-control capacity, self-efficacy, and self-esteem at the beginning of the school year. Five months later, anxiety-impaired cognition during math examinations was assessed. Higher self-control capacity, but neither self-efficacy nor self-esteem, predicted lower anxiety-impaired cognition 5 months later, over and above baseline anxiety-impaired cognition. Moreover, self-control capacity was indirectly related to math grades via anxiety-impaired cognition. The findings suggest that improving self-control capacity may enable students to deal with anxiety-related problems during school tests. PMID:27065013

  10. Higher Self-Control Capacity Predicts Lower Anxiety-Impaired Cognition during Math Examinations.

    PubMed

    Bertrams, Alex; Baumeister, Roy F; Englert, Chris

    2016-01-01

    We assumed that self-control capacity, self-efficacy, and self-esteem would enable students to keep attentional control during tests. Therefore, we hypothesized that the three personality traits would be negatively related to anxiety-impaired cognition during math examinations. Secondary school students (N = 158) completed measures of self-control capacity, self-efficacy, and self-esteem at the beginning of the school year. Five months later, anxiety-impaired cognition during math examinations was assessed. Higher self-control capacity, but neither self-efficacy nor self-esteem, predicted lower anxiety-impaired cognition 5 months later, over and above baseline anxiety-impaired cognition. Moreover, self-control capacity was indirectly related to math grades via anxiety-impaired cognition. The findings suggest that improving self-control capacity may enable students to deal with anxiety-related problems during school tests. PMID:27065013

  11. Mixed H2/H∞ robust model predictive control with saturated inputs

    NASA Astrophysics Data System (ADS)

    Huang, He; Li, Dewei; Xi, Yugeng

    2014-12-01

    In this paper, we investigate the mixed H2/H∞ robust model predictive control (RMPC) for polytopic uncertain systems, which refers to the infinite horizon optimal guaranteed cost control (OGCC). To fully use the capability of actuators, we adopt a saturating feedback control law as the control strategy of RMPC. As the saturating feedback control law can be effectively represented by the convex hull of a group of auxiliary linear feedback laws, the auxiliary feedback laws allow us to design the actual feedback control law without consideration of the input constraints directly to achieve the improved performance. Moreover, we suggest the relative weights on the actual and auxiliary feedback laws to the RMPC, which in turn improves the closed-loop system performance. Furthermore, an off-line design of the proposed RMPC is also developed to make it more practical. Numerical studies demonstrate the effectiveness of the proposed algorithm.

  12. Model Predictive Optimal Control of a Time-Delay Distributed-Parameter Systems

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan

    2006-01-01

    This paper presents an optimal control method for a class of distributed-parameter systems governed by first order, quasilinear hyperbolic partial differential equations that arise in many physical systems. Such systems are characterized by time delays since information is transported from one state to another by wave propagation. A general closed-loop hyperbolic transport model is controlled by a boundary control embedded in a periodic boundary condition. The boundary control is subject to a nonlinear differential equation constraint that models actuator dynamics of the system. The hyperbolic equation is thus coupled with the ordinary differential equation via the boundary condition. Optimality of this coupled system is investigated using variational principles to seek an adjoint formulation of the optimal control problem. The results are then applied to implement a model predictive control design for a wind tunnel to eliminate a transport delay effect that causes a poor Mach number regulation.

  13. The design and optimization for light-algae bioreactor controller based on Artificial Neural Network-Model Predictive Control

    NASA Astrophysics Data System (ADS)

    Hu, Dawei; Liu, Hong; Yang, Chenliang; Hu, Enzhu

    As a subsystem of the bioregenerative life support system (BLSS), light-algae bioreactor (LABR) has properties of high reaction rate, efficiently synthesizing microalgal biomass, absorbing CO2 and releasing O2, so it is significant for BLSS to provide food and maintain gas balance. In order to manipulate the LABR properly, it has been designed as a closed-loop control system, and technology of Artificial Neural Network-Model Predictive Control (ANN-MPC) is applied to design the controller for LABR in which green microalgae, Spirulina platensis is cultivated continuously. The conclusion is drawn by computer simulation that ANN-MPC controller can intelligently learn the complicated dynamic performances of LABR, and automatically, robustly and self-adaptively regulate the light intensity illuminating on the LABR, hence make the growth of microalgae in the LABR be changed in line with the references, meanwhile provide appropriate damping to improve markedly the transient response performance of LABR.

  14. The Effects of Predictive Solutions on Training Time and Post-Training Performance for Control Systems with Human Operators.

    ERIC Educational Resources Information Center

    Myers, David Lee

    The effect of predictive solutions on training time (speed) and subsequent performance in a complex manual control system was investigated. A control system with a slow and complex response to the input signals was formulated. Fifty control operators, 25 with the aid of predictive solutions and 25 without, were tested; the mean performances of the…

  15. Improving the feed-forward compensator in predictive control for setpoint tracking.

    PubMed

    Valencia-Palomo, G; Rossiter, J A; López-Estrada, F R

    2014-05-01

    Simple predictive control (MPC) algorithms produce a feed-forward compensator that may be a suboptimal choice. This paper gives some insights into this issue and simple means of modifying the feed-forward to produce a more systematic and optimal design. In particular, it is shown that the optimum procedure depends upon the underlying loop tuning and also that there are, as yet under utilised, potential benefits with regard to constraint handling procedures, which helps to improve the computational efficiency of the online controller implementation. A laboratory test in a programmable logic controller (PLC) was carried out to demonstrate the code on real hardware and the effectiveness of the solution. PMID:24657005

  16. Prediction of Abstinence, Controlled Drinking, and Heavy Drinking Outcomes Following Behavioral Self-Control Training.

    ERIC Educational Resources Information Center

    Miller, William R.; Joyce, Mark A.

    1979-01-01

    Examined prognostic value of client characteristics for problem drinkers treated with an initial goal of controlled drinking. Clients achieving moderation had less severe symptoms and less family history of problem drinking than abstainers or uncontrolled cases. Females were more successful in attaining moderation. Males were overrepresented among…

  17. Modeling a multivariable reactor and on-line model predictive control.

    PubMed

    Yu, D W; Yu, D L

    2005-10-01

    A nonlinear first principle model is developed for a laboratory-scaled multivariable chemical reactor rig in this paper and the on-line model predictive control (MPC) is implemented to the rig. The reactor has three variables-temperature, pH, and dissolved oxygen with nonlinear dynamics-and is therefore used as a pilot system for the biochemical industry. A nonlinear discrete-time model is derived for each of the three output variables and their model parameters are estimated from the real data using an adaptive optimization method. The developed model is used in a nonlinear MPC scheme. An accurate multistep-ahead prediction is obtained for MPC, where the extended Kalman filter is used to estimate system unknown states. The on-line control is implemented and a satisfactory tracking performance is achieved. The MPC is compared with three decentralized PID controllers and the advantage of the nonlinear MPC over the PID is clearly shown. PMID:16294779

  18. Real-time prediction of unsteady aerodynamics: Application for aircraft control and manoeuvrability enhancement.

    PubMed

    Faller, W E; Schreck, S J

    1995-01-01

    The capability to control unsteady separated flow fields could dramatically enhance aircraft agility. To enable control, however, real-time prediction of these flow fields over a broad parameter range must be realized. The present work describes real-time predictions of three-dimensional unsteady separated flow fields and aerodynamic coefficients using neural networks. Unsteady surface-pressure readings were obtained from an airfoil pitched at a constant rate through the static stall angle. All data sets were comprised of 15 simultaneously acquired pressure records and one pitch angle record. Five such records and the associated pitch angle histories were used to train the neural network using a time-series algorithm. Post-training, the input to the network was the pitch angle (alpha), the angular velocity (dalpha/dt), and the initial 15 recorded surface pressures at time (t (0)). Subsequently, the time (t+Deltat) network predictions, for each of the surface pressures, were fed back as the input to the network throughout the pitch history. The results indicated that the neural network accurately predicted the unsteady separated flow fields as well as the aerodynamic coefficients to within 5% of the experimental data. Consistent results were obtained both for the training set as well as for generalization to both other constant pitch rates and to sinusoidal pitch motions. The results clearly indicated that the neural-network model could predict the unsteady surface-pressure distributions and aerodynamic coefficients based solely on angle of attack information. The capability for real-time prediction of both unsteady separated flow fields and aerodynamic coefficients across a wide range of parameters in turn provides a critical step towards the development of control systems targeted at exploiting unsteady aerodynamics for aircraft manoeuvrability enhancement. PMID:18263439

  19. Decision tree-based learning to predict patient controlled analgesia consumption and readjustment

    PubMed Central

    2012-01-01

    Background Appropriate postoperative pain management contributes to earlier mobilization, shorter hospitalization, and reduced cost. The under treatment of pain may impede short-term recovery and have a detrimental long-term effect on health. This study focuses on Patient Controlled Analgesia (PCA), which is a delivery system for pain medication. This study proposes and demonstrates how to use machine learning and data mining techniques to predict analgesic requirements and PCA readjustment. Methods The sample in this study included 1099 patients. Every patient was described by 280 attributes, including the class attribute. In addition to commonly studied demographic and physiological factors, this study emphasizes attributes related to PCA. We used decision tree-based learning algorithms to predict analgesic consumption and PCA control readjustment based on the first few hours of PCA medications. We also developed a nearest neighbor-based data cleaning method to alleviate the class-imbalance problem in PCA setting readjustment prediction. Results The prediction accuracies of total analgesic consumption (continuous dose and PCA dose) and PCA analgesic requirement (PCA dose only) by an ensemble of decision trees were 80.9% and 73.1%, respectively. Decision tree-based learning outperformed Artificial Neural Network, Support Vector Machine, Random Forest, Rotation Forest, and Naïve Bayesian classifiers in analgesic consumption prediction. The proposed data cleaning method improved the performance of every learning method in this study of PCA setting readjustment prediction. Comparative analysis identified the informative attributes from the data mining models and compared them with the correlates of analgesic requirement reported in previous works. Conclusion This study presents a real-world application of data mining to anesthesiology. Unlike previous research, this study considers a wider variety of predictive factors, including PCA demands over time. We analyzed

  20. Predicting postoperative vomiting among orthopedic patients receiving patient-controlled epidural analgesia using SVM and LR

    PubMed Central

    Wu, Hsin-Yun; Gong, Cihun-Siyong Alex; Lin, Shih-Pin; Chang, Kuang-Yi; Tsou, Mei-Yung; Ting, Chien-Kun

    2016-01-01

    Patient-controlled epidural analgesia (PCEA) has been applied to reduce postoperative pain in orthopedic surgical patients. Unfortunately, PCEA is occasionally accompanied by nausea and vomiting. The logistic regression (LR) model is widely used to predict vomiting, and recently support vector machines (SVM), a supervised machine learning method, has been used for classification and prediction. Unlike our previous work which compared Artificial Neural Networks (ANNs) with LR, this study uses a SVM-based predictive model to identify patients with high risk of vomiting during PCEA and comparing results with those derived from the LR-based model. From January to March 2007, data from 195 patients undergoing PCEA following orthopedic surgery were applied to develop two predictive models. 75% of the data were randomly selected for training, while the remainder was used for testing to validate predictive performance. The area under curve (AUC) was measured using the Receiver Operating Characteristic curve (ROC). The area under ROC curves of LR and SVM models were 0.734 and 0.929, respectively. A computer-based predictive model can be used to identify those who are at high risk for vomiting after PCEA, allowing for patient-specific therapeutic intervention or the use of alternative analgesic methods. PMID:27247165

  1. Predicting postoperative vomiting among orthopedic patients receiving patient-controlled epidural analgesia using SVM and LR.

    PubMed

    Wu, Hsin-Yun; Gong, Cihun-Siyong Alex; Lin, Shih-Pin; Chang, Kuang-Yi; Tsou, Mei-Yung; Ting, Chien-Kun

    2016-01-01

    Patient-controlled epidural analgesia (PCEA) has been applied to reduce postoperative pain in orthopedic surgical patients. Unfortunately, PCEA is occasionally accompanied by nausea and vomiting. The logistic regression (LR) model is widely used to predict vomiting, and recently support vector machines (SVM), a supervised machine learning method, has been used for classification and prediction. Unlike our previous work which compared Artificial Neural Networks (ANNs) with LR, this study uses a SVM-based predictive model to identify patients with high risk of vomiting during PCEA and comparing results with those derived from the LR-based model. From January to March 2007, data from 195 patients undergoing PCEA following orthopedic surgery were applied to develop two predictive models. 75% of the data were randomly selected for training, while the remainder was used for testing to validate predictive performance. The area under curve (AUC) was measured using the Receiver Operating Characteristic curve (ROC). The area under ROC curves of LR and SVM models were 0.734 and 0.929, respectively. A computer-based predictive model can be used to identify those who are at high risk for vomiting after PCEA, allowing for patient-specific therapeutic intervention or the use of alternative analgesic methods. PMID:27247165

  2. Advanced Models and Controls for Prediction and Extension of Battery Lifetime (Presentation)

    SciTech Connect

    Smith, K.; Wood, E.; Santhanagopalan, S.; Kim, G.; Pesaran, A.

    2014-02-01

    Predictive models of capacity and power fade must consider a multiplicity of degradation modes experienced by Li-ion batteries in the automotive environment. Lacking accurate models and tests, lifetime uncertainty must presently be absorbed by overdesign and excess warranty costs. To reduce these costs and extend life, degradation models are under development that predict lifetime more accurately and with less test data. The lifetime models provide engineering feedback for cell, pack and system designs and are being incorporated into real-time control strategies.

  3. Model predictive control of a wet limestone flue gas desulfurization pilot plant

    SciTech Connect

    Perales, A.L.V.; Ollero, P.; Ortiz, F.J.G.; Gomez-Barea, A.

    2009-06-15

    A model predictive control (MPC) strategy based on a dynamic matrix (DMC) is designed and applied to a wet limestone flue gas desulfurization (WLFGD) pilot plant to evaluate what enhancement in control performance can be achieved with respect to a conventional decentralized feedback control strategy. The results reveal that MPC can significantly improve both reference tracking and disturbance rejection. For disturbance rejection, the main control objective in WLFGD plants, selection of tuning parameters and sample time, is of paramount importance due to the fast effect of the main disturbance (inlet SO{sub 2} load to the absorber) on the most important controlled variable (outlet flue gas SO{sub 2} concentration). The proposed MPC strategy can be easily applied to full-scale WLFGD plants.

  4. Model predictive control application to spacecraft rendezvous in mars sample return scenario

    NASA Astrophysics Data System (ADS)

    Saponara, M.; Barrena, V.; Bemporad, A.; Hartley, E. N.; Maciejowski, J.; Richards, A.; Tramutola, A.; Trodden, P.

    2013-12-01

    Model Predictive Control (MPC) is an optimization-based control strategy that is considered extremely attractive in the autonomous space rendezvous scenarios. The Online Recon¦guration Control System and Avionics Architecture (ORCSAT) study addresses its applicability in Mars Sample Return (MSR) mission, including the implementation of the developed solution in a space representative avionic architecture system. With respect to a classical control solution High-integrity Autonomous RendezVous and Docking control system (HARVD), MPC allows a signi¦cant performance improvement both in trajectory and in propellant save. Furthermore, thanks to the online optimization, it allows to identify improvements in other areas (i. e., at mission de¦nition level) that could not be known a priori.

  5. Avionic Architecture for Model Predictive Control Application in Mars Sample & Return Rendezvous Scenario

    NASA Astrophysics Data System (ADS)

    Saponara, M.; Tramutola, A.; Creten, P.; Hardy, J.; Philippe, C.

    2013-08-01

    Optimization-based control techniques such as Model Predictive Control (MPC) are considered extremely attractive for space rendezvous, proximity operations and capture applications that require high level of autonomy, optimal path planning and dynamic safety margins. Such control techniques require high-performance computational needs for solving large optimization problems. The development and implementation in a flight representative avionic architecture of a MPC based Guidance, Navigation and Control system has been investigated in the ESA R&T study “On-line Reconfiguration Control System and Avionics Architecture” (ORCSAT) of the Aurora programme. The paper presents the baseline HW and SW avionic architectures, and verification test results obtained with a customised RASTA spacecraft avionics development platform from Aeroflex Gaisler.

  6. Rumination and self-control interact to predict bulimic symptomatology in college students.

    PubMed

    Breithaupt, Lauren; Rallis, Bethany; Mehlenbeck, Robyn; Kleiman, Evan

    2016-08-01

    Recent studies suggest that a ruminative response style may contribute to the development and maintenance of Bulimia nervosa. However it is not clear what factors may contribute to the relationship between rumination and BN. One factor may be self-control, as studies suggest that BN symptomatology relates to deficits in self-control. In the present study, we hypothesized that the association between rumination and BN symptomatology would be the strongest among individuals with lower self-control relative to those with higher self-control. Participants were 353 students at a large university. Participants completed measures of self-control, rumination, and eating disorder symptomology as part of an online study. A hierarchical regression supported an interaction between rumination and self-control predicting bulimic symptomatology, controlling for BMI. Individuals with higher levels of rumination presented more bulimic symptoms if they also had lower levels of self-control, supporting our hypothesis. Based on these findings, assessing rumination in conjunction with self-control among individuals who present with eating concerns may help to direct treatment. Additionally, clinical interventions increasing self-control may also alleviate some BN symptoms in ruminators. PMID:27033968

  7. Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory

    SciTech Connect

    Gregor P. Henze; Moncef Krarti

    2003-12-17

    Cooling of commercial buildings contributes significantly to the peak demand placed on an electrical utility grid. Time-of-use electricity rates encourage shifting of electrical loads to off-peak periods at night and weekends. Buildings can respond to these pricing signals by shifting cooling-related thermal loads either by precooling the building's massive structure or the use of active thermal energy storage systems such as ice storage. While these two thermal batteries have been engaged separately in the past, this project investigates the merits of harnessing both storage media concurrently in the context of predictive optimal control. This topical report describes the demonstration of the model-based predictive optimal control for active and passive building thermal storage inventory in a test facility in real-time using time-of-use differentiated electricity prices without demand charges. The laboratory testing findings presented in this topical report cover the second of three project phases. The novel supervisory controller successfully executed a three-step procedure consisting of (1) short-term weather prediction, (2) optimization of control strategy over the next planning horizon using a calibrated building model, and (3) post-processing of the optimal strategy to yield a control command for the current time step that can be executed in the test facility. The primary and secondary building mechanical systems were effectively orchestrated by the model-based predictive optimal controller in real-time while observing comfort and operational constraints. The findings reveal that when the optimal controller is given imperfect weather fore-casts and when the building model used for planning control strategies does not match the actual building perfectly, measured utility costs savings relative to conventional building operation can be substantial. This requires that the facility under control lends itself to passive storage utilization and the building model

  8. Validation of a multigenic model to predict seizure control in newly treated epilepsy.

    PubMed

    Shazadi, Kanvel; Petrovski, Slavé; Roten, Annie; Miller, Hugh; Huggins, Richard M; Brodie, Martin J; Pirmohamed, Munir; Johnson, Michael R; Marson, Anthony G; O'Brien, Terence J; Sills, Graeme J

    2014-12-01

    A multigenic classifier based on five single nucleotide polymorphisms (SNPs) was previously reported to predict treatment response in an Australian newly-diagnosed epilepsy cohort using a k-nearest neighbour (kNN) algorithm. We assessed the validity of this classifier in predicting response to initial antiepileptic drug (AED) treatment in two UK cohorts of newly-diagnosed epilepsy and investigated the utility of these five SNPs in predicting seizure control in general. The original Australian cohort constituted the training set for the classifier and was used to predict response to the first well-tolerated AED monotherapy in independently recruited UK cohorts (Glasgow, n=281; SANAD, n=491). A "leave-one-out" cross-validation was also employed, with training sets derived internally from the UK datasets. The multigenic classifier using the Australian cohort as the training set was unable to predict treatment response in either UK cohort. In the "leave-one-out" analysis, the five SNPs collectively predicted treatment response in both Glasgow and SANAD patients prescribed either carbamazepine or valproate (Glasgow OR=3.1, 95% CI=1.4-6.6, p=0.018; SANAD OR=2.8, 95% CI=1.3-6.1, p=0.048), but not those receiving lamotrigine (Glasgow OR=1.3, 95% CI=0.6-2.8, p=1.0; SANAD OR=2.2, 95% CI=0.9-5.4, p=0.36) or other AEDs (Glasgow OR=0.6, 95% CI=0.2-2.0, p=1.0; SANAD OR=1.9, 95% CI=0.9-4.2, p=0.36). The Australian-based multigenic kNN model is not predictive of initial treatment response in UK cohorts of newly-diagnosed epilepsy. However, the five SNPs identified in the original Australian study appear to collectively have a predictive influence in UK patients prescribed either carbamazepine or valproate. PMID:25282706

  9. Model-based planning and real-time predictive control for laser-induced thermal therapy

    PubMed Central

    Feng, Yusheng; Fuentes, David

    2014-01-01

    In this article, the major idea and mathematical aspects of model-based planning and real-time predictive control for laser-induced thermal therapy (LITT) are presented. In particular, a computational framework and its major components developed by authors in recent years are reviewed. The framework provides the backbone for not only treatment planning but also real-time surgical monitoring and control with a focus on MR thermometry enabled predictive control and applications to image-guided LITT, or MRgLITT. Although this computational framework is designed for LITT in treating prostate cancer, it is further applicable to other thermal therapies in focal lesions induced by radio-frequency (RF), microwave and high-intensity-focused ultrasound (HIFU). Moreover, the model-based dynamic closed-loop predictive control algorithms in the framework, facilitated by the coupling of mathematical modelling and computer simulation with real-time imaging feedback, has great potential to enable a novel methodology in thermal medicine. Such technology could dramatically increase treatment efficacy and reduce morbidity. PMID:22098360

  10. A novel predictive control algorithm and robust stability criteria for integrating processes.

    PubMed

    Zhang, Bin; Yang, Weimin; Zong, Hongyuan; Wu, Zhiyong; Zhang, Weidong

    2011-07-01

    This paper introduces a novel predictive controller for single-input/single-output (SISO) integrating systems, which can be directly applied without pre-stabilizing the process. The control algorithm is designed on the basis of the tested step response model. To produce a bounded system response along the finite predictive horizon, the effect of the integrating mode must be zeroed while unmeasured disturbances exist. Here, a novel predictive feedback error compensation method is proposed to eliminate the permanent offset between the setpoint and the process output while the integrating system is affected by load disturbance. Also, a rotator factor is introduced in the performance index, which is contributed to the improvement robustness of the closed-loop system. Then on the basis of Jury's dominant coefficient criterion, a robust stability condition of the resulted closed loop system is given. There are only two parameters which need to be tuned for the controller, and each has a clear physical meaning, which is convenient for implementation of the control algorithm. Lastly, simulations are given to illustrate that the proposed algorithm can provide excellent closed loop performance compared with some reported methods. PMID:21353217

  11. Probabilistic Movement Models Show that Postural Control Precedes and Predicts Volitional Motor Control.

    PubMed

    Rueckert, Elmar; Čamernik, Jernej; Peters, Jan; Babič, Jan

    2016-01-01

    Human motor skill learning is driven by the necessity to adapt to new situations. While supportive contacts are essential for many tasks, little is known about their impact on motor learning. To study the effect of contacts an innovative full-body experimental paradigm was established. The task of the subjects was to reach for a distant target while postural stability could only be maintained by establishing an additional supportive hand contact. To examine adaptation, non-trivial postural perturbations of the subjects' support base were systematically introduced. A novel probabilistic trajectory model approach was employed to analyze the correlation between the motions of both arms and the trunk. We found that subjects adapted to the perturbations by establishing target dependent hand contacts. Moreover, we found that the trunk motion adapted significantly faster than the motion of the arms. However, the most striking finding was that observations of the initial phase of the left arm or trunk motion (100-400 ms) were sufficient to faithfully predict the complete movement of the right arm. Overall, our results suggest that the goal-directed arm movements determine the supportive arm motions and that the motion of heavy body parts adapts faster than the light arms. PMID:27328750

  12. Probabilistic Movement Models Show that Postural Control Precedes and Predicts Volitional Motor Control

    PubMed Central

    Rueckert, Elmar; Čamernik, Jernej; Peters, Jan; Babič, Jan

    2016-01-01

    Human motor skill learning is driven by the necessity to adapt to new situations. While supportive contacts are essential for many tasks, little is known about their impact on motor learning. To study the effect of contacts an innovative full-body experimental paradigm was established. The task of the subjects was to reach for a distant target while postural stability could only be maintained by establishing an additional supportive hand contact. To examine adaptation, non-trivial postural perturbations of the subjects’ support base were systematically introduced. A novel probabilistic trajectory model approach was employed to analyze the correlation between the motions of both arms and the trunk. We found that subjects adapted to the perturbations by establishing target dependent hand contacts. Moreover, we found that the trunk motion adapted significantly faster than the motion of the arms. However, the most striking finding was that observations of the initial phase of the left arm or trunk motion (100–400 ms) were sufficient to faithfully predict the complete movement of the right arm. Overall, our results suggest that the goal-directed arm movements determine the supportive arm motions and that the motion of heavy body parts adapts faster than the light arms. PMID:27328750

  13. Variability in phenylalanine control predicts IQ and executive abilities in children with phenylketonuria.

    PubMed

    Hood, Anna; Grange, Dorothy K; Christ, Shawn E; Steiner, Robert; White, Desirée A

    2014-04-01

    A number of studies have revealed significant relationships between cognitive performance and average phenylalanine (Phe) levels in children with phenylketonuria (PKU), but only a few studies have been conducted to examine the relationships between cognitive performance and variability (fluctuations) in Phe levels. In the current study, we examined a variety of indices of Phe control to determine which index best predicted IQ and executive abilities in 47 school-age children with early- and continuously-treated PKU. Indices of Phe control were mean Phe, the index of dietary control, change in Phe with age, and several indices of variability in Phe (standard deviation, standard error of estimate, and percentage of spikes). These indices were computed over the lifetime and during 3 developmental epochs (<5, 5.0-9.9, and ≥10 years of age). Results indicated that variability in Phe was generally a stronger predictor of cognitive performance than other indices of Phe control. In addition, executive performance was better predicted by variability in Phe during older than younger developmental epochs. These results indicate that variability in Phe should be carefully controlled to maximize cognitive outcomes and that Phe control should not be liberalized as children with PKU age. PMID:24568837

  14. Event-driven model predictive control of sewage pumping stations for sulfide mitigation in sewer networks.

    PubMed

    Liu, Yiqi; Ganigué, Ramon; Sharma, Keshab; Yuan, Zhiguo

    2016-07-01

    Chemicals such as Mg(OH)2 and iron salts are widely dosed to sewage for mitigating sulfide-induced corrosion and odour problems in sewer networks. The chemical dosing rate is usually not automatically controlled but profiled based on experience of operators, often resulting in over- or under-dosing. Even though on-line control algorithms for chemical dosing in single pipes have been developed recently, network-wide control algorithms are currently not available. The key challenge is that a sewer network is typically wide-spread comprising many interconnected sewer pipes and pumping stations, making network-wide sulfide mitigation with a relatively limited number of dosing points challenging. In this paper, we propose and demonstrate an Event-driven Model Predictive Control (EMPC) methodology, which controls the flows of sewage streams containing the dosed chemical to ensure desirable distribution of the dosed chemical throughout the pipe sections of interests. First of all, a network-state model is proposed to predict the chemical concentration in a network. An EMPC algorithm is then designed to coordinate sewage pumping station operations to ensure desirable chemical distribution in the network. The performance of the proposed control methodology is demonstrated by applying the designed algorithm to a real sewer network simulated with the well-established SeweX model using real sewage flow and characteristics data. The EMPC strategy significantly improved the sulfide mitigation performance with the same chemical consumption, compared to the current practice. PMID:27124127

  15. Variability in Phenylalanine Control Predicts IQ and Executive Abilities in Children with Phenylketonuria

    PubMed Central

    Hood, Anna; Grange, Dorothy K.; Christ, Shawn E.; Steiner, Robert; White, Desirée A.

    2014-01-01

    A number of studies have revealed significant relationships between cognitive performance and average phenylalanine (Phe) levels in children with phenylketonuria (PKU), but only a few studies have been conducted to examine relationships between cognitive performance and variability (fluctuations) in Phe levels. In the current study, we examined a variety of indices of Phe control to determine which index best predicted IQ and executive abilities in 47 school-age children with early- and continuously-treated PKU. Indices of Phe control were mean Phe, the index of dietary control, change in Phe with age, and several indices of variability in Phe (standard deviation, standard error of estimate, and percentage of spikes). These indices were computed over the lifetime and during 3 developmental epochs (< 5, 5.0 – 9.9, and ≥ 10 yrs. of age). Results indicated that variability in Phe was generally a stronger predictor of cognitive performance than other indices of Phe control. In addition, executive performance was better predicted by variability in Phe during older than younger developmental epochs. These results indicate that variability in Phe should be carefully controlled to maximize cognitive outcomes, and that Phe control should not be liberalized as children with PKU age. PMID:24568837

  16. Lithium-ion battery cell-level control using constrained model predictive control and equivalent circuit models

    NASA Astrophysics Data System (ADS)

    Xavier, Marcelo A.; Trimboli, M. Scott

    2015-07-01

    This paper introduces a novel application of model predictive control (MPC) to cell-level charging of a lithium-ion battery utilizing an equivalent circuit model of battery dynamics. The approach employs a modified form of the MPC algorithm that caters for direct feed-though signals in order to model near-instantaneous battery ohmic resistance. The implementation utilizes a 2nd-order equivalent circuit discrete-time state-space model based on actual cell parameters; the control methodology is used to compute a fast charging profile that respects input, output, and state constraints. Results show that MPC is well-suited to the dynamics of the battery control problem and further suggest significant performance improvements might be achieved by extending the result to electrochemical models.

  17. Lithium-ion battery cell-level control using constrained model predictive control and equivalent circuit models

    SciTech Connect

    Xavier, MA; Trimboli, MS

    2015-07-01

    This paper introduces a novel application of model predictive control (MPC) to cell-level charging of a lithium-ion battery utilizing an equivalent circuit model of battery dynamics. The approach employs a modified form of the MPC algorithm that caters for direct feed-though signals in order to model near-instantaneous battery ohmic resistance. The implementation utilizes a 2nd-order equivalent circuit discrete-time state-space model based on actual cell parameters; the control methodology is used to compute a fast charging profile that respects input, output, and state constraints. Results show that MPC is well-suited to the dynamics of the battery control problem and further suggest significant performance improvements might be achieved by extending the result to electrochemical models. (C) 2015 Elsevier B.V. All rights reserved.

  18. HIV-1 DNA predicts disease progression and post-treatment virological control.

    PubMed

    Williams, James P; Hurst, Jacob; Stöhr, Wolfgang; Robinson, Nicola; Brown, Helen; Fisher, Martin; Kinloch, Sabine; Cooper, David; Schechter, Mauro; Tambussi, Giuseppe; Fidler, Sarah; Carrington, Mary; Babiker, Abdel; Weber, Jonathan; Koelsch, Kersten K; Kelleher, Anthony D; Phillips, Rodney E; Frater, John

    2014-01-01

    In HIV-1 infection, a population of latently infected cells facilitates viral persistence despite antiretroviral therapy (ART). With the aim of identifying individuals in whom ART might induce a period of viraemic control on stopping therapy, we hypothesised that quantification of the pool of latently infected cells in primary HIV-1 infection (PHI) would predict clinical progression and viral replication following ART. We measured HIV-1 DNA in a highly characterised randomised population of individuals with PHI. We explored associations between HIV-1 DNA and immunological and virological markers of clinical progression, including viral rebound in those interrupting therapy. In multivariable analyses, HIV-1 DNA was more predictive of disease progression than plasma viral load and, at treatment interruption, predicted time to plasma virus rebound. HIV-1 DNA may help identify individuals who could safely interrupt ART in future HIV-1 eradication trials. PMID:25217531

  19. Using micro saint to predict performance in a nuclear power plant control room

    SciTech Connect

    Lawless, M.T.; Laughery, K.R.; Persenky, J.J.

    1995-09-01

    The United States Nuclear Regulatory Commission (NRC) requires a technical basis for regulatory actions. In the area of human factors, one possible technical basis is human performance modeling technology including task network modeling. This study assessed the feasibility and validity of task network modeling to predict the performance of control room crews. Task network models were built that matched the experimental conditions of a study on computerized procedures that was conducted at North Carolina State University. The data from the {open_quotes}paper procedures{close_quotes} conditions were used to calibrate the task network models. Then, the models were manipulated to reflect expected changes when computerized procedures were used. These models` predictions were then compared to the experimental data from the {open_quotes}computerized conditions{close_quotes} of the North Carolina State University study. Analyses indicated that the models predicted some subsets of the data well, but not all. Implications for the use of task network modeling are discussed.

  20. Predicting the flying performance of thermal flying-height control sliders in hard disk drives

    NASA Astrophysics Data System (ADS)

    Liu, Nan; Zheng, Jinglin; Bogy, David B.

    2010-07-01

    Thermal flying-height control (TFC) sliders have been recently used in commercial hard disk drives (HDDs) to increase the HDDs' capacity. The design of this new class of sliders depends on the numerical prediction of their flying performance, which requires a model for heat flux on the surface of the slider facing the disk. The currently widely used heat flux model is based on a first order slip theory and is believed to lack sufficient accuracy due to its limitation of applicability. This paper implements an improved heat flux model and compares numerical predictions of a TFC slider's flying performance based on these two models with experiments. It is found that the numerical prediction based on the currently used model has a relative error less than 10% for a state-of-the-art TFC slider. It is suggested that the currently used model might cause large errors for the sliders which do not have a pressure peak near the transducer.

  1. Dopamine Gene Profiling to Predict Impulse Control and Effects of Dopamine Agonist Ropinirole.

    PubMed

    MacDonald, Hayley J; Stinear, Cathy M; Ren, April; Coxon, James P; Kao, Justin; Macdonald, Lorraine; Snow, Barry; Cramer, Steven C; Byblow, Winston D

    2016-07-01

    Dopamine agonists can impair inhibitory control and cause impulse control disorders for those with Parkinson disease (PD), although mechanistically this is not well understood. In this study, we hypothesized that the extent of such drug effects on impulse control is related to specific dopamine gene polymorphisms. This double-blind, placebo-controlled study aimed to examine the effect of single doses of 0.5 and 1.0 mg of the dopamine agonist ropinirole on impulse control in healthy adults of typical age for PD onset. Impulse control was measured by stop signal RT on a response inhibition task and by an index of impulsive decision-making on the Balloon Analogue Risk Task. A dopamine genetic risk score quantified basal dopamine neurotransmission from the influence of five genes: catechol-O-methyltransferase, dopamine transporter, and those encoding receptors D1, D2, and D3. With placebo, impulse control was better for the high versus low genetic risk score groups. Ropinirole modulated impulse control in a manner dependent on genetic risk score. For the lower score group, both doses improved response inhibition (decreased stop signal RT) whereas the lower dose reduced impulsiveness in decision-making. Conversely, the higher score group showed a trend for worsened response inhibition on the lower dose whereas both doses increased impulsiveness in decision-making. The implications of the present findings are that genotyping can be used to predict impulse control and whether it will improve or worsen with the administration of dopamine agonists. PMID:26942320

  2. Prediction of Traffic Complexity and Controller Workload in Mixed Equipage NextGen Environments

    NASA Technical Reports Server (NTRS)

    Lee, Paul U.; Prevot, Thomas

    2012-01-01

    Controller workload is a key factor in limiting en route air traffic capacity. Past efforts to quantify and predict workload have resulted in identifying objective metrics that correlate well with subjective workload ratings during current air traffic control operations. Although these metrics provide a reasonable statistical fit to existing data, they do not provide a good mechanism for estimating controller workload for future air traffic concepts and environments that make different assumptions about automation, enabling technologies, and controller tasks. One such future environment is characterized by en route airspace with a mixture of aircraft equipped with and without Data Communications (Data Comm). In this environment, aircraft with Data Comm will impact controller workload less than aircraft requiring voice communication, altering the close correlation between aircraft count and controller workload that exists in current air traffic operations. This paper outlines a new trajectory-based complexity (TBX) calculation that was presented to controllers during a human-in-the-loop simulation. The results showed that TBX accurately estimated the workload in a mixed Data Comm equipage environment and the resulting complexity values were understood and readily interpreted by the controllers. The complexity was represented as a "modified aircraft account" that weighted different complexity factors and summed them in such a way that the controllers could effectively treat them as aircraft count. The factors were also relatively easy to tune without an extensive data set. The results showed that the TBX approach is well suited for presenting traffic complexity in future air traffic environments.

  3. Observer-based predictive controller design with network-enhanced time-delay compensation

    NASA Astrophysics Data System (ADS)

    Florin Caruntu, Constantin

    2015-02-01

    State feedback control is very attractive due to the precise computation of the gain matrix, but the implementation of a state feedback controller is possible only when all state variables are directly measurable. This condition is almost impossible to accomplish due to the excess number of required sensors or unavailability of states for measurement in most of the practical situations. Hence, the need for an estimator or observer is obvious to estimate all the state variables by observing the input and the output of the controlled system. As such, the goal of this paper is to provide a control design methodology based on a Luenberger observer design that can assure the closed-loop performances of a vehicle drivetrain with backlash, while compensating the network-enhanced time-varying delays. This goal is achieved in a sequential manner: firstly, a piecewise linear model of two inertias drivetrain, which takes into consideration the backlash nonlinearity and the network-enhanced time-varying delay effects is derived; then, a Luenberger observer which estimates the state variables is synthesized and the robust full state-feedback predictive controller based on flexible control Lyapunov functions is designed to explicitly take into account the bounds of the disturbances caused by time-varying delays and to guarantee also the input-to-state stability of the system in a non-conservative way. The full state-feedback predictive control strategy based on the Luenberger observer design was experimentally tested on a vehicle drivetrain emulator controlled through controller area network, with the aim of minimizing the backlash effects while compensating the network-enhanced delays.

  4. Within-socket myoelectric prediction of continuous ankle kinematics for control of a powered transtibial prosthesis

    NASA Astrophysics Data System (ADS)

    Farmer, Samuel; Silver-Thorn, Barbara; Voglewede, Philip; Beardsley, Scott A.

    2014-10-01

    Objective. Powered robotic prostheses create a need for natural-feeling user interfaces and robust control schemes. Here, we examined the ability of a nonlinear autoregressive model to continuously map the kinematics of a transtibial prosthesis and electromyographic (EMG) activity recorded within socket to the future estimates of the prosthetic ankle angle in three transtibial amputees. Approach. Model performance was examined across subjects during level treadmill ambulation as a function of the size of the EMG sampling window and the temporal ‘prediction’ interval between the EMG/kinematic input and the model’s estimate of future ankle angle to characterize the trade-off between model error, sampling window and prediction interval. Main results. Across subjects, deviations in the estimated ankle angle from the actual movement were robust to variations in the EMG sampling window and increased systematically with prediction interval. For prediction intervals up to 150 ms, the average error in the model estimate of ankle angle across the gait cycle was less than 6°. EMG contributions to the model prediction varied across subjects but were consistently localized to the transitions to/from single to double limb support and captured variations from the typical ankle kinematics during level walking. Significance. The use of an autoregressive modeling approach to continuously predict joint kinematics using natural residual muscle activity provides opportunities for direct (transparent) control of a prosthetic joint by the user. The model’s predictive capability could prove particularly useful for overcoming delays in signal processing and actuation of the prosthesis, providing a more biomimetic ankle response.

  5. Indoor environmental quality (IEQ) and building energy optimization through model predictive control (MPC)

    NASA Astrophysics Data System (ADS)

    Woldekidan, Korbaga

    This dissertation aims at developing a novel and systematic approach to apply Model Predictive Control (MPC) to improve energy efficiency and indoor environmental quality in office buildings. Model predictive control is one of the advanced optimal control approaches that use models to predict the behavior of the process beyond the current time to optimize the system operation at the present time. In building system, MPC helps to exploit buildings' thermal storage capacity and to use the information on future disturbances like weather and internal heat gains to estimate optimal control inputs ahead of time. In this research the major challenges of applying MPC to building systems are addressed. A systematic framework has been developed for ease of implementation. New methods are proposed to develop simple and yet reasonably accurate models that can minimize the MPC development effort as well as computational time. The developed MPC is used to control a detailed building model represented by whole building performance simulation tool, EnergyPlus. A co-simulation strategy is used to communicate the MPC control developed in Matlab platform with the case building model in EnergyPlus. The co-simulation tool used (MLE+) also has the ability to talk to actual building management systems that support the BACnet communication protocol which makes it easy to implement the developed MPC control in actual buildings. A building that features an integrated lighting and window control and HVAC system with a dedicated outdoor air system and ceiling radiant panels was used as a case building. Though this study is specifically focused on the case building, the framework developed can be applied to any building type. The performance of the developed MPC was compared against a baseline control strategy using Proportional Integral and Derivative (PID) control. Various conventional and advanced thermal comfort as well as ventilation strategies were considered for the comparison. These

  6. A predictive biophysical model of translational coupling to coordinate and control protein expression in bacterial operons

    PubMed Central

    Tian, Tian; Salis, Howard M.

    2015-01-01

    Natural and engineered genetic systems require the coordinated expression of proteins. In bacteria, translational coupling provides a genetically encoded mechanism to control expression level ratios within multi-cistronic operons. We have developed a sequence-to-function biophysical model of translational coupling to predict expression level ratios in natural operons and to design synthetic operons with desired expression level ratios. To quantitatively measure ribosome re-initiation rates, we designed and characterized 22 bi-cistronic operon variants with systematically modified intergenic distances and upstream translation rates. We then derived a thermodynamic free energy model to calculate de novo initiation rates as a result of ribosome-assisted unfolding of intergenic RNA structures. The complete biophysical model has only five free parameters, but was able to accurately predict downstream translation rates for 120 synthetic bi-cistronic and tri-cistronic operons with rationally designed intergenic regions and systematically increased upstream translation rates. The biophysical model also accurately predicted the translation rates of the nine protein atp operon, compared to ribosome profiling measurements. Altogether, the biophysical model quantitatively predicts how translational coupling controls protein expression levels in synthetic and natural bacterial operons, providing a deeper understanding of an important post-transcriptional regulatory mechanism and offering the ability to rationally engineer operons with desired behaviors. PMID:26117546

  7. Design and analysis of a model predictive controller for active queue management.

    PubMed

    Wang, Ping; Chen, Hong; Yang, Xiaoping; Ma, Yan

    2012-01-01

    Model predictive (MP) control as a novel active queue management (AQM) algorithm in dynamic computer networks is proposed. According to the predicted future queue length in the data buffer, early packets at the router are dropped reasonably by the MPAQM controller so that the queue length reaches the desired value with minimal tracking error. The drop probability is obtained by optimizing the network performance. Further, randomized algorithms are applied to analyze the robustness of MPAQM successfully, and also to provide the stability domain of systems with uncertain network parameters. The performances of MPAQM are evaluated through a series of simulations in NS2. The simulation results show that the MPAQM algorithm outperforms RED, PI, and REM algorithms in terms of stability, disturbance rejection, and robustness. PMID:21963108

  8. Stock management in hospital pharmacy using chance-constrained model predictive control.

    PubMed

    Jurado, I; Maestre, J M; Velarde, P; Ocampo-Martinez, C; Fernández, I; Tejera, B Isla; Prado, J R Del

    2016-05-01

    One of the most important problems in the pharmacy department of a hospital is stock management. The clinical need for drugs must be satisfied with limited work labor while minimizing the use of economic resources. The complexity of the problem resides in the random nature of the drug demand and the multiple constraints that must be taken into account in every decision. In this article, chance-constrained model predictive control is proposed to deal with this problem. The flexibility of model predictive control allows taking into account explicitly the different objectives and constraints involved in the problem while the use of chance constraints provides a trade-off between conservativeness and efficiency. The solution proposed is assessed to study its implementation in two Spanish hospitals. PMID:26724992

  9. Prediction of forces and moments for flight vehicle control effectors: Workplan

    NASA Technical Reports Server (NTRS)

    Maughmer, Mark D.

    1989-01-01

    Two research activities directed at hypersonic vehicle configurations are currently underway. The first involves the validation of a number of classical local surface inclination methods commonly employed in preliminary design studies of hypersonic flight vehicles. Unlike studies aimed at validating such methods for predicting overall vehicle aerodynamics, this effort emphasizes validating the prediction of forces and moments for flight control studies. Specifically, several vehicle configurations for which experimental or flight-test data are available are being examined. By comparing the theoretical predictions with these data, the strengths and weaknesses of the local surface inclination methods can be ascertained and possible improvements suggested. The second research effort, of significance to control during take-off and landing of most proposed hypersonic vehicle configurations, is aimed at determining the change due to ground effect in control effectiveness of highly swept delta planforms. Central to this research is the development of a vortex-lattice computer program which incorporates an unforced trailing vortex sheet and an image ground plane. With this program, the change in pitching moment of the basic vehicle due to ground proximity, and whether or not there is sufficient control power available to trim, can be determined. In addition to the current work, two different research directions are suggested for future study. The first is aimed at developing an interactive computer program to assist the flight controls engineer in determining the forces and moments generated by different types of control effectors that might be used on hypersonic vehicles. The first phase of this work would deal in the subsonic portion of the flight envelope, while later efforts would explore the supersonic/hypersonic flight regimes. The second proposed research direction would explore methods for determining the aerodynamic trim drag of a generic hypersonic flight vehicle

  10. Remotely controlled mandibular positioner predicts efficacy of oral appliances in sleep apnea.

    PubMed

    Tsai, Willis H; Vazquez, Juan-Carlos; Oshima, Tsutomu; Dort, Leslie; Roycroft, Brian; Lowe, Alan A; Hajduk, Eric; Remmers, John E

    2004-08-15

    Anterior mandibular positioners (AMPs) have become increasingly popular as alternatives to continuous positive airway pressure for the treatment of obstructive sleep apnea. However, widespread acceptance of AMP is limited by an efficacy rate of 50-80% and an inability to predict which patients will respond to therapy. We evaluated 23 patients with obstructive sleep apnea (respiratory disturbance index [RDI] >/= 15 h(-1)) with a remotely controlled mandibular positioner (RCMP), a temporary oral appliance that can advance or retract the mandible in a process analogous to changing the mask pressure during a continuous positive airway pressure titration study. We hypothesized that the elimination of respiratory events and significant nocturnal oxygen desaturation during an RCMP overnight study would predict AMP efficacy, as defined by an absolute reduction in RDI to less than 15 h(-1), a relative reduction in RDI of more than 30% from baseline, and a subjective improvement in symptoms. AMP compliance was 82%, and therapeutic efficacy was 53%. Among compliant patients, the positive and negative predictive value of an RCMP study in predicting AMP treatment success was 90% and 89%, respectively. An overnight RCMP study is highly predictive of AMP response. PMID:15105166

  11. Planning horizon for a predictive optimal controller for thermal energy storage systems

    SciTech Connect

    Krarti, M.; Henze, G.P.; Bell, D.

    1999-07-01

    This paper presents the results of a detailed simulation analysis to determine the planning horizon for a predictive optimal controller for thermal energy storage (TES) systems. The objective of the simulation analysis is to determine the sensitivity of the performance of a TES optimal controller and the planning horizon length to different design parameters, including: chiller capacity, cooling plant model, storage system capacity, and load profile. The analysis is performed using two commercial buildings: a 20-floor office building in Wisconsin, and a hotel in California.

  12. Controlling bimetallic nanostructures by the microemulsion method with subnanometer resolution using a prediction model

    DOE PAGESBeta

    Buceta, David; Tojo, Concha; Vukmirovic, Miomir B.; Deepak, F. Leonard; Lopez-Quintela, M. Arturo

    2015-06-02

    In this study, we present a theoretical model to predict the atomic structure of Au/Pt nanoparticles synthesized in microemulsions. Excellent concordance with the experimental results shows that the structure of the nanoparticles can be controlled at sub-nanometer resolution simply by changing the reactants concentration. The results of this study not only offer a better understanding of the complex mechanisms governing reactions in microemulsions, but open up a simple new way to synthesize bimetallic nanoparticles with ad-hoc controlled nanostructures.

  13. Correlation of Predicted and Observed Optical Properties of Multilayer Thermal Control Coatings

    NASA Technical Reports Server (NTRS)

    Jaworske, Donald A.

    1998-01-01

    Thermal control coatings on spacecraft will be increasingly important, as spacecraft grow smaller and more compact. New thermal control coatings will be needed to meet the demanding requirements of next generation spacecraft. Computer programs are now available to design optical coatings and one such program was used to design several thermal control coatings consisting of alternating layers of WO3 and SiO2. The coatings were subsequently manufactured with electron beam evaporation and characterized with both optical and thermal techniques. Optical data were collected in both the visible region of the spectrum and the infrared. Predictions of solar absorptance and infrared emittance were successfully correlated to the observed thermal control properties. Functional performance of the coatings was verified in a bench top thermal vacuum chamber.

  14. Predicted performance benefits of an adaptive digital engine control system of an F-15 airplane

    NASA Technical Reports Server (NTRS)

    Burcham, F. W., Jr.; Myers, L. P.; Ray, R. J.

    1985-01-01

    The highly integrated digital electronic control (HIDEC) program will demonstrate and evaluate the improvements in performance and mission effectiveness that result from integrating engine-airframe control systems. Currently this is accomplished on the NASA Ames Research Center's F-15 airplane. The two control modes used to implement the systems are an integrated flightpath management mode and in integrated adaptive engine control system (ADECS) mode. The ADECS mode is a highly integrated mode in which the airplane flight conditions, the resulting inlet distortion, and the available engine stall margin are continually computed. The excess stall margin is traded for thrust. The predicted increase in engine performance due to the ADECS mode is presented in this report.

  15. Predicted performance benefits of an adaptive digital engine control system on an F-15 airplane

    NASA Technical Reports Server (NTRS)

    Burcham, F. W., Jr.; Myers, L. P.; Ray, R. J.

    1985-01-01

    The highly integrated digital electronic control (HIDEC) program will demonstrate and evaluate the improvements in performance and mission effectiveness that result from integrating engine-airframe control systems. Currently this is accomplished on the NASA Ames Research Center's F-15 airplane. The two control modes used to implement the systems are an integrated flightpath management mode and an integrated adaptive engine control system (ADECS) mode. The ADECS mode is a highly integrated mode in which the airplane flight conditions, the resulting inlet distortion, and the available engine stall margin are continually computed. The excess stall margin is traded for thrust. The predicted increase in engine performance due to the ADECS mode is presented in this report.

  16. Correcting hypothalamic-pituitary-adrenal axis dysfunction using observer-based explicit nonlinear model predictive control.

    PubMed

    Chakrabarty, Ankush; Buzzard, Gregery T; Corless, Martin J; Zak, Stanislaw H; Rundell, Ann E

    2014-01-01

    The hypothalamic-pituitary-adrenal (HPA) axis is critical in maintaining homeostasis under physical and psychological stress by modulating cortisol levels in the body. Dysregulation of cortisol levels is linked to numerous stress-related disorders. In this paper, an automated treatment methodology is proposed, employing a variant of nonlinear model predictive control (NMPC), called explicit MPC (EMPC). The controller is informed by an unknown input observer (UIO), which estimates various hormonal levels in the HPA axis system in conjunction with the magnitude of the stress applied on the body, based on measured concentrations of adreno-corticotropic hormones (ACTH). The proposed closed-loop control strategy is tested on multiple in silico patients and the effectiveness of the controller performance is demonstrated. PMID:25570727

  17. Jacques Loeb, B. F. Skinner, and the legacy of prediction and control.

    PubMed

    Hackenberg, T D

    1995-01-01

    The biologist Jacques Loeb is an important figure in the history of behavior analysis. Between 1890 and 1915, Loeb championed an approach to experimental biology that would later exert substantial influence on the work of B. F. Skinner and behavior analysis. This paper examines some of these sources of influence, with a particular emphasis on Loeb's firm commitment to prediction and control as fundamental goals of an experimental life science, and how these goals were extended and broadened by Skinner. Both Loeb and Skinner adopted a pragmatic approach to science that put practical control of their subject matter above formal theory testing, both based their research programs on analyses of reproducible units involving the intact organism, and both strongly endorsed technological applications of basic laboratory science. For Loeb, but especially for Skinner, control came to mean something more than mere experimental or technological control for its own sake; it became synonomous with scientific understanding. This view follows from (a) the successful working model of science Loeb and Skinner inherited from Ernst Mach, in which science is viewed as human social activity, and effective practical action is taken as the basis of scientific knowledge, and (b) Skinner's analysis of scientific activity, situated in the world of direct experience and related to practices arranged by scientific verbal communities. From this perspective, prediction and control are human acts that arise from and are maintained by social circumstances in which such acts meet with effective consequences. PMID:22478220

  18. Controller Strategies for Automation Tool Use under Varying Levels of Trajectory Prediction Uncertainty

    NASA Technical Reports Server (NTRS)

    Morey, Susan; Prevot, Thomas; Mercer, Joey; Martin, Lynne; Bienert, Nancy; Cabrall, Christopher; Hunt, Sarah; Homola, Jeffrey; Kraut, Joshua

    2013-01-01

    A human-in-the-loop simulation was conducted to examine the effects of varying levels of trajectory prediction uncertainty on air traffic controller workload and performance, as well as how strategies and the use of decision support tools change in response. This paper focuses on the strategies employed by two controllers from separate teams who worked in parallel but independently under identical conditions (airspace, arrival traffic, tools) with the goal of ensuring schedule conformance and safe separation for a dense arrival flow in en route airspace. Despite differences in strategy and methods, both controllers achieved high levels of schedule conformance and safe separation. Overall, results show that trajectory uncertainties introduced by wind and aircraft performance prediction errors do not affect the controllers' ability to manage traffic. Controller strategies were fairly robust to changes in error, though strategies were affected by the amount of delay to absorb (scheduled time of arrival minus estimated time of arrival). Using the results and observations, this paper proposes an ability to dynamically customize the display of information including delay time based on observed error to better accommodate different strategies and objectives.

  19. Testing predictions from the male control theory of men's partner violence.

    PubMed

    Bates, Elizabeth A; Graham-Kevan, Nicola; Archer, John

    2014-01-01

    The aim of this study was to test predictions from the male control theory of intimate partner violence (IPV) and Johnson's [Johnson, M. P. (1995). Journal of Marriage and the Family, 57, 282-294] typology. A student sample (N = 1,104) reported on their use of physical aggression and controlling behavior, to partners and to same-sex non-intimates. Contrary to the male control theory, women were found to be more physically aggressive to their partners than men were, and the reverse pattern was found for aggression to same-sex non-intimates. Furthermore, there were no substantial sex differences in controlling behavior, which significantly predicted physical aggression in both sexes. IPV was found to be associated with physical aggression to same-sex non-intimates, thereby demonstrating a link with aggression outside the family. Using Johnson's typology, women were more likely than men to be classed as "intimate terrorists," which was counter to earlier findings. Overall, these results do not support the male control theory of IPV. Instead, they fit the view that IPV does not have a special etiology, and is better studied within the context of other forms of aggression. PMID:23878077

  20. Low speed hybrid generalized predictive control of a gasoline-propelled car.

    PubMed

    Romero, M; de Madrid, A P; Mañoso, C; Milanés, V

    2015-07-01

    Low-speed driving in traffic jams causes significant pollution and wasted time for commuters. Additionally, from the passengers׳ standpoint, this is an uncomfortable, stressful and tedious scene that is suitable to be automated. The highly nonlinear dynamics of car engines at low-speed turn its automation in a complex problem that still remains as unsolved. Considering the hybrid nature of the vehicle longitudinal control at low-speed, constantly switching between throttle and brake pedal actions, hybrid control is a good candidate to solve this problem. This work presents the analytical formulation of a hybrid predictive controller for automated low-speed driving. It takes advantage of valuable characteristics supplied by predictive control strategies both for compensating un-modeled dynamics and for keeping passengers security and comfort analytically by means of the treatment of constraints. The proposed controller was implemented in a gas-propelled vehicle to experimentally validate the adopted solution. To this end, different scenarios were analyzed varying road layouts and vehicle speeds within a private test track. The production vehicle is a commercial Citroën C3 Pluriel which has been modified to automatically act over its throttle and brake pedals. PMID:25634584

  1. A non-linear model predictive controller with obstacle avoidance for a space robot

    NASA Astrophysics Data System (ADS)

    Wang, Mingming; Luo, Jianjun; Walter, Ulrich

    2016-04-01

    This study investigates the use of the non-linear model predictive control (NMPC) strategy for a kinematically redundant space robot to approach an un-cooperative target in complex space environment. Collision avoidance, traditionally treated as a high level planning problem, can be effectively translated into control constraints as part of the NMPC. The objective of this paper is to evaluate the performance of the predictive controller in a constrained workspace and to investigate the feasibility of imposing additional constraints into the NMPC. In this paper, we reformulated the issue of the space robot motion control by using NMPC with predefined objectives under input, output and obstacle constraints over a receding horizon. An on-line quadratic programming (QP) procedure is employed to obtain the constrained optimal control decisions in real-time. This study has been implemented for a 7 degree-of-freedom (DOF) kinematically redundant manipulator mounted on a 6 DOF free-floating spacecraft via simulation studies. Real-time trajectory tracking and collision avoidance particularly demonstrate the effectiveness and potential of the proposed NMPC strategy for the space robot.

  2. Nonlinear Model Predictive Control Based on a Self-Organizing Recurrent Neural Network.

    PubMed

    Han, Hong-Gui; Zhang, Lu; Hou, Ying; Qiao, Jun-Fei

    2016-02-01

    A nonlinear model predictive control (NMPC) scheme is developed in this paper based on a self-organizing recurrent radial basis function (SR-RBF) neural network, whose structure and parameters are adjusted concurrently in the training process. The proposed SR-RBF neural network is represented in a general nonlinear form for predicting the future dynamic behaviors of nonlinear systems. To improve the modeling accuracy, a spiking-based growing and pruning algorithm and an adaptive learning algorithm are developed to tune the structure and parameters of the SR-RBF neural network, respectively. Meanwhile, for the control problem, an improved gradient method is utilized for the solution of the optimization problem in NMPC. The stability of the resulting control system is proved based on the Lyapunov stability theory. Finally, the proposed SR-RBF neural network-based NMPC (SR-RBF-NMPC) is used to control the dissolved oxygen (DO) concentration in a wastewater treatment process (WWTP). Comparisons with other existing methods demonstrate that the SR-RBF-NMPC can achieve a considerably better model fitting for WWTP and a better control performance for DO concentration. PMID:26336152

  3. Global predictive real-time control of Quebec Urban Community's westerly sewer network.

    PubMed

    Pleau, M; Pelletier, G; Colas, H; Lavallée, P; Bonin, R

    2001-01-01

    Quebec Urban Community (QUC) has selected Global Predictive Real-Time Control (GP-RTC) as the most efficient approach to achieve environmental objectives defined by the Ministry of Environment. QUC wants to reduce combined sewer overflows (CSOs) frequency to the St Lawrence river to two events per summer period in order to reclaim the use of Jacques-Cartier Beach for recreational activities and sports of primary contact. QUC's control scheme is based on the Certainty Equivalent Control Open Loop Feedback (CEOLF) strategy which permits one to introduce, at each control period, updated measurements and meteorological predictions. A non-linear programming package is used to find the flow set points that minimise a multi-objective (cost) function, subjected to linear equality and inequality constraints representing the physical and operational constraints on the sewer network. Implementation of GP-RTC on QUC's westerly network was performed in the summer of 1999 and was operational by mid-August. Reductions in overflow volumes with GP-RTC compared to static control are attributed to the optimal use of two existing tunnels as retention facilities as well as the maximal use of the wastewater treatment plant (WWTP) capacity. PMID:11385838

  4. Generalized Predictive Control of Dynamic Systems with Rigid-Body Modes

    NASA Technical Reports Server (NTRS)

    Kvaternik, Raymond G.

    2013-01-01

    Numerical simulations to assess the effectiveness of Generalized Predictive Control (GPC) for active control of dynamic systems having rigid-body modes are presented. GPC is a linear, time-invariant, multi-input/multi-output predictive control method that uses an ARX model to characterize the system and to design the controller. Although the method can accommodate both embedded (implicit) and explicit feedforward paths for incorporation of disturbance effects, only the case of embedded feedforward in which the disturbances are assumed to be unknown is considered here. Results from numerical simulations using mathematical models of both a free-free three-degree-of-freedom mass-spring-dashpot system and the XV-15 tiltrotor research aircraft are presented. In regulation mode operation, which calls for zero system response in the presence of disturbances, the simulations showed reductions of nearly 100%. In tracking mode operations, where the system is commanded to follow a specified path, the GPC controllers produced the desired responses, even in the presence of disturbances.

  5. Efficacy of predictive wavefront control for compensating aero-optical aberrations

    NASA Astrophysics Data System (ADS)

    Goorskey, David J.; Schmidt, Jason; Whiteley, Matthew R.

    2013-07-01

    Imaging and laser beam propagation from airborne platforms are degraded by dynamic aberrations due to air flow around the aircraft, aero-mechanical distortions and jitter, and free atmospheric turbulence. For certain applications, like dim-object imaging, free-space optical communications, and laser weapons, adaptive optics (AO) is necessary to compensate for the aberrations in real time. Aero-optical flow is a particularly interesting source of aberrations whose flowing structures can be exploited by adaptive and predictive AO controllers, thereby realizing significant performance gains. We analyze dynamic aero-optical wavefronts to determine the pointing angles at which predictive wavefront control is more effective than conventional, fixed-gain, linear-filter control. It was found that properties of the spatial decompositions and temporal statistics of the wavefronts are directly traceable to specific features in the air flow. Furthermore, the aero-optical wavefront aberrations at the side- and aft-looking angles were the most severe, but they also benefited the most from predictive AO.

  6. Does Sense of Control Predict Depression Among Individuals After Psychiatric Hospital Discharge?

    PubMed

    Kim, Yoo Jung; Fusco, Rachel A

    2015-11-01

    Sense of control is known to be related to depression. Yet, few studies have examined the role of sense of control as related to depression for discharged psychiatric patients. In this study the longitudinal relationship between sense of control and depressive mood was examined using the MacArthur Violence Risk Assessment Study, a 6-wave, 1-year study of 948 ethnically diverse postdischarge psychiatric patients. Sense of control was decomposed into 2 components (i.e., a time-invariant as well as a time-varying component) and so as to examine which component of sense of control would more accurately explain this relationship. Results demonstrated that time-varying sense of control significantly predicted changes in depressive mood during the transition to community environment. Time-invariant sense of control, however, was not significantly related to changes in depressive mood. Findings of this study hold important implications for intervention practice with people before or after psychiatric discharge, including the need for incorporation of therapeutic and psychoeducational efforts that bolster sense of control. PMID:26488915

  7. Predictive functional control for active queue management in congested TCP/IP networks.

    PubMed

    Bigdeli, N; Haeri, M

    2009-01-01

    Predictive functional control (PFC) as a new active queue management (AQM) method in dynamic TCP networks supporting explicit congestion notification (ECN) is proposed. The ability of the controller in handling system delay along with its simplicity and low computational load makes PFC a privileged AQM method in the high speed networks. Besides, considering the disturbance term (which represents model/process mismatches, external disturbances, and existing noise) in the control formulation adds some level of robustness into the PFC-AQM controller. This is an important and desired property in the control of dynamically-varying computer networks. In this paper, the controller is designed based on a small signal linearized fluid-flow model of the TCP/AQM networks. Then, closed-loop transfer function representation of the system is derived to analyze the robustness with respect to the network and controller parameters. The analytical as well as the packet-level ns-2 simulation results show the out-performance of the developed controller for both queue regulation and resource utilization. Fast response, low queue fluctuations (and consequently low delay jitter), high link utilization, good disturbance rejection, scalability, and low packet marking probability are other features of the developed method with respect to other well-known AQM methods such as RED, PI, and REM which are also simulated for comparison. PMID:18995853

  8. Flood mitigation through optimal control of a network of multi-purpose reservoirs by using Model Predictive Control

    NASA Astrophysics Data System (ADS)

    MyoLin, Nay; Rutten, Martine; van de Giesen, Nick

    2016-04-01

    Flooding is a common natural disaster in the world. Construction of reservoirs, sluice gates, dikes, embankments and sea walls are implemented to minimize loss of life and property in a flood event. Rather than completely relying on large structural measures, non-structural measures such as real time control of a reservoir system can also improve flood prevention and water supply in a river basin. In this paper, we present the optimal operation of a multi-reservoir system by using Model Predictive Control (MPC) and particular attention is focused on flood mitigation of the Sittaung River Basin, Myanmar. The main challenges are non-linearity in the dynamic behavior of the water system and exponential growth of computational complexity with the state and control dimension. To deal with an issue related to non-linearity, we applied simplified internal model based on linearization scheme with a large grid length. For solving curse of dimensionality, we utilize the reduced model in which the states of the system are reduced by considering outflows from uncontrolled catchments as disturbances in the water system. We also address the computational time for real time control by using large time step scheme. Simulation results indicate that this model is able to use for real time control of a reservoir system addressing trade-offs between the multiple objectives.

  9. A cerebellar model for predictive motor control tested in a brain-based device

    PubMed Central

    McKinstry, Jeffrey L.; Edelman, Gerald M.; Krichmar, Jeffrey L.

    2006-01-01

    The cerebellum is known to be critical for accurate adaptive control and motor learning. We propose here a mechanism by which the cerebellum may replace reflex control with predictive control. This mechanism is embedded in a learning rule (the delayed eligibility trace rule) in which synapses onto a Purkinje cell or onto a cell in the deep cerebellar nuclei become eligible for plasticity only after a fixed delay from the onset of suprathreshold presynaptic activity. To investigate the proposal that the cerebellum is a general-purpose predictive controller guided by a delayed eligibility trace rule, a computer model based on the anatomy and dynamics of the cerebellum was constructed. It contained components simulating cerebellar cortex and deep cerebellar nuclei, and it received input from a middle temporal visual area and the inferior olive. The model was incorporated in a real-world brain-based device (BBD) built on a Segway robotic platform that learned to traverse curved paths. The BBD learned which visual motion cues predicted impending collisions and used this experience to avoid path boundaries. During learning, the BBD adapted its velocity and turning rate to successfully traverse various curved paths. By examining neuronal activity and synaptic changes during this behavior, we found that the cerebellar circuit selectively responded to motion cues in specific receptive fields of simulated middle temporal visual areas. The system described here prompts several hypotheses about the relationship between perception and motor control and may be useful in the development of general-purpose motor learning systems for machines. PMID:16488974

  10. A cerebellar model for predictive motor control tested in a brain-based device.

    PubMed

    McKinstry, Jeffrey L; Edelman, Gerald M; Krichmar, Jeffrey L

    2006-02-28

    The cerebellum is known to be critical for accurate adaptive control and motor learning. We propose here a mechanism by which the cerebellum may replace reflex control with predictive control. This mechanism is embedded in a learning rule (the delayed eligibility trace rule) in which synapses onto a Purkinje cell or onto a cell in the deep cerebellar nuclei become eligible for plasticity only after a fixed delay from the onset of suprathreshold presynaptic activity. To investigate the proposal that the cerebellum is a general-purpose predictive controller guided by a delayed eligibility trace rule, a computer model based on the anatomy and dynamics of the cerebellum was constructed. It contained components simulating cerebellar cortex and deep cerebellar nuclei, and it received input from a middle temporal visual area and the inferior olive. The model was incorporated in a real-world brain-based device (BBD) built on a Segway robotic platform that learned to traverse curved paths. The BBD learned which visual motion cues predicted impending collisions and used this experience to avoid path boundaries. During learning, the BBD adapted its velocity and turning rate to successfully traverse various curved paths. By examining neuronal activity and synaptic changes during this behavior, we found that the cerebellar circuit selectively responded to motion cues in specific receptive fields of simulated middle temporal visual areas. The system described here prompts several hypotheses about the relationship between perception and motor control and may be useful in the development of general-purpose motor learning systems for machines. PMID:16488974

  11. Threat Interference Biases Predict Socially Anxious Behavior: The Role of Inhibitory Control and Minute of Stressor.

    PubMed

    Gorlin, Eugenia I; Teachman, Bethany A

    2015-07-01

    The current study brings together two typically distinct lines of research. First, social anxiety is inconsistently associated with behavioral deficits in social performance, and the factors accounting for these deficits remain poorly understood. Second, research on selective processing of threat cues, termed cognitive biases, suggests these biases typically predict negative outcomes, but may sometimes be adaptive, depending on the context. Integrating these research areas, the current study examined whether conscious and/or unconscious threat interference biases (indexed by the unmasked and masked emotional Stroop) can explain unique variance, beyond self-reported anxiety measures, in behavioral avoidance and observer-rated anxious behavior during a public speaking task. Minute of speech and general inhibitory control (indexed by the color-word Stroop) were examined as within-subject and between-subject moderators, respectively. Highly socially anxious participants (N=135) completed the emotional and color-word Stroop blocks prior to completing a 4-minute videotaped speech task, which was later coded for anxious behaviors (e.g., speech dysfluency). Mixed-effects regression analyses revealed that general inhibitory control moderated the relationship between both conscious and unconscious threat interference bias and anxious behavior (though not avoidance), such that lower threat interference predicted higher levels of anxious behavior, but only among those with relatively weaker (versus stronger) inhibitory control. Minute of speech further moderated this relationship for unconscious (but not conscious) social-threat interference, such that lower social-threat interference predicted a steeper increase in anxious behaviors over the course of the speech (but only among those with weaker inhibitory control). Thus, both trait and state differences in inhibitory control resources may influence the behavioral impact of threat biases in social anxiety. PMID:26163713

  12. Parafoveal Target Detectability Reversal Predicted by Local Luminance and Contrast Gain Control

    NASA Technical Reports Server (NTRS)

    Ahumada, Albert J., Jr.; Beard, Bettina L.; Null, Cynthia H. (Technical Monitor)

    1996-01-01

    This project is part of a program to develop image discrimination models for the prediction of the detectability of objects in a range of backgrounds. We wanted to see if the models could predict parafoveal object detection as well as they predict detection in foveal vision. We also wanted to make our simplified models more general by local computation of luminance and contrast gain control. A signal image (0.78 x 0.17 deg) was made by subtracting a simulated airport runway scene background image (2.7 deg square) from the same scene containing an obstructing aircraft. Signal visibility contrast thresholds were measured in a fully crossed factorial design with three factors: eccentricity (0 deg or 4 deg), background (uniform or runway scene background), and fixed-pattern white noise contrast (0%, 5%, or 10%). Three experienced observers responded to three repetitions of 60 2IFC trials in each condition and thresholds were estimated by maximum likelihood probit analysis. In the fovea the average detection contrast threshold was 4 dB lower for the runway background than for the uniform background, but in the parafovea, the average threshold was 6 dB higher for the runway background than for the uniform background. This interaction was similar across the different noise levels and for all three observers. A likely reason for the runway background giving a lower threshold in the fovea is the low luminance near the signal in that scene. In our model, the local luminance computation is controlled by a spatial spread parameter. When this parameter and a corresponding parameter for the spatial spread of contrast gain were increased for the parafoveal predictions, the model predicts the interaction of background with eccentricity.

  13. Changes in predictive motor control in drop-jumps based on uncertainties in task execution.

    PubMed

    Leukel, Christian; Taube, Wolfgang; Lorch, Michael; Gollhofer, Albert

    2012-02-01

    Drop-jumps are controlled by predictive and reactive motor strategies which differ with respect to the utilization of sensory feedback. With reaction, sensory feedback is integrated while performing the task. With prediction, sensory information may be used prior to movement onset. Certainty about upcoming events is important for prediction. The present study aimed at investigating how uncertainties in the task execution affect predictive motor control in drop-jumps. Ten healthy subjects (22±1 years, M±SD) participated. The subjects performed either (i) drop-jumps by knowing that they might had to switch to a landing movement upon an auditory cue, which was sometimes elicited prior to touch-down (uncertainty). In (ii), subjects performed drop-jumps by knowing that there would be no auditory cue and consequently no switch of the movement (certainty). The m. soleus EMG prior to touch-down was higher when subjects knew there would be no auditory cue compared to when subjects performed the same task but switching from drop-jump to landing was possible (uncertainty). The EMG was reversed in the late concentric phase, meaning that it was higher in the high uncertainty task. The results of the present study showed that the muscular activity was predictively adjusted according to uncertainties in task execution. It is argued that tendomuscular stiffness was the variable responsible for the adjustment of muscular activity. The required tendomuscular stiffness was higher in drop-jumps than in landings. Consequently, when it was not certain whether to jump or to land, muscular activity and therefore tendomuscular stiffness was reduced. PMID:21757248

  14. State dependent model predictive control for orbital rendezvous using pulse-width pulse-frequency modulated thrusters

    NASA Astrophysics Data System (ADS)

    Li, Peng; Zhu, Zheng H.; Meguid, S. A.

    2016-07-01

    This paper studies the pulse-width pulse-frequency modulation based trajectory planning for orbital rendezvous and proximity maneuvering near a non-cooperative spacecraft in an elliptical orbit. The problem is formulated by converting the continuous control input, output from the state dependent model predictive control, into a sequence of pulses of constant magnitude by controlling firing frequency and duration of constant-magnitude thrusters. The state dependent model predictive control is derived by minimizing the control error of states and control roughness of control input for a safe, smooth and fuel efficient approaching trajectory. The resulting nonlinear programming problem is converted into a series of quadratic programming problem and solved by numerical iteration using the receding horizon strategy. The numerical results show that the proposed state dependent model predictive control with the pulse-width pulse-frequency modulation is able to effectively generate optimized trajectories using equivalent control pulses for the proximity maneuvering with less energy consumption.

  15. Level and Change in Perceived Control Predict 19-Year Mortality: Findings from the Americans' Changing Lives Study

    ERIC Educational Resources Information Center

    Infurna, Frank J.; Ram, Nilam; Gerstorf, Denis

    2013-01-01

    Perceived control plays an important role for health across adulthood and old age. However, little is known about the factors that account for such associations and whether changes in control (or control trajectory) uniquely predict major health outcomes over and above mean levels of control. Using data from the nationwide Americans' Changing…

  16. GOBF-ARMA based model predictive control for an ideal reactive distillation column.

    PubMed

    Seban, Lalu; Kirubakaran, V; Roy, B K; Radhakrishnan, T K

    2015-11-01

    This paper discusses the control of an ideal reactive distillation column (RDC) using model predictive control (MPC) based on a combination of deterministic generalized orthonormal basis filter (GOBF) and stochastic autoregressive moving average (ARMA) models. Reactive distillation (RD) integrates reaction and distillation in a single process resulting in process and energy integration promoting green chemistry principles. Improved selectivity of products, increased conversion, better utilization and control of reaction heat, scope for difficult separations and the avoidance of azeotropes are some of the advantages that reactive distillation offers over conventional technique of distillation column after reactor. The introduction of an in situ separation in the reaction zone leads to complex interactions between vapor-liquid equilibrium, mass transfer rates, diffusion and chemical kinetics. RD with its high order and nonlinear dynamics, and multiple steady states is a good candidate for testing and verification of new control schemes. Here a combination of GOBF-ARMA models is used to catch and represent the dynamics of the RDC. This GOBF-ARMA model is then used to design an MPC scheme for the control of product purity of RDC under different operating constraints and conditions. The performance of proposed modeling and control using GOBF-ARMA based MPC is simulated and analyzed. The proposed controller is found to perform satisfactorily for reference tracking and disturbance rejection in RDC. PMID:25956185

  17. Why achievement motivation predicts success in business but failure in politics: the importance of personal control.

    PubMed

    Winter, David G

    2010-12-01

    Several decades of research have established that implicit achievement motivation (n Achievement) is associated with success in business, particularly in entrepreneurial or sales roles. However, several political psychology studies have shown that achievement motivation is not associated with success in politics; rather, implicit power motivation often predicts political success. Having versus lacking control may be a key difference between business and politics. Case studies suggest that achievement-motivated U.S. presidents and other world leaders often become frustrated and thereby fail because of lack of control, whereas power-motivated presidents develop ways to work with this inherent feature of politics. A reevaluation of previous research suggests that, in fact, relationships between achievement motivation and business success only occur when control is high. The theme of control is also prominent in the development of achievement motivation. Cross-national data are also consistent with this analysis: In democratic industrialized countries, national levels of achievement motivation are associated with strong executive control. In countries with low opportunity for education (thus fewer opportunities to develop a sense of personal control), achievement motivation is associated with internal violence. Many of these manifestations of frustrated achievement motivation in politics resemble authoritarianism. This conclusion is tested by data from a longitudinal study of 113 male college students, showing that high initial achievement motivation combined with frustrated desires for control is related to increases in authoritarianism (F-scale scores) during the college years. Implications for the psychology of leadership and practical politics are discussed. PMID:21039527

  18. Cognitive Control Predicts Use of Model-Based Reinforcement-Learning

    PubMed Central

    Otto, A. Ross; Skatova, Anya; Madlon-Kay, Seth; Daw, Nathaniel D.

    2015-01-01

    Accounts of decision-making and its neural substrates have long posited the operation of separate, competing valuation systems in the control of choice behavior. Recent theoretical and experimental work suggest that this classic distinction between behaviorally and neurally dissociable systems for habitual and goal-directed (or more generally, automatic and controlled) choice may arise from two computational strategies for reinforcement learning (RL), called model-free and model-based RL, but the cognitive or computational processes by which one system may dominate over the other in the control of behavior is a matter of ongoing investigation. To elucidate this question, we leverage the theoretical framework of cognitive control, demonstrating that individual differences in utilization of goal-related contextual information—in the service of overcoming habitual, stimulus-driven responses—in established cognitive control paradigms predict model-based behavior in a separate, sequential choice task. The behavioral correspondence between cognitive control and model-based RL compellingly suggests that a common set of processes may underpin the two behaviors. In particular, computational mechanisms originally proposed to underlie controlled behavior may be applicable to understanding the interactions between model-based and model-free choice behavior. PMID:25170791

  19. Degradation Mechanisms and Lifetime Prediction for Lithium-Ion Batteries -- A Control Perspective: Preprint

    SciTech Connect

    Smith, Kandler; Shi, Ying; Santhanagopalan, Shriram

    2015-07-29

    Predictive models of Li-ion battery lifetime must consider a multiplicity of electrochemical, thermal, and mechanical degradation modes experienced by batteries in application environments. To complicate matters, Li-ion batteries can experience different degradation trajectories that depend on storage and cycling history of the application environment. Rates of degradation are controlled by factors such as temperature history, electrochemical operating window, and charge/discharge rate. We present a generalized battery life prognostic model framework for battery systems design and control. The model framework consists of trial functions that are statistically regressed to Li-ion cell life datasets wherein the cells have been aged under different levels of stress. Degradation mechanisms and rate laws dependent on temperature, storage, and cycling condition are regressed to the data, with multiple model hypotheses evaluated and the best model down-selected based on statistics. The resulting life prognostic model, implemented in state variable form, is extensible to arbitrary real-world scenarios. The model is applicable in real-time control algorithms to maximize battery life and performance. We discuss efforts to reduce lifetime prediction error and accommodate its inevitable impact in controller design.

  20. Establishing Causality Using Longitudinal Hierarchical Linear Modeling: An Illustration Predicting Achievement From Self-Control

    PubMed Central

    Duckworth, Angela Lee; Tsukayama, Eli; May, Henry

    2010-01-01

    The predictive validity of personality for important life outcomes is well established, but conventional longitudinal analyses cannot rule out the possibility that unmeasured third-variable confounds fully account for the observed relationships. Longitudinal hierarchical linear models (HLM) with time-varying covariates allow each subject to serve as his or her own control, thus eliminating between-individual confounds. HLM also allows the directionality of the causal relationship to be tested by reversing time-lagged predictor and outcome variables. We illustrate these techniques through a series of models that demonstrate that within-individual changes in self-control over time predict subsequent changes in GPA but not vice-versa. The evidence supporting a causal role for self-control was not moderated by IQ, gender, ethnicity, or income. Further analyses rule out one time-varying confound: self-esteem. The analytic approach taken in this study provides the strongest evidence to date for the causal role of self-control in determining achievement. PMID:20976121

  1. Prediction of circulation control performance characteristics for Super STOL and STOL applications

    NASA Astrophysics Data System (ADS)

    Naqvi, Messam Abbas

    due to the lack of a simple prediction capability. This research effort was focused on the creation of a rapid prediction capability of Circulation Control Aerodynamic Characteristics which could help designers with rapid performance estimates for design space exploration. A morphological matrix was created with the available set of options which could be chosen to create this prediction capability starting with purely analytical physics based modeling to high fidelity CFD codes. Based on the available constraints, and desired accuracy meta-models have been created around the two dimensional circulation control performance results computed using Navier Stokes Equations (Computational Fluid Dynamics). DSS2, a two dimensional RANS code written by Professor Lakshmi Sankar was utilized for circulation control airfoil characteristics. The CFD code was first applied to the NCCR 1510-7607N airfoil to validate the model with available experimental results. It was then applied to compute the results of a fractional factorial design of experiments array. Metamodels were formulated using the neural networks to the results obtained from the Design of Experiments. Additional validation runs were performed to validate the model predictions. Metamodels are not only capable of rapid performance prediction, but also help generate the relation trends of response matrices with control variables and capture the complex interactions between control variables. Quantitative as well as qualitative assessments of results were performed by computation of aerodynamic forces & moments and flow field visualizations. Wing characteristics in three dimensions were obtained by integration over the whole wing using Prandtl's Wing Theory. The baseline Super STOL configuration [3] was then analyzed with the application of circulation control technology. The desired values of lift and drag to achieve the target values of Takeoff & Landing performance were compared with the optimal configurations obtained

  2. Model Predictive Control-based Optimal Coordination of Distributed Energy Resources

    SciTech Connect

    Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming; Elizondo, Marcelo A.

    2013-04-03

    Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive control (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.

  3. Model Predictive Control-based Optimal Coordination of Distributed Energy Resources

    SciTech Connect

    Mayhorn, Ebony T.; Kalsi, Karanjit; Lian, Jianming; Elizondo, Marcelo A.

    2013-01-07

    Distributed energy resources, such as renewable energy resources (wind, solar), energy storage and demand response, can be used to complement conventional generators. The uncertainty and variability due to high penetration of wind makes reliable system operations and controls challenging, especially in isolated systems. In this paper, an optimal control strategy is proposed to coordinate energy storage and diesel generators to maximize wind penetration while maintaining system economics and normal operation performance. The goals of the optimization problem are to minimize fuel costs and maximize the utilization of wind while considering equipment life of generators and energy storage. Model predictive control (MPC) is used to solve a look-ahead dispatch optimization problem and the performance is compared to an open loop look-ahead dispatch problem. Simulation studies are performed to demonstrate the efficacy of the closed loop MPC in compensating for uncertainties and variability caused in the system.

  4. Wide-area Power System Oscillation Damping using Model Predictive Control Technique

    NASA Astrophysics Data System (ADS)

    Mohamed, Tarek Hassan; Abdel-Rahim, Abdel-Moamen Mohammed; Hassan, Ahmed Abd-Eltawwab; Hiyama, Takashi

    This paper presents a new approach to deal with the problem of robust tuning of power system stabilizer (PSS) and automatic voltage regulator (AVR) in multi-machine power systems. The proposed method is based on a model predictive control (MPC) technique, for improvement stability of the wide-area power system with multiple generators and distribution systems including dispersed generations. The proposed method provides better damping of power system oscillations under small and large disturbances even with the inclusion of local PSSs. The effectiveness of the proposed approach is demonstrated through a two areas, four machines power system. A performance comparison between the proposed controller and some of other controllers is carried out confirming the superiority of the proposed technique. It has also been observed that the proposed algorithm can be successfully applied to larger multiarea power systems and do not suffer with computational difficulties. The proposed algorithm carried out using MATLAB/SIMULINK software package.

  5. Predictive control for voltage collapse avoidance using a modified discrete multi-valued PSO algorithm.

    PubMed

    Pourjafari, Ebrahim; Mojallali, Hamed

    2011-04-01

    Voltage stability is one of the most challenging concerns that power utilities are confronted with, and this paper proposes a voltage control scheme based on Model Predictive Control (MPC) to overcome this kind of instability. Voltage instability has a close relation with the adequacy of reactive power and the response of Under Load Tap Changers (ULTCs) to the voltage drop after the occurrence of a contingency. Therefore, the proposed method utilizes reactive power injection and tap changing to avoid voltage collapse. Considering discrete nature of the changes in the tap ratio and also in the reactive power injected by capacitor banks, the search area for the optimizer of MPC will be an integer area; consequently, a modified discrete multi-valued Particle Swarm Optimization (PSO) is considered to perform this optimization. Simulation results of applying the proposed control scheme to a 4-bus system confirm its capability to prevent voltage collapse. PMID:21251650

  6. High Accuracy Liquid Propellant Slosh Predictions Using an Integrated CFD and Controls Analysis Interface

    NASA Technical Reports Server (NTRS)

    Marsell, Brandon; Griffin, David; Schallhorn, Dr. Paul; Roth, Jacob

    2012-01-01

    Coupling computational fluid dynamics (CFD) with a controls analysis tool elegantly allows for high accuracy predictions of the interaction between sloshing liquid propellants and th e control system of a launch vehicle. Instead of relying on mechanical analogs which are not valid during aU stages of flight, this method allows for a direct link between the vehicle dynamic environments calculated by the solver in the controls analysis tool to the fluid flow equations solved by the CFD code. This paper describes such a coupling methodology, presents the results of a series of test cases, and compares said results against equivalent results from extensively validated tools. The coupling methodology, described herein, has proven to be highly accurate in a variety of different cases.

  7. Rear wheel torque vectoring model predictive control with velocity regulation for electric vehicles

    NASA Astrophysics Data System (ADS)

    Siampis, Efstathios; Velenis, Efstathios; Longo, Stefano

    2015-11-01

    In this paper we propose a constrained optimal control architecture for combined velocity, yaw and sideslip regulation for stabilisation of the vehicle near the limit of lateral acceleration using the rear axle electric torque vectoring configuration of an electric vehicle. A nonlinear vehicle and tyre model are used to find reference steady-state cornering conditions and design two model predictive control (MPC) strategies of different levels of fidelity: one that uses a linearised version of the full vehicle model with the rear wheels' torques as the input, and another one that neglects the wheel dynamics and uses the rear wheels' slips as the input instead. After analysing the relative trade-offs between performance and computational effort, we compare the two MPC strategies against each other and against an unconstrained optimal control strategy in Simulink and Carsim environment.

  8. Fuzzy modeling and predictive control of superheater steam temperature for power plant.

    PubMed

    Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

    2015-05-01

    This paper develops a stable fuzzy model predictive controller (SFMPC) to solve the superheater steam temperature (SST) control problem in a power plant. First, a data-driven Takagi-Sugeno (TS) fuzzy model is developed to approximate the behavior of the SST control system using the subspace identification (SID) method. Then, an SFMPC for output regulation is designed based on the TS-fuzzy model to regulate the SST while guaranteeing the input-to-state stability under the input constraints. The effect of modeling mismatches and unknown plant behavior variations are overcome by the use of a disturbance term and steady-state target calculator (SSTC). Simulation results for a 600 MW power plant show that an offset-free tracking of SST can be achieved over a wide range of load variation. PMID:25530258

  9. Integrated CFD and Controls Analysis Interface for High Accuracy Liquid Propellant Slosh Predictions

    NASA Technical Reports Server (NTRS)

    Marsell, Brandon; Griffin, David; Schallhorn, Paul; Roth, Jacob

    2012-01-01

    Coupling computational fluid dynamics (CFD) with a controls analysis tool elegantly allows for high accuracy predictions of the interaction between sloshing liquid propellants and the control system of a launch vehicle. Instead of relying on mechanical analogs which are n0t va lid during all stages of flight, this method allows for a direct link between the vehicle dynamic environments calculated by the solver in the controls analysis tool to the fluid now equations solved by the CFD code. This paper describes such a coupling methodology, presents the results of a series of test cases, and compares said results against equivalent results from extensively validated tools. The coupling methodology, described herein, has proven to be highly accurate in a variety of different cases.

  10. A Prediction Method of TV Camera Image for Space Manual-control Rendezvous and Docking

    NASA Astrophysics Data System (ADS)

    Zhen, Huang; Qing, Yang; Wenrui, Wu

    Space manual-control rendezvous and docking (RVD) is a key technology for accomplishing the RVD mission in manned space engineering, especially when automatic control system is out of work. The pilot on chase spacecraft manipulates the hand-stick by the image of target spacecraft captured by TV camera. From the TV image, the relative position and attitude of chase and target spacecrafts can be shown. Therefore, the size, the position, the brightness and the shadow of the target on TV camera are key to guarantee the success of manual-control RVD. A method of predicting the on-orbit TV camera image at different relative positions and light conditions during the process of RVD is discussed. Firstly, the basic principle of capturing the image of cross drone on target spacecraft by TV camera is analyzed theoretically, based which the strategy of manual-control RVD is discussed in detail. Secondly, the relationship between the displayed size or position and the real relative distance of chase and target spacecrafts is presented, the brightness and reflection by the target spacecraft at different light conditions are decribed, the shadow on cross drone caused by the chase or target spacecraft is analyzed. Thirdly, a prediction method of on-orbit TV camera images at certain orbit and light condition is provided, and the characteristics of TV camera image during the RVD is analyzed. Finally, the size, the position, the brightness and the shadow of target spacecraft on TV camera image at typical orbit is simulated. The result, by comparing the simulated images with the real images captured by the TV camera on Shenzhou manned spaceship , shows that the prediction method is reasonable

  11. Hedonic Hunger Prospectively Predicts Onset and Maintenance of Loss of Control Eating among College Women

    PubMed Central

    Lowe, Michael R.; Arigo, Danielle; Butryn, Meghan L.; Gilbert, Jennifer R; Sarwer, David; Stice, Eric

    2016-01-01

    Objective The subjective feeling of loss of control (LOC) over eating is common among eating disordered individuals and has predicted weight gain in past research. Restrained eating and negative affect are risk factors for binge eating (which involves LOC), but intense feelings of pleasure derived from palatable foods might also predict the emergence or intensification of LOC eating. The Power of Food Scale (PFS; Lowe et al., 2009) assesses preoccupation with the pleasure derived from palatable food. Method The current sample (n = 294) comprised female college freshmen at risk for weight gain. LOC was assessed using an abbreviated version of the Eating Disorders Examination interview. LOC was assessed at baseline, 6 weeks and 6, 12 and 24 months follow-ups. Results Among those exhibiting LOC eating at baseline, (and controlling for baseline depression, restrained eating and body image dissatisfaction), those scoring higher on the PFS at baseline showed a smaller reduction in LOC frequency over time relative to those scoring lower. Using the same covariates, the PFS predicted the first emergence of LOC over two years among those showing no LOC at baseline. Conclusions These results suggest that powerful hedonic attraction to palatable foods may represent a risk factor for the maintenance of LOC in those initially experiencing it and the emergence of LOC eating in those who are not. An enhanced ability to identify individuals at increased risk of developing or maintaining LOC eating could be useful in prevention programs. PMID:26690638

  12. Prediction of forces and moments for hypersonic flight vehicle control effectors

    NASA Technical Reports Server (NTRS)

    Maughmer, Mark D.; Long, Lyle N.; Pagano, Peter J.

    1991-01-01

    Developing methods of predicting flight control forces and moments for hypersonic vehicles, included a preliminary assessment of subsonic/supersonic panel methods and hypersonic local flow inclination methods for such predictions. While these findings clearly indicate the usefulness of such methods for conceptual design activities, deficiencies exist in some areas. Thus, a second phase of research was proposed in which a better understanding is sought for the reasons of the successes and failures of the methods considered, particularly for the cases at hypersonic Mach numbers. To obtain this additional understanding, a more careful study of the results obtained relative to the methods used was undertaken. In addition, where appropriate and necessary, a more complete modeling of the flow was performed using well proven methods of computational fluid dynamics. As a result, assessments will be made which are more quantitative than those of phase 1 regarding the uncertainty involved in the prediction of the aerodynamic derivatives. In addition, with improved understanding, it is anticipated that improvements resulting in better accuracy will be made to the simple force and moment prediction.

  13. Can Self-Prediction Overcome Barriers to Hepatitis B Vaccination? A Randomized Controlled Trial

    PubMed Central

    Cox, Anthony D.; Cox, Dena; Cyrier, Rosalie; Graham-Dotson, Yolanda; Zimet, Gregory D.

    2011-01-01

    Objective Hepatitis B virus (HBV) infection remains a serious public health problem, due in part to low vaccination rates among high-risk adults, many of whom decline vaccination because of barriers such as perceived inconvenience or discomfort. This study evaluates the efficacy of a self-prediction intervention to increase HBV vaccination rates among high-risk adults. Method Randomized controlled trial of 1175 adults recruited from three STD clinics in the United States over 28 months. Participants completed an audio-computer-assisted self-interview (A-CASI), which presented information about HBV infection and vaccination, and measured relevant beliefs, behaviors and demographics. Half of participants were assigned randomly to a "self-prediction" intervention, asking them to predict their future acceptance of HBV vaccination. The main outcome measure was subsequent vaccination behavior. Other measures included perceived barriers to HBV vaccination, measured prior to the intervention. Results There was a significant interaction between the intervention and vaccination barriers, indicating the effect of the intervention differed depending on perceived vaccination barriers. Among high-barriers patients, the intervention significantly increased vaccination acceptance. Among low-barrier patients, the intervention did not influence vaccination acceptance. Conclusions The self-prediction intervention significantly increased vaccination acceptance among "high-barriers" patients, who typically have very low vaccination rates. This brief intervention could be a useful tool in increasing vaccine uptake among high-barriers patients. PMID:21875205

  14. Power and Performance Management in Nonlinear Virtualized Computing Systems via Predictive Control.

    PubMed

    Wen, Chengjian; Mu, Yifen

    2015-01-01

    The problem of power and performance management captures growing research interest in both academic and industrial field. Virtulization, as an advanced technology to conserve energy, has become basic architecture for most data centers. Accordingly, more sophisticated and finer control are desired in virtualized computing systems, where multiple types of control actions exist as well as time delay effect, which make it complicated to formulate and solve the problem. Furthermore, because of improvement on chips and reduction of idle power, power consumption in modern machines shows significant nonlinearity, making linear power models(which is commonly adopted in previous work) no longer suitable. To deal with this, we build a discrete system state model, in which all control actions and time delay effect are included by state transition and performance and power can be defined on each state. Then, we design the predictive controller, via which the quadratic cost function integrating performance and power can be dynamically optimized. Experiment results show the effectiveness of the controller. By choosing a moderate weight, a good balance can be achieved between performance and power: 99.76% requirements can be dealt with and power consumption can be saved by 33% comparing to the case with open loop controller. PMID:26225769

  15. Power and Performance Management in Nonlinear Virtualized Computing Systems via Predictive Control

    PubMed Central

    Wen, Chengjian; Mu, Yifen

    2015-01-01

    The problem of power and performance management captures growing research interest in both academic and industrial field. Virtulization, as an advanced technology to conserve energy, has become basic architecture for most data centers. Accordingly, more sophisticated and finer control are desired in virtualized computing systems, where multiple types of control actions exist as well as time delay effect, which make it complicated to formulate and solve the problem. Furthermore, because of improvement on chips and reduction of idle power, power consumption in modern machines shows significant nonlinearity, making linear power models(which is commonly adopted in previous work) no longer suitable. To deal with this, we build a discrete system state model, in which all control actions and time delay effect are included by state transition and performance and power can be defined on each state. Then, we design the predictive controller, via which the quadratic cost function integrating performance and power can be dynamically optimized. Experiment results show the effectiveness of the controller. By choosing a moderate weight, a good balance can be achieved between performance and power: 99.76% requirements can be dealt with and power consumption can be saved by 33% comparing to the case with open loop controller. PMID:26225769

  16. Pole-placement Predictive Functional Control for over-damped systems with real poles.

    PubMed

    Rossiter, J A; Haber, R; Zabet, K

    2016-03-01

    This paper gives new insight and design proposals for Predictive Functional Control (PFC) algorithms. Common practice and indeed a requirement of PFC is to select a coincidence horizon greater than one for high-order systems and for the link between the design parameters and the desired dynamic to be weak. Here the proposal is to use parallel first-order models to form an independent prediction model and show that with these it is possible both to use a coincidence horizon of one and moreover to obtain precisely the desired closed-loop dynamics. It is shown through analysis that the use of a coincidence horizon of one greatly simplifies coding, tuning, constraint handling and implementation. The paper derives the key results for high-order and non-minimum phase processes and also demonstrates the flexibility and potential industrial utility of the proposal. PMID:26723844

  17. Prediction of pressure and flow transients in a gaseous bipropellant reaction control rocket engine

    NASA Technical Reports Server (NTRS)

    Markowsky, J. J.; Mcmanus, H. N., Jr.

    1974-01-01

    An analytic model is developed to predict pressure and flow transients in a gaseous hydrogen-oxygen reaction control rocket engine feed system. The one-dimensional equations of momentum and continuity are reduced by the method of characteristics from partial derivatives to a set of total derivatives which describe the state properties along the feedline. System components, e.g., valves, manifolds, and injectors are represented by pseudo steady-state relations at discrete junctions in the system. Solutions were effected by a FORTRAN IV program on an IBM 360/65. The results indicate the relative effect of manifold volume, combustion lag time, feedline pressure fluctuations, propellant temperature, and feedline length on the chamber pressure transient. The analytical combustion model is verified by good correlation between predicted and observed chamber pressure transients. The developed model enables a rocket designer to vary the design parameters analytically to obtain stable combustion for a particular mode of operation which is prescribed by mission objectives.

  18. Reliance on functional resting-state network for stable task control predicts behavioral tendency for cooperation.

    PubMed

    Hahn, Tim; Notebaert, Karolien; Anderl, Christine; Reicherts, Philipp; Wieser, Matthias; Kopf, Juliane; Reif, Andreas; Fehl, Katrin; Semmann, Dirk; Windmann, Sabine

    2015-09-01

    Humans display individual variability in cooperative behavior. While an ever-growing body of research has investigated the neural correlates of task-specific cooperation, the mechanisms by which situation-independent, stable differences in cooperation render behavior consistent across a wide range of situations remain elusive. Addressing this issue, we show that the individual tendency to behave in a prosocial or individualistic manner can be predicted from the functional resting-state connectome. More specifically, connections of the cinguloopercular network which supports goal-directed behavior encode cooperative tendency. Effects of virtual lesions to this network on the efficacy of information exchange throughout the brain corroborate our findings. These results shed light on the neural mechanisms underlying individualists' and prosocials' habitual social decisions by showing that reliance on the cinguloopercular task-control network predicts stable cooperative behavior. Based on this evidence, we provide a unifying framework for the interpretation of functional imaging and behavioral studies of cooperative behavior. PMID:26070266

  19. Evaluation of Transport and Dispersion Models: A Controlled Comparison of HPAC and NARAC Predictions

    SciTech Connect

    Warner, S; Heagy, J F; Platt, N; Larson, D; Sugiyama, G; Nasstrom, J S; Foster, K T; Bradley, S; Bieberbach, G

    2001-05-01

    During fiscal year 2000, a series of studies in support of the Defense Threat Reduction Agency (DTRA) was begun. The goal of these studies is to improve the verification, validation, and accreditation (VV&A) of hazard prediction and assessment models and capabilities. These studies are part of a larger joint VV&A collaborative effort that DTRA and the Department of Energy (DOE), via the Lawrence Livermore National Laboratory (LLNL), are conducting. This joint effort includes comparisons of the LLNL and DTRA transport and dispersion (T&D) modeling systems, NARAC and HPAC, respectively. The purpose of this work is to compare, in a systematic way, HPAC and NARAC model predictions for a set of controlled hypothetical release scenarios. Only ''model-versus-model'' comparisons are addressed in this work. Model-to-field trial comparisons for HPAC and NARAC have been addressed in a recent companion study, in support of the same joint VV&A effort.

  20. Models of basal ganglia and cerebellum for sensorimotor integration and predictive control

    NASA Astrophysics Data System (ADS)

    Jabri, Marwan A.; Huang, Jerry; Coenen, Olivier J. D.; Sejnowski, Terrence J.

    2000-10-01

    This paper presents a sensorimotor architecture integrating computational models of a cerebellum and a basal ganglia and operating on a microrobot. The computational models enable a microrobot to learn to track a moving object and anticipate future positions using a CCD camera. The architecture features pre-processing modules for coordinate transformation and instantaneous orientation extraction. Learning of motor control is implemented using predictive Hebbian reinforcement-learning algorithm in the basal ganglia model. Learning of sensory predictions makes use of a combination of long-term depression (LTD) and long-term potentiation (LTP) adaptation rules within the cerebellum model. The basal ganglia model uses the visual inputs to develop sensorimotor mapping for motor control, while the cerebellum module uses robot orientation and world- coordinate transformed inputs to predict the location of the moving object in a robot centered coordinate system. We propose several hypotheses about the functional role of cell populations in the cerebellum and argue that mossy fiber projections to the deep cerebellar nucleus (DCN) could play a coordinate transformation role and act as gain fields. We propose that such transformation could be learnt early in the brain development stages and could be guided by the activity of the climbing fibers. Proprioceptor mossy fibers projecting to the DCN and providing robot orientation with respect to a reference system could be involved in this case. Other mossy fibers carrying visual sensory input provide visual patterns to the granule cells. The combined activities of the granule and the Purkinje cells store spatial representations of the target patterns. The combinations of mossy and Purkinje projections to the DCN provide a prediction of the location of the moving target taking into consideration the robot orientation. Results of lesion simulations based on our model show degradations similar to those reported in cerebellar lesion

  1. A Computational Model for Aperture Control in Reach-to-Grasp Movement Based on Predictive Variability

    PubMed Central

    Takemura, Naohiro; Fukui, Takao; Inui, Toshio

    2015-01-01

    In human reach-to-grasp movement, visual occlusion of a target object leads to a larger peak grip aperture compared to conditions where online vision is available. However, no previous computational and neural network models for reach-to-grasp movement explain the mechanism of this effect. We simulated the effect of online vision on the reach-to-grasp movement by proposing a computational control model based on the hypothesis that the grip aperture is controlled to compensate for both motor variability and sensory uncertainty. In this model, the aperture is formed to achieve a target aperture size that is sufficiently large to accommodate the actual target; it also includes a margin to ensure proper grasping despite sensory and motor variability. To this end, the model considers: (i) the variability of the grip aperture, which is predicted by the Kalman filter, and (ii) the uncertainty of the object size, which is affected by visual noise. Using this model, we simulated experiments in which the effect of the duration of visual occlusion was investigated. The simulation replicated the experimental result wherein the peak grip aperture increased when the target object was occluded, especially in the early phase of the movement. Both predicted motor variability and sensory uncertainty play important roles in the online visuomotor process responsible for grip aperture control. PMID:26696874

  2. Predicting premature termination within a randomized controlled trial for binge-eating patients.

    PubMed

    Flückiger, Christoph; Meyer, Andrea; Wampold, Bruce E; Gassmann, Daniel; Messerli-Bürgy, Nadine; Munsch, Simone

    2011-12-01

    Understanding the dropout rates of efficacious forms of psychotherapy for patients with binge eating disorder (BED) is an unsolved problem within this increasing population. Up until now the role of psychotherapy process characteristics as predictors of premature termination has not been investigated in the BED literature. Within a randomized controlled trial (N=78) we investigated the degree to which early psychological process characteristics, such as components of the therapeutic relationship and the experiences of mastery and motivational clarification, predicted premature termination of treatment. We statistically controlled for the influences of covariates such as rapid response of treatment, treatment group, body mass index, Axis II disorder, and patients' preexisting generalized self-efficacy at baseline. Patients' postsession reports from Sessions 1 to 5 indicated that low self-esteem in-session experiences was a stable predictor of premature termination. Its predictive value persisted after controlling for the above-mentioned covariates. Exploratory analyses further revealed low self-esteem experiences, low global alliance, and low mastery and clarification experiences as predictors in those patients who explicitly specified discontentment with therapy as reason for premature termination. These results indicate that patients' self-esteem experiences may not be an epiphenomenon of their specific psychopathology but may represent general mechanisms on which remaining or withdrawing from psychotherapeutic treatment depends. Early psychotherapy process characteristics should therefore be considered in training and evaluation of psychotherapists carrying through BED treatments. PMID:22035999

  3. Perceived Sexual Control, Sex-Related Alcohol Expectancies and Behavior Predict Substance-Related Sexual Revictimization

    PubMed Central

    Walsh, Kate; Messman-Moore, Terri; Zerubavel, Noga; Chandley, Rachel B.; DeNardi, Kathleen A.; Walker, Dave P.

    2013-01-01

    Objectives Although numerous studies have documented linkages between childhood sexual abuse (CSA) and later sexual revictimization, mechanisms underlying revictimization, particularly assaults occurring in the context of substance use, are not well-understood. Consistent with Traumagenic Dynamics theory, the present study tested a path model positing that lowered perceptions of sexual control resulting from CSA may be associated with increased sex-related alcohol expectancies and heightened likelihood of risky sexual behavior, which in turn, may predict adult substance-related rape. Methods Participants were 546 female college students who completed anonymous surveys regarding CSA and adult rape, perceptions of sexual control, sex-related alcohol expectancies, and likelihood of engaging in risky sexual behavior. Results The data fit the hypothesized model well and all hypothesized path coefficients were significant and in the expected directions. As expected, sex-related alcohol expectancies and likelihood of risky sexual behavior only predicted substance-related rape, not forcible rape. Conclusions Findings suggested that low perceived sexual control stemming from CSA is associated with increased sex-related alcohol expectancies and a higher likelihood of engaging in sexual behavior in the context of alcohol use. In turn these proximal risk factors heighten vulnerability to substance-related rape. Programs which aim to reduce risk for substance-related rape could be improved by addressing expectancies and motivations for risky sexual behavior in the context of substance use. Implications and future directions are discussed. PMID:23312991

  4. Low Vitamin D Levels Do Not Predict Hyperglycemia in Elderly Endurance Athletes (but in Controls)

    PubMed Central

    Nistler, Sonja; Batmyagmar, Delgerdalai; Ponocny-Seliger, Elisabeth; Perkmann, Thomas; Scherzer, Thomas M.; Kundi, Michael; Endler, Georg; Ratzinger, Franz; Pilger, Alexander; Wagner, Oswald F.; Winker, Robert

    2016-01-01

    Background and Aim Recent studies revealed a link between hypovitaminosis D3 and the risk for hyperglycemia. Further mechanistic and interventional investigations suggested a common reason for both conditions rather than a causal relationship. Exposure to sunlight is the most relevant source of vitamin D3 (25(OH)D), whereas adipose tissue is able to store relevant amounts of the lipophilic vitamin. Since running/bicycling leads to increased out-door time and alters physiological response mechanisms, it can be hypothesized that the correlation between hypovitaminosis D3 and hyperglycemia might be disturbed in outdoor athletes. Methods 47 elderly marathoners/bicyclists and 47 age/sex matched controls were studied in a longitudinal setting at baseline and after three years. HbA1c as a surrogate for (pre-)diabetic states was quantified via HPLC, 25(OH)D levels were measured by means of chemiluminescent assays. Physical performance was assessed by ergometry. Results When adjusted for seasonal variations, 25(OH)D was significantly higher in athletes than in controls. 25(OH)D levels inversely correlated with triglycerides in both groups, whereas only in controls an association between high BMI or low physical performance with hypovitaminosis D3 had been found. Likewise, the presence of hypovitaminosis D3 at baseline successfully predicted hyperglycemia at the follow up examinations within the control group (AUC = 0.85, 95% CI [0.74, 0.96], p < .001, statistically independent from BMI), but not in athletes. Conclusion Our data suggest that mechanisms of HbA1c elevation might differ between athletes and controls. Thus, intense physical activity must be taken into account as a potential pre-analytic confounder when it is aimed to predict metabolic risk by vitamin D3 levels. PMID:27304888

  5. Internally directed cognition and mindfulness: an integrative perspective derived from predictive and reactive control systems theory

    PubMed Central

    Tops, Mattie; Boksem, Maarten A. S.; Quirin, Markus; IJzerman, Hans; Koole, Sander L.

    2013-01-01

    In the present paper, we will apply the predictive and reactive control systems (PARCS) theory as a framework that integrates competing theories of neural substrates of awareness by describing the “default mode network” (DMN) and anterior insula (AI) as parts of two different behavioral and homeostatic control systems. The DMN, a network that becomes active at rest when there is no external stimulation or task to perform, has been implicated in self-reflective awareness and prospection. By contrast, the AI is associated with awareness and task-related attention. This has led to competing theories stressing the role of the DMN in self-awareness vs. the role of interoceptive and emotional information integration in the AI in awareness of the emotional moment. In PARCS, the respective functions of the DMN and AI in a specific control system explains their association with different qualities of awareness, and how mental states can shift from one state (e.g., prospective self-reflection) to the other (e.g., awareness of the emotional moment) depending on the relative dominance of control systems. These shifts between reactive and predictive control are part of processes that enable the intake of novel information, integration of this novel information within existing knowledge structures, and the creation of a continuous personal context in which novel information can be integrated and understood. As such, PARCS can explain key characteristics of mental states, such as their temporal and spatial focus (e.g., a focus on the here and now vs. the future; a first person vs. a third person perspective). PARCS further relates mental states to brain states and functions, such as activation of the DMN or hemispheric asymmetry in frontal cortical functions. Together, PARCS deepens the understanding of a broad range of mental states, including mindfulness, mind wandering, rumination, autobiographical memory, imagery, and the experience of self. PMID:24904455

  6. Prediction and control of vortex-dominated and vortex-wake flows

    NASA Technical Reports Server (NTRS)

    Kandil, Osama

    1993-01-01

    This progress report documents the accomplishments achieved in the period from December 1, 1992 until November 30, 1993. These accomplishments include publications, national and international presentations, NASA presentations, and the research group supported under this grant. Topics covered by documents incorporated into this progress report include: active control of asymmetric conical flow using spinning and rotary oscillation; supersonic vortex breakdown over a delta wing in transonic flow; shock-vortex interaction over a 65-degree delta wing in transonic flow; three dimensional supersonic vortex breakdown; numerical simulation and physical aspects of supersonic vortex breakdown; and prediction of asymmetric vortical flows around slender bodies using Navier-Stokes equations.

  7. Predictive control of a chaotic permanent magnet synchronous generator in a wind turbine system

    NASA Astrophysics Data System (ADS)

    Manal, Messadi; Adel, Mellit; Karim, Kemih; Malek, Ghanes

    2015-01-01

    This paper investigates how to address the chaos problem in a permanent magnet synchronous generator (PMSG) in a wind turbine system. Predictive control approach is proposed to suppress chaotic behavior and make operating stable; the advantage of this method is that it can only be applied to one state of the wind turbine system. The use of the genetic algorithms to estimate the optimal parameter values of the wind turbine leads to maximization of the power generation. Moreover, some simulation results are included to visualize the effectiveness and robustness of the proposed method. Project supported by the CMEP-TASSILI Project (Grant No. 14MDU920).

  8. Prediction and Control of Slip-Free Rotation States in Sphere Assemblies

    NASA Astrophysics Data System (ADS)

    Stäger, D. V.; Araújo, N. A. M.; Herrmann, H. J.

    2016-06-01

    We study fixed assemblies of touching spheres that can individually rotate. From any initial state, sliding friction drives an assembly toward a slip-free rotation state. For bipartite assemblies, which have only even loops, this state has at least four degrees of freedom. For exactly four degrees of freedom, we analytically predict the final state, which we prove to be independent of the strength of sliding friction, from an arbitrary initial one. With a tabletop experiment, we show how to impose any slip-free rotation state by only controlling two spheres, regardless of the total number.

  9. Prediction and Control of Slip-Free Rotation States in Sphere Assemblies.

    PubMed

    Stäger, D V; Araújo, N A M; Herrmann, H J

    2016-06-24

    We study fixed assemblies of touching spheres that can individually rotate. From any initial state, sliding friction drives an assembly toward a slip-free rotation state. For bipartite assemblies, which have only even loops, this state has at least four degrees of freedom. For exactly four degrees of freedom, we analytically predict the final state, which we prove to be independent of the strength of sliding friction, from an arbitrary initial one. With a tabletop experiment, we show how to impose any slip-free rotation state by only controlling two spheres, regardless of the total number. PMID:27391726

  10. Numerical prediction of energy consumption in buildings with controlled interior temperature

    SciTech Connect

    Jarošová, P.; Št’astník, S.

    2015-03-10

    New European directives bring strong requirement to the energy consumption of building objects, supporting the renewable energy sources. Whereas in the case of family and similar houses this can lead up to absurd consequences, for building objects with controlled interior temperature the optimization of energy demand is really needed. The paper demonstrates the system approach to the modelling of thermal insulation and accumulation abilities of such objetcs, incorporating the significant influence of additional physical processes, as surface heat radiation and moisture-driven deterioration of insulation layers. An illustrative example shows the numerical prediction of energy consumption of a freezing plant in one Central European climatic year.

  11. On prediction of longitudinal attitude of planing craft based on controllable hydrofoils

    NASA Astrophysics Data System (ADS)

    Ling, Hongjie; Wang, Zhidong; Wu, Na

    2013-09-01

    The purpose of this research study was to examine the attitude response of a planing craft under the controllable hydrofoils. Firstly, a non-linear longitudinal attitude model was established. In the mathematical model, effects of wind loads were considered. Both the wetted length and windward area varied in different navigation conditions. Secondly, control strategies for hydrofoils were specified. Using the above strategies, the heave and trim of the planing craft was adjusted by controllable hydrofoils. Finally, a simulation program was developed to predict the longitudinal attitudes of the planing craft with wind loads. A series of simulations were performed and effects of control strategies on longitudinal attitudes were analyzed. The results show that under effects of wind loads, heave of fixed hydrofoils planing craft decreased by 6.3%, and pitch increased by 8.6% when the main engine power was constant. Heave decreased by less than 1% and trim angle decreased by 1.7% as a result of using variable attack angle hydrofoils; however, amplitude changes of heave and pitch were less than 1% under the control of changeable attack angle hydrofoils and longitudinal attitude.

  12. Design of a data-driven predictive controller for start-up process of AMT vehicles.

    PubMed

    Lu, Xiaohui; Chen, Hong; Wang, Ping; Gao, Bingzhao

    2011-12-01

    In this paper, a data-driven predictive controller is designed for the start-up process of vehicles with automated manual transmissions (AMTs). It is obtained directly from the input-output data of a driveline simulation model constructed by the commercial software AMESim. In order to obtain offset-free control for the reference input, the predictor equation is gained with incremental inputs and outputs. Because of the physical characteristics, the input and output constraints are considered explicitly in the problem formulation. The contradictory requirements of less friction losses and less driveline shock are included in the objective function. The designed controller is tested under nominal conditions and changed conditions. The simulation results show that, during the start-up process, the AMT clutch with the proposed controller works very well, and the process meets the control objectives: fast clutch lockup time, small friction losses, and the preservation of driver comfort, i.e., smooth acceleration of the vehicle. At the same time, the closed-loop system has the ability to reject uncertainties, such as the vehicle mass and road grade. PMID:21954207

  13. Algorithms for a Closed-Loop Artificial Pancreas: The Case for Model Predictive Control

    PubMed Central

    Bequette, B. Wayne

    2013-01-01

    The relative merits of model predictive control (MPC) and proportional-integral-derivative (PID) control are discussed, with the end goal of a closed-loop artificial pancreas (AP). It is stressed that neither MPC nor PID are single algorithms, but rather are approaches or strategies that may be implemented very differently by different engineers. The primary advantages to MPC are that (i) constraints on the insulin delivery rate (and/or insulin on board) can be explicitly included in the control calculation; (ii) it is a general framework that makes it relatively easy to include the effect of meals, exercise, and other events that are a function of the time of day; and (iii) it is flexible enough to include many different objectives, from set-point tracking (target) to zone (control to range). In the end, however, it is recognized that the control algorithm, while important, represents only a portion of the effort required to develop a closed-loop AP. Thus, any number of algorithms/approaches can be successful—the engineers involved in the design must have experience with the particular technique, including the important experience of implementing the algorithm in human studies and not simply through simulation studies. PMID:24351190

  14. Modelling and control issues of dynamically substructured systems: adaptive forward prediction taken as an example

    PubMed Central

    Tu, Jia-Ying; Hsiao, Wei-De; Chen, Chih-Ying

    2014-01-01

    Testing techniques of dynamically substructured systems dissects an entire engineering system into parts. Components can be tested via numerical simulation or physical experiments and run synchronously. Additional actuator systems, which interface numerical and physical parts, are required within the physical substructure. A high-quality controller, which is designed to cancel unwanted dynamics introduced by the actuators, is important in order to synchronize the numerical and physical outputs and ensure successful tests. An adaptive forward prediction (AFP) algorithm based on delay compensation concepts has been proposed to deal with substructuring control issues. Although the settling performance and numerical conditions of the AFP controller are improved using new direct-compensation and singular value decomposition methods, the experimental results show that a linear dynamics-based controller still outperforms the AFP controller. Based on experimental observations, the least-squares fitting technique, effectiveness of the AFP compensation and differences between delay and ordinary differential equations are discussed herein, in order to reflect the fundamental issues of actuator modelling in relevant literature and, more specifically, to show that the actuator and numerical substructure are heterogeneous dynamic components and should not be collectively modelled as a homogeneous delay differential equation. PMID:25104902

  15. Hybrid Active/Passive Control of Sound Radiation from Panels with Constrained Layer Damping and Model Predictive Feedback Control

    NASA Technical Reports Server (NTRS)

    Cabell, Randolph H.; Gibbs, Gary P.

    2000-01-01

    make the controller adaptive. For example, a mathematical model of the plant could be periodically updated as the plant changes, and the feedback gains recomputed from the updated model. To be practical, this approach requires a simple plant model that can be updated quickly with reasonable computational requirements. A recent paper by the authors discussed one way to simplify a feedback controller, by reducing the number of actuators and sensors needed for good performance. The work was done on a tensioned aircraft-style panel excited on one side by TBL flow in a low speed wind tunnel. Actuation was provided by a piezoelectric (PZT) actuator mounted on the center of the panel. For sensing, the responses of four accelerometers, positioned to approximate the response of the first radiation mode of the panel, were summed and fed back through the controller. This single input-single output topology was found to have nearly the same noise reduction performance as a controller with fifteen accelerometers and three PZT patches. This paper extends the previous results by looking at how constrained layer damping (CLD) on a panel can be used to enhance the performance of the feedback controller thus providing a more robust and efficient hybrid active/passive system. The eventual goal is to use the CLD to reduce sound radiation at high frequencies, then implement a very simple, reduced order, low sample rate adaptive controller to attenuate sound radiation at low frequencies. Additionally this added damping smoothes phase transitions over the bandwidth which promotes robustness to natural frequency shifts. Experiments were conducted in a transmission loss facility on a clamped-clamped aluminum panel driven on one side by a loudspeaker. A generalized predictive control (GPC) algorithm, which is suited to online adaptation of its parameters, was used in single input-single output and multiple input-single output configurations. Because this was a preliminary look at the potential

  16. Simulation of complex glazing products; from optical data measurements to model based predictive controls

    SciTech Connect

    Kohler, Christian

    2012-08-01

    Complex glazing systems such as venetian blinds, fritted glass and woven shades require more detailed optical and thermal input data for their components than specular non light-redirecting glazing systems. Various methods for measuring these data sets are described in this paper. These data sets are used in multiple simulation tools to model the thermal and optical properties of complex glazing systems. The output from these tools can be used to generate simplified rating values or as an input to other simulation tools such as whole building annual energy programs, or lighting analysis tools. I also describe some of the challenges of creating a rating system for these products and which factors affect this rating. A potential future direction of simulation and building operations is model based predictive controls, where detailed computer models are run in real-time, receiving data for an actual building and providing control input to building elements such as shades.

  17. [Study of VOCs emission prediction and control based on dynamic CGE].

    PubMed

    Liu, Chang-Xin; Wang, Yu-Fei; Hao, Zheng-Ping; Wang, Zheng

    2013-12-01

    Researches on controlling volatile organic compounds (VOCs) through macroeconomic policy from the view of cost-benefit analysis are very important for our country to improve the air environment. Based on our previous study, this paper predicted future VOCs emissions until 2020 under current policies with 2007 as reference year by using dynamic CGE model. Meanwhile, environmental tax was imposed in ten industries with high emission and the impacts of emissions and economic system were discussed. Finally, policy implementations for VOCs emission control were suggested for policy-makers. The results showed that environment tax could mitigate VOCs emission, but it also resulted in high cost. Owing to the highly related relationship between different sectors, although transport sector was not taxed, it also suffered a great economic influence. Thus, when using the tax policy for reducing VOCs, subsidy for special sector is necessary. PMID:24640924

  18. Interior noise control prediction study for high-speed propeller-driven aircraft

    NASA Technical Reports Server (NTRS)

    Rennison, D. C.; Wilby, J. F.; Marsh, A. H.; Wilby, E. G.

    1979-01-01

    An analytical model was developed to predict the noise levels inside propeller-driven aircraft during cruise at M = 0.8. The model was applied to three study aircraft with fuselages of different size (wide body, narrow body and small diameter) in order to determine the noise reductions required to achieve the goal of an A-weighted sound level which does not exceed 80 dB. The model was then used to determine noise control methods which could achieve the required noise reductions. Two classes of noise control treatments were investigated: add-on treatments which can be added to existing structures, and advanced concepts which would require changes to the fuselage primary structure. Only one treatment, a double wall with limp panel, provided the required noise reductions. Weight penalties associated with the treatment were estimated for the three study aircraft.

  19. Self-statements, locus of control, and depression in predicting self-esteem.

    PubMed

    Philpot, V D; Holliman, W B; Madonna, S

    1995-06-01

    The contributions of frequency of positive and negative self-statements and their ratio, locus of control, and depression in prediction of self-esteem were examined. Volunteers were 145 college students (100 women and 45 men) who were administered the Coopersmith Self-esteem Inventory-Adult Form, Automatic Thought Questionnaire-Revised, the Beck Depression Inventory, and the Rotter Internal-External Locus of Control Scale. Intercorrelations suggested significant relationships among variables. The magnitude of the relationship was strongest between the frequency of negative self-statements and self-esteem. These results are consistent with and lend further support to prior studies of Kendall, et al. and Schwartz and Michaelson. PMID:7568574

  20. Optimal dosing of cancer chemotherapy using model predictive control and moving horizon state/parameter estimation.

    PubMed

    Chen, Tao; Kirkby, Norman F; Jena, Raj

    2012-12-01

    Model predictive control (MPC), originally developed in the community of industrial process control, is a potentially effective approach to optimal scheduling of cancer therapy. The basis of MPC is usually a state-space model (a system of ordinary differential equations), whereby existing studies usually assume that the entire states can be directly measured. This paper aims to demonstrate that when the system states are not fully measurable, in conjunction with model parameter discrepancy, MPC is still a useful method for cancer treatment. This aim is achieved through the application of moving horizon estimation (MHE), an optimisation-based method to jointly estimate the system states and parameters. The effectiveness of the MPC-MHE scheme is illustrated through scheduling the dose of tamoxifen for simulated tumour-bearing patients, and the impact of estimation horizon and magnitude of parameter discrepancy is also investigated. PMID:22739208

  1. Iterated non-linear model predictive control based on tubes and contractive constraints.

    PubMed

    Murillo, M; Sánchez, G; Giovanini, L

    2016-05-01

    This paper presents a predictive control algorithm for non-linear systems based on successive linearizations of the non-linear dynamic around a given trajectory. A linear time varying model is obtained and the non-convex constrained optimization problem is transformed into a sequence of locally convex ones. The robustness of the proposed algorithm is addressed adding a convex contractive constraint. To account for linearization errors and to obtain more accurate results an inner iteration loop is added to the algorithm. A simple methodology to obtain an outer bounding-tube for state trajectories is also presented. The convergence of the iterative process and the stability of the closed-loop system are analyzed. The simulation results show the effectiveness of the proposed algorithm in controlling a quadcopter type unmanned aerial vehicle. PMID:26850752

  2. Prediction of forces and moments for hypersonic flight vehicle control effectors

    NASA Technical Reports Server (NTRS)

    Maughmer, Mark D.; Long, Lyle N.; Guilmette, Neal; Pagano, Peter

    1993-01-01

    This research project includes three distinct phases. For completeness, all three phases of the work are briefly described in this report. The goal was to develop methods of predicting flight control forces and moments for hypersonic vehicles which could be used in a preliminary design environment. The first phase included a preliminary assessment of subsonic/supersonic panel methods and hypersonic local flow inclination methods for such predictions. While these findings clearly indicated the usefulness of such methods for conceptual design activities, deficiencies exist in some areas. Thus, a second phase of research was conducted in which a better understanding was sought for the reasons behind the successes and failures of the methods considered, particularly for the cases at hypersonic Mach numbers. This second phase involved using computational fluid dynamics methods to examine the flow fields in detail. Through these detailed predictions, the deficiencies in the simple surface inclination methods were determined. In the third phase of this work, an improvement to the surface inclination methods was developed. This used a novel method for including viscous effects by modifying the geometry to include the viscous/shock layer.

  3. HIV-1 DNA predicts disease progression and post-treatment virological control

    PubMed Central

    Williams, James P; Hurst, Jacob; Stöhr, Wolfgang; Robinson, Nicola; Brown, Helen; Fisher, Martin; Kinloch, Sabine; Cooper, David; Schechter, Mauro; Tambussi, Giuseppe; Fidler, Sarah; Carrington, Mary; Babiker, Abdel; Weber, Jonathan

    2014-01-01

    In HIV-1 infection, a population of latently infected cells facilitates viral persistence despite antiretroviral therapy (ART). With the aim of identifying individuals in whom ART might induce a period of viraemic control on stopping therapy, we hypothesised that quantification of the pool of latently infected cells in primary HIV-1 infection (PHI) would predict clinical progression and viral replication following ART. We measured HIV-1 DNA in a highly characterised randomised population of individuals with PHI. We explored associations between HIV-1 DNA and immunological and virological markers of clinical progression, including viral rebound in those interrupting therapy. In multivariable analyses, HIV-1 DNA was more predictive of disease progression than plasma viral load and, at treatment interruption, predicted time to plasma virus rebound. HIV-1 DNA may help identify individuals who could safely interrupt ART in future HIV-1 eradication trials. Clinical trial registration: ISRCTN76742797 and EudraCT2004-000446-20 DOI: http://dx.doi.org/10.7554/eLife.03821.001 PMID:25217531

  4. Backflow length predictions during flow-controlled infusions using a nonlinear biphasic finite element model.

    PubMed

    Orozco, Gustavo A; Smith, Joshua H; García, José J

    2014-10-01

    A previously proposed finite element model that considers geometric and material nonlinearities and the free boundary problems that occur at the catheter tip and in the annular zone around the lateral surface of the catheter was revised and was used to fit a power-law formula to predict backflow length during infusions into brain tissue. Compared to a closed-form solution based on linear elasticity, the power-law formula for compliant materials predicted a substantial lower influence of the shear modulus and catheter radius on the backflow length, whereas the corresponding influence for stiffer materials was more consistent with the closed-form solution. The finite element model predicted decreases of the backflow length for reduction of the shear modulus for highly compliant materials (shear modulus less than 500 Pa) due to the increased area of infusion and the high fluid fraction near the infusion cavity that greatly increased the surface area available for fluid transfer and reduced the hydraulic resistance toward the tissue. These results show the importance of taking into account the material and geometrical nonlinearities that arise near the infusion surface as well as the change of hydraulic conductivity with strain for a proper characterization of backflow length during flow-controlled infusions into the brain. PMID:25154980

  5. Real-time implementation of model predictive control on Maricopa-Stanfield irrigation and drainage district's WM canal

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Water resources are limited in many agricultural areas. One method to improve the effective use of water is to improve delivery service from irrigation canals. This can be done by applying automatic control methods that control the gates in an irrigation canal. The model predictive control MPC is ...

  6. Conjunctively optimizing flash flood control and water quality in urban water reservoirs by model predictive control and dynamic emulation

    NASA Astrophysics Data System (ADS)

    Galelli, Stefano; Goedbloed, Albert; Schmitter, Petra; Castelletti, Andrea

    2014-05-01

    Urban water reservoirs are a viable adaptation option to account for increasing drinking water demand of urbanized areas as they allow storage and re-use of water that is normally lost. In addition, the direct availability of freshwater reduces pumping costs and diversifies the portfolios of drinking water supply. Yet, these benefits have an associated twofold cost. Firstly, the presence of large, impervious areas increases the hydraulic efficiency of urban catchments, with short time of concentration, increased runoff rates, losses of infiltration and baseflow, and higher risk of flash floods. Secondly, the high concentration of nutrients and sediments characterizing urban discharges is likely to cause water quality problems. In this study we propose a new control scheme combining Model Predictive Control (MPC), hydro-meteorological forecasts and dynamic model emulation to design real-time operating policies that conjunctively optimize water quantity and quality targets. The main advantage of this scheme stands in its capability of exploiting real-time hydro-meteorological forecasts, which are crucial in such fast-varying systems. In addition, the reduced computational requests of the MPC scheme allows coupling it with dynamic emulators of water quality processes. The approach is demonstrated on Marina Reservoir, a multi-purpose reservoir located in the heart of Singapore and characterized by a large, highly urbanized catchment with a short (i.e. approximately one hour) time of concentration. Results show that the MPC scheme, coupled with a water quality emulator, provides a good compromise between different operating objectives, namely flood risk reduction, drinking water supply and salinity control. Finally, the scheme is used to assess the effect of source control measures (e.g. green roofs) aimed at restoring the natural hydrological regime of Marina Reservoir catchment.

  7. Pragmatism, mathematical models, and the scientific ideal of prediction and control.

    PubMed

    Moore, J

    2015-05-01

    Mathematical models are often held to be valuable, if not necessary, for theories and explanations in the quantitative analysis of behavior. The present review suggests that mathematical models primarily derived from the observation of functional relations do indeed contribute to the scientific value of theories and explanations, even though the final form of the models appears to be highly abstract. However, mathematical models not primarily so derived risk being essentialist in character, based on a particular view of formal causation. Such models invite less effective and frequently mentalistic theories and explanations of behavior. Models may be evaluated in terms of both (a) the verbal processes responsible for their origin and development and (b) the prediction and control engendered by the theories and explanations that incorporate the models, however indirect or abstract that prediction and control may be. Overall, the present review suggests that technological application and theoretical contemplation may be usefully viewed as continuous and overlapping forms of scientific activity, rather than dichotomous and mutually exclusive. PMID:25596451

  8. Exploratory Studies in Generalized Predictive Control for Active Gust Load Alleviation

    NASA Technical Reports Server (NTRS)

    Kvaternik, Raymond G.; Eure, Kenneth W.; Juang, Jer-Nan

    2006-01-01

    The results of numerical simulations aimed at assessing the efficacy of Generalized Predictive Control (GPC) for active gust load alleviation using trailing- and leading-edge control surfaces are presented. The equations underlying the method are presented and discussed, including system identification, calculation of control law matrices, and calculation of commands applied to the control effectors. Both embedded and explicit feedforward paths for inclusion of disturbance effects are addressed. Results from two types of simulations are shown. The first used a 3-DOF math model of a mass-spring-dashpot system subject to user-defined external disturbances. The second used open-loop data from a wind-tunnel test in which a wing model was excited by sinusoidal vertical gusts; closed-loop behavior was simulated in post-test calculations. Results obtained from these simulations have been decidedly positive. In particular, results of closed-loop simulations for the wing model showed reductions in root moments by factors as high as 1000, depending on whether the excitation is from a constant- or variable-frequency gust and on the direction of the response.

  9. An Improved Formulation of Hybrid Model Predictive Control With Application to Production-Inventory Systems.

    PubMed

    Nandola, Naresh N; Rivera, Daniel E

    2013-01-01

    We consider an improved model predictive control (MPC) formulation for linear hybrid systems described by mixed logical dynamical (MLD) models. The algorithm relies on a multiple-degree-of-freedom parametrization that enables the user to adjust the speed of setpoint tracking, measured disturbance rejection and unmeasured disturbance rejection independently in the closed-loop system. Consequently, controller tuning is more flexible and intuitive than relying on objective function weights (such as move suppression) traditionally used in MPC schemes. The controller formulation is motivated by the needs of non-traditional control applications that are suitably described by hybrid production-inventory systems. Two applications are considered in this paper: adaptive, time-varying interventions in behavioral health, and inventory management in supply chains under conditions of limited capacity. In the adaptive intervention application, a hypothetical intervention inspired by the Fast Track program, a real-life preventive intervention for reducing conduct disorder in at-risk children, is examined. In the inventory management application, the ability of the algorithm to judiciously alter production capacity under conditions of varying demand is presented. These case studies demonstrate that MPC for hybrid systems can be tuned for desired performance under demanding conditions involving noise and uncertainty. PMID:24348004

  10. Predicting the effects of unmodeled dynamics on an aircraft flight control system design using eigenspace assignment

    NASA Technical Reports Server (NTRS)

    Johnson, Eric N.; Davidson, John B.; Murphy, Patrick C.

    1994-01-01

    When using eigenspace assignment to design an aircraft flight control system, one must first develop a model of the plant. Certain questions arise when creating this model as to which dynamics of the plant need to be included in the model and which dynamics can be left out or approximated. The answers to these questions are important because a poor choice can lead to closed-loop dynamics that are unpredicted by the design model. To alleviate this problem, a method has been developed for predicting the effect of not including certain dynamics in the design model on the final closed-loop eigenspace. This development provides insight as to which characteristics of unmodeled dynamics will ultimately affect the closed-loop rigid-body dynamics. What results from this insight is a guide for eigenstructure control law designers to aid them in determining which dynamics need or do not need to be included and a new way to include these dynamics in the flight control system design model to achieve a required accuracy in the closed-loop rigid-body dynamics. The method is illustrated for a lateral-directional flight control system design using eigenspace assignment for the NASA High Alpha Research Vehicle (HARV).

  11. A distributed model predictive control (MPC) fault reconfiguration strategy for formation flying satellites

    NASA Astrophysics Data System (ADS)

    Esfahani, N. R.; Khorasani, K.

    2016-05-01

    In this paper, an active distributed (also referred to as semi-decentralised) fault recovery control scheme is proposed that employs inaccurate and unreliable fault information into a model-predictive-control-based design. The objective is to compensate for the identified actuator faults that are subject to uncertainties and detection time delays, in the attitude control subsystems of formation flying satellites. The proposed distributed fault recovery scheme is developed through a two-level hierarchical framework. In the first level, or the agent level, the fault is recovered locally to maintain as much as possible the design specifications, feasibility, and tracking performance of all the agents. In the second level, or the formation level, the recovery is carried out by enhancing the entire team performance. The fault recovery performance of our proposed distributed (semi-decentralised) scheme is compared with two other alternative schemes, namely the centralised and the decentralised fault recovery schemes. It is shown that the distributed (semi-decentralised) fault recovery scheme satisfies the recovery design specifications and also imposes lower fault compensation control effort cost and communication bandwidth requirements as compared to the centralised scheme. Our proposed distributed (semi-decentralised) scheme also outperforms the achievable performance capabilities of the decentralised scheme. Simulation results corresponding to a network of four precision formation flight satellites are also provided to demonstrate and illustrate the advantages of our proposed distributed (semi-decentralised) fault recovery strategy.

  12. Predictive ion source control using artificial neural network for RFT-30 cyclotron

    NASA Astrophysics Data System (ADS)

    Kong, Young Bae; Hur, Min Goo; Lee, Eun Je; Park, Jeong Hoon; Park, Yong Dae; Yang, Seung Dae

    2016-01-01

    An RFT-30 cyclotron is a 30 MeV proton accelerator for radioisotope production and fundamental research. The ion source of the RFT-30 cyclotron creates plasma from hydrogen gas and transports an ion beam into the center region of the cyclotron. Ion source control is used to search source parameters for best quality of the ion beam. Ion source control in a real system is a difficult and time consuming task, and the operator should search the source parameters by manipulating the cyclotron directly. In this paper, we propose an artificial neural network based predictive control approach for the RFT-30 ion source. The proposed approach constructs the ion source model by using an artificial neural network and finds the optimized parameters with the simulated annealing algorithm. To analyze the performance of the proposed approach, we evaluated the simulations with the experimental data of the ion source. The performance results show that the proposed approach can provide an efficient way to analyze and control the ion source of the RFT-30 cyclotron.

  13. Simulation of the Predictive Control Algorithm for Container Crane Operation using Matlab Fuzzy Logic Tool Box

    NASA Technical Reports Server (NTRS)

    Richardson, Albert O.

    1997-01-01

    This research has investigated the use of fuzzy logic, via the Matlab Fuzzy Logic Tool Box, to design optimized controller systems. The engineering system for which the controller was designed and simulate was the container crane. The fuzzy logic algorithm that was investigated was the 'predictive control' algorithm. The plant dynamics of the container crane is representative of many important systems including robotic arm movements. The container crane that was investigated had a trolley motor and hoist motor. Total distance to be traveled by the trolley was 15 meters. The obstruction height was 5 meters. Crane height was 17.8 meters. Trolley mass was 7500 kilograms. Load mass was 6450 kilograms. Maximum trolley and rope velocities were 1.25 meters per sec. and 0.3 meters per sec., respectively. The fuzzy logic approach allowed the inclusion, in the controller model, of performance indices that are more effectively defined in linguistic terms. These include 'safety' and 'cargo swaying'. Two fuzzy inference systems were implemented using the Matlab simulation package, namely the Mamdani system (which relates fuzzy input variables to fuzzy output variables), and the Sugeno system (which relates fuzzy input variables to crisp output variable). It is found that the Sugeno FIS is better suited to including aspects of those plant dynamics whose mathematical relationships can be determined.

  14. Reinforcement learning versus model predictive control: a comparison on a power system problem.

    PubMed

    Ernst, Damien; Glavic, Mevludin; Capitanescu, Florin; Wehenkel, Louis

    2009-04-01

    This paper compares reinforcement learning (RL) with model predictive control (MPC) in a unified framework and reports experimental results of their application to the synthesis of a controller for a nonlinear and deterministic electrical power oscillations damping problem. Both families of methods are based on the formulation of the control problem as a discrete-time optimal control problem. The considered MPC approach exploits an analytical model of the system dynamics and cost function and computes open-loop policies by applying an interior-point solver to a minimization problem in which the system dynamics are represented by equality constraints. The considered RL approach infers in a model-free way closed-loop policies from a set of system trajectories and instantaneous cost values by solving a sequence of batch-mode supervised learning problems. The results obtained provide insight into the pros and cons of the two approaches and show that RL may certainly be competitive with MPC even in contexts where a good deterministic system model is available. PMID:19095542

  15. Effects of modeling errors on trajectory predictions in air traffic control automation

    NASA Technical Reports Server (NTRS)

    Jackson, Michael R. C.; Zhao, Yiyuan; Slattery, Rhonda

    1996-01-01

    Air traffic control automation synthesizes aircraft trajectories for the generation of advisories. Trajectory computation employs models of aircraft performances and weather conditions. In contrast, actual trajectories are flown in real aircraft under actual conditions. Since synthetic trajectories are used in landing scheduling and conflict probing, it is very important to understand the differences between computed trajectories and actual trajectories. This paper examines the effects of aircraft modeling errors on the accuracy of trajectory predictions in air traffic control automation. Three-dimensional point-mass aircraft equations of motion are assumed to be able to generate actual aircraft flight paths. Modeling errors are described as uncertain parameters or uncertain input functions. Pilot or autopilot feedback actions are expressed as equality constraints to satisfy control objectives. A typical trajectory is defined by a series of flight segments with different control objectives for each flight segment and conditions that define segment transitions. A constrained linearization approach is used to analyze trajectory differences caused by various modeling errors by developing a linear time varying system that describes the trajectory errors, with expressions to transfer the trajectory errors across moving segment transitions. A numerical example is presented for a complete commercial aircraft descent trajectory consisting of several flight segments.

  16. Model Predictive Control of HVAC Systems: Implementation and Testing at the University of California, Merced

    SciTech Connect

    Haves, Phillip; Hencey, Brandon; Borrell, Francesco; Elliot, John; Ma, Yudong; Coffey, Brian; Bengea, Sorin; Wetter, Michael

    2010-06-29

    A Model Predictive Control algorithm was developed for the UC Merced campus chilled water plant. Model predictive control (MPC) is an advanced control technology that has proven successful in the chemical process industry and other industries. The main goal of the research was to demonstrate the practical and commercial viability of MPC for optimization of building energy systems. The control algorithms were developed and implemented in MATLAB, allowing for rapid development, performance, and robustness assessment. The UC Merced chilled water plant includes three water-cooled chillers and a two million gallon chilled water storage tank. The tank is charged during the night to minimize on-peak electricity consumption and take advantage of the lower ambient wet bulb temperature. The control algorithms determined the optimal chilled water plant operation including chilled water supply (CHWS) temperature set-point, condenser water supply (CWS) temperature set-point and the charging start and stop times to minimize a cost function that includes energy consumption and peak electrical demand over a 3-day prediction horizon. A detailed model of the chilled water plant and simplified models of the buildings served by the plant were developed using the equation-based modeling language Modelica. Steady state models of the chillers, cooling towers and pumps were developed, based on manufacturers performance data, and calibrated using measured data collected and archived by the control system. A detailed dynamic model of the chilled water storage tank was also developed and calibrated. Simple, semi-empirical models were developed to predict the temperature and flow rate of the chilled water returning to the plant from the buildings. These models were then combined and simplified for use in a model predictive control algorithm that determines the optimal chiller start and stop times and set-points for the condenser water temperature and the chilled water supply temperature. The

  17. A practical approach to Model Predictive Control (MPC) for solar communities

    NASA Astrophysics Data System (ADS)

    Quintana, Humberto

    Solar district heating (SDH) systems are part of the solution to reduce energy consumption and GHG emissions required for space heating. This kind of installation takes advantage of the convenience of a centralized system and of solar energy to reduce dependency on fossil-fuels. An SDH system is a proven concept that can be enhanced with the addition of long-term thermal energy storage to compensate the seasonal disparity between solar energy supply and heating load demand. These systems are especially deployed in Europe. In Canada, the only SDH installation is the Drake Landing Solar Community (DLSC). This project, which includes seasonal storage (Borehole Thermal Energy Storage-BTES), has been a remarkable success, reaching a solar fraction of 97% by the fifth year of operation. An SDH system cannot be complete without an appropriate supervisory control that coordinates the operation and interaction of system components. The control is based on a set of rules that must consider the system's internal status and external conditions to guarantee occupant comfort with minimal fossil-fuels consumption. This research project is mainly focused on conceiving and assessing new control mechanisms aiming towards an increase of SDH systems' overall energy efficiency. The case study is the DLSC plant, and the proposed control strategies are based on the practical application of Model Predictive Control (MPC) theory. A calibrated model of DLSC including the supervisory control strategies was developed in TRNSYS, building upon the model used for design studies. The model was improved and new components were created when needed. The calibration process delivered a very good agreement for the most important yearly energy performance indices (2 % for solar heat input to the district and for gas consumption, and 5 % for electricity use). Proposed control strategies were conceived for modifying four aspects of the current control: the parameters that define the interaction between

  18. Predictive Optimal Control of Active and Passive Building Thermal Storage Inventory

    SciTech Connect

    Gregor P. Henze; Moncef Krarti

    2005-09-30

    Cooling of commercial buildings contributes significantly to the peak demand placed on an electrical utility grid. Time-of-use electricity rates encourage shifting of electrical loads to off-peak periods at night and weekends. Buildings can respond to these pricing signals by shifting cooling-related thermal loads either by precooling the building's massive structure or the use of active thermal energy storage systems such as ice storage. While these two thermal batteries have been engaged separately in the past, this project investigated the merits of harnessing both storage media concurrently in the context of predictive optimal control. To pursue the analysis, modeling, and simulation research of Phase 1, two separate simulation environments were developed. Based on the new dynamic building simulation program EnergyPlus, a utility rate module, two thermal energy storage models were added. Also, a sequential optimization approach to the cost minimization problem using direct search, gradient-based, and dynamic programming methods was incorporated. The objective function was the total utility bill including the cost of reheat and a time-of-use electricity rate either with or without demand charges. An alternative simulation environment based on TRNSYS and Matlab was developed to allow for comparison and cross-validation with EnergyPlus. The initial evaluation of the theoretical potential of the combined optimal control assumed perfect weather prediction and match between the building model and the actual building counterpart. The analysis showed that the combined utilization leads to cost savings that is significantly greater than either storage but less than the sum of the individual savings. The findings reveal that the cooling-related on-peak electrical demand of commercial buildings can be considerably reduced. A subsequent analysis of the impact of forecasting uncertainty in the required short-term weather forecasts determined that it takes only very simple

  19. Integrating Predictive Modeling with Control System Design for Managed Aquifer Recharge and Recovery Applications

    NASA Astrophysics Data System (ADS)

    Drumheller, Z. W.; Regnery, J.; Lee, J. H.; Illangasekare, T. H.; Kitanidis, P. K.; Smits, K. M.

    2014-12-01

    Aquifers around the world show troubling signs of irreversible depletion and seawater intrusion as climate change, population growth, and urbanization led to reduced natural recharge rates and overuse. Scientists and engineers have begun to re-investigate the technology of managed aquifer recharge and recovery (MAR) as a means to increase the reliability of the diminishing and increasingly variable groundwater supply. MAR systems offer the possibility of naturally increasing groundwater storage while improving the quality of impaired water used for recharge. Unfortunately, MAR systems remain wrought with operational challenges related to the quality and quantity of recharged and recovered water stemming from a lack of data-driven, real-time control. Our project seeks to ease the operational challenges of MAR facilities through the implementation of active sensor networks, adaptively calibrated flow and transport models, and simulation-based meta-heuristic control optimization methods. The developed system works by continually collecting hydraulic and water quality data from a sensor network embedded within the aquifer. The data is fed into an inversion algorithm, which calibrates the parameters and initial conditions of a predictive flow and transport model. The calibrated model is passed to a meta-heuristic control optimization algorithm (e.g. genetic algorithm) to execute the simulations and determine the best course of action, i.e., the optimal pumping policy for current aquifer conditions. The optimal pumping policy is manually or autonomously applied. During operation, sensor data are used to assess the accuracy of the optimal prediction and augment the pumping strategy as needed. At laboratory-scale, a small (18"H x 46"L) and an intermediate (6'H x 16'L) two-dimensional synthetic aquifer were constructed and outfitted with sensor networks. Data collection and model inversion components were developed and sensor data were validated by analytical measurements.

  20. Prediction and Control of Brucellosis Transmission of Dairy Cattle in Zhejiang Province, China

    PubMed Central

    Sun, Xiang-Dong; Hou, Qiang; Li, Mingtao; Huang, Baoxu; Wang, Haiyan; Jin, Zhen

    2014-01-01

    Brucellosis is a bacterial disease caused by brucella; mainly spread by direct contact transmission through the brucella carriers, or indirect contact transmission by the environment containing large quantities of bacteria discharged by the infected individuals. At the beginning of 21st century, the epidemic among dairy cows in Zhejiang province, began to come back and has become a localized prevalent epidemic. Combining the pathology of brucellosis, the reported positive data characteristics, and the feeding method in Zhejiang province, this paper establishes an dynamic model to excavate the internal transmission dynamics, fit the real disease situation, predict brucellosis tendency and assess control measures in dairy cows. By careful analysis, we give some quantitative results as follows. (1) The external input of dairy cows from northern areas may lead to high fluctuation of the number of the infectious cows in Zhejiang province that can reach several hundreds. In this case, the disease cannot be controlled and the infection situation cannot easily be predicted. Thus, this paper encourages cows farms to insist on self-supplying production of the dairy cows. (2) The effect of transmission rate of brucella in environment to dairy cattle on brucellosis spreading is greater than transmission rate of the infectious dairy cattle to susceptible cattle. The prevalence of the epidemic is mainly aroused by environment transmission. (3) Under certain circumstances, the epidemic will become a periodic phenomenon. (4) For Zhejiang province, besides measures that have already been adopted, sterilization times of the infected regions is suggested as twice a week, and should be combined with management of the birth rate of dairy cows to control brucellosis spread. PMID:25386963

  1. Multi-model predictive control based on LMI: from the adaptation of the state-space model to the analytic description of the control law

    NASA Astrophysics Data System (ADS)

    Falugi, P.; Olaru, S.; Dumur, D.

    2010-08-01

    This article proposes an explicit robust predictive control solution based on linear matrix inequalities (LMIs). The considered predictive control strategy uses different local descriptions of the system dynamics and uncertainties and thus allows the handling of less conservative input constraints. The computed control law guarantees constraint satisfaction and asymptotic stability. The technique is effective for a class of nonlinear systems embedded into polytopic models. A detailed discussion of the procedures which adapt the partition of the state space is presented. For the practical implementation the construction of suitable (explicit) descriptions of the control law are described upon concrete algorithms.

  2. Predominant Environmental Factors Controlling and Predicting Phenological Seasonality Across the CONUS over the Last Decade

    NASA Astrophysics Data System (ADS)

    Hargrove, W. W.; Kumar, J.; Erguner-Baytok, Y.; Hoffman, F. M.

    2014-12-01

    up to that DOY was developed to predict DOY when a particular Phenological Milestone was achieved within each phenoregion. Resulting maps of R-squared, primary driver, and residuals were coherent and interpretable. The desert southwest "spring" was highly predictable, and was controlled predominantly by accumulated precipitation.

  3. Control beliefs can predict the ability to up-regulate sensorimotor rhythm during neurofeedback training

    PubMed Central

    Witte, Matthias; Kober, Silvia Erika; Ninaus, Manuel; Neuper, Christa; Wood, Guilherme

    2013-01-01

    Technological progress in computer science and neuroimaging has resulted in many approaches that aim to detect brain states and translate them to an external output. Studies from the field of brain-computer interfaces (BCI) and neurofeedback (NF) have validated the coupling between brain signals and computer devices; however a cognitive model of the processes involved remains elusive. Psychological parameters usually play a moderate role in predicting the performance of BCI and NF users. The concept of a locus of control, i.e., whether one’s own action is determined by internal or external causes, may help to unravel inter-individual performance capacities. Here, we present data from 20 healthy participants who performed a feedback task based on EEG recordings of the sensorimotor rhythm (SMR). One group of 10 participants underwent 10 training sessions where the amplitude of the SMR was coupled to a vertical feedback bar. The other group of ten participants participated in the same task but relied on sham feedback. Our analysis revealed that a locus of control score focusing on control beliefs with regard to technology negatively correlated with the power of SMR. These preliminary results suggest that participants whose confidence in control over technical devices is high might consume additional cognitive resources. This higher effort in turn may interfere with brain states of relaxation as reflected in the SMR. As a consequence, one way to improve control over brain signals in NF paradigms may be to explicitly instruct users not to force mastery but instead to aim at a state of effortless relaxation. PMID:23966933

  4. Predictive Sea State Estimation for Automated Ride Control and Handling - PSSEARCH

    NASA Technical Reports Server (NTRS)

    Huntsberger, Terrance L.; Howard, Andrew B.; Aghazarian, Hrand; Rankin, Arturo L.

    2012-01-01

    PSSEARCH provides predictive sea state estimation, coupled with closed-loop feedback control for automated ride control. It enables a manned or unmanned watercraft to determine the 3D map and sea state conditions in its vicinity in real time. Adaptive path-planning/ replanning software and a control surface management system will then use this information to choose the best settings and heading relative to the seas for the watercraft. PSSEARCH looks ahead and anticipates potential impact of waves on the boat and is used in a tight control loop to adjust trim tabs, course, and throttle settings. The software uses sensory inputs including IMU (Inertial Measurement Unit), stereo, radar, etc. to determine the sea state and wave conditions (wave height, frequency, wave direction) in the vicinity of a rapidly moving boat. This information can then be used to plot a safe path through the oncoming waves. The main issues in determining a safe path for sea surface navigation are: (1) deriving a 3D map of the surrounding environment, (2) extracting hazards and sea state surface state from the imaging sensors/map, and (3) planning a path and control surface settings that avoid the hazards, accomplish the mission navigation goals, and mitigate crew injuries from excessive heave, pitch, and roll accelerations while taking into account the dynamics of the sea surface state. The first part is solved using a wide baseline stereo system, where 3D structure is determined from two calibrated pairs of visual imagers. Once the 3D map is derived, anything above the sea surface is classified as a potential hazard and a surface analysis gives a static snapshot of the waves. Dynamics of the wave features are obtained from a frequency analysis of motion vectors derived from the orientation of the waves during a sequence of inputs. Fusion of the dynamic wave patterns with the 3D maps and the IMU outputs is used for efficient safe path planning.

  5. An Optimal Current Observer for Predictive Current Controlled Buck DC-DC Converters

    PubMed Central

    Min, Run; Chen, Chen; Zhang, Xiaodong; Zou, Xuecheng; Tong, Qiaoling; Zhang, Qiao

    2014-01-01

    In digital current mode controlled DC-DC converters, conventional current sensors might not provide isolation at a minimized price, power loss and size. Therefore, a current observer which can be realized based on the digital circuit itself, is a possible substitute. However, the observed current may diverge due to the parasitic resistors and the forward conduction voltage of the diode. Moreover, the divergence of the observed current will cause steady state errors in the output voltage. In this paper, an optimal current observer is proposed. It achieves the highest observation accuracy by compensating for all the known parasitic parameters. By employing the optimal current observer-based predictive current controller, a buck converter is implemented. The converter has a convergently and accurately observed inductor current, and shows preferable transient response than the conventional voltage mode controlled converter. Besides, costs, power loss and size are minimized since the strategy requires no additional hardware for current sensing. The effectiveness of the proposed optimal current observer is demonstrated experimentally. PMID:24854061

  6. Cognitive task load in a naval ship control centre: from identification to prediction.

    PubMed

    Grootjen, M; Neerincx, M A; Veltman, J A

    Deployment of information and communication technology will lead to further automation of control centre tasks and an increasing amount of information to be processed. A method for establishing adequate levels of cognitive task load for the operators in such complex environments has been developed. It is based on a model distinguishing three load factors: time occupied, task-set switching, and level of information processing. Application of the method resulted in eight scenarios for eight extremes of task load (i.e. low and high values for each load factor). These scenarios were performed by 13 teams in a high-fidelity control centre simulator of the Royal Netherlands Navy. The results show that the method provides good prediction of the task load that will actually appear in the simulator. The model allowed identification of under- and overload situations showing negative effects on operator performance corresponding to controlled experiments in a less realistic task environment. Tools proposed to keep the operator at an optimum task load are (adaptive) task allocation and interface support. PMID:17008255

  7. An optimal current observer for predictive current controlled buck DC-DC converters.

    PubMed

    Min, Run; Chen, Chen; Zhang, Xiaodong; Zou, Xuecheng; Tong, Qiaoling; Zhang, Qiao

    2014-01-01

    In digital current mode controlled DC-DC converters, conventional current sensors might not provide isolation at a minimized price, power loss and size. Therefore, a current observer which can be realized based on the digital circuit itself, is a possible substitute. However, the observed current may diverge due to the parasitic resistors and the forward conduction voltage of the diode. Moreover, the divergence of the observed current will cause steady state errors in the output voltage. In this paper, an optimal current observer is proposed. It achieves the highest observation accuracy by compensating for all the known parasitic parameters. By employing the optimal current observer-based predictive current controller, a buck converter is implemented. The converter has a convergently and accurately observed inductor current, and shows preferable transient response than the conventional voltage mode controlled converter. Besides, costs, power loss and size are minimized since the strategy requires no additional hardware for current sensing. The effectiveness of the proposed optimal current observer is demonstrated experimentally. PMID:24854061

  8. Real-time optical path control method that utilizes multiple support vector machines for traffic prediction

    NASA Astrophysics Data System (ADS)

    Kawase, Hiroshi; Mori, Yojiro; Hasegawa, Hiroshi; Sato, Ken-ichi

    2016-02-01

    An effective solution to the continuous Internet traffic expansion is to offload traffic to lower layers such as the L2 or L1 optical layers. One possible approach is to introduce dynamic optical path operations such as adaptive establishment/tear down according to traffic variation. Path operations cannot be done instantaneously; hence, traffic prediction is essential. Conventional prediction techniques need optimal parameter values to be determined in advance by averaging long-term variations from the past. However, this does not allow adaptation to the ever-changing short-term variations expected to be common in future networks. In this paper, we propose a real-time optical path control method based on a machinelearning technique involving support vector machines (SVMs). A SVM learns the most recent traffic characteristics, and so enables better adaptation to temporal traffic variations than conventional techniques. The difficulty lies in determining how to minimize the time gap between optical path operation and buffer management at the originating points of those paths. The gap makes the required learning data set enormous and the learning process costly. To resolve the problem, we propose the adoption of multiple SVMs running in parallel, trained with non-overlapping subsets of the original data set. The maximum value of the outputs of these SVMs will be the estimated number of necessary paths. Numerical experiments prove that our proposed method outperforms a conventional prediction method, the autoregressive moving average method with optimal parameter values determined by Akaike's information criterion, and reduces the packet-loss ratio by up to 98%.

  9. Robust meta-analytic-predictive priors in clinical trials with historical control information.

    PubMed

    Schmidli, Heinz; Gsteiger, Sandro; Roychoudhury, Satrajit; O'Hagan, Anthony; Spiegelhalter, David; Neuenschwander, Beat

    2014-12-01

    Historical information is always relevant for clinical trial design. Additionally, if incorporated in the analysis of a new trial, historical data allow to reduce the number of subjects. This decreases costs and trial duration, facilitates recruitment, and may be more ethical. Yet, under prior-data conflict, a too optimistic use of historical data may be inappropriate. We address this challenge by deriving a Bayesian meta-analytic-predictive prior from historical data, which is then combined with the new data. This prospective approach is equivalent to a meta-analytic-combined analysis of historical and new data if parameters are exchangeable across trials. The prospective Bayesian version requires a good approximation of the meta-analytic-predictive prior, which is not available analytically. We propose two- or three-component mixtures of standard priors, which allow for good approximations and, for the one-parameter exponential family, straightforward posterior calculations. Moreover, since one of the mixture components is usually vague, mixture priors will often be heavy-tailed and therefore robust. Further robustness and a more rapid reaction to prior-data conflicts can be achieved by adding an extra weakly-informative mixture component. Use of historical prior information is particularly attractive for adaptive trials, as the randomization ratio can then be changed in case of prior-data conflict. Both frequentist operating characteristics and posterior summaries for various data scenarios show that these designs have desirable properties. We illustrate the methodology for a phase II proof-of-concept trial with historical controls from four studies. Robust meta-analytic-predictive priors alleviate prior-data conflicts ' they should encourage better and more frequent use of historical data in clinical trials. PMID:25355546

  10. Automatic generation of predictive dynamic models reveals nuclear phosphorylation as the key Msn2 control mechanism.

    PubMed

    Sunnåker, Mikael; Zamora-Sillero, Elias; Dechant, Reinhard; Ludwig, Christina; Busetto, Alberto Giovanni; Wagner, Andreas; Stelling, Joerg

    2013-05-28

    Predictive dynamical models are critical for the analysis of complex biological systems. However, methods to systematically develop and discriminate among systems biology models are still lacking. We describe a computational method that incorporates all hypothetical mechanisms about the architecture of a biological system into a single model and automatically generates a set of simpler models compatible with observational data. As a proof of principle, we analyzed the dynamic control of the transcription factor Msn2 in Saccharomyces cerevisiae, specifically the short-term mechanisms mediating the cells' recovery after release from starvation stress. Our method determined that 12 of 192 possible models were compatible with available Msn2 localization data. Iterations between model predictions and rationally designed phosphoproteomics and imaging experiments identified a single-circuit topology with a relative probability of 99% among the 192 models. Model analysis revealed that the coupling of dynamic phenomena in Msn2 phosphorylation and transport could lead to efficient stress response signaling by establishing a rate-of-change sensor. Similar principles could apply to mammalian stress response pathways. Systematic construction of dynamic models may yield detailed insight into nonobvious molecular mechanisms. PMID:23716718

  11. A tide prediction and tide height control system for laboratory mesocosms

    PubMed Central

    Long, Jeremy D.

    2015-01-01

    Experimental mesocosm studies of rocky shore and estuarine intertidal systems may benefit from the application of natural tide cycles to better replicate variation in immersion time, water depth, and attendant fluctuations in abiotic and edaphic conditions. Here we describe a stand-alone microcontroller tide prediction open-source software program, coupled with a mechanical tidal elevation control system, which allows continuous adjustment of aquarium water depths in synchrony with local tide cycles. We used this system to monitor the growth of Spartina foliosa marsh cordgrass and scale insect herbivores at three simulated shore elevations in laboratory mesocosms. Plant growth decreased with increasing shore elevation, while scale insect population growth on the plants was not strongly affected by immersion time. This system shows promise for a range of laboratory mesocosm studies where natural tide cycling could impact organism performance or behavior, while the tide prediction system could additionally be utilized in field experiments where treatments need to be applied at certain stages of the tide cycle. PMID:26623195

  12. Predicting private and public helping behaviour by implicit attitudes and the motivation to control prejudiced reactions.

    PubMed

    Gabriel, Ute; Banse, Rainer; Hug, Florian

    2007-06-01

    The role of individual differences in implicit attitudes toward homosexuals and motivation to control prejudiced reactions (MCPR) in predicting private and public helping behaviour was investigated. After assessing the predictor variables, 69 male students were informed about a campaign of a local gay organization. They were provided with an opportunity to donate money and sign a petition in the presence (public setting) or absence (private setting) of the experimenter. As expected, more helping behaviour was shown in the public than in the private setting. However, while the explicit cognitive attitude accounted for helping behaviour in both settings, an implicit attitude x MCPR interaction accounted for additional variability of helping in the public setting only. Three different mediating processes are discussed as possible causes of the observed effects. PMID:17565787

  13. Prediction of the operating point of dendrites growing under coupled thermosolutal control at high growth velocity.

    PubMed

    Mullis, A M

    2011-06-01

    We use a phase-field model for the growth of dendrites in dilute binary alloys under coupled thermosolutal control to explore the dependence of the dendrite tip velocity and radius of curvature upon undercooling, Lewis number (ratio of thermal to solutal diffusivity), alloy concentration, and equilibrium partition coefficient. Constructed in the quantitatively valid thin-interface limit, the model uses advanced numerical techniques such as mesh adaptivity, multigrid, and implicit time stepping to solve the nonisothermal alloy solidification problem for material parameters that are realistic for metals. From the velocity and curvature data we estimate the dendrite operating point parameter σ*. We find that σ* is nonconstant and, over a wide parameter space, displays first a local minimum followed by a local maximum as the undercooling is increased. This behavior is contrasted with a similar type of behavior to that predicted by simple marginal stability models to occur in the radius of curvature, on the assumption of constant σ*. PMID:21797374

  14. Expansion and validation of the spiritual health locus of control scale: factorial analysis and predictive validity.

    PubMed

    Holt, Cheryl L; Clark, Eddie M; Klem, Patrick R

    2007-07-01

    The present study reports on the development and validation of an expanded scale assessing spiritual health locus of control beliefs. Additional items were developed, and the scale was pilot tested among 108 church-attending African American women. The scale was multidimensional, comprised of the original Active and Passive Spiritual dimensions, and additional subscales reflecting 'Spiritual Life and Faith' and 'God's Grace'. Internal consistency was acceptable, and predictive validity was evidenced by negative correlations between the Passive Spiritual dimension and knowledge about mammography, breast cancer, and breast cancer treatment, and mammography utilization. This instrument provides an in-depth assessment of beliefs regarding the role of God in one's health, and may be useful for the development of church-based health education serving African Americans. PMID:17584811

  15. Parenting and Child DRD4 Genotype Interact to Predict Children’s Early Emerging Effortful Control

    PubMed Central

    Smith, Heather J.; Sheikh, Haroon I.; Dyson, Margaret W.; Olino, Thomas M.; Laptook, Rebecca S.; Durbin, C. Emily; Hayden, Elizabeth P.; Singh, Shiva M.; Klein, Daniel N.

    2012-01-01

    Effortful control (EC), or the trait-like capacity to regulate dominant responses, has important implications for children’s development. Although genetic factors and parenting likely influence EC, few studies have examined whether they interact to predict its development. The current study examined whether the DRD4 exon III variable number tandem repeat polymorphism moderated the relationship between parenting and children’s EC. A total of 382 three-year-olds and primary caregivers completed behavioural tasks assessing children’s EC and parenting. Children’s DRD4 genotypes moderated the relationship between parenting and EC: children with at least one 7-repeat allele displayed lower EC in the context of negative parenting than children without this allele. These findings suggest opportunities for modifying early risk for low EC. PMID:22862680

  16. Optimization of microalgal photobioreactor system using model predictive control with experimental validation.

    PubMed

    Yoo, Sung Jin; Jeong, Dong Hwi; Kim, Jung Hun; Lee, Jong Min

    2016-08-01

    To maximize biomass and lipid concentrations, various optimization methods were investigated in microalgal photobioreactor systems under mixotrophic conditions. Lipid concentration was estimated using unscented Kalman filter (UKF) with other measurable sources and subsequently used as lipid data for performing model predictive control (MPC). In addition, the maximized biomass and lipid trajectory obtained by open-loop optimization were used as target trajectory for tracking by MPC. Simulation studies and experimental validation were performed and significant improvements in biomass and lipid productivity were achieved in the case where MPC was applied. However, occurence of a lag phase was observed while manipulating the feed flow rates, which is induced by large amount of inputs. This is an important phenomenon that can lead to model-plant mismatch and requires further study for the optimization of microalgal photobioreactors. PMID:27094678

  17. Predicting the Timing and Magnitude of Tropical Mosquito Population Peaks for Maximizing Control Efficiency

    PubMed Central

    Yang, Guo-Jing; Brook, Barry W.; Bradshaw, Corey J. A.

    2009-01-01

    The transmission of mosquito-borne diseases is strongly linked to the abundance of the host vector. Identifying the environmental and biological precursors which herald the onset of peaks in mosquito abundance would give health and land-use managers the capacity to predict the timing and distribution of the most efficient and cost-effective mosquito control. We analysed a 15-year time series of monthly abundance of Aedes vigilax, a tropical mosquito species from northern Australia, to determine periodicity and drivers of population peaks (high-density outbreaks). Two sets of density-dependent models were used to examine the correlation between mosquito abundance peaks and the environmental drivers of peaks or troughs (low-density periods). The seasonal peaks of reproduction (r) and abundance () occur at the beginning of September and early November, respectively. The combination of low mosquito abundance and a low frequency of a high tide exceeding 7 m in the previous low-abundance (trough) period were the most parsimonious predictors of a peak's magnitude, with this model explaining over 50% of the deviance in . Model weights, estimated using AICc, were also relatively high for those including monthly maximum tide height, monthly accumulated tide height or total rainfall per month in the trough, with high values in the trough correlating negatively with the onset of a high-abundance peak. These findings illustrate that basic environmental monitoring data can be coupled with relatively simple density feedback models to predict the timing and magnitude of mosquito abundance peaks. Decision-makers can use these methods to determine optimal levels of control (i.e., least-cost measures yielding the largest decline in mosquito abundance) and so reduce the risk of disease outbreaks in human populations. PMID:19238191

  18. Individual Differences in Childhood Sleep Problems Predict Later Cognitive Executive Control

    PubMed Central

    Friedman, Naomi P.; Corley, Robin P.; Hewitt, John K.; Wright, Kenneth P.

    2009-01-01

    Study Objective: To determine whether individual differences in developmental patterns of general sleep problems are associated with 3 executive function abilities—inhibiting, updating working memory, and task shifting—in late adolescence. Participants: 916 twins (465 female, 451 male) and parents from the Colorado Longitudinal Twin Study. Measurements and Results: Parents reported their children's sleep problems at ages 4 years, 5 y, 7 y, and 9–16 y based on a 7-item scale from the Child-Behavior Checklist; a subset of children (n = 568) completed laboratory assessments of executive functions at age 17. Latent variable growth curve analyses were used to model individual differences in longitudinal trajectories of childhood sleep problems. Sleep problems declined over time, with ~70% of children having ≥ 1 problem at age 4 and ~33% of children at age 16. However, significant individual differences in both the initial levels of problems (intercept) and changes across time (slope) were observed. When executive function latent variables were added to the model, the intercept did not significantly correlate with the later executive function latent variables; however, the slope variable significantly (P < 0.05) negatively correlated with inhibiting (r = −0.27) and updating (r = −0.21), but not shifting (r = −0.10) abilities. Further analyses suggested that the slope variable predicted the variance common to the 3 executive functions (r = −0.29). Conclusions: Early levels of sleep problems do not seem to have appreciable implications for later executive functioning. However, individuals whose sleep problems decrease more across time show better general executive control in late adolescence. Citation: Friedman NP; Corley RP; Hewitt JK; Wright KP. Individual differences in childhood sleep problems predict later cognitive executive control. SLEEP 2009;32(3):323-333. PMID:19294952

  19. Decisions on control of foot-and-mouth disease informed using model predictions.

    PubMed

    Halasa, T; Willeberg, P; Christiansen, L E; Boklund, A; Alkhamis, M; Perez, A; Enøe, C

    2013-11-01

    The decision on whether or not to change the control strategy, such as introducing emergency vaccination, is perhaps one of the most difficult decisions faced by the veterinary authorities during a foot-and-mouth disease (FMD) epidemic. A simple tool that may predict the epidemic outcome and consequences would be useful to assist the veterinary authorities in the decision-making process. A previously proposed simple quantitative tool based on the first 14 days outbreaks (FFO) of FMD was used with results from an FMD simulation exercise. Epidemic outcomes included the number of affected herds, epidemic duration, geographical size and costs. The first 14 days spatial spread (FFS) was also included to further support the prediction. The epidemic data was obtained from a Danish version (DTU-DADS) of a pre-existing FMD simulation model (Davis Animal Disease Spread - DADS) adapted to model the spread of FMD in Denmark. The European Union (EU) and Danish regulations for FMD control were used in the simulation. The correlations between FFO and FFS and the additional number of affected herds after day 14 following detection of the first infected herd were 0.66 and 0.82, respectively. The variation explained by the FFO at day 14 following detection was high (P-value<0.001). This indicates that the FFO may take a part in the decision of whether or not to intensify FMD control, for instance by introducing emergency vaccination and/or pre-emptive depopulation, which might prevent a "catastrophic situation". A significant part of the variation was explained by supplementing the model with the FFS (P-value<0.001). Furthermore, the type of the index-herd was also a significant predictor of the epidemic outcomes (P-value<0.05). The results of the current study suggest that national veterinary authorities should consider to model their national situation and to use FFO and FFS to help planning and updating their contingency plans and FMD emergency control strategies. PMID:24080392

  20. Implementation of reactive and predictive real-time control strategies to optimize dry stormwater detention ponds

    NASA Astrophysics Data System (ADS)

    Gaborit, Étienne; Anctil, François; Vanrolleghem, Peter A.; Pelletier, Geneviève

    2013-04-01

    Dry detention ponds have been widely implemented in U.S.A (National Research Council, 1993) and Canada (Shammaa et al. 2002) to mitigate the impacts of urban runoff on receiving water bodies. The aim of such structures is to allow a temporary retention of the water during rainfall events, decreasing runoff velocities and volumes (by infiltration in the pond) as well as providing some water quality improvement from sedimentation. The management of dry detention ponds currently relies on static control through a fixed pre-designed limitation of their maximum outflow (Middleton and Barrett 2008), for example via a proper choice of their outlet pipe diameter. Because these ponds are designed for large storms, typically 1- or 2-hour duration rainfall events with return periods comprised between 5 and 100 years, one of their main drawbacks is that they generally offer almost no retention for smaller rainfall events (Middleton and Barrett 2008), which are by definition much more common. Real-Time Control (RTC) has a high potential for optimizing retention time (Marsalek 2005) because it allows adopting operating strategies that are flexible and hence more suitable to the prevailing fluctuating conditions than static control. For dry ponds, this would basically imply adapting the outlet opening percentage to maximize water retention time, while being able to open it completely for severe storms. This study developed several enhanced RTC scenarios of a dry detention pond located at the outlet of a small urban catchment near Québec City, Canada, following the previous work of Muschalla et al. (2009). The catchment's runoff quantity and TSS concentration were simulated by a SWMM5 model with an improved wash-off formulation. The control procedures rely on rainfall detection and measures of the pond's water height for the reactive schemes, and on rainfall forecasts in addition to these variables for the predictive schemes. The automatic reactive control schemes implemented

  1. Serum Cholinesterase Activities Distinguish between Stroke Patients and Controls and Predict 12-Month Mortality

    PubMed Central

    Ben Assayag, Einor; Shenhar-Tsarfaty, Shani; Ofek, Keren; Soreq, Lilach; Bova, Irena; Shopin, Ludmila; Berg, Ronan MG; Berliner, Shlomo; Shapira, Itzhak; Bornstein, Natan M; Soreq, Hermona

    2010-01-01

    To date there is no diagnostic biomarker for mild stroke, although elevation of inflammatory biomarkers has been reported at early stages. Previous studies implicated acetylcholinesterase (AChE) involvement in stroke, and circulating AChE activity reflects inflammatory response, since acetylcholine suppresses inflammation. Therefore, carriers of polymorphisms that modify cholinergic activity should be particularly susceptible to inflammatory damage. Our study sought diagnostic values of AChE and Cholinergic Status (CS, the total capacity for acetylcholine hydrolysis) in suspected stroke patients. For this purpose, serum cholinesterase activities, butyrylcholinesterase-K genotype and inflammatory biomarkers were determined in 264 ischemic stroke patients and matched controls during the acute phase. AChE activities were lower (P < 0.001), and butyrylcholinesterase activities were higher in patients than in controls (P = 0.004). When normalized to sampling time from stroke occurrence, both cholinergic parameters were correlated with multiple inflammatory biomarkers, including fibrinogen, interleukin-6 and C-reactive protein (r = 0.713, r = 0.607; r = 0.421, r = 0.341; r = 0.276, r = 0.255; respectively; all P values < 0.001). Furthermore, very low AChE activities predicted subsequent nonsurvival (P = 0.036). Also, carriers of the unstable butyrylcholinesterase-K variant were more abundant among patients than controls, and showed reduced activity (P < 0.001). Importantly, a cholinergic score combining the two cholinesterase activities discriminated between 94.3% matched pairs of patients and controls, compared with only 75% for inflammatory measures. Our findings present the power of circulation cholinesterase measurements as useful early diagnostic tools for the occurrence of stroke. Importantly, these were considerably more distinctive than the inflammatory biomarkers, albeit closely associated with them, which may open new venues for stroke diagnosis and treatment

  2. Salvage brachytherapy in prostate local recurrence after radiation therapy: predicting factors for control and toxicity

    PubMed Central

    2014-01-01

    Purpose To evaluate efficacy and toxicity after salvage brachytherapy (BT) in prostate local recurrence after radiation therapy. Methods and materials Between 1993 and 2007, we retrospectively analyzed 56 consecutively patients (pts) undergoing salvage brachytherapy. After local biopsy-proven recurrence, pts received 145 Gy LDR-BT (37 pts, 66%) or HDR-BT (19 pts, 34%) in different dose levels according to biological equivalent doses (BED2 Gy). By the time of salvage BT, only 15 pts (27%) received ADT. Univariate and multivariate analyses were performed to identify predictors of biochemical control and toxicities. Acute and late genitourinary (GU) and gastrointestinal (GI) toxicities were graded using Common Terminology Criteria for Adverse Events (CTCv3.0). Results Median follow-up after salvage BT was 48 months. The 5-year FFbF was 77%. HDR and LDR late grade 3 GU toxicities were observed in 21% and 24%. Late grade 3 GI toxicities were observed in 2% (HDR) and 2.7% (LDR). On univariate analysis, pre-salvage prostate-specific antigen (PSA) > 10 ng/ml (p = 0.004), interval to relapse after initial treatment < 24 months (p = 0.004) and salvage HDR-BT doses BED2 Gy level < 227 Gy (p = 0.012) were significant in predicting biochemical failure. On Cox multivariate analysis, pre-salvage PSA, and time to relapse were significant in predicting biochemical failure. HDR-BT BED2 Gy (α/β 1.5 Gy) levels ≥ 227 (p = 0.013), and ADT (p = 0.049) were significant in predicting grade ≥ 2 urinary toxicity. Conclusions Prostate BT is an effective salvage modality in some selected prostate local recurrence patients after radiation therapy. Even, we provide some potential predictors of biochemical control and toxicity for prostate salvage BT, further investigation is recommended. PMID:24885287

  3. Remotely Controlled Mandibular Protrusion during Sleep Predicts Therapeutic Success with Oral Appliances in Patients with Obstructive Sleep Apnea

    PubMed Central

    Remmers, John; Charkhandeh, Shouresh; Grosse, Joshua; Topor, Zbigniew; Brant, Rollin; Santosham, Peter; Bruehlmann, Sabina

    2013-01-01

    Study Objectives: The present study addresses the need for a validated tool that prospectively identifies favorable candidates for oral appliance therapy in treatment of obstructive sleep apnea. The objective of the study was to evaluate the ability of a mandibular titration study, performed with a remotely controlled mandibular positioner (RCMP), to predict treatment outcome with a mandibular repositioning appliance (MRA) and to predict an effective target protrusive position (ETPP). Design: A prospective, blinded, outcome study. Setting: Standard clinical care with tests performed in the polysomnographic laboratory. Participants: Consecutive patients (n = 67) recruited from a sleep center or a dental practice using broad inclusion criteria (age 21-80 years; AHI > 10/h; BMI < 40 kg/m2). Interventions: Therapeutic outcome with a mandibular protruding oral appliance was predicted following a mandibular protrusive titration study in the polysomnographic laboratory using a remotely controlled positioner and prospectively established predictive rules. An ETPP was also prospectively determined for participants predicted to be therapeutically successful with MRA therapy. All participants were blindly treated with a MRA, at either the predicted ETPP or a sham position, and therapeutic outcome was compared against prediction. Measurements and Results: At the final protrusive position, standard predictive parameters (sensitivity, specificity, positive and negative predictive values) showed statistically significant predictive accuracy (P < 0.05) in the range of 83% to 94%. The predicted ETPP provided an efficacious protrusive position in 87% of participants predicted to be therapeutically successful with MRA therapy (P < 0.05). Conclusions: Using prospectively established rules for interpreting the polysomnographic data, the mandibular titration study predicted mandibular repositioning appliance therapeutic outcome with significant accuracy, particularly with regard to

  4. Inhibitory Control in Preschool Predicts Early Math Skills in First Grade: Evidence from an Ethnically Diverse Sample

    ERIC Educational Resources Information Center

    Ng, Florrie Fei-Yin; Tamis-LeMonda, Catherine; Yoshikawa, Hirokazu; Sze, Irene Nga-Lam

    2015-01-01

    Preschoolers' inhibitory control and early math skills were concurrently and longitudinally examined in 255 Chinese, African American, Dominican, and Mexican 4-year-olds in the United States. Inhibitory control at age 4, assessed with a peg-tapping task, was associated with early math skills at age 4 and predicted growth in such skills from…

  5. Hybrid Model Predictive Control for Sequential Decision Policies in Adaptive Behavioral Interventions

    PubMed Central

    Dong, Yuwen; Deshpande, Sunil; Rivera, Daniel E.; Downs, Danielle S.; Savage, Jennifer S.

    2015-01-01

    Control engineering offers a systematic and efficient method to optimize the effectiveness of individually tailored treatment and prevention policies known as adaptive or “just-in-time” behavioral interventions. The nature of these interventions requires assigning dosages at categorical levels, which has been addressed in prior work using Mixed Logical Dynamical (MLD)-based hybrid model predictive control (HMPC) schemes. However, certain requirements of adaptive behavioral interventions that involve sequential decision making have not been comprehensively explored in the literature. This paper presents an extension of the traditional MLD framework for HMPC by representing the requirements of sequential decision policies as mixed-integer linear constraints. This is accomplished with user-specified dosage sequence tables, manipulation of one input at a time, and a switching time strategy for assigning dosages at time intervals less frequent than the measurement sampling interval. A model developed for a gestational weight gain (GWG) intervention is used to illustrate the generation of these sequential decision policies and their effectiveness for implementing adaptive behavioral interventions involving multiple components. PMID:25635157

  6. Application of explicit model predictive control to a hybrid battery-ultracapacitor power source

    NASA Astrophysics Data System (ADS)

    Hredzak, Branislav; Agelidis, Vassilios G.; Demetriades, Georgios

    2015-03-01

    An explicit model predictive control (EMPC) system for a hybrid battery-ultracapacitor power source is proposed and experimentally verified in this paper. The main advantage of using the EMPC system is that the control law computation is reduced to evaluation of an explicitly defined piecewise linear function of the states. Separate EMPC systems for the total output current loop, the battery loop and the ultracapacitor loop are designed. This modular design approach allows evaluation of the performance of each individual EMPC system separately and also improves the convergence of the EMPC system design algorithm as the models used to design each loop are smaller. In order to protect the hybrid power source, the designed EMPC systems maintain operation of the hybrid power source within specified constraints, namely, battery and ultracapacitor current constraints, battery state of charge constraints and ultracapacitor voltage constraints. At the same time, the total output current EMPC system allocates high frequency current changes to the ultracapacitor and the low frequency current changes to the battery thus extending the battery lifetime. Presented experimental results verify that the hybrid power source operates within the specified constraints while allocating high and low frequency current changes to the ultracapacitor and battery respectively.

  7. A Risk-based Model Predictive Control Approach to Adaptive Interventions in Behavioral Health.

    PubMed

    Zafra-Cabeza, Ascensión; Rivera, Daniel E; Collins, Linda M; Ridao, Miguel A; Camacho, Eduardo F

    2011-07-01

    This paper examines how control engineering and risk management techniques can be applied in the field of behavioral health through their use in the design and implementation of adaptive behavioral interventions. Adaptive interventions are gaining increasing acceptance as a means to improve prevention and treatment of chronic, relapsing disorders, such as abuse of alcohol, tobacco, and other drugs, mental illness, and obesity. A risk-based Model Predictive Control (MPC) algorithm is developed for a hypothetical intervention inspired by Fast Track, a real-life program whose long-term goal is the prevention of conduct disorders in at-risk children. The MPC-based algorithm decides on the appropriate frequency of counselor home visits, mentoring sessions, and the availability of after-school recreation activities by relying on a model that includes identifiable risks, their costs, and the cost/benefit assessment of mitigating actions. MPC is particularly suited for the problem because of its constraint-handling capabilities, and its ability to scale to interventions involving multiple tailoring variables. By systematically accounting for risks and adapting treatment components over time, an MPC approach as described in this paper can increase intervention effectiveness and adherence while reducing waste, resulting in advantages over conventional fixed treatment. A series of simulations are conducted under varying conditions to demonstrate the effectiveness of the algorithm. PMID:21643450

  8. Inferential modeling and predictive feedback control in real-time motion compensation using the treatment couch during radiotherapy.

    PubMed

    Qiu, Peng; D'Souza, Warren D; McAvoy, Thomas J; Ray Liu, K J

    2007-10-01

    Tumor motion induced by respiration presents a challenge to the reliable delivery of conformal radiation treatments. Real-time motion compensation represents the technologically most challenging clinical solution but has the potential to overcome the limitations of existing methods. The performance of a real-time couch-based motion compensation system is mainly dependent on two aspects: the ability to infer the internal anatomical position and the performance of the feedback control system. In this paper, we propose two novel methods for the two aspects respectively, and then combine the proposed methods into one system. To accurately estimate the internal tumor position, we present partial-least squares (PLS) regression to predict the position of the diaphragm using skin-based motion surrogates. Four radio-opaque markers were placed on the abdomen of patients who underwent fluoroscopic imaging of the diaphragm. The coordinates of the markers served as input variables and the position of the diaphragm served as the output variable. PLS resulted in lower prediction errors compared with standard multiple linear regression (MLR). The performance of the feedback control system depends on the system dynamics and dead time (delay between the initiation and execution of the control action). While the dynamics of the system can be inverted in a feedback control system, the dead time cannot be inverted. To overcome the dead time of the system, we propose a predictive feedback control system by incorporating forward prediction using least-mean-square (LMS) and recursive least square (RLS) filtering into the couch-based control system. Motion data were obtained using a skin-based marker. The proposed predictive feedback control system was benchmarked against pure feedback control (no forward prediction) and resulted in a significant performance gain. Finally, we combined the PLS inference model and the predictive feedback control to evaluate the overall performance of the

  9. Thermal control system of the Exoplanet Characterisation Observatory Payload: design and predictions

    NASA Astrophysics Data System (ADS)

    Morgante, G.; Terenzi, L.; Eccleston, P.; Bradshaw, T.; Crook, M.; Linder, M.; Hunt, T.; Winter, B.; Focardi, M.; Malaguti, G.; Micela, G.; Pace, E.; Tinetti, G.

    2015-12-01

    The Exoplanet Characterisation Observatory (EChO) is a space mission dedicated to investigate exoplanetary atmospheres by undertaking spectroscopy of transiting planets in a wide spectral region from the visible to the mid-InfraRed (IR). The high sensitivity and the long exposures required by the mission need an extremely stable thermo-mechanical platform. The instrument is passively cooled down to approximately 40 K, together with the telescope assembly, by a V-Groove based design that exploits the L2 orbit favourable thermal conditions. The visible and short-IR wavelength detectors are maintained at the operating temperature of 40 K by a dedicated radiator coupled to the cold space. The mid-IR channels, require a lower operating temperature and are cooled by an active refrigerator: a 28 K Neon Joule-Thomson (JT) cold end, fed by a mechanical compressor. Temperature stability is one of the challenging issues of the whole architecture: periodical perturbations must be controlled before they reach the sensitive units of the instrument. An efficient thermal control system is required: the design is based on a combination of passive and active solutions. In this paper we describe the thermal architecture of the payload with the main cryo-chain stages and their temperature control systems. The requirements that drive the design and the trade-offs needed to enable the EChO exciting science in a technically feasible payload design are discussed. Thermal modelling results and preliminary performance predictions in terms of steady state and transient conditions are also reported. This paper is presented on behalf of the EChO Consortium.

  10. Factors Predicting Suicide among Russians in Estonia in Comparison with Estonians: A Case-Control Study

    PubMed Central

    Kõlves, Kairi; Sisask, Merike; Anion, Liivia; Samm, Algi; Värnik, Airi

    2006-01-01

    Aim To explore differences between suicide victims among Russian immigrants in Estonia and native Estonians, according to socio-demographic background, substance use pattern, and recent life events to find out immigration-specific factors predicting suicide. Methods The psychological autopsy study included 427 people who committed suicide in 1999 and 427 randomly selected controls matched by region, gender, age, and nationality. Results The only variable that differed significantly between Russian and Estonian suicide cases was substance use pattern. Logistic regression models showed that factors associated with suicide for both nationalities were substance dependence and abuse (Russians: odds ratio [OR], 12.9; 95% confidence interval [95% CI], 4.2-39.2; Estonians: OR, 8.1; 95% CI, 3.9-16.4), economical inactivity Russians: OR 5.5; 95% CI, 1.3-22.9; Estonians: OR, 3.1; 95% CI, 1.3-7.1), and recent family discord (Russians: OR, 3.2; 95% CI, 1.1-9.9; Estonians: OR, 4.5; 95%, CI, 2.1-9.8). The variables that remained significant in the final model were having no partner (Estonians: OR, 3.0; 95% CI, 1.6-5.5), being unemployed (Estonians: OR, 5.5; 95% CI, 2.0-15.4), and being an abstainer (Estonians: OR, 6.7; 95% CI, 2.5-17.6) for Estonians, and somatic illness (Russians: OR, 4.1; 95% CI, 1.4-11.7), separation (Russians: OR, 32.3; 95% CI, 2.9-364.1), and death of a close person (Russians: OR, 0.2; 95% CI, 0.04-0.7) for Russians. Conclusion Although the predicting factors of suicide were similar among the Estonian Russians and Estonians, there were still some differences in the nature of recent life events. Higher suicide rate among Estonian Russians in 1999 could be at least partly attributable to their higher substance consumption. PMID:17171808

  11. Changes of the Antarctic ozone hole: Controlling mechanisms, seasonal predictability, and evolution

    NASA Astrophysics Data System (ADS)

    Salby, Murry L.; Titova, Evgenia A.; Deschamps, Lilia

    2012-05-01

    The ozone hole changes considerably from one year to the next. It varies between conditions in which springtime ozone is strongly depleted to others in which ozone is only weakly depleted. Those changes are shown to closely track anomalous planetary wave forcing of the residual circulation. The strong coherence with planetary wave forcing is consistent with similar coherence of springtime temperature, which modulates Polar Stratospheric Cloud (PSC). By controlling the lifetime of PSC, anomalous wave forcing determines the net activation of chlorine and bromine and, hence, springtime depletion of ozone during individual years. The strong coherence with planetary wave forcing affords long-range predictability. It supports a seasonal forecast of springtime depletion, which, through the ozone mass deficit, perturbs ozone across much of the Southern Hemisphere during subsequent months of summer. Conditioned upon wintertime wave structure, a hindcast of springtime depletion faithfully predicts the anomalous ozone observed. A reliable forecast of tropospheric planetary waves would thus enable springtime depletion to be predicted. The current evolution of Antarctic ozone is dominated by dynamically-induced changes. Representing its climate variability, those large changes obscure the more gradual evolution of springtime depletion, like that associated with the decline of chlorine. The strong dependence on planetary wave forcing, however, enables dynamically-induced changes of ozone to be identified accurately. Removing them unmasks the secular variation of Antarctic ozone, the part coherent over a decade and longer. Independent of dynamically-induced changes, that component discriminates to changes associated with stratospheric composition. It reveals a gradual but systematic rebound over the last decade. The upward trend is shown to be robust, significant at the 99.5% level. Uncertainty in this trend is thus small enough to make the probability of it arising through

  12. Reduction of computer usage costs in predicting unsteady aerodynamic loadings caused by control surface motion. Addendum to computer program description

    NASA Technical Reports Server (NTRS)

    Rowe, W. S.; Petrarca, J. R.

    1980-01-01

    Changes to be made that provide increased accuracy and increased user flexibility in prediction of unsteady loadings caused by control surface motions are described. Analysis flexibility is increased by reducing the restrictions on the location of the downwash stations relative to the leading edge and the edges of the control surface boundaries. Analysis accuracy is increased in predicting unsteady loading for high Mach number analysis conditions through use of additional chordwise downwash stations. User guideline are presented to enlarge analysis capabilities of unusual wing control surface configurations. Comparative results indicate that the revised procedures provide accurate predictions of unsteady loadings as well as providing reductions of 40 to 75 percent in computer usage cost required by previous versions of this program.

  13. Reduction of computer usage costs in predicting unsteady aerodynamic loadings caused by control surface motions: Analysis and results

    NASA Technical Reports Server (NTRS)

    Rowe, W. S.; Sebastian, J. D.; Petrarca, J. R.

    1979-01-01

    Results of theoretical and numerical investigations conducted to develop economical computing procedures were applied to an existing computer program that predicts unsteady aerodynamic loadings caused by leading and trailing edge control surface motions in subsonic compressible flow. Large reductions in computing costs were achieved by removing the spanwise singularity of the downwash integrand and evaluating its effect separately in closed form. Additional reductions were obtained by modifying the incremental pressure term that account for downwash singularities at control surface edges. Accuracy of theoretical predictions of unsteady loading at high reduced frequencies was increased by applying new pressure expressions that exactly satisified the high frequency boundary conditions of an oscillating control surface. Comparative computer result indicated that the revised procedures provide more accurate predictions of unsteady loadings as well as providing reduction of 50 to 80 percent in computer usage costs.

  14. In flight ground control of high drag satellites utilizing on-board accelerometer data and rapid orbit prediction techniques

    NASA Technical Reports Server (NTRS)

    Fuchs, A. J.; Velez, C. E.

    1974-01-01

    High drag satellites frequently require precise verification of orbital maneuvers and the accurate prediction of perigee height. An in-flight ground support system designed to monitor and compute orbital state and maneuvers is described. The use of on-board three-axis accelerometer data in a flight support software system to perform on-line maneuver analysis and atmospheric model updating is discussed. In addition, automated analytic techniques to rapidly and accurately predict perigee height following a maneuver are described, as well as semianalytic averaging techniques designed to predict a decaying orbital state for mission control.

  15. Improving Computational Efficiency of Model Predictive Control Genetic Algorithms for Real-Time Decision Support

    NASA Astrophysics Data System (ADS)

    Minsker, B. S.; Zimmer, A. L.; Ostfeld, A.; Schmidt, A.

    2014-12-01

    Enabling real-time decision support, particularly under conditions of uncertainty, requires computationally efficient algorithms that can rapidly generate recommendations. In this paper, a suite of model predictive control (MPC) genetic algorithms are developed and tested offline to explore their value for reducing CSOs during real-time use in a deep-tunnel sewer system. MPC approaches include the micro-GA, the probability-based compact GA, and domain-specific GA methods that reduce the number of decision variable values analyzed within the sewer hydraulic model, thus reducing algorithm search space. Minimum fitness and constraint values achieved by all GA approaches, as well as computational times required to reach the minimum values, are compared to large population sizes with long convergence times. Optimization results for a subset of the Chicago combined sewer system indicate that genetic algorithm variations with coarse decision variable representation, eventually transitioning to the entire range of decision variable values, are most efficient at addressing the CSO control problem. Although diversity-enhancing micro-GAs evaluate a larger search space and exhibit shorter convergence times, these representations do not reach minimum fitness and constraint values. The domain-specific GAs prove to be the most efficient and are used to test CSO sensitivity to energy costs, CSO penalties, and pressurization constraint values. The results show that CSO volumes are highly dependent on the tunnel pressurization constraint, with reductions of 13% to 77% possible with less conservative operational strategies. Because current management practices may not account for varying costs at CSO locations and electricity rate changes in the summer and winter, the sensitivity of the results is evaluated for variable seasonal and diurnal CSO penalty costs and electricity-related system maintenance costs, as well as different sluice gate constraint levels. These findings indicate

  16. A predicted and controlled jøkulhlaup (GLOF) from Harbardsbreen, Norway.

    NASA Astrophysics Data System (ADS)

    Jackson, Miriam; Engeset, Rune; Elvehøy, Hallgeir

    2016-04-01

    A jøkulhlaup (GLOF) from Harbardsbreen, Norway in 2015 was predicted and the runoff of over five million cubic metres of water was released in a controlled manner through a hydropower reservoir. The glacier-dammed lake was investigated in early August and showed evidence (change in water-level, radial crevasses) of movement of water from the lake to subglacial storage. The water level in the glacier-dammed lake was over overburden pressure but the event didn't occur until two weeks later. There have been previous events from this glacier, with annual events between 1996 and 2001 due to glacier thinning. The glacier continued to thin substantially (20m) over the next decade but the next event didn't occur until 2010 when over five million cubic metres of water was released as well as additional runoff due to heavy precipitation and melting. At this time the reservoir couldn't accommodate the extra water and there was flow over the dam. Several glaciers in Norway have had one or several jøkulhlaups in the last fifteen years due to glacier thinning, and at several others, glacier-dammed lakes have appeared for the first time. Hydropower reservoirs are situated downstream from some of these glaciers, so such an event can have a beneficial effect. However, negative glacier mass balance and subsequent glacier thinning is increasing the magnitude and frequency of events.

  17. A Hybrid Model Predictive Control Strategy for Optimizing a Smoking Cessation Intervention

    PubMed Central

    Timms, Kevin P.; Rivera, Daniel E.; Piper, Megan E.; Collins, Linda M.

    2014-01-01

    The chronic, relapsing nature of tobacco use represents a major challenge in smoking cessation treatment. Recently, novel intervention paradigms have emerged that seek to adjust treatments over time in order to meet a patient’s changing needs. This article demonstrates that Hybrid Model Predictive Control (HMPC) offers an appealing framework for designing these optimized, time-varying smoking cessation interventions. HMPC is a particularly appropriate approach as it recognizes that intervention doses must be assigned in predetermined, discrete units while retaining receding-horizon, constraint-handling, and combined feedback and feedforward capabilities. Specifically, an intervention algorithm is developed here in which counseling and two pharmacotherapies are manipulated to reduce daily smoking and craving levels. The potential usefulness of such an intervention is illustrated through simulated treatment of a quit attempt in a hypothetical patient, which highlights that prioritizing reduction in craving over total daily smoking levels significantly reduces craving levels, suppresses relapse, and successfully rejects time-varying disturbances such as stress, all while adhering to several practical operational constraints and resource use considerations. PMID:25400326

  18. Numerical Prediction of Surface Heat Flux During Multiple Jets Firing for Missile Control

    NASA Astrophysics Data System (ADS)

    Saha, S.; Sinha, P. K.; Chakraborty, D.

    2013-01-01

    Numerical simulations are carried out to obtain the flowfield and heat flux arising out of the flow interactions of different control thrusters viz. vernier, pitch, yaw, roll and divert thruster among themselves as well as with free stream at different altitudes of operation. Three critical points on a typical trajectory of a missile are chosen and combinations of the thrusters operating at those conditions are considered. Simulations have also been performed to simulate DT motor interaction with free stream at different altitude. The interaction of different motor flowfield with the free stream presents a very complex flowfield. Flow gradients are very high close to the nozzle exit because of high altitude operation of motors. 3-Dimensional RANS equations are solved along with k-ɛ turbulence model on unstructured tetrahedral grid using commercial CFD software. The flow properties along with the surface heat flux distribution for four isothermal wall temperatures 350, 450, 550, 650 K are computed and provided for surface temperature prediction. It is observed that with increase in altitude, the high heat flux region reduces and heat transfer coefficient is independent of wall temperature.

  19. Cognitive trait anxiety, situational stress, and mental effort predict shifting efficiency: Implications for attentional control theory.

    PubMed

    Edwards, Elizabeth J; Edwards, Mark S; Lyvers, Michael

    2015-06-01

    Attentional control theory (ACT) predicts that trait anxiety and situational stress interact to impair performance on tasks that involve attentional shifting. The theory suggests that anxious individuals recruit additional effort to prevent shortfalls in performance effectiveness (accuracy), with deficits becoming evident in processing efficiency (the relationship between accuracy and time taken to perform the task). These assumptions, however, have not been systematically tested. The relationship between cognitive trait anxiety, situational stress, and mental effort in a shifting task (Wisconsin Card Sorting Task) was investigated in 90 participants. Cognitive trait anxiety was operationalized using questionnaire scores, situational stress was manipulated through ego threat instructions, and mental effort was measured using a visual analogue scale. Dependent variables were performance effectiveness (an inverse proportion of perseverative errors) and processing efficiency (an inverse proportion of perseverative errors divided by response time on perseverative error trials). The predictors were not associated with performance effectiveness; however, we observed a significant 3-way interaction on processing efficiency. At higher mental effort (+1 SD), higher cognitive trait anxiety was associated with poorer efficiency independently of situational stress, whereas at lower effort (-1 SD), this relationship was highly significant and most pronounced for those in the high-stress condition. These results are important because they provide the first systematic test of the relationship between trait anxiety, situational stress, and mental effort on shifting performance. The data are also consistent with the notion that effort moderates the relationship between anxiety and shifting efficiency, but not effectiveness. PMID:25642722

  20. Dynamic behavioural changes in the Spontaneously Hyperactive Rat: 3. Control by reinforcer rate changes and predictability.

    PubMed

    Williams, Jonathan; Sagvolden, Geir; Taylor, Eric; Sagvolden, Terje

    2009-03-17

    Variable intervals are widely believed to produce steady rates of responding. However, based on the calming effect of unpredictability in attention deficit hyperactivity disorder (ADHD) we hypothesised that an animal model of this disorder, the Spontaneously Hyperactive (or Hypertensive) Rat, would become less active following particularly variable sequences of interval-lengths in a variable interval schedule. From a large dataset of holepokes and tray-reports by rats in a variable interval reinforcement schedule, we extracted numerous short sequences of intervals on the basis of the first, second, and third derivatives of reinforcement timing (i.e. rate, acceleration, and jerk) in recent intervals. Sets of selected intervals were compared with one another to elucidate the effect of these different derivatives on behaviour in the current interval. Results show that SHR are more active after richer recent reinforcement; after decelerating reinforcers; and after predictable reinforcers. The hypothesis is supported. In conclusion, SHR behaviour largely complies with the Extended Temporal Difference model which in turn has been previously validated against published data in ADHD. The Extended TD model therefore is able to account for two species' behaviour in a wide range of experimental paradigms. SHR are similar in several respects to group averages of children with ADHD, except that SHR have reduced variability and perform actions faster than controls. Hyperactivity in the SHR is very dependent on momentary environmentally determined states, which is an important area for future investigation of ADHD. PMID:18824035

  1. Predicting childhood effortful control from interactions between early parenting quality and children's dopamine transporter gene haplotypes.

    PubMed

    Li, Yi; Sulik, Michael J; Eisenberg, Nancy; Spinrad, Tracy L; Lemery-Chalfant, Kathryn; Stover, Daryn A; Verrelli, Brian C

    2016-02-01

    Children's observed effortful control (EC) at 30, 42, and 54 months (n = 145) was predicted from the interaction between mothers' observed parenting with their 30-month-olds and three variants of the solute carrier family C6, member 3 (SLC6A3) dopamine transporter gene (single nucleotide polymorphisms in intron8 and intron13, and a 40 base pair variable number tandem repeat [VNTR] in the 3'-untranslated region [UTR]), as well as haplotypes of these variants. Significant moderating effects were found. Children without the intron8-A/intron13-G, intron8-A/3'-UTR VNTR-10, or intron13-G/3'-UTR VNTR-10 haplotypes (i.e., haplotypes associated with the reduced SLC6A3 gene expression and thus lower dopamine functioning) appeared to demonstrate altered levels of EC as a function of maternal parenting quality, whereas children with these haplotypes demonstrated a similar EC level regardless of the parenting quality. Children with these haplotypes demonstrated a trade-off, such that they showed higher EC, relative to their counterparts without these haplotypes, when exposed to less supportive maternal parenting. The findings revealed a diathesis-stress pattern and suggested that different SLC6A3 haplotypes, but not single variants, might represent different levels of young children's sensitivity/responsivity to early parenting. PMID:25924976

  2. Can metabolic control variables of diabetic patients predict their quality of life?

    PubMed

    Dogan, Hakan; Harman, Ece; Kocoglu, Hakan; Sargin, Gokhan

    2016-01-01

    The type and the complexity of regimen aimed at achieving better glycemic control may impact patient's health-related quality of life (HRQoL) in diabetic patients. But, the relationship between HbA1c levels of diabetic patients and their HRQoL is not clear. Our study aims to determine whether metabolic control variables can predict HRQoL or not and also the impact of hypertension (HT) on HRQoL in type II diabetic patients. A total of 469 patients with type II diabetes and 134 control subjects were studied. Medical Outcomes Study Short-Form-General Health Survey (SF-36) questionnaire was used as a health survey tool to measure the QoL of patients in the study. SF-36 includes 8 individual subscales and two summary scales (physical component summary [PCS] and mental component summary [MCS]). Age, gender, fasting blood glucose, postprandial blood glucose, HbA1c, high-density lipoprotein-cholesterol (HDL-C), low-density lipoprotein-cholesterol (LDL-C), triglyceride, total cholesterol, Apolipoprotein B (apoB), non-HDL-C, and body mass index values of the subjects were recorded. For statistical evaluation, SPSS (Statistical Package for the Social Sciences) 15 under Windows 7 was used. MCS values of patients group were statistically lower than control group (P < .05). There was no significant difference in PCS values between groups (P > .05). Diabetic patients with HT had significantly lower PCS and MCS values than those without HT. In addition, there was a negative correlation between HbA1c level and PCS and MCS values (P < .05). Hypertensive diabetic patients had significantly higher fasting blood glucose, postprandial blood glucose, HbA1c, HDL-C, LDL-C, total cholesterol, and body mass index values than hypertensive control subjects (P < .05). Normotensive diabetic patients also had significantly lower PCS value than normotensive control subjects (P < .05). But, MCS value was not different between groups (P > .05). PCS values in diabetic male patients were significantly

  3. Assessment of quantitative structure-activity relationship of toxicity prediction models for Korean chemical substance control legislation

    PubMed Central

    Kim, Kwang-Yon; Shin, Seong Eun; No, Kyoung Tai

    2015-01-01

    Objectives For successful adoption of legislation controlling registration and assessment of chemical substances, it is important to obtain sufficient toxicological experimental evidence and other related information. It is also essential to obtain a sufficient number of predicted risk and toxicity results. Particularly, methods used in predicting toxicities of chemical substances during acquisition of required data, ultimately become an economic method for future dealings with new substances. Although the need for such methods is gradually increasing, the-required information about reliability and applicability range has not been systematically provided. Methods There are various representative environmental and human toxicity models based on quantitative structure-activity relationships (QSAR). Here, we secured the 10 representative QSAR-based prediction models and its information that can make predictions about substances that are expected to be regulated. We used models that predict and confirm usability of the information expected to be collected and submitted according to the legislation. After collecting and evaluating each predictive model and relevant data, we prepared methods quantifying the scientific validity and reliability, which are essential conditions for using predictive models. Results We calculated predicted values for the models. Furthermore, we deduced and compared adequacies of the models using the Alternative non-testing method assessed for Registration, Evaluation, Authorization, and Restriction of Chemicals Substances scoring system, and deduced the applicability domains for each model. Additionally, we calculated and compared inclusion rates of substances expected to be regulated, to confirm the applicability. Conclusions We evaluated and compared the data, adequacy, and applicability of our selected QSAR-based toxicity prediction models, and included them in a database. Based on this data, we aimed to construct a system that can be used

  4. A temporal predictive code for voice motor control: Evidence from ERP and behavioral responses to pitch-shifted auditory feedback.

    PubMed

    Behroozmand, Roozbeh; Sangtian, Stacey; Korzyukov, Oleg; Larson, Charles R

    2016-04-01

    The predictive coding model suggests that voice motor control is regulated by a process in which the mismatch (error) between feedforward predictions and sensory feedback is detected and used to correct vocal motor behavior. In this study, we investigated how predictions about timing of pitch perturbations in voice auditory feedback would modulate ERP and behavioral responses during vocal production. We designed six counterbalanced blocks in which a +100cents pitch-shift stimulus perturbed voice auditory feedback during vowel sound vocalizations. In three blocks, there was a fixed delay (500, 750 or 1000ms) between voice and pitch-shift stimulus onset (predictable), whereas in the other three blocks, stimulus onset delay was randomized between 500, 750 and 1000ms (unpredictable). We found that subjects produced compensatory (opposing) vocal responses that started at 80ms after the onset of the unpredictable stimuli. However, for predictable stimuli, subjects initiated vocal responses at 20ms before and followed the direction of pitch shifts in voice feedback. Analysis of ERPs showed that the amplitudes of the N1 and P2 components were significantly reduced in response to predictable compared with unpredictable stimuli. These findings indicate that predictions about temporal features of sensory feedback can modulate vocal motor behavior. In the context of the predictive coding model, temporally-predictable stimuli are learned and reinforced by the internal feedforward system, and as indexed by the ERP suppression, the sensory feedback contribution is reduced for their processing. These findings provide new insights into the neural mechanisms of vocal production and motor control. PMID:26835556

  5. Implementation of PFC (Predictive Functional Control) in a PLC (Programmable Logic Controller) for a HVAC (Heating, Ventilation and Air Conditioning) system

    NASA Astrophysics Data System (ADS)

    Kreutz, M.; Richalet, J.; Mocha, K.; Haber, R.

    2014-12-01

    HVAC systems of industrial buildings consume a lot of energy. Therefore it is important to know the performance of these systems and strategies to optimize the hardware and the control. Tackling the temperature control of the HVAC system promises quick savings by tuning the control within specified tolerance limits, which mostly can be done by low investment. This paper mainly deals with the implementation strategy of a new controller in a PLC using the predictive functional control for temperature control. The different stages of the implementation from the simulation over the SCL code till to the real-time operation are presented. A bumpless switch between the PI(D) and the PFC control was realized, as well.

  6. Implicit and Explicit Attitudes Predict Smoking Cessation: Moderating Effects of Experienced Failure to Control Smoking and Plans to Quit

    PubMed Central

    Chassin, Laurie; Presson, Clark C.; Sherman, Steven J.; Seo, Dong-Chul; Macy, Jon

    2010-01-01

    The current study tested implicit and explicit attitudes as prospective predictors of smoking cessation in a Midwestern community sample of smokers. Results showed that the effects of attitudes significantly varied with levels of experienced failure to control smoking and plans to quit. Explicit attitudes significantly predicted later cessation among those with low (but not high or average) levels of experienced failure to control smoking. Conversely, however, implicit attitudes significantly predicted later cessation among those with high levels of experienced failure to control smoking, but only if they had a plan to quit. Because smoking cessation involves both controlled and automatic processes, interventions may need to consider attitude change interventions that focus on both implicit and explicit attitudes. PMID:21198227

  7. Use of Plant Hydraulic Theory to Predict Ecosystem Fluxes Across Mountainous Gradients in Environmental Controls and Insect Disturbances

    NASA Astrophysics Data System (ADS)

    Ewers, B. E.; Pendall, E.; Reed, D. E.; Barnard, H. R.; Whitehouse, F.; Frank, J. M.; Massman, W. J.; Brooks, P. D.; Biederman, J. A.; Harpold, A. A.; Naithani, K. J.; Mitra, B.; Mackay, D. S.; Norton, U.; Borkhuu, B.

    2011-12-01

    While mountainous areas are critical for providing numerous ecosystem benefits at the regional scale, the strong gradients in environmental controls make predictions difficult. A key part of the problem is quantifying and predicting the feedback between mountain gradients and plant function which then controls ecosystem cycling. The emerging theory of plant hydraulics provides a rigorous yet simple platform from which to generate testable hypotheses and predictions of ecosystem pools and fluxes. Plant hydraulic theory predicts that plant controls over carbon, water, energy and nutrient fluxes can be derived from the limitation of plant water transport from the soil through xylem and out of stomata. In addition, the limit to plant water transport can be predicted by combining plant structure (e.g. xylem diameters or root-to-shoot ratios) and plant function (response of stomatal conductance to vapor pressure deficit or root vulnerability to cavitation). We evaluate the predictions of the plant hydraulic theory by testing it against data from a mountain gradient encompassing sagebrush steppe through subalpine forests (2700 to 3400 m). We further test the theory by predicting the carbon, water and nutrient exchanges from several coniferous trees in the same gradient that are dying from xylem dysfunction caused by blue-stain fungi carried by bark beetles. The common theme of both of these data sets is a change in water limitation caused by either changing precipitation along the mountainous gradient or lack of access to soil water from xylem-occluding fungi. Across all of the data sets which range in scale from individual plants to hillslopes, the data fit the predictions of plant hydraulic theory. Namely, there was a proportional tradeoff between the reference canopy stomatal conductance to water vapor and the sensitivity of that conductance to vapor pressure deficit that quantitatively fits the predictions of plant hydraulic theory. Incorporating this result into

  8. Positron Emission Tomography (PET) Evaluation After Initial Chemotherapy and Radiation Therapy Predicts Local Control in Rhabdomyosarcoma

    SciTech Connect

    Dharmarajan, Kavita V.; Wexler, Leonard H.; Gavane, Somali; Fox, Josef J.; Schoder, Heiko; Tom, Ashlyn K.; Price, Alison N.; Meyers, Paul A.; Wolden, Suzanne L.

    2012-11-15

    Purpose: 18-fluorodeoxyglucose positron emission tomography (PET) is already an integral part of staging in rhabdomyosarcoma. We investigated whether primary-site treatment response characterized by serial PET imaging at specific time points can be correlated with local control. Patients and Methods: We retrospectively examined 94 patients with rhabdomyosarcoma who received initial chemotherapy 15 weeks (median) before radiotherapy and underwent baseline, preradiation, and postradiation PET. Baseline PET standardized uptake values (SUVmax) and the presence or absence of abnormal uptake (termed PET-positive or PET-negative) both before and after radiation were examined for the primary site. Local relapse-free survival (LRFS) was calculated according to baseline SUVmax, PET-positive status, and PET-negative status by the Kaplan-Meier method, and comparisons were tested with the log-rank test. Results: The median patient age was 11 years. With 3-year median follow-up, LRFS was improved among postradiation PET-negative vs PET-positive patients: 94% vs 75%, P=.02. By contrast, on baseline PET, LRFS was not significantly different for primary-site SUVmax {<=}7 vs >7 (median), although the findings suggested a trend toward improved LRFS: 96% for SUVmax {<=}7 vs 79% for SUVmax >7, P=.08. Preradiation PET also suggested a statistically insignificant trend toward improved LRFS for PET-negative (97%) vs PET-positive (81%) patients (P=.06). Conclusion: Negative postradiation PET predicted improved LRFS. Notably, 77% of patients with persistent postradiation uptake did not experience local failure, suggesting that these patients could be closely followed up rather than immediately referred for intervention. Negative baseline and preradiation PET findings suggested statistically insignificant trends toward improved LRFS. Additional study may further understanding of relationships between PET findings at these time points and outcome in rhabdomyosarcoma.

  9. Parametric computation predicts a multiplicative interaction between synaptic strength parameters that control gamma oscillations

    PubMed Central

    Chambers, Jordan D.; Bethwaite, Blair; Diamond, Neil T.; Peachey, Tom; Abramson, David; Petrou, Steve; Thomas, Evan A.

    2012-01-01

    Gamma oscillations are thought to be critical for a number of behavioral functions, they occur in many regions of the brain and through a variety of mechanisms. Fast repetitive bursting (FRB) neurons in layer 2 of the cortex are able to drive gamma oscillations over long periods of time. Even though the oscillation is driven by FRB neurons, strong feedback within the rest of the cortex must modulate properties of the oscillation such as frequency and power. We used a highly detailed model of the cortex to determine how a cohort of 33 parameters controlling synaptic drive might modulate gamma oscillation properties. We were interested in determining not just the effects of parameters individually, but we also wanted to reveal interactions between parameters beyond additive effects. To prevent a combinatorial explosion in parameter combinations that might need to be simulated, we used a fractional factorial design (FFD) that estimated the effects of individual parameters and two parameter interactions. This experiment required only 4096 model runs. We found that the largest effects on both gamma power and frequency came from a complex interaction between efficacy of synaptic connections from layer 2 inhibitory neurons to layer 2 excitatory neurons and the parameter for the reciprocal connection. As well as the effect of the individual parameters determining synaptic efficacy, there was an interaction between these parameters beyond the additive effects of the parameters alone. The magnitude of this effect was similar to that of the individual parameters, predicting that it is physiologically important in setting gamma oscillation properties. PMID:22837747

  10. Model Predictive Control techniques with application to photovoltaic, DC Microgrid, and a multi-sourced hybrid energy system

    NASA Astrophysics Data System (ADS)

    Shadmand, Mohammad Bagher

    Renewable energy sources continue to gain popularity. However, two major limitations exist that prevent widespread adoption: availability and variability of the electricity generated and the cost of the equipment. The focus of this dissertation is Model Predictive Control (MPC) for optimal sized photovoltaic (PV), DC Microgrid, and multi-sourced hybrid energy systems. The main considered applications are: maximum power point tracking (MPPT) by MPC, droop predictive control of DC microgrid, MPC of grid-interaction inverter, MPC of a capacitor-less VAR compensator based on matrix converter (MC). This dissertation firstly investigates a multi-objective optimization technique for a hybrid distribution system. The variability of a high-penetration PV scenario is also studied when incorporated into the microgrid concept. Emerging (PV) technologies have enabled the creation of contoured and conformal PV surfaces; the effect of using non-planar PV modules on variability is also analyzed. The proposed predictive control to achieve maximum power point for isolated and grid-tied PV systems speeds up the control loop since it predicts error before the switching signal is applied to the converter. The low conversion efficiency of PV cells means we want to ensure always operating at maximum possible power point to make the system economical. Thus the proposed MPPT technique can capture more energy compared to the conventional MPPT techniques from same amount of installed solar panel. Because of the MPPT requirement, the output voltage of the converter may vary. Therefore a droop control is needed to feed multiple arrays of photovoltaic systems to a DC bus in microgrid community. Development of a droop control technique by means of predictive control is another application of this dissertation. Reactive power, denoted as Volt Ampere Reactive (VAR), has several undesirable consequences on AC power system network such as reduction in power transfer capability and increase in

  11. Predicting Participation in Group Parenting Education in an Australian Sample: The Role of Attitudes, Norms, and Control Factors

    ERIC Educational Resources Information Center

    White, Katherine M.; Wellington, Larne

    2009-01-01

    We examined the theory of planned behavior (TPB) in predicting intentions to participate in group parenting education. One hundred and seventy-six parents (138 mothers and 38 fathers) with a child under 12 years completed TPB items assessing attitude, subjective norms, perceived behavioral control (PBC), and two additional social influence…

  12. Intentions and Trait Self-Control Predict Fruit and Vegetable Consumption during the Transition to First-Year University

    ERIC Educational Resources Information Center

    Tomasone, Jennifer R.; Meikle, Natasha; Bray, Steven R.

    2015-01-01

    Objective: To examine the independent and combined effects of Theory of Planned Behavior (TPB) variables and trait self-control (TSC) in the prediction of fruit and vegetable consumption (FVC) among first-year university students. Participants: Seventy-six first-year undergraduate university students. Methods: In their first week of class…

  13. Image Discrimination Predictions of a Single Channel Model with Contrast Gain Control

    NASA Technical Reports Server (NTRS)

    Ahumada, Albert J., Jr.; Null, Cynthia H.

    1995-01-01

    Image discrimination models predict the number of just-noticeable-differences between two images. We report the predictions of a single channel model with contrast masking for a range of standard discrimination experiments. Despite its computational simplicity, this model has performed as well as a multiple channel model in an object detection task.

  14. A double-loop structure in the adaptive generalized predictive control algorithm for control of robot end-point contact force.

    PubMed

    Wen, Shuhuan; Zhu, Jinghai; Li, Xiaoli; Chen, Shengyong

    2014-09-01

    Robot force control is an essential issue in robotic intelligence. There is much high uncertainty when robot end-effector contacts with the environment. Because of the environment stiffness effects on the system of the robot end-effector contact with environment, the adaptive generalized predictive control algorithm based on quantitative feedback theory is designed for robot end-point contact force system. The controller of the internal loop is designed on the foundation of QFT to control the uncertainty of the system. An adaptive GPC algorithm is used to design external loop controller to improve the performance and the robustness of the system. Two closed loops used in the design approach realize the system׳s performance and improve the robustness. The simulation results show that the algorithm of the robot end-effector contacting force control system is effective. PMID:24973336

  15. Adjoint Method and Predictive Control for 1-D Flow in NASA Ames 11-Foot Transonic Wind Tunnel

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan; Ardema, Mark

    2006-01-01

    This paper describes a modeling method and a new optimal control approach to investigate a Mach number control problem for the NASA Ames 11-Foot Transonic Wind Tunnel. The flow in the wind tunnel is modeled by the 1-D unsteady Euler equations whose boundary conditions prescribe a controlling action by a compressor. The boundary control inputs to the compressor are in turn controlled by a drive motor system and an inlet guide vane system whose dynamics are modeled by ordinary differential equations. The resulting Euler equations are thus coupled to the ordinary differential equations via the boundary conditions. Optimality conditions are established by an adjoint method and are used to develop a model predictive linear-quadratic optimal control for regulating the Mach number due to a test model disturbance during a continuous pitch

  16. Poor self-control and harsh punishment in childhood prospectively predict borderline personality symptoms in adolescent girls.

    PubMed

    Hallquist, Michael N; Hipwell, Alison E; Stepp, Stephanie D

    2015-08-01

    Developmental theories of borderline personality disorder (BPD) propose that harsh, invalidating parenting of a child with poor self-control and heightened negative emotionality often leads to a coercive cycle of parent-child transactions that increase risk for BPD symptoms such as emotion dysregulation. Although parenting practices and child temperament have previously been linked with BPD, less is known about the prospective influences of caregiver and child characteristics. Using annual longitudinal data from the Pittsburgh Girls Study (n = 2,450), our study examined how reciprocal influences among harsh parenting, self-control, and negative emotionality between ages 5 and 14 predicted the development of BPD symptoms in adolescent girls ages 14 to 17. Consistent with developmental theories, we found that harsh punishment, poor self-control, and negative emotionality predicted BPD symptom severity at age 14. Only worsening self-control between ages 12 and 14, however, predicted growth in BPD symptoms from 14 to 17. Furthermore, the effects of harsh punishment and poor self-control on age 14 BPD symptoms were partially mediated by their earlier reciprocal effects on each other between ages 5 and 14. Our findings underscore the need to address both child and parental contributions to dysfunctional transactions in order to stem the development of BPD symptoms. Moreover, problems with self-regulation in early adolescence may indicate heightened risk for subsequent BPD. Altogether, these results increase our understanding of developmental trajectories associated with BPD symptoms in adolescent girls. PMID:25961815

  17. Poor Self-Control and Harsh Punishment in Childhood Prospectively Predict Borderline Personality Symptoms in Adolescent Girls

    PubMed Central

    Hallquist, Michael N.; Hipwell, Alison E.; Stepp, Stephanie D.

    2015-01-01

    Developmental theories of borderline personality disorder (BPD) propose that harsh, invalidating parenting of a child with poor self-control and heightened negative emotionality often leads to a coercive cycle of parent-child transactions that increase risk for BPD symptoms such as emotion dysregulation. Although parenting practices and child temperament have previously been linked with BPD, less is known about the prospective influences of caregiver and child characteristics. Using annual longitudinal data from the Pittsburgh Girls Study (n = 2450), our study examined how reciprocal influences among harsh parenting, self-control, and negative emotionality between ages 5 and 14 predicted the development of BPD symptoms in adolescent girls ages 14 to 17. Consistent with developmental theories, we found that harsh punishment, poor self-control, and negative emotionality predicted BPD symptom severity at age 14. Only worsening self-control between ages 12 and 14, however, predicted growth in BPD symptoms from 14 to 17. Furthermore, the effects of harsh punishment and poor self-control on age 14 BPD symptoms were partially mediated by their earlier reciprocal effects on each other between ages 5 and 14. Our findings underscore the need to address both child and parental contributions to dysfunctional transactions in order to stem the development of BPD symptoms. Moreover, problems with self-regulation in early adolescence may indicate heightened risk for subsequent BPD. Altogether, these results increase our understanding of developmental trajectories associated with BPD symptoms in adolescent girls. PMID:25961815

  18. The Natural Course of Intermittent Exotropia over a 3-year Period and the Factors Predicting the Control Deterioration

    PubMed Central

    Kwok, Jeremy J. S. W.; Chong, Gabriela S. L.; Ko, Simon T. C.; Yam, Jason C.S.

    2016-01-01

    The natural course of intermittent exotropia and the factors affecting its control has been unclear. We aim to report the natural course of our cohort of 117 Chinese children with intermittent exotropia and to identify baseline parameters that may have predictive value in the control deterioration of the disease. The visual acuity, spherical equivalent, compliance to orthoptic exercise, angle of deviation fusional convergence parameters and Newcastle Control Score were recorded for all children at baseline and at 3 years apart. Patients were divided into two groups according to the change in control over the 3 years: group 1 included patients who had no deterioration or had improvement in disease control; and group 2 were those who had deteriorated control or had undergone surgery. There were 77 patients (66%) in group 1 and 40 (34%) patients in group 2. Comparing the baseline parameters of the two groups, group 1 had statistically significantly smaller angle of deviation, larger fusional reserve, larger fusional recovery, and higher fusional reserve ratio (p < 0.05). Other baseline parameters were similar between the two groups. The baseline fusional parameters may have predictive value in determining the control of intermittent exotropia. PMID:27257120

  19. An Experimental Evaluation of Generalized Predictive Control for Tiltrotor Aeroelastic Stability Augmentation in Airplane Mode of Flight

    NASA Technical Reports Server (NTRS)

    Kvaternik, Raymond G.; Piatak, David J.; Nixon, Mark W.; Langston, Chester W.; Singleton, Jeffrey D.; Bennett, Richard L.; Brown, Ross K.

    2001-01-01

    The results of a joint NASA/Army/Bell Helicopter Textron wind-tunnel test to assess the potential of Generalized Predictive Control (GPC) for actively controlling the swashplate of tiltrotor aircraft to enhance aeroelastic stability in the airplane mode of flight are presented. GPC is an adaptive time-domain predictive control method that uses a linear difference equation to describe the input-output relationship of the system and to design the controller. The test was conducted in the Langley Transonic Dynamics Tunnel using an unpowered 1/5-scale semispan aeroelastic model of the V-22 that was modified to incorporate a GPC-based multi-input multi-output control algorithm to individually control each of the three swashplate actuators. Wing responses were used for feedback. The GPC-based control system was highly effective in increasing the stability of the critical wing mode for all of the conditions tested, without measurable degradation of the damping in the other modes. The algorithm was also robust with respect to its performance in adjusting to rapid changes in both the rotor speed and the tunnel airspeed.

  20. Ongoing Activity in Temporally Coherent Networks Predicts Intra-Subject Fluctuation of Response Time to Sporadic Executive Control Demands

    PubMed Central

    Nozawa, Takayuki; Sugiura, Motoaki; Yokoyama, Ryoichi; Ihara, Mizuki; Kotozaki, Yuka; Miyauchi, Carlos Makoto; Kanno, Akitake; Kawashima, Ryuta

    2014-01-01

    Can ongoing fMRI BOLD signals predict fluctuations in swiftness of a person’s response to sporadic cognitive demands? This is an important issue because it clarifies whether intrinsic brain dynamics, for which spatio-temporal patterns are expressed as temporally coherent networks (TCNs), have effects not only on sensory or motor processes, but also on cognitive processes. Predictivity has been affirmed, although to a limited extent. Expecting a predictive effect on executive performance for a wider range of TCNs constituting the cingulo-opercular, fronto-parietal, and default mode networks, we conducted an fMRI study using a version of the color–word Stroop task that was specifically designed to put a higher load on executive control, with the aim of making its fluctuations more detectable. We explored the relationships between the fluctuations in ongoing pre-trial activity in TCNs and the task response time (RT). The results revealed the existence of TCNs in which fluctuations in activity several seconds before the onset of the trial predicted RT fluctuations for the subsequent trial. These TCNs were distributed in the cingulo-opercular and fronto-parietal networks, as well as in perceptual and motor networks. Our results suggest that intrinsic brain dynamics in these networks constitute “cognitive readiness,” which plays an active role especially in situations where information for anticipatory attention control is unavailable. Fluctuations in these networks lead to fluctuations in executive control performance. PMID:24901995

  1. The minimum requirements of language control: evidence from sequential predictability effects in language switching.

    PubMed

    Declerck, Mathieu; Koch, Iring; Philipp, Andrea M

    2015-03-01

    The current study systematically examined the influence of sequential predictability of languages and concepts on language switching. To this end, 2 language switching paradigms were combined. To measure language switching with a random sequence of languages and/or concepts, we used a language switching paradigm that implements visual cues and stimuli. The other paradigm implements a fixed sequence of languages and/or concepts to measure predictable language switching. Four experiments that used these 2 paradigms showed that switch costs were smaller when both the language and concept were predictably known, whereas no overall switch cost reduction was found when just the language or concept was predictable. These results indicate that knowing both language and concept (i.e., response) can resolve language interference. However, interference resolution does not start solely based on the knowledge of which concept or language one has to produce. We discuss how existent models should be revised to accommodate these results. PMID:24999708

  2. The predictability of frequency-altered auditory feedback changes the weighting of feedback and feedforward input for speech motor control.

    PubMed

    Scheerer, Nichole E; Jones, Jeffery A

    2014-12-01

    Speech production requires the combined effort of a feedback control system driven by sensory feedback, and a feedforward control system driven by internal models. However, the factors that dictate the relative weighting of these feedback and feedforward control systems are unclear. In this event-related potential (ERP) study, participants produced vocalisations while being exposed to blocks of frequency-altered feedback (FAF) perturbations that were either predictable in magnitude (consistently either 50 or 100 cents) or unpredictable in magnitude (50- and 100-cent perturbations varying randomly within each vocalisation). Vocal and P1-N1-P2 ERP responses revealed decreases in the magnitude and trial-to-trial variability of vocal responses, smaller N1 amplitudes, and shorter vocal, P1 and N1 response latencies following predictable FAF perturbation magnitudes. In addition, vocal response magnitudes correlated with N1 amplitudes, vocal response latencies, and P2 latencies. This pattern of results suggests that after repeated exposure to predictable FAF perturbations, the contribution of the feedforward control system increases. Examination of the presentation order of the FAF perturbations revealed smaller compensatory responses, smaller P1 and P2 amplitudes, and shorter N1 latencies when the block of predictable 100-cent perturbations occurred prior to the block of predictable 50-cent perturbations. These results suggest that exposure to large perturbations modulates responses to subsequent perturbations of equal or smaller size. Similarly, exposure to a 100-cent perturbation prior to a 50-cent perturbation within a vocalisation decreased the magnitude of vocal and N1 responses, but increased P1 and P2 latencies. Thus, exposure to a single perturbation can affect responses to subsequent perturbations. PMID:25263844

  3. High trait self-control predicts positive health behaviors and success in weight loss

    PubMed Central

    Crescioni, A. Will; Ehrlinger, Joyce; Alquist, Jessica L.; Conlon, Kyle E.; Baumeister, Roy F.; Schatschneider, Christopher; Dutton, Gareth R.

    2015-01-01

    Surprisingly few studies have explored the intuitive connection between self-control and weight loss. We tracked participants’ diet, exercise and weight loss during a 12-week weight loss program. Participants higher in self-control weighed less and reported exercising more than their lower self-control counterparts at baseline. Independent of baseline differences, individuals high in dispositional self-control ate fewer calories overall and fewer calories from fat, burned marginally more calories through exercise, and lost more weight during the program than did those lower in self-control. These data suggest that trait self-control is, indeed, an important predictor of health behaviors. PMID:21421645

  4. Restrained eating predicts effortful self-control as indicated by heart rate variability during food exposure.

    PubMed

    Geisler, Fay C M; Kleinfeldt, Anne; Kubiak, Thomas

    2016-01-01

    When confronted with food, restrained eaters have to inhibit the pursuit of the short-term goal of enjoying their food for the sake of the long-term goal of controlling their weight. Thus, restrained eating creates a self-control situation. In the present study we investigated the initiation of effortful self-control by food cues in accordance with the level of restrained eating. We expected that a preceding act of self-control would moderate the association between restrained eating and effortful self-control initiated by food cues. Participants (N=111) were randomly assigned to a task requiring self-control or a task not requiring self-control. Subsequently, participants were exposed to palatable food, and effortful self-control was measured via heart rate variability (HRV). Restrained eating was associated with enhanced HRV during food exposure after exercising self-control but not after not exercising self-control. The results indicate that maintaining dieting goals results in food cues initiating effortful self-control after a preceding act of self-control. We suggest considering the effect of acts of self-control when modeling the initial steps on the path from food cues to unsuccessful restrained eating. PMID:26500202

  5. Prediction of fruit and vegetable intake from biomarkers using individual participant data of diet-controlled intervention studies.

    PubMed

    Souverein, Olga W; de Vries, Jeanne H M; Freese, Riitta; Watzl, Bernhard; Bub, Achim; Miller, Edgar R; Castenmiller, Jacqueline J M; Pasman, Wilrike J; van Het Hof, Karin; Chopra, Mridula; Karlsen, Anette; Dragsted, Lars O; Winkels, Renate; Itsiopoulos, Catherine; Brazionis, Laima; O'Dea, Kerin; van Loo-Bouwman, Carolien A; Naber, Ton H J; van der Voet, Hilko; Boshuizen, Hendriek C

    2015-05-14

    Fruit and vegetable consumption produces changes in several biomarkers in blood. The present study aimed to examine the dose-response curve between fruit and vegetable consumption and carotenoid (α-carotene, β-carotene, β-cryptoxanthin, lycopene, lutein and zeaxanthin), folate and vitamin C concentrations. Furthermore, a prediction model of fruit and vegetable intake based on these biomarkers and subject characteristics (i.e. age, sex, BMI and smoking status) was established. Data from twelve diet-controlled intervention studies were obtained to develop a prediction model for fruit and vegetable intake (including and excluding fruit and vegetable juices). The study population in the present individual participant data meta-analysis consisted of 526 men and women. Carotenoid, folate and vitamin C concentrations showed a positive relationship with fruit and vegetable intake. Measures of performance for the prediction model were calculated using cross-validation. For the prediction model of fruit, vegetable and juice intake, the root mean squared error (RMSE) was 258.0 g, the correlation between observed and predicted intake was 0.78 and the mean difference between observed and predicted intake was - 1.7 g (limits of agreement: - 466.3, 462.8 g). For the prediction of fruit and vegetable intake (excluding juices), the RMSE was 201.1 g, the correlation was 0.65 and the mean bias was 2.4 g (limits of agreement: -368.2, 373.0 g). The prediction models which include the biomarkers and subject characteristics may be used to estimate average intake at the group level and to investigate the ranking of individuals with regard to their intake of fruit and vegetables when validating questionnaires that measure intake. PMID:25850683

  6. Demand response-enabled model predictive HVAC load control in buildings using real-time electricity pricing

    NASA Astrophysics Data System (ADS)

    Avci, Mesut

    A practical cost and energy efficient model predictive control (MPC) strategy is proposed for HVAC load control under dynamic real-time electricity pricing. The MPC strategy is built based on a proposed model that jointly minimizes the total energy consumption and hence, cost of electricity for the user, and the deviation of the inside temperature from the consumer's preference. An algorithm that assigns temperature set-points (reference temperatures) to price ranges based on the consumer's discomfort tolerance index is developed. A practical parameter prediction model is also designed for mapping between the HVAC load and the inside temperature. The prediction model and the produced temperature set-points are integrated as inputs into the MPC controller, which is then used to generate signal actions for the AC unit. To investigate and demonstrate the effectiveness of the proposed approach, a simulation based experimental analysis is presented using real-life pricing data. An actual prototype for the proposed HVAC load control strategy is then built and a series of prototype experiments are conducted similar to the simulation studies. The experiments reveal that the MPC strategy can lead to significant reductions in overall energy consumption and cost savings for the consumer. Results suggest that by providing an efficient response strategy for the consumers, the proposed MPC strategy can enable the utility providers to adopt efficient demand management policies using real-time pricing. Finally, a cost-benefit analysis is performed to display the economic feasibility of implementing such a controller as part of a building energy management system, and the payback period is identified considering cost of prototype build and cost savings to help the adoption of this controller in the building HVAC control industry.

  7. Missed by an inch or a mile? Predicting the size of intention-behaviour gap from measures of executive control.

    PubMed

    Allan, Julia L; Johnston, Marie; Campbell, Neil

    2011-06-01

    Failing to achieve healthy intentions can have a direct impact on subsequent health. The extent of this impact is partially determined by the size of the discrepancy between intentions and behaviour, that is, on whether an unachieved behavioural target is missed by an inch or a mile. Over two studies, measures of 'executive control' ability were used to predict the size of the intention-behaviour gap for two dietary behaviours - eating fruits and vegetables and snacking. In Study 1, participants (n=50) reported intended dietary intake, completed objective and self-report measures of executive control ability and recorded actual dietary intake over 3 days with computerised diaries. Using multiple regression, general executive control ability was found to account for 16-23% of the variance in the size of intention-behaviour gap for both the dietary behaviours. In Study 2 (n=52), deviation from intentions about snacking was significantly related to individual differences in prepotent response inhibition. Overall, individuals with weak executive control ate less fruits and vegetables and more snacks than intended. Intention-behaviour 'failures' are not homogenous, but instead vary predictably with the availability of executive control resources. This suggests that individuals with large intention-behaviour shortfalls may benefit from interventions designed to reduce the demands on executive control. PMID:21360414

  8. A study of the prediction of cruise noise and laminar flow control noise criteria for subsonic air transports

    NASA Technical Reports Server (NTRS)

    Swift, G.; Mungur, P.

    1979-01-01

    General procedures for the prediction of component noise levels incident upon airframe surfaces during cruise are developed. Contributing noise sources are those associated with the propulsion system, the airframe and the laminar flow control (LFC) system. Transformation procedures from the best prediction base of each noise source to the transonic cruise condition are established. Two approaches to LFC/acoustic criteria are developed. The first is a semi-empirical extension of the X-21 LFC/acoustic criteria to include sensitivity to the spectrum and directionality of the sound field. In the second, the more fundamental problem of how sound excites boundary layer disturbances is analyzed by deriving and solving an inhomogeneous Orr-Sommerfeld equation in which the source terms are proportional to the production and dissipation of sound induced fluctuating vorticity. Numerical solutions are obtained and compared with corresponding measurements. Recommendations are made to improve and validate both the cruise noise prediction methods and the LFC/acoustic criteria.

  9. The Brief Self-Control Scale Predicts Jail Inmates’ Recidivism, Substance Dependence, and Post-Release Adjustment

    PubMed Central

    2015-01-01

    Previous research finds that self-control is positively associated with adaptive and negatively associated with maladaptive behavior. However, most previous studies employ cross-sectional designs, low-risk samples, and limited assessments of self-control. This study of 553 jail inmates examined the relationship of a valid measure of self-control (Brief Self-Control Scale; BSCS) completed upon incarceration with behavior before, during, and one year after incarceration. After controlling for positive impression management (PIM), self-control was negatively related to substance misuse, suicidality, risky sex, and criminal history prior to incarceration and post-release illegal substance misuse, recidivism, and positive adjustment. Lower self-control predicted increases in substance dependence at post-release compared to pre-incarceration. Self-control was not related to misbehavior during incarceration, nor alcohol use or HIV-risk behavior one year post-release. Results were consistent as a function of age, race, and gender. This study supports self-control as an important risk and protective factor in a sample of criminal offenders. PMID:24345712

  10. Nomogram to predict the number of oocytes retrieved in controlled ovarian stimulation

    PubMed Central

    Moon, Kyoung Yong; Kim, Hoon; Lee, Joong Yeup; Lee, Jung Ryeol; Jee, Byung Chul; Suh, Chang Suk; Kim, Ki Chul; Lee, Won Don; Lim, Jin Ho

    2016-01-01

    Objective Ovarian reserve tests are commonly used to predict ovarian response in infertile patients undergoing ovarian stimulation. Although serum markers such as basal follicle-stimulating hormone (FSH) or random anti-Müllerian hormone (AMH) level and ultrasonographic markers (antral follicle count, AFC) are good predictors, no single test has proven to be the best predictor. In this study, we developed appropriate equations and novel nomograms to predict the number of oocytes that will be retrieved using patients' age, serum levels of basal FSH and AMH, and AFC. Methods We analyzed a database containing clinical and laboratory information of 141 stimulated in vitro fertilization (IVF) cycles performed at a university-based hospital between September 2009 and December 2013. We used generalized linear models for prediction of the number of oocytes. Results Age, basal serum FSH level, serum AMH level, and AFC were significantly related to the number of oocytes retrieved according to the univariate and multivariate analyses. The equations that predicted the number of oocytes retrieved (log scale) were as follows: model (1) 3.21–0.036×(age)+0.089×(AMH), model (2) 3.422–0.03×(age)–0.049×(FSH)+0.08×(AMH), model (3) 2.32–0.017×(age)+0.039×(AMH)+0. 03×(AFC), model (4) 2.584–0.015×(age)–0.035×(FSH)+0.038×(AMH)+0.026×(AFC). model 4 showed the best performance. On the basis of these variables, we developed nomograms to predict the number of oocytes that can be retrieved. Conclusion Our nomograms helped predict the number of oocytes retrieved in stimulated IVF cycles. PMID:27358830

  11. Sensor-model prediction, monitoring and in-situ control of liquid RTM advanced fiber architecture composite processing

    NASA Astrophysics Data System (ADS)

    Kranbuehl, D.; Kingsley, P.; Hart, S.; Loos, A.; Hasko, G.; Dexter, B.

    In-situ frequency dependent electromagnetic sensors (FDEMS) and the Loos resin transfer model have been used to select and control the processing properties of an epoxy resin during liquid pressure RTM impregnation and cure. Once correlated with viscosity and degree of cure the FDEMS sensor monitors and the RTM processing model predicts the reaction advancement of the resin, viscosity and the impregnation of the fabric. This provides a direct means for predicting, monitoring, and controlling the liquid RTM process in-situ in the mold throughout the fabrication process and the effects of time, temperature, vacuum and pressure. Most importantly, the FDEMS-sensor model system has been developed to make intelligent decisions, thereby automating the liquid RTM process and removing the need for operator direction.

  12. Sensor-model prediction, monitoring and in-situ control of liquid RTM advanced fiber architecture composite processing

    NASA Technical Reports Server (NTRS)

    Kranbuehl, D.; Kingsley, P.; Hart, S.; Loos, A.; Hasko, G.; Dexter, B.

    1992-01-01

    In-situ frequency dependent electromagnetic sensors (FDEMS) and the Loos resin transfer model have been used to select and control the processing properties of an epoxy resin during liquid pressure RTM impregnation and cure. Once correlated with viscosity and degree of cure the FDEMS sensor monitors and the RTM processing model predicts the reaction advancement of the resin, viscosity and the impregnation of the fabric. This provides a direct means for predicting, monitoring, and controlling the liquid RTM process in-situ in the mold throughout the fabrication process and the effects of time, temperature, vacuum and pressure. Most importantly, the FDEMS-sensor model system has been developed to make intelligent decisions, thereby automating the liquid RTM process and removing the need for operator direction.

  13. Nonlinear predictive controller based on S-PARAFAC Volterra models applied to a communicating two-tank system

    NASA Astrophysics Data System (ADS)

    Khouaja, Anis; Garna, Tarek; Ragot, José; Messaoud, Hassani

    2015-08-01

    This paper proposes a new predictive controller approach for nonlinear process based on a reduced complexity homogeneous, quadratic discrete-time Volterra model called quadratic S-PARAFAC Volterra model. The proposed model is yielded by using the symmetry property of the Volterra kernels and their tensor decomposition using the PARAFAC technique that provides a parametric reduction compared to the conventional Volterra model. This property allows synthesising a new nonlinear-model-based predictive control (NMBPC). We develop the general form of a new predictor, and therefore, we propose an optimisation algorithm formulated as a quadratic programming under linear and nonlinear constraints. The performances of the proposed quadratic S-PARAFAC Volterra model and the developed NMBPC algorithm are illustrated on a numerical simulation and validated on a benchmark as a continuous stirred-tank reactor system. Moreover, the efficiency of the proposed quadratic S-PARAFAC Volterra model and the NMBPC approach are validated on an experimental communicating two-tank system.

  14. Individual differences in self-reported self-control predict successful emotion regulation.

    PubMed

    Paschke, Lena M; Dörfel, Denise; Steimke, Rosa; Trempler, Ima; Magrabi, Amadeus; Ludwig, Vera U; Schubert, Torsten; Stelzel, Christine; Walter, Henrik

    2016-08-01

    Both self-control and emotion regulation enable individuals to adapt to external circumstances and social contexts, and both are assumed to rely on the overlapping neural resources. Here, we tested whether high self-reported self-control is related to successful emotion regulation on the behavioral and neural level. One hundred eight participants completed three self-control questionnaires and regulated their negative emotions during functional magnetic resonance imaging using reappraisal (distancing). Trait self-control correlated positively with successful emotion regulation both subjectively and neurally, as indicated by online ratings of negative emotions and functional connectivity strength between the amygdala and prefrontal areas, respectively. This stronger overall connectivity of the left amygdala was related to more successful subjective emotion regulation. Comparing amygdala activity over time showed that high self-controllers successfully maintained down-regulation of the left amygdala over time, while low self-controllers failed to down-regulate towards the end of the experiment. This indicates that high self-controllers are better at maintaining a motivated state supporting emotion regulation over time. Our results support assumptions concerning a close relation of self-control and emotion regulation as two domains of behavioral control. They further indicate that individual differences in functional connectivity between task-related brain areas directly relate to differences in trait self-control. PMID:27013102

  15. Markov Model Predicts Changes in STH Prevalence during Control Activities Even with a Reduced Amount of Baseline Information

    PubMed Central

    Montresor, Antonio; Deol, Arminder; à Porta, Natacha; Lethanh, Nam; Jankovic, Dina

    2016-01-01

    Background Estimating the reduction in levels of infection during implementation of soil-transmitted helminth (STH) control programmes is important to measure their performance and to plan interventions. Markov modelling techniques have been used with some success to predict changes in STH prevalence following treatment in Viet Nam. The model is stationary and to date, the prediction has been obtained by calculating the transition probabilities between the different classes of intensity following the first year of drug distribution and assuming that these remain constant in subsequent years. However, to run this model longitudinal parasitological data (including intensity of infection) are required for two consecutive years from at least 200 individuals. Since this amount of data is not often available from STH control programmes, the possible application of the model in control programme is limited. The present study aimed to address this issue by adapting the existing Markov model to allow its application when a more limited amount of data is available and to test the predictive capacities of these simplified models. Method We analysed data from field studies conducted with different combination of three parameters: (i) the frequency of drug administration; (ii) the drug distributed; and (iii) the target treatment population (entire population or school-aged children only). This analysis allowed us to define 10 sets of standard transition probabilities to be used to predict prevalence changes when only baseline data are available (simplified model 1). We also formulated three equations (one for each STH parasite) to calculate the predicted prevalence of the different classes of intensity from the total prevalence. These equations allowed us to design a simplified model (SM2) to obtain predictions when the classes of intensity at baseline were not known. To evaluate the performance of the simplified models, we collected data from the scientific literature on

  16. Correlation of Predicted and Flight Derived Stability and Control Derivatives with Particular Application to Tailless Delta Wing Configurations

    NASA Technical Reports Server (NTRS)

    Weil, J.

    1981-01-01

    Flight derived longitudinal and lateral-directional stability and control derivatives were compared to wind-tunnel derived values. As a result of these comparisons, boundaries representing the uncertainties that could be expected from wind-tunnel predictions were established. These boundaries provide a useful guide for control system sensitivity studies prior to flight. The primary application for this data was the space shuttle, and as a result the configurations included in the study were those most applicable to the space shuttle. The configurations included conventional delta wing aircraft as well as the X-15 and lifting body vehicles.

  17. The Minimum Requirements of Language Control: Evidence from Sequential Predictability Effects in Language Switching

    ERIC Educational Resources Information Center

    Declerck, Mathieu; Koch, Iring; Philipp, Andrea M.

    2015-01-01

    The current study systematically examined the influence of sequential predictability of languages and concepts on language switching. To this end, 2 language switching paradigms were combined. To measure language switching with a random sequence of languages and/or concepts, we used a language switching paradigm that implements visual cues and…

  18. Computational studies of a strain-based deformation shape prediction algorithm for control and monitoring applications

    NASA Astrophysics Data System (ADS)

    Derkevorkian, Armen; Alvarenga, Jessica; Masri, Sami F.; Boussalis, Helen; Richards, W. Lance

    2012-04-01

    A modal approach is investigated for real-time deformation shape prediction of lightweight unmanned flying aerospace structures, for the purposes of Structural Health Monitoring (SHM) and condition assessment. The deformation prediction algorithm depends on the modal properties of the structure and uses high-resolution fiber-optic sensors to obtain strain data from a representative aerospace structure (e.g., flying wing) in order to predict the associated real-time deflection shape. The method is based on the use of fiber-optic sensors such as optical Fiber Bragg Gratings (FBGs) which are known for their accuracy and light weight. In this study, the modal method is examined through computational models involving Finite-Element Analysis (FEA). Furthermore, sensitivity analyses are performed to investigate the effects of several external factors such as sensor locations and noise pollution on the performance of the algorithm. This work analyzes the numerous complications and difficulties that might potentially arise from combining the state-of-the-art advancements in sensing technology, deformation shape prediction, and structural health monitoring, to achieve a robust way of monitoring ultra lightweight flying wings or next-generation commercial airplanes.

  19. Put on a happy face! Inhibitory control and socioemotional knowledge predict emotion regulation in 5- to 7-year-olds.

    PubMed

    Hudson, Amanda; Jacques, Sophie

    2014-07-01

    Children's developing capacity to regulate emotions may depend on individual characteristics and other abilities, including age, sex, inhibitory control, theory of mind, and emotion and display rule knowledge. In the current study, we examined the relations between these variables and children's (N=107) regulation of emotion in a disappointing gift paradigm as well as their relations with the amount of effort to control emotion children exhibited after receiving the disappointing gift. Regression analyses were also conducted to identify unique predictors. Children's understanding of others' emotions and emotion display rules, as well as their inhibitory control skills, emerged as significant correlates of emotion regulation and predicted children's responses to the disappointing gift even after controlling for other relevant variables. Age and inhibitory control significantly predicted the amount of overt effort that went into regulating emotions, as did emotion knowledge (albeit only marginally). Together, findings suggest that effectively regulating emotions requires (a) knowledge of context-appropriate emotions along with (b) inhibitory skills to implement that knowledge. PMID:24691036

  20. Data-driven modeling and predictive control for boiler-turbine unit using fuzzy clustering and subspace methods.

    PubMed

    Wu, Xiao; Shen, Jiong; Li, Yiguo; Lee, Kwang Y

    2014-05-01

    This paper develops a novel data-driven fuzzy modeling strategy and predictive controller for boiler-turbine unit using fuzzy clustering and subspace identification (SID) methods. To deal with the nonlinear behavior of boiler-turbine unit, fuzzy clustering is used to provide an appropriate division of the operation region and develop the structure of the fuzzy model. Then by combining the input data with the corresponding fuzzy membership functions, the SID method is extended to extract the local state-space model parameters. Owing to the advantages of the both methods, the resulting fuzzy model can represent the boiler-turbine unit very closely, and a fuzzy model predictive controller is designed based on this model. As an alternative approach, a direct data-driven fuzzy predictive control is also developed following the same clustering and subspace methods, where intermediate subspace matrices developed during the identification procedure are utilized directly as the predictor. Simulation results show the advantages and effectiveness of the proposed approach. PMID:24559835

  1. On the predictive control of foveal eye tracking and slow phases of optokinetic and vestibular nystagmus.

    PubMed Central

    Yasui, S; Young, L R

    1984-01-01

    Smooth pursuit and saccadic components of foveal visual tracking as well as more involuntary ocular movements of optokinetic (o.k.n.) and vestibular nystagmus slow phase components were investigated in man, with particular attention given to their possible input-adaptive or predictive behaviour. Each component in question was isolated from the eye movement records through a computer-aided procedure. The frequency response method was used with sinusoidal (predictable) and pseudo-random (unpredictable) stimuli. When the target motion was pseudo-random, the frequency response of pursuit eye movements revealed a large phase lead (up to about 90 degrees) at low stimulus frequencies. It is possible to interpret this result as a predictive effect, even though the stimulation was pseudo-random and thus 'unpredictable'. The pseudo-random-input frequency response intrinsic to the saccadic system was estimated in an indirect way from the pursuit and composite (pursuit + saccade) frequency response data. The result was fitted well by a servo-mechanism model, which has a simple anticipatory mechanism to compensate for the inherent neuromuscular saccadic delay by utilizing the retinal slip velocity signal. The o.k.n. slow phase also exhibited a predictive effect with sinusoidal inputs; however, pseudo-random stimuli did not produce such phase lead as found in the pursuit case. The vestibular nystagmus slow phase showed no noticeable sign of prediction in the frequency range examined (0 approximately 0.7 Hz), in contrast to the results of the visually driven eye movements (i.e. saccade, pursuit and o.k.n. slow phase) at comparable stimulus frequencies. PMID:6707954

  2. High Self-Control Predicts More Positive Emotions, Better Engagement, and Higher Achievement in School

    ERIC Educational Resources Information Center

    King, Ronnel B.; Gaerlan, Marianne Jennifer M.

    2014-01-01

    The control-value theory of academic emotions has emerged as a useful framework for studying the antecedents and consequences of different emotions in school. This framework focuses on the role of control-related and value-related appraisals as proximal antecedents of emotions. In this study, we take an individual differences approach to examine…

  3. How Home Gets to School: Parental Control Strategies Predict Children's School Readiness

    ERIC Educational Resources Information Center

    Walker, Aimee Kleisner; MacPhee, David

    2011-01-01

    At-risk families' control style (autonomy support and coercive control) was examined in relation to children's school readiness; children's social skills and mastery motivation were hypothesized mediating variables. In two different, low-income samples from diverse ethnic backgrounds, one preschool sample recruited from Head Start (N = 199) and a…

  4. Prediction of Children's Empathy-Related Responding from Their Effortful Control and Parents' Expressivity

    ERIC Educational Resources Information Center

    Valiente, Carlos; Eisenberg, Nancy; Fabes, Richard A.; Shepard, Stephanie A.; Cumberland, Amanda; Losoya, Sandra H.

    2004-01-01

    In this study, the linear and interactive relations of children's effortful control and parents' emotional expressivity to children's empathy-related responses were examined. Participants were 214 children, 4.5 to 8 years old. Children's effortful control was negatively related to their personal distress and was positively related to their…

  5. Using a hybrid model to predict solute transfer from initially saturated soil into surface runoff with controlled drainage water.

    PubMed

    Tong, Juxiu; Hu, Bill X; Yang, Jinzhong; Zhu, Yan

    2016-06-01

    The mixing layer theory is not suitable for predicting solute transfer from initially saturated soil to surface runoff water under controlled drainage conditions. By coupling the mixing layer theory model with the numerical model Hydrus-1D, a hybrid solute transfer model has been proposed to predict soil solute transfer from an initially saturated soil into surface water, under controlled drainage water conditions. The model can also consider the increasing ponding water conditions on soil surface before surface runoff. The data of solute concentration in surface runoff and drainage water from a sand experiment is used as the reference experiment. The parameters for the water flow and solute transfer model and mixing layer depth under controlled drainage water condition are identified. Based on these identified parameters, the model is applied to another initially saturated sand experiment with constant and time-increasing mixing layer depth after surface runoff, under the controlled drainage water condition with lower drainage height at the bottom. The simulation results agree well with the observed data. Study results suggest that the hybrid model can accurately simulate the solute transfer from initially saturated soil into surface runoff under controlled drainage water condition. And it has been found that the prediction with increasing mixing layer depth is better than that with the constant one in the experiment with lower drainage condition. Since lower drainage condition and deeper ponded water depth result in later runoff start time, more solute sources in the mixing layer are needed for the surface water, and larger change rate results in the increasing mixing layer depth. PMID:26983916

  6. Clinical Evaluation of an Automated Artificial Pancreas Using Zone-Model Predictive Control and Health Monitoring System

    PubMed Central

    Harvey, Rebecca A.; Dassau, Eyal; Bevier, Wendy C.; Seborg, Dale E.; Jovanovič, Lois; Doyle, Francis J.

    2014-01-01

    Abstract Background: This study was performed to evaluate the safety and efficacy of a fully automated artificial pancreas using zone-model predictive control (zone-MPC) with the health monitoring system (HMS) during unannounced meals and overnight and exercise periods. Subjects and Methods: A fully automated closed-loop artificial pancreas was evaluated in 12 subjects (eight women, four men) with type 1 diabetes (mean±SD age, 49.4±10.4 years; diabetes duration, 32.7±16.0 years; glycosylated hemoglobin, 7.3±1.2%). The zone-MPC controller used an a priori model that was initialized using the subject's total daily insulin. The controller was designed to keep glucose levels between 80 and 140 mg/dL. A hypoglycemia prediction algorithm, a module of the HMS, was used in conjunction with the zone controller to alert the user to consume carbohydrates if the glucose level was predicted to fall below 70 mg/dL in the next 15 min. Results: The average time spent in the 70–180 mg/dL range, measured by the YSI glucose and lactate analyzer (Yellow Springs Instruments, Yellow Springs, OH), was 80% for the entire session, 92% overnight from 12 a.m. to 7 a.m., and 69% and 61% for the 5-h period after dinner and breakfast, respectively. The time spent <60 mg/dL for the entire session by YSI was 0%, with no safety events. The HMS sent appropriate warnings to prevent hypoglycemia via short and multimedia message services, at an average of 3.8 treatments per subject. Conclusions: The combination of the zone-MPC controller and the HMS hypoglycemia prevention algorithm was able to safely regulate glucose in a tight range with no adverse events despite the challenges of unannounced meals and moderate exercise. PMID:24471561

  7. Prediction of Children’s Academic Competence From Their Effortful Control, Relationships, and Classroom Participation

    PubMed Central

    Lemery-Chalfant, Kathryn; Swanson, Jodi; Reiser, Mark

    2010-01-01

    The authors examined the relations among children’s effortful control, school relationships, classroom participation, and academic competence with a sample of 7- to 12-year-old children (N = 264). Parents and children reported on children’s effortful control, and teachers and children reported on children’s school relationships and classroom participation. Children’s grade point averages (GPAs) and absences were obtained from school-issued report cards. Significant positive correlations existed between effortful control, school relationships, classroom participation, and academic competence. Consistent with expectations, the teacher–child relationship, social competence, and classroom participation partially mediated the relation between effortful control and change in GPA from the beginning to the end of the school year. The teacher–child relationship and classroom participation also partially mediated the relation between effortful control and change in school absences across the year. PMID:21212831

  8. Higher Levels of Psychopathy Predict Poorer Motor Control: Implications for Understanding the Psychopathy Construct

    PubMed Central

    Robinson, Michael D.; Bresin, Konrad

    2014-01-01

    A review of the literature suggests that higher levels of psychopathy may be linked to less effective behavioral control. However, several commentators have urged caution in making statements of this type in the absence of direct evidence. In two studies (total N = 142), moment-to-moment accuracy in a motor control task was examined as a function of dimensional variations in psychopathy in an undergraduate population. As hypothesized, motor control was distinctively worse at higher levels of psychopathy relative to lower levels, both as a function of primary and secondary psychopathy and particularly their shared variance. These novel findings provide support for the idea that motor control systematically varies by psychopathy, in a basic manner, consistent with views of psychopathy emphasizing lesser control. PMID:25419045

  9. Prediction of "fear" acquisition in healthy control participants in a de novo fear-conditioning paradigm.

    PubMed

    Otto, Michael W; Leyro, Teresa M; Christian, Kelly; Deveney, Christen M; Reese, Hannah; Pollack, Mark H; Orr, Scott P

    2007-01-01

    Studies using fear-conditioning paradigms have found that anxiety patients are more conditionable than individuals without these disorders, but these effects have been demonstrated inconsistently. It is unclear whether these findings have etiological significance or whether enhanced conditionability is linked only to certain anxiety characteristics. To further examine these issues, the authors assessed the predictive significance of relevant subsyndromal characteristics in 72 healthy adults, including measures of worry, avoidance, anxious mood, depressed mood, and fears of anxiety symptoms (anxiety sensitivity), as well as the dimensions of Neuroticism and Extraversion. Of these variables, the authors found that the combination of higher levels of subsyndromal worry and lower levels of behavioral avoidance predicted heightened conditionability, raising questions about the etiological significance of these variables in the acquisition or maintenance of anxiety disorders. In contrast, the authors found that anxiety sensitivity was more linked to individual differences in orienting response than differences in conditioning per se. PMID:17179530

  10. From neuron to behavior: dynamic equation-based prediction of biological processes in motor control.

    PubMed

    Daun-Gruhn, Silvia; Büschges, Ansgar

    2011-07-01

    This article presents the use of continuous dynamic models in the form of differential equations to describe and predict temporal changes in biological processes and discusses several of its important advantages over discontinuous bistable ones, exemplified on the stick insect walking system. In this system, coordinated locomotion is produced by concerted joint dynamics and interactions on different dynamical scales, which is therefore difficult to understand. Modeling using differential equations possesses, in general, the potential for the inclusion of biological detail, the suitability for simulation, and most importantly, parameter manipulation to make predictions about the system behavior. We will show in this review article how, in case of the stick insect walking system, continuous dynamical system models can help to understand coordinated locomotion. PMID:21769740

  11. Physical controls and predictability of stream hyporheic flow evaluated with a multiscale model

    USGS Publications Warehouse

    Stonedahl, Susa H.; Harvey, Judson W.; Detty, Joel; Aubeneau, Antoine; Packman, Aaron I.

    2012-01-01

    Improved predictions of hyporheic exchange based on easily measured physical variables are needed to improve assessment of solute transport and reaction processes in watersheds. Here we compare physically based model predictions for an Indiana stream with stream tracer results interpreted using the Transient Storage Model (TSM). We parameterized the physically based, Multiscale Model (MSM) of stream-groundwater interactions with measured stream planform and discharge, stream velocity, streambed hydraulic conductivity and porosity, and topography of the streambed at distinct spatial scales (i.e., ripple, bar, and reach scales). We predicted hyporheic exchange fluxes and hyporheic residence times using the MSM. A Continuous Time Random Walk (CTRW) model was used to convert the MSM output into predictions of in stream solute transport, which we compared with field observations and TSM parameters obtained by fitting solute transport data. MSM simulations indicated that surface-subsurface exchange through smaller topographic features such as ripples was much faster than exchange through larger topographic features such as bars. However, hyporheic exchange varies nonlinearly with groundwater discharge owing to interactions between flows induced at different topographic scales. MSM simulations showed that groundwater discharge significantly decreased both the volume of water entering the subsurface and the time it spent in the subsurface. The MSM also characterized longer timescales of exchange than were observed by the tracer-injection approach. The tracer data, and corresponding TSM fits, were limited by tracer measurement sensitivity and uncertainty in estimates of background tracer concentrations. Our results indicate that rates and patterns of hyporheic exchange are strongly influenced by a continuum of surface-subsurface hydrologic interactions over a wide range of spatial and temporal scales rather than discrete processes.

  12. Bayesian neural adjustment of inhibitory control predicts emergence of problem stimulant use.

    PubMed

    Harlé, Katia M; Stewart, Jennifer L; Zhang, Shunan; Tapert, Susan F; Yu, Angela J; Paulus, Martin P

    2015-11-01

    Bayesian ideal observer models quantify individuals' context- and experience-dependent beliefs and expectations about their environment, which provides a powerful approach (i) to link basic behavioural mechanisms to neural processing; and (ii) to generate clinical predictors for patient populations. Here, we focus on (ii) and determine whether individual differences in the neural representation of the need to stop in an inhibitory task can predict the development of problem use (i.e. abuse or dependence) in individuals experimenting with stimulants. One hundred and fifty-seven non-dependent occasional stimulant users, aged 18-24, completed a stop-signal task while undergoing functional magnetic resonance imaging. These individuals were prospectively followed for 3 years and evaluated for stimulant use and abuse/dependence symptoms. At follow-up, 38 occasional stimulant users met criteria for a stimulant use disorder (problem stimulant users), while 50 had discontinued use (desisted stimulant users). We found that those individuals who showed greater neural responses associated with Bayesian prediction errors, i.e. the difference between actual and expected need to stop on a given trial, in right medial prefrontal cortex/anterior cingulate cortex, caudate, anterior insula, and thalamus were more likely to exhibit problem use 3 years later. Importantly, these computationally based neural predictors outperformed clinical measures and non-model based neural variables in predicting clinical status. In conclusion, young adults who show exaggerated brain processing underlying whether to 'stop' or to 'go' are more likely to develop stimulant abuse. Thus, Bayesian cognitive models provide both a computational explanation and potential predictive biomarkers of belief processing deficits in individuals at risk for stimulant addiction. PMID:26336910

  13. Prediction-learning in infants as a mechanism for gaze control during object exploration

    PubMed Central

    Schlesinger, Matthew; Johnson, Scott P.; Amso, Dima

    2014-01-01

    We are pursuing the hypothesis that visual exploration and learning in young infants is achieved by producing gaze-sample sequences that are sequentially predictable. Our recent analysis of infants’ gaze patterns during image free-viewing (Schlesinger and Amso, 2013) provides support for this idea. In particular, this work demonstrates that infants’ gaze samples are more easily learnable than those produced by adults, as well as those produced by three artificial-observer models. In the current study, we extend these findings to a well-studied object-perception task, by investigating 3-month-olds’ gaze patterns as they view a moving, partially occluded object. We first use infants’ gaze data from this task to produce a set of corresponding center-of-gaze (COG) sequences. Next, we generate two simulated sets of COG samples, from image-saliency and random-gaze models, respectively. Finally, we generate learnability estimates for the three sets of COG samples by presenting each as a training set to an SRN. There are two key findings. First, as predicted, infants’ COG samples from the occluded-object task are learned by a pool of simple recurrent networks faster than the samples produced by the yoked, artificial-observer models. Second, we also find that resetting activity in the recurrent layer increases the network’s prediction errors, which further implicates the presence of temporal structure in infants’ COG sequences. We conclude by relating our findings to the role of image-saliency and prediction-learning during the development of object perception. PMID:24904460

  14. Fault diagnosis and fault-tolerant finite control set-model predictive control of a multiphase voltage-source inverter supplying BLDC motor.

    PubMed

    Salehifar, Mehdi; Moreno-Equilaz, Manuel

    2016-01-01

    Due to its fault tolerance, a multiphase brushless direct current (BLDC) motor can meet high reliability demand for application in electric vehicles. The voltage-source inverter (VSI) supplying the motor is subjected to open circuit faults. Therefore, it is necessary to design a fault-tolerant (FT) control algorithm with an embedded fault diagnosis (FD) block. In this paper, finite control set-model predictive control (FCS-MPC) is developed to implement the fault-tolerant control algorithm of a five-phase BLDC motor. The developed control method is fast, simple, and flexible. A FD method based on available information from the control block is proposed; this method is simple, robust to common transients in motor and able to localize multiple open circuit faults. The proposed FD and FT control algorithm are embedded in a five-phase BLDC motor drive. In order to validate the theory presented, simulation and experimental results are conducted on a five-phase two-level VSI supplying a five-phase BLDC motor. PMID:26549566

  15. Predicting Disease Risk, Identifying Stakeholders, and Informing Control Strategies: A Case Study of Anthrax in Montana.

    PubMed

    Morris, Lillian R; Blackburn, Jason K

    2016-06-01

    Infectious diseases that affect wildlife and livestock are challenging to manage and can lead to large-scale die-offs, economic losses, and threats to human health. The management of infectious diseases in wildlife and livestock is made easier with knowledge of disease risk across space and identifying stakeholders associated with high-risk landscapes. This study focuses on anthrax, caused by the bacterium Bacillus anthracis, risk to wildlife and livestock in Montana. There is a history of anthrax in Montana, but the spatial extent of disease risk and subsequent wildlife species at risk are not known. Our objective was to predict the potential geographic distribution of anthrax risk across Montana, identify wildlife species at risk and their distributions, and define stakeholders. We used an ecological niche model to predict the potential distribution of anthrax risk. We overlaid susceptible wildlife species distributions and land ownership delineations on our risk map. We found that there was an extensive region across Montana predicted as potential anthrax risk. These potentially risky landscapes overlapped the ranges of all 6 ungulate species considered in the analysis and livestock grazing allotments, and this overlap was on public and private land for all species. Our findings suggest that there is the potential for a multi-species anthrax outbreak on multiple landscapes across Montana. Our potential anthrax risk map can be used to prioritize landscapes for surveillance and for implementing livestock vaccination programs. PMID:27169560

  16. A mathematical model for predicting controlled release of bioactive agents from composite fiber structures.

    PubMed

    Zilberman, Meital; Sofer, Moran

    2007-03-01

    A mathematical model for predicting bioactive agent release profiles from core/shell fiber structures was developed and studied. These new composite fibers, which combine good mechanical properties with desired protein release profiles, are designed for use in tissue regeneration and other biomedical applications. These fibers are composed of an inner dense polymeric core surrounded by a porous bioresorbable shell, which encapsulates the bioactive agent molecules. The model is based on Fick's second law of diffusion, and on two major assumptions: (a) first-order degradation kinetics of the porous shell, and (b) a nonconstant diffusion coefficient for the bioactive agent, which increases with time because of degradation of the host polymer. Three factors are evaluated and included in this model: a porosity factor, a tortuosity factor, and a polymer concentration factor. Our study indicates that the model correlates well with in vitro release results, exhibiting a mean error of less than 2.2% for most studied cases. In this study, the model was used for predicting protein release profiles from fibers with shells of various initial molecular weights and for predicting the release of proteins with various molecular weights. This new model exhibits a potential for simulating fibrous systems for a wide variety of biomedical applications. PMID:17072845

  17. Linear quadratic game and non-cooperative predictive methods for potential application to modelling driver-AFS interactive steering control

    NASA Astrophysics Data System (ADS)

    Na, Xiaoxiang; Cole, David J.

    2013-02-01

    This paper is concerned with the modelling of strategic interactions between the human driver and the vehicle active front steering (AFS) controller in a path-following task where the two controllers hold different target paths. The work is aimed at extending the use of mathematical models in representing driver steering behaviour in complicated driving situations. Two game theoretic approaches, namely linear quadratic game and non-cooperative model predictive control (non-cooperative MPC), are used for developing the driver-AFS interactive steering control model. For each approach, the open-loop Nash steering control solution is derived; the influences of the path-following weights, preview and control horizons, driver time delay and arm neuromuscular system (NMS) dynamics are investigated, and the CPU time consumed is recorded. It is found that the two approaches give identical time histories as well as control gains, while the non-cooperative MPC method uses much less CPU time. Specifically, it is observed that the introduction of weight on the integral of vehicle lateral displacement error helps to eliminate the steady-state path-following error; the increase in preview horizon and NMS natural frequency and the decline in time delay and NMS damping ratio improve the path-following accuracy.

  18. Do Deterrence and Social-Control Theories Predict Driving after Drinking 15 years after a DWI Conviction?

    PubMed Central

    Lapham, Sandra C.; Todd, Michael

    2012-01-01

    Objective This study investigates the utility of deterrence and social-control theories for prospective prediction of driving-while-impaired (DWI) outcomes of first-time DWI offenders. Method The sample consisted of a subset of 544 convicted first-time DWI offenders (n = 337 females) who were interviewed 5 and 15 years after referral to a screening program in Bernalillo County, New Mexico. Variables collected at the 5-year (initial) interview were used in structural equation models to predict past 3-months, self-reported DWI at the 15-year follow-up (follow-up) interview. These variables represented domains defined by deterrence and social-control theories of DWI behavior, with one model corresponding to deterrence theory and one to social-control theory. Results Both models fit the data. DWI jail time was positively related to perceived enforcement, which was negatively but not significantly related to self-reported DWI. Neither jail time for DWI nor perceived likelihood of arrest was linearly related to self-reported DWI at follow-up. Interactions between jail time and prior DWI behavior indicated relatively weaker associations between initial and 15-year DWI for those reporting more jail time. Conclusion Our prospective study demonstrated that for this convicted DWI offender cohort, classic formulations of deterrence and social-control theories did not account for DWI. However, results suggest that punishment may decrease the likelihood of DWI recidivism. PMID:22269495

  19. What predicts intention-behavior discordance? A review of the action control framework.

    PubMed

    Rhodes, Ryan E; de Bruijn, Gert-Jan

    2013-10-01

    The physical activity intention-behavior gap is a focus of considerable research. The purpose of this article is to overview contemporary evidence for predictors of this intention-behavior discordance using the action control framework developed in our laboratories. We propose the hypothesis that intention-behavior discordance is from motivational (affective attitude, perceived behavioral control), self-regulatory (behavioral processes), and habitual (automaticity) constructs. PMID:23873134

  20. Evaluation of model predictive control in run-to-run processing in semiconductor manufacturing

    NASA Astrophysics Data System (ADS)

    Mullins, James A.; Campbell, W. J.; Stock, Allen D.

    1997-08-01

    Many steps in the manufacturing of semiconductors offer no opportunity for real-time measurement of the wafer state, necessitating the use of pre- and post-process measurements of the wafer state in a run-to-run control algorithm. The predominant algorithm in the industry is an extended form of SPC using an EWMA filter to adjust a model parameter vector using the available measurements. This paper evaluates the merits of using an optimal discrete controller relying on a discrete-time constrained state-space process model that incorporates feedforward action using the pre-process measurement and feedback using the post-process measurement, accounts for the process statistics using a noise model and optimal filtering theory, and ensures integral action in the controller by estimating unmeasured disturbances. Comparison to the EWMA algorithm are presented using simulations based on actual plant data from a chemical-mechanical polishing application. The polish process is particularly suitable for the application of such a controller because of the natural method the controller provides for incorporating unmeasured disturbances, like pad and slurry changes, in the control action.

  1. Piloted Simulation Evaluation of a Model-Predictive Automatic Recovery System to Prevent Vehicle Loss of Control on Approach

    NASA Technical Reports Server (NTRS)

    Litt, Jonathan; Liu, Yuan; Sowers, T. Shane; Owen, A. Karl; Guo, Ten-Huei

    2014-01-01

    This paper describes a model-predictive automatic recovery system for aircraft on the verge of a loss-of-control situation. The system determines when it must intervene to prevent an imminent accident, resulting from a poor approach. It estimates the altitude loss that would result from a go-around maneuver at the current flight condition. If the loss is projected to violate a minimum altitude threshold, the maneuver is automatically triggered. The system deactivates to allow landing once several criteria are met. Piloted flight simulator evaluation showed the system to provide effective envelope protection during extremely unsafe landing attempts. The results demonstrate how flight and propulsion control can be integrated to recover control of the vehicle automatically and prevent a potential catastrophe.

  2. Using an Informative Missing Data Model to Predict the Ability to Assess Recovery of Balance Control after Spaceflight

    NASA Technical Reports Server (NTRS)

    Feiveson, Alan H.; Wood, Scott J.; Jain, Varsha

    2008-01-01

    Astronauts show degraded balance control immediately after spaceflight. To assess this change, astronauts' ability to maintain a fixed stance under several challenging stimuli on a movable platform is quantified by "equilibrium" scores (EQs) on a scale of 0 to 100, where 100 represents perfect control (sway angle of 0) and 0 represents data loss where no sway angle is observed because the subject has to be restrained from falling. By comparing post- to pre-flight EQs for actual astronauts vs. controls, we built a classifier for deciding when an astronaut has recovered. Future diagnostic performance depends both on the sampling distribution of the classifier as well as the distribution of its input data. Taking this into consideration, we constructed a predictive ROC by simulation after modeling P(EQ = 0) in terms of a latent EQ-like beta-distributed random variable with random effects.

  3. Prediction of the Wrist Joint Position During a Postural Tremor Using Neural Oscillators and an Adaptive Controller

    PubMed Central

    Kobravi, Hamid Reza; Ali, Sara Hemmati; Vatandoust, Masood; Marvi, Rasoul

    2016-01-01

    The prediction of the joint angle position, especially during tremor bursts, can be useful for detecting, tracking, and forecasting tremors. Thus, this research proposes a new model for predicting the wrist joint position during rhythmic bursts and inter-burst intervals. Since a tremor is an approximately rhythmic and roughly sinusoidal movement, neural oscillators have been selected to underlie the proposed model. Two neural oscillators were adopted. Electromyogram (EMG) signals were recorded from the extensor carpi radialis and flexor carpi radialis muscles concurrent with the joint angle signals of a stroke subject in an arm constant-posture. The output frequency of each oscillator was equal to the frequency corresponding to the maximum value of power spectrum related to the rhythmic wrist joint angle signals which had been recorded during a postural tremor. The phase shift between the outputs of the two oscillators was equal to the phase shift between the muscle activation of the wrist flexor and extensor muscles. The difference between the two oscillators’ output signals was considered the main pattern. Along with a proportional compensator, an adaptive neural controller has adjusted the amplitude of the main pattern in such a way so as to minimize the wrist joint prediction error during a stroke patient's tremor burst and a healthy subject's generated artificial tremor. In regard to the range of wrist joint movement during the observed rhythmic motions, a calculated prediction error is deemed acceptable. PMID:27186540

  4. Lagrangian and Control Volume Models for Prediction of Cooling Lake Performance at SRP

    SciTech Connect

    Garrett, A.J.

    2001-06-26

    The model validation described in this document indicates that the methods described here and by Cooper (1984) for predicting the performance of the proposed L-Area cooling lake are reliable. Extensive observations from the Par Pond system show that lake surface temperatures exceeding 32.2 degrees C (90 degrees F) are attained occasionally in the summer in areas where there is little or no heating from the P-Area Reactor. Regulations which restrict lake surface temperatures to less than 32.2 degrees C should be structured to allow for these naturally-occurring thermal excursions.

  5. Applications of system identification methods to the prediction of helicopter stability, control and handling characteristics

    NASA Technical Reports Server (NTRS)

    Padfield, G. D.; Duval, R. K.

    1982-01-01

    A set of results on rotorcraft system identification is described. Flight measurements collected on an experimental Puma helicopter are reviewed and some notable characteristics highlighted. Following a brief review of previous work in rotorcraft system identification, the results of state estimation and model structure estimation processes applied to the Puma data are presented. The results, which were obtained using NASA developed software, are compared with theoretical predictions of roll, yaw and pitching moment derivatives for a 6 degree of freedom model structure. Anomalies are reported. The theoretical methods used are described. A framework for reduced order modelling is outlined.

  6. A model-based approach to predict muscle synergies using optimization: application to feedback control

    PubMed Central

    Sharif Razavian, Reza; Mehrabi, Naser; McPhee, John

    2015-01-01

    This paper presents a new model-based method to define muscle synergies. Unlike the conventional factorization approach, which extracts synergies from electromyographic data, the proposed method employs a biomechanical model and formally defines the synergies as the solution of an optimal control problem. As a result, the number of required synergies is directly related to the dimensions of the operational space. The estimated synergies are posture-dependent, which correlate well with the results of standard factorization methods. Two examples are used to showcase this method: a two-dimensional forearm model, and a three-dimensional driver arm model. It has been shown here that the synergies need to be task-specific (i.e., they are defined for the specific operational spaces: the elbow angle and the steering wheel angle in the two systems). This functional definition of synergies results in a low-dimensional control space, in which every force in the operational space is accurately created by a unique combination of synergies. As such, there is no need for extra criteria (e.g., minimizing effort) in the process of motion control. This approach is motivated by the need for fast and bio-plausible feedback control of musculoskeletal systems, and can have important implications in engineering, motor control, and biomechanics. PMID:26500530

  7. Changes in frontal EEG coherence across infancy predict cognitive abilities at age 3: The mediating role of attentional control.

    PubMed

    Whedon, Margaret; Perry, Nicole B; Calkins, Susan D; Bell, Martha Ann

    2016-09-01

    Theoretical perspectives of cognitive development have maintained that functional integration of the prefrontal cortex across infancy underlies the emergence of attentional control and higher cognitive abilities in early childhood. To investigate these proposed relations, we tested whether functional integration of prefrontal regions across the second half of the first year predicted observed cognitive performance in early childhood 1 year prior indirectly through observed attentional control (N = 300). Results indicated that greater change in left-but not right-frontal EEG coherence between 5 and 10 months was positively associated with attentional control, cognitive flexibility, receptive language, and behavioral inhibitory control. Specifically, a larger increase in coherence between left frontal regions was positively associated with accuracy on a visual search task at Age 2, and visual search accuracy was positively associated with receptive vocabulary, performance on a set-shifting task (DCCS), and delay of gratification at Age 3. Finally, the indirect effects from the change in left frontal EEG coherence to 3-year cognitive flexibility, receptive language, and behavioral inhibitory control were significant, suggesting that internally controlled attention is a mechanism through which early neural maturation influences children's cognitive development. (PsycINFO Database Record PMID:27441486

  8. Prediction of the spatial evolution and effects of control measures for the unfolding Haiti cholera outbreak

    NASA Astrophysics Data System (ADS)

    Bertuzzo, E.; Mari, L.; Righetto, L.; Gatto, M.; Casagrandi, R.; Blokesch, M.; Rodriguez-Iturbe, I.; Rinaldo, A.

    2011-03-01

    Here we propose spatially explicit predictions of the residual progression of the current Haiti cholera outbreak accounting for the dynamics of susceptible and infected individuals within different local human communities, and for the redistribution among them of Vibrio cholerae, the causative agent of the disease. Spreading mechanisms include the diffusion of pathogens in the aquatic environment and their dissemination due to the movement of human carriers. The model reproduces the spatiotemporal features of the outbreak to date, thus suggesting the robustness of predicted future developments of the epidemic. We estimate that, under unchanged conditions, the number of new cases in the whole country should start to decrease in January. During this month the epidemic should mainly involve the Ouest department (Port-au-Prince) while fading out in northern regions. Our spatially explicit model allows also the analysis of the effectiveness of alternative intervention strategies. To that end our results show that mass vaccinations would have a negligible impact at this stage of the epidemic. We also show that targeted sanitation strategies, providing clean drinking water supply and/or staging educational campaigns aimed at reducing exposure, may weaken the strength of the residual evolution of the infection.

  9. Final Scientific Technical Report: INTEGRATED PREDICTIVE DEMAND RESPONSE CONTROLLER FOR COMMERCIAL BUILDINGS

    SciTech Connect

    Wenzel, Mike

    2013-10-14

    This project provides algorithms to perform demand response using the thermal mass of a building. Using the thermal mass of the building is an attractive method for performing demand response because there is no need for capital expenditure. The algorithms rely on the thermal capacitance inherent in the building?s construction materials. A near-optimal ?day ahead? predictive approach is developed that is meant to keep the building?s electrical demand constant during the high cost periods. This type of approach is appropriate for both time-of-use and critical peak pricing utility rate structures. The approach uses the past days data in order to determine the best temperature setpoints for the building during the high price periods on the next day. A second ?model predictive approach? (MPC) uses a thermal model of the building to determine the best temperature for the next sample period. The approach uses constant feedback from the building and is capable of appropriately handling real time pricing. Both approaches are capable of using weather forecasts to improve performance.

  10. Morphoelastic control of gastro-intestinal organogenesis: Theoretical predictions and numerical insights

    NASA Astrophysics Data System (ADS)

    Balbi, V.; Kuhl, E.; Ciarletta, P.

    2015-05-01

    With nine meters in length, the gastrointestinal tract is not only our longest, but also our structurally most diverse organ. During embryonic development, it evolves as a bilayered tube with an inner endodermal lining and an outer mesodermal layer. Its inner surface displays a wide variety of morphological patterns, which are closely correlated to digestive function. However, the evolution of these intestinal patterns remains poorly understood. Here we show that geometric and mechanical factors can explain intestinal pattern formation. Using the nonlinear field theories of mechanics, we model surface morphogenesis as the instability problem of constrained differential growth. To allow for internal and external expansion, we model the gastrointestinal tract with homogeneous Neumann boundary conditions. To establish estimates for the folding pattern at the onset of folding, we perform a linear stability analysis supplemented by the perturbation theory. To predict pattern evolution in the post-buckling regime, we perform a series of nonlinear finite element simulations. Our model explains why longitudinal folds emerge in the esophagus with a thick and stiff outer layer, whereas circumferential folds emerge in the jejunum with a thinner and softer outer layer. In intermediate regions like the feline esophagus, longitudinal and circumferential folds emerge simultaneously. Our model could serve as a valuable tool to explain and predict alterations in esophageal morphology as a result of developmental disorders or certain digestive pathologies including food allergies.

  11. Sorbent utilization prediction methodology: sulfur control in fluidized-bed combustors

    SciTech Connect

    Fee, D.C.; Wilson, W.I.; Shearer, J.A.; Smith, G.W.; Lenc, J.F.; Fan, L.S.; Myles, K.M.; Johnson, I.

    1980-09-01

    The United States Government has embarked on an ambitious program to develop and commercialize technologies to efficiently extract energy from coal in an environmentally acceptable manner. One of the more promising new technologies for steam and power generation is the fluidized-bed combustion of coal. In this process, coal is burned in a fluidized bed composed mainly of calcined limestone sorbent. The calcium oxide reacts chemically to capture the sulfur dioxide formed during the combustion and to maintain the stack gas sulfur emissions at acceptable levels. The spent sulfur sorbent, containing calcium sulfate, is a dry solid that can be disposed of along with coal ash or potentially used. Other major advantages of fluidized-bed combustion are the reduction in nitrogen oxide emissions because of the relatively low combustion temperatures, the capability of burning wide varieties of fuel, the high carbon combustion efficiencies, and the high heat-transfer coefficients. A key to the widespread commercialization of fluidized-bed technology is the ability to accurately predict the amount of sulfur that will be captured by a given sorbent. This handbook meets this need by providing a simple, yet reliable, user-oriented methodology (the ANL method) that allows performance of a sorbent to be predicted. The methodology is based on only three essential sorbent parameters, each of which can be readily obtained from standardized laboratory tests. These standard tests and the subsequent method of data reduction are described in detail.

  12. Optimal control model predictions of system performance and attention allocation and their experimental validation in a display design study

    NASA Technical Reports Server (NTRS)

    Johannsen, G.; Govindaraj, T.

    1980-01-01

    The influence of different types of predictor displays in a longitudinal vertical takeoff and landing (VTOL) hover task is analyzed in a theoretical study. Several cases with differing amounts of predictive and rate information are compared. The optimal control model of the human operator is used to estimate human and system performance in terms of root-mean-square (rms) values and to compute optimized attention allocation. The only part of the model which is varied to predict these data is the observation matrix. Typical cases are selected for a subsequent experimental validation. The rms values as well as eye-movement data are recorded. The results agree favorably with those of the theoretical study in terms of relative differences. Better matching is achieved by revised model input data.

  13. Predicting Ares I Reaction Control System Performance by Utilizing Analysis Anchored with Development Test Data

    NASA Technical Reports Server (NTRS)

    Stein, William B.; Holt, K.; Holton, M.; Williams, J. H.; Butt, A.; Dervan, M.; Sharp, D.

    2010-01-01

    The Ares I launch vehicle is an integral part of NASA s Constellation Program, providing a foundation for a new era of space access. The Ares I is designed to lift the Orion Crew Module and will enable humans to return to the Moon as well as explore Mars.1 The Ares I is comprised of two inline stages: a Space Shuttle-derived five-segment Solid Rocket Booster (SRB) First Stage (FS) and an Upper Stage (US) powered by a Saturn V-derived J-2X engine. A dedicated Roll Control System (RoCS) located on the connecting interstage provides roll control prior to FS separation. Induced yaw and pitch moments are handled by the SRB nozzle vectoring. The FS SRB operates for approximately two minutes after which the US separates from the vehicle and the US Reaction Control System (ReCS) continues to provide reaction control for the remainder of the mission. A representation of the Ares I launch vehicle in the stacked configuration and including the Orion Crew Exploration Vehicle (CEV) is shown in Figure 1. Each Reaction Control System (RCS) design incorporates a Gaseous Helium (GHe) pressurization system combined with a monopropellant Hydrazine (N2H4) propulsion system. Both systems have two diametrically opposed thruster modules. This architecture provides one failure tolerance for function and prevention of catastrophic hazards such as inadvertent thruster firing, bulk propellant leakage, and over-pressurization. The pressurization system on the RoCS includes two ambient pressure-referenced regulators on parallel strings in order to attain the required system level single Fault Tolerant (FT) design for function while the ReCS utilizes a blow-down approach. A single burst disk and relief valve assembly is also included on the RoCS to ensure single failure tolerance for must-not-occur catastrophic hazards. The Reaction Control Systems are designed to support simultaneously firing multiple thrusters as required

  14. Effect of interfacial turbulence and accommodation coefficient on CFD predictions of pressurization and pressure control in cryogenic storage tank

    NASA Astrophysics Data System (ADS)

    Kassemi, Mohammad; Kartuzova, Olga

    2016-03-01

    Pressurization and pressure control in cryogenic storage tanks are to a large extent affected by heat and mass transport across the liquid-vapor interface. These mechanisms are, in turn, controlled by the kinetics of the phase change process and the dynamics of the turbulent recirculating flows in the liquid and vapor phases. In this paper, the effects of accommodation coefficient and interfacial turbulence on tank pressurization and pressure control simulations are examined. Comparison between numerical predictions and ground-based measurements in two large liquid hydrogen tank experiments, performed in the K-site facility at NASA Glenn Research Center (GRC) and the Multi-purpose Hydrogen Test Bed (MHTB) facility at NASA Marshall Space Flight Center (MSFC), are used to show the impact of accommodation coefficient and interfacial and vapor phase turbulence on evolution of pressure and temperatures in the cryogenic storage tanks. In particular, the self-pressurization comparisons indicate that: (1) numerical predictions are essentially independent of the magnitude of the accommodation coefficient; and (2) surprisingly, laminar models sometimes provide results that are in better agreement with experimental self-pressurization rates, even in parametric ranges where the bulk flow is deemed fully turbulent. In this light, shortcomings of the present CFD models, especially, numerical treatments of interfacial mass transfer and turbulence, as coupled to the Volume-of-Fluid (VOF) interface capturing scheme, are underscored and discussed.

  15. How Predictive Is Grip Force Control in the Complete Absence of Somatosensory Feedback?

    ERIC Educational Resources Information Center

    Nowak, Dennis A.; Glasauer, Stefan; Hermsdorfer, Joachim

    2004-01-01

    Grip force control relies on accurate internal models of the dynamics of our motor system and the external objects we manipulate. Internal models are not fixed entities, but rather are trained and updated by sensory experience. Sensory feedback signals relevant object properties and mechanical events, e.g. at the skin-object interface, to modify…

  16. Smoking Behaviors and Attitudes During Adolescence Prospectively Predict Support for Tobacco Control Policies in Adulthood

    PubMed Central

    Chassin, Laurie; Presson, Clark C.

    2012-01-01

    Introduction: Several cross-sectional studies have examined factors associated with support for tobacco control policies. The current study utilized a longitudinal design to test smoking status and attitude toward smoking measured in adolescence as prospective predictors of support for tobacco control policies measured in adulthood. Methods: Participants (N = 4,834) were from a longitudinal study of a Midwestern community-based sample. Hierarchical multiple regression analyses tested adolescent smoking status and attitude toward smoking as prospective predictors (after controlling for sociodemographic factors, adult smoking status, and adult attitude toward smoking) of support for regulation of smoking in public places, discussion of the dangers of smoking in public schools, prohibiting smoking in bars, eliminating smoking on television and in movies, prohibiting smoking in restaurants, and increasing taxes on cigarettes. Results: Participants who smoked during adolescence demonstrated more support for discussion of the dangers of smoking in public schools and less support for increasing taxes on cigarettes but only among those who smoked as adults. Those with more positive attitudes toward smoking during adolescence demonstrated less support as adults for prohibiting smoking in bars and eliminating smoking on television and in movies. Moreover, a significant interaction indicated that those with more positive attitudes toward smoking as adolescents demonstrated less support as adults for prohibiting smoking in restaurants, but only if they became parents as adults. Conclusions: This study’s findings suggest that interventions designed to deter adolescent smoking may have future benefits in increasing support for tobacco control policies. PMID:22193576

  17. Effortful Control in "Hot" and "Cool" Tasks Differentially Predicts Children's Behavior Problems and Academic Performance

    ERIC Educational Resources Information Center

    Kim, Sanghag; Nordling, Jamie Koenig; Yoon, Jeung Eun; Boldt, Lea J.; Kochanska, Grazyna

    2013-01-01

    Effortful control (EC), the capacity to deliberately suppress a dominant response and perform a subdominant response, rapidly developing in toddler and preschool age, has been shown to be a robust predictor of children's adjustment. Not settled, however, is whether a view of EC as a heterogeneous rather than unidimensional construct may offer…

  18. Impaired Activation in Cognitive Control Regions Predicts Reversal Learning in Schizophrenia.

    PubMed

    Culbreth, Adam J; Gold, James M; Cools, Roshan; Barch, Deanna M

    2016-03-01

    Reinforcement learning deficits have been associated with schizophrenia (SZ). However, the pathophysiology that gives rise to these abnormalities remains unclear. To address this question, SZ patients (N = 58) and controls (CN; N = 36) completed a probabilistic reversal-learning paradigm during functional magnetic resonance imaging scanning. During the task, participants choose between 2 stimuli. Initially, 1 stimulus was frequently rewarded (80%); the other was infrequently rewarded (20%). The reward contingencies reversed periodically because the participant learned the more rewarded stimulus. The results indicated that SZ patients achieved fewer reversals than CN, and demonstrated decreased winstay-loseshift decision-making behavior. On loseshift compared to winstay trials, SZ patients showed reduced Blood Oxygen Level Dependent activation compared to CN in a network of brain regions widely associated with cognitive control, and striatal regions. Importantly, relationships between group membership and behavior were mediated by alterations in the activity of cognitive control regions, but not striatum. These findings indicate an important role for the cognitive control network in mediating the use and updating of value representations in SZ. Such results provide biological targets for further inquiry because researchers attempt to better characterize decision-making neural circuitry in SZ as a means to discover new pathways for interventions. PMID:26049083

  19. Parental Warmth, Control, and Involvement in Schooling: Predicting Academic Achievement among Korean American Adolescents.

    ERIC Educational Resources Information Center

    Kim, Kyoungho; Rohner, Ronald P.

    2002-01-01

    Explored the relationship between parenting style and academic achievement of Korean American adolescents, investigating the influence of perceived parental warmth and control and improvement in schooling. Survey data indicated that authoritative paternal parenting related to optimal academic achievement. Differences in maternal parenting styles…

  20. Attachment anxiety and attentional control predict immediate and delayed emotional Stroop interference.

    PubMed

    Bailey, Heidi N; Paret, Laura; Battista, Christian; Xue, Ya

    2012-04-01

    Attachment anxiety has been associated with a hyperactivating response to threat. A modified emotional Stroop task was used to investigate temporal characteristics of the threat response by assessing response latencies to interpersonally threatening words (immediate interference) and two directly subsequent neutral filler words (delayed interference). Greater immediate and delayed interference to threatening words was observed (n = 125), with higher levels of attachment anxiety associated with immediate interference to threatening cues, and lower levels with delayed interference. Thus, attachment anxiety was related to the speed at which moderate perceived threat disrupted ongoing processes under top-down attentional control. Furthermore, top-down attentional control moderated the extent to which immediate or delayed interference was observed. Among participants who demonstrated relatively stronger top-down attentional control, immediate and delayed interference to threatening cues was minimal, suggesting that results involving emotional Stroop interference were primarily attributable to participants with relatively weaker top-down attentional control. The implications of these findings are considered within the broader context of performance-based and neuroimaging research, with suggestions for future applied research. PMID:22468618

  1. Frontostriatal Maturation Predicts Cognitive Control Failure to Appetitive Cues in Adolescents

    ERIC Educational Resources Information Center

    Somerville, Leah H.; Hare, Todd; Casey, B. J.

    2011-01-01

    Adolescent risk-taking is a public health issue that increases the odds of poor lifetime outcomes. One factor thought to influence adolescents' propensity for risk-taking is an enhanced sensitivity to appetitive cues, relative to an immature capacity to exert sufficient cognitive control. We tested this hypothesis by characterizing interactions…

  2. Predicting and Explaining Students' Stress with the Demand-Control Model: Does Neuroticism Also Matter?

    ERIC Educational Resources Information Center

    Schmidt, Laura I.; Sieverding, Monika; Scheiter, Fabian; Obergfell, Julia

    2015-01-01

    University students often report high stress levels, and studies even suggest a recent increase. However, there is a lack of theoretically based research on the structural conditions that influence students' perceived stress. The current study compared the effects of Karasek's demand-control dimensions with the influence of neuroticism to address…

  3. Predicting Health Care Utilization among Latinos: Health Locus of Control Beliefs or Access Factors?

    ERIC Educational Resources Information Center

    De Jesus, Maria; Xiao, Chenyang

    2014-01-01

    There are two competing research explanations to account for Latinos' underutilization of health services relative to non-Latino Whites in the United States. One hypothesis examines the impact of health locus of control (HLOC) beliefs, while the other focuses on the role of access factors on health care use. To date, the relative strength of…

  4. A Rapid Test for Prediction of Nutrient Release from Controlled Release Fertilizers

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Nutrient release from soluble granular fertilizers can be modified by polymer coating. The coating technology can be fine-tuned to change the duration (3 to 9 months) and rate of nutrient release, hence these products are termed as controlled release fertilizers (CRF). There is a need to develop a r...

  5. A rapid technique for prediction of nutrient release from controlled release fertilizers

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Nutrient release from soluble granular fertilizers can be modified by polymer coating to extend the total duration nutrient release up to 3 to 9 months and rate of release to match the nutrient requirement of the plant during the growing period. Hence these products are termed as “Controlled Release...

  6. Controlling misses and false alarms in a machine learning framework for predicting uniformity of printed pages

    NASA Astrophysics Data System (ADS)

    Nguyen, Minh Q.; Allebach, Jan P.

    2015-01-01

    In our previous work1 , we presented a block-based technique to analyze printed page uniformity both visually and metrically. The features learned from the models were then employed in a Support Vector Machine (SVM) framework to classify the pages into one of the two categories of acceptable and unacceptable quality. In this paper, we introduce a set of tools for machine learning in the assessment of printed page uniformity. This work is primarily targeted to the printing industry, specifically the ubiquitous laser, electrophotographic printer. We use features that are well-correlated with the rankings of expert observers to develop a novel machine learning framework that allows one to achieve the minimum "false alarm" rate, subject to a chosen "miss" rate. Surprisingly, most of the research that has been conducted on machine learning does not consider this framework. During the process of developing a new product, test engineers will print hundreds of test pages, which can be scanned and then analyzed by an autonomous algorithm. Among these pages, most may be of acceptable quality. The objective is to find the ones that are not. These will provide critically important information to systems designers, regarding issues that need to be addressed in improving the printer design. A "miss" is defined to be a page that is not of acceptable quality to an expert observer that the prediction algorithm declares to be a "pass". Misses are a serious problem, since they represent problems that will not be seen by the systems designers. On the other hand, "false alarms" correspond to pages that an expert observer would declare to be of acceptable quality, but which are flagged by the prediction algorithm as "fails". In a typical printer testing and development scenario, such pages would be examined by an expert, and found to be of acceptable quality after all. "False alarm" pages result in extra pages to be examined by expert observers, which increases labor cost. But "false

  7. A new ovarian response prediction index (ORPI): implications for individualised controlled ovarian stimulation

    PubMed Central

    2012-01-01

    Background The objective was to present a new ovarian response prediction index (ORPI), which was based on anti-Müllerian hormone (AMH) levels, antral follicle count (AFC) and age, and to verify whether it could be a reliable predictor of the ovarian stimulation response. Methods A total of 101 patients enrolled in the ICSI programme were included. The ORPI values were calculated by multiplying the AMH level (ng/ml) by the number of antral follicles (2–9 mm), and the result was divided by the age (years) of the patient (ORPI=(AMH x AFC)/Patient age). Results The regression analysis demonstrated significant (P<0.0001) positive correlations between the ORPI and the total number of oocytes and of MII oocytes collected. The logistic regression revealed that the ORPI values were significantly associated with the likelihood of pregnancy (odds ratio (OR): 1.86; P=0.006) and collecting greater than or equal to 4 oocytes (OR: 49.25; P<0.0001), greater than or equal to 4 MII oocytes (OR: 6.26; P<0.0001) and greater than or equal to 15 oocytes (OR: 6.10; P<0.0001). Regarding the probability of collecting greater than or equal to 4 oocytes according to the ORPI value, the ROC curve showed an area under the curve (AUC) of 0.91 and an efficacy of 88% at a cut-off of 0.2. In relation to the probability of collecting greater than or equal to 4 MII oocytes according to the ORPI value, the ROC curve had an AUC of 0.84 and an efficacy of 81% at a cut-off of 0.3. The ROC curve for the probability of collecting greater than or equal to 15 oocytes resulted in an AUC of 0.89 and an efficacy of 82% at a cut-off of 0.9. Finally, regarding the probability of pregnancy occurrence according to the ORPI value, the ROC curve showed an AUC of 0.74 and an efficacy of 62% at a cut-off of 0.3. Conclusions The ORPI exhibited an excellent ability to predict a low ovarian response and a good ability to predict a collection of greater than or equal to 4 MII oocytes, an excessive ovarian response and

  8. Catalytic Control in Cyclizations: From Computational Mechanistic Understanding to Selectivity Prediction.

    PubMed

    Peng, Qian; Paton, Robert S

    2016-05-17

    This Account describes the use of quantum-chemical calculations to elucidate mechanisms and develop catalysts to accomplish highly selective cyclization reactions. Chemistry is awash with cyclic molecules, and the creation of rings is central to organic synthesis. Cyclization reactions, the formation of rings by the reaction of two ends of a linear precursor, have been instrumental in the development of predictive models for chemical reactivity, from Baldwin's classification and rules for ring closure to the Woodward and Hoffmann rules based on the conservation of orbital symmetry and beyond. Ring formation provides a productive and fertile testing ground for the exploration of catalytic mechanisms and chemo-, regio-, diastereo-, and enantioselectivity using computational and experimental approaches. This Account is organized around case studies from our laboratory and illustrates the ways in which computations provide a deeper understanding of the mechanisms of catalysis in 5-endo cyclizations and how computational predictions can lead to the development of new catalysts for enhanced stereoselectivities in asymmetric cycloisomerizations. We have explored the extent to which several cation-directed 5-endo ring-closing reactions may be considered as electrocyclic and demonstrated that reaction pathways and magnetic parameters of transition structures computed using quantum chemistry are inconsistent with this notion, instead favoring a polar mechanism. A rare example of selectivity in favor of 5-endo-trig ring closure is shown to result from subtle substrate effects that bias the reactant conformation out-of-plane, limiting the involvement of cyclic conjugation. The mode of action of a chiral ammonium counterion was deduced via conformational sampling of the transition state assembly and involves coordination to the substrate via a series of nonclassical hydrogen bonds. We describe how computational mechanistic understanding has led directly to the discovery of new

  9. Clinical prediction of the need for interventions for the control of myopia.

    PubMed

    McMonnies, Charles W

    2015-11-01

    The prevalence of myopia is increasing in Western populations but in East Asian countries, it is increasing to epidemic levels, where there are also markedly increased rates of progression to pathological myopia. Measures to more effectively control the development and progression of myopia are urgently needed. Notwithstanding a large volume of research, especially regarding the different mechanisms for the development of myopia and the efficacy of particular methods of intervention, there is still a great need and scope for improvements in clinical efforts to prevent and/or control myopic progression. Too often clinical efforts may involve only one method of intervention; however, the heterogenous nature of myopia suggests that clinical intervention may be more successful when interventions are employed in combination. The decision to prescribe interventions for the control of myopia in children, especially prior to onset, may be better framed by a comprehensive estimation of the degree of risk for the development and/or progression of myopia. For example, rather than ascribing equal weight to any degree of parental myopia, more accurate estimates may be obtained, if risk is judged to increase with the degree of parental myopia and the extent of any associated degenerative pathology. Risk estimates may be limited to broad mild, moderate and severe classifications due to lack of accurate weighting of risk factors. Nevertheless, comprehensive assessment of risk factors appears likely to better inform a prognosis and discussions with parents. Consideration of numerous environmental influences, for example, such as continuity and intensity of near work and time spent outdoors, may contribute to better risk estimation. Family-based practice appears to be ideally suited for risk estimation and the clinical application of approaches to control myopia. A proactive approach to estimating risk of developing myopia prior to its onset may be beneficial. Earlier implementation

  10. Controlled formation of polymer nanocapsules with high diffusion-barrier properties and prediction of encapsulation efficiency.

    PubMed

    Hofmeister, Ines; Landfester, Katharina; Taden, Andreas

    2015-01-01

    Polymer nanocapsules with high diffusion-barrier performance were designed following simple thermodynamic considerations. Hindered diffusion of the enclosed material leads to high encapsulation efficiencies (EEs), which was demonstrated based on the encapsulation of highly volatile compounds of different chemical natures. Low interactions between core and shell materials are key factors to achieve phase separation and a high diffusion barrier of the resulting polymeric shell. These interactions can be characterized and quantified using the Hansen solubility parameters. A systematic study of our copolymer system revealed a linear relationship between the Hansen parameter for hydrogen bonding (δh ) and encapsulation efficiencies which enables the prediction of encapsulated amounts for any material. Furthermore EEs of poorly encapsulated materials can be increased by mixing them with a mediator compound to give lower overall δh values. PMID:25363542

  11. Flexible control in processing affective and non-affective material predicts individual differences in trait resilience.

    PubMed

    Genet, Jessica J; Siemer, Matthias

    2011-02-01

    Trait resilience is a stable personality characteristic that involves the self-reported ability to flexibly adapt to emotional events and situations. The present study examined cognitive processes that may explain individual differences in trait resilience. Participants completed self-report measures of trait resilience, cognitive flexibility and working memory capacity tasks, and a novel affective task-switching paradigm that assesses the ability to flexibly switch between processing the affective versus non-affective qualities of affective stimuli (i.e., flexible affective processing). As hypothesised, cognitive flexibility and flexible affective processing were unique predictors of trait resilience. Working memory capacity was not predictive of trait resilience, indicating that trait resilience is tied to specific cognitive processes rather than overall better cognitive functioning. Cognitive flexibility and flexible affective processing were not associated with other trait measures, suggesting that these flexibility processes are unique to trait resilience. This study was among the first to investigate the cognitive abilities underlying trait resilience. PMID:21432680

  12. A Sensorless Predictive Current Controlled Boost Converter by Using an EKF with Load Variation Effect Elimination Function

    PubMed Central

    Tong, Qiaoling; Chen, Chen; Zhang, Qiao; Zou, Xuecheng

    2015-01-01

    To realize accurate current control for a boost converter, a precise measurement of the inductor current is required to achieve high resolution current regulating. Current sensors are widely used to measure the inductor current. However, the current sensors and their processing circuits significantly contribute extra hardware cost, delay and noise to the system. They can also harm the system reliability. Therefore, current sensorless control techniques can bring cost effective and reliable solutions for various boost converter applications. According to the derived accurate model, which contains a number of parasitics, the boost converter is a nonlinear system. An Extended Kalman Filter (EKF) is proposed for inductor current estimation and output voltage filtering. With this approach, the system can have the same advantages as sensored current control mode. To implement EKF, the load value is necessary. However, the load may vary from time to time. This can lead to errors of current estimation and filtered output voltage. To solve this issue, a load variation elimination effect elimination (LVEE) module is added. In addition, a predictive average current controller is used to regulate the current. Compared with conventional voltage controlled system, the transient response is greatly improved since it only takes two switching cycles for the current to reach its reference. Finally, experimental results are presented to verify the stable operation and output tracking capability for large-signal transients of the proposed algorithm. PMID:25928061

  13. A Sensorless Predictive Current Controlled Boost Converter by Using an EKF with Load Variation Effect Elimination Function.

    PubMed

    Tong, Qiaoling; Chen, Chen; Zhang, Qiao; Zou, Xuecheng

    2015-01-01

    To realize accurate current control for a boost converter, a precise measurement of the inductor current is required to achieve high resolution current regulating. Current sensors are widely used to measure the inductor current. However, the current sensors and their processing circuits significantly contribute extra hardware cost, delay and noise to the system. They can also harm the system reliability. Therefore, current sensorless control techniques can bring cost effective and reliable solutions for various boost converter applications. According to the derived accurate model, which contains a number of parasitics, the boost converter is a nonlinear system. An Extended Kalman Filter (EKF) is proposed for inductor current estimation and output voltage filtering. With this approach, the system can have the same advantages as sensored current control mode. To implement EKF, the load value is necessary. However, the load may vary from time to time. This can lead to errors of current estimation and filtered output voltage. To solve this issue, a load variation elimination effect elimination (LVEE) module is added. In addition, a predictive average current controller is used to regulate the current. Compared with conventional voltage controlled system, the transient response is greatly improved since it only takes two switching cycles for the current to reach its reference. Finally, experimental results are presented to verify the stable operation and output tracking capability for large-signal transients of the proposed algorithm. PMID:25928061

  14. Predictive factors for renal failure and a control and treatment algorithm

    PubMed Central

    Cerqueira, Denise de Paula; Tavares, José Roberto; Machado, Regimar Carla

    2014-01-01

    Objectives to evaluate the renal function of patients in an intensive care unit, to identify the predisposing factors for the development of renal failure, and to develop an algorithm to help in the control of the disease. Method exploratory, descriptive, prospective study with a quantitative approach. Results a total of 30 patients (75.0%) were diagnosed with kidney failure and the main factors associated with this disease were: advanced age, systemic arterial hypertension, diabetes mellitus, lung diseases, and antibiotic use. Of these, 23 patients (76.6%) showed a reduction in creatinine clearance in the first 24 hours of hospitalization. Conclusion a decline in renal function was observed in a significant number of subjects, therefore, an algorithm was developed with the aim of helping in the control of renal failure in a practical and functional way. PMID:26107827

  15. Individual but not fragile: individual differences in task control predict Stroop facilitation.

    PubMed

    Kalanthroff, E; Henik, A

    2013-06-01

    The Stroop effect is composed of interference and facilitation effects. The facilitation is less stable and thus many times is referred to as a "fragile effect". Here we suggest the facilitation effect is highly vulnerable to individual differences in control over the task conflict (between relevant color naming and irrelevant word reading in the Stroop task). We replicated previous findings of a significant correlation between stop-signal reaction time (SSRT) and Stroop interference, and also found a significant correlation between SSRT and the Stroop facilitation effect-participants with low inhibitory control (i.e., long SSRT) had no facilitation effect or even a reversed one. These results shed new light on the "fragile" facilitation effect and highlight the necessity of awareness of task conflict, especially in the Stroop task. PMID:23416541

  16. Idiosyncratic responding during movie-watching predicted by age differences in attentional control

    PubMed Central

    Campbell, Karen L.; Shafto, Meredith A.; Wright, Paul; Tsvetanov, Kamen A.; Geerligs, Linda; Cusack, Rhodri; Tyler, Lorraine K.; Brayne, Carol; Bullmore, Ed; Calder, Andrew; Cusack, Rhodri; Dalgleish, Tim; Duncan, John; Henson, Rik; Matthews, Fiona; Marslen-Wilson, William; Rowe, James; Shafto, Meredith; Campbell, Karen; Cheung, Teresa; Davis, Simon; Geerligs, Linda; Kievit, Rogier; McCarrey, Anna; Price, Darren; Taylor, Jason; Tsvetanov, Kamen; Williams, Nitin; Bates, Lauren; Emery, Tina; Erzinçlioglu, Sharon; Gadie, Andrew; Gerbase, Sofia; Georgieva, Stanimira; Hanley, Claire; Parkin, Beth; Troy, David; Allen, Jodie; Amery, Gillian; Amunts, Liana; Barcroft, Anne; Castle, Amanda; Dias, Cheryl; Dowrick, Jonathan; Fair, Melissa; Fisher, Hayley; Goulding, Anna; Grewal, Adarsh; Hale, Geoff; Hilton, Andrew; Johnson, Frances; Johnston, Patricia; Kavanagh-Williamson, Thea; Kwasniewska, Magdalena; McMinn, Alison; Norman, Kim; Penrose, Jessica; Roby, Fiona; Rowland, Diane; Sargeant, John; Squire, Maggie; Stevens, Beth; Stoddart, Aldabra; Stone, Cheryl; Thompson, Tracy; Yazlik, Ozlem; Dixon, Marie; Barnes, Dan; Hillman, Jaya; Mitchell, Joanne; Villis, Laura; Tyler, Lorraine K.

    2015-01-01

    Much is known about how age affects the brain during tightly controlled, though largely contrived, experiments, but do these effects extrapolate to everyday life? Naturalistic stimuli, such as movies, closely mimic the real world and provide a window onto the brain's ability to respond in a timely and measured fashion to complex, everyday events. Young adults respond to these stimuli in a highly synchronized fashion, but it remains to be seen how age affects neural responsiveness during naturalistic viewing. To this end, we scanned a large (N = 218), population-based sample from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) during movie-watching. Intersubject synchronization declined with age, such that older adults' response to the movie was more idiosyncratic. This decreased synchrony related to cognitive measures sensitive to attentional control. Our findings suggest that neural responsivity changes with age, which likely has important implications for real-world event comprehension and memory. PMID:26359527

  17. Idiosyncratic responding during movie-watching predicted by age differences in attentional control.

    PubMed

    Campbell, Karen L; Shafto, Meredith A; Wright, Paul; Tsvetanov, Kamen A; Geerligs, Linda; Cusack, Rhodri; Tyler, Lorraine K

    2015-11-01

    Much is known about how age affects the brain during tightly controlled, though largely contrived, experiments, but do these effects extrapolate to everyday life? Naturalistic stimuli, such as movies, closely mimic the real world and provide a window onto the brain's ability to respond in a timely and measured fashion to complex, everyday events. Young adults respond to these stimuli in a highly synchronized fashion, but it remains to be seen how age affects neural responsiveness during naturalistic viewing. To this end, we scanned a large (N = 218), population-based sample from the Cambridge Centre for Ageing and Neuroscience (Cam-CAN) during movie-watching. Intersubject synchronization declined with age, such that older adults' response to the movie was more idiosyncratic. This decreased synchrony related to cognitive measures sensitive to attentional control. Our findings suggest that neural responsivity changes with age, which likely has important implications for real-world event comprehension and memory. PMID:26359527

  18. The use of test structures for reliability prediction and process control of integrated circuits and photovoltaics

    NASA Astrophysics Data System (ADS)

    Trachtenberg, I.

    How a reliability model might be developed with new data from accelerated stress testing, failure mechanisms, process control monitoring, and test structure evaluations is illustrated. The effects of the acceleration of temperature on operating life is discussed. Test structures that will further accelerate the failure rate are discussed. Corrosion testing is addressed. The uncoated structure is encapsulated in a variety of mold compounds and subjected to pressure-cooker testing.

  19. Pitch control margin at high angle of attack - Quantitative requirements (flight test correlation with simulation predictions)

    NASA Technical Reports Server (NTRS)

    Lackey, J.; Hadfield, C.

    1992-01-01

    Recent mishaps and incidents on Class IV aircraft have shown a need for establishing quantitative longitudinal high angle of attack (AOA) pitch control margin design guidelines for future aircraft. NASA Langley Research Center has conducted a series of simulation tests to define these design guidelines. Flight test results have confirmed the simulation studies in that pilot rating of high AOA nose-down recoveries were based on the short-term response interval in the forms of pitch acceleration and rate.

  20. Improving the Forecast Accuracy of an Ocean Observation and Prediction System by Adaptive Control of the Sensor Network

    NASA Astrophysics Data System (ADS)

    Talukder, A.; Panangadan, A. V.; Blumberg, A. F.; Herrington, T.; Georgas, N.

    2008-12-01

    The New York Harbor Observation and Prediction System (NYHOPS) is a real-time, estuarine and coastal ocean observing and modeling system for the New York Harbor and surrounding waters. Real-time measurements from in-situ mobile and stationary sensors in the NYHOPS networks are assimilated into marine forecasts in order to reduce the discrepancy with ground truth. The forecasts are obtained from the ECOMSED hydrodynamic model, a shallow water derivative of the Princeton Ocean Model. Currently, all sensors in the NYHOPS system are operated in a fixed mode with uniform sampling rates. This technology infusion effort demonstrates the use of Model Predictive Control (MPC) to autonomously adapt the operation of both mobile and stationary sensors in response to changing events that are -automatically detected from the ECOMSED forecasts. The controller focuses sensing resources on those regions that are expected to be impacted by the detected events. The MPC approach involves formulating the problem of calculating the optimal sensor parameters as a constrained multi-objective optimization problem. We have developed an objective function that takes into account the spatiotemporal relationship of the in-situ sensor locations and the locations of events detected by the model. Experiments in simulation were carried out using data collected during a freshwater flooding event. The location of the resulting freshwater plume was calculated from the corresponding model forecasts and was used by the MPC controller to derive control parameters for the sensing assets. The operational parameters that are controlled include the sampling rates of stationary sensors, paths of unmanned underwater vehicles (UUVs), and data transfer routes between sensors and the central modeling computer. The simulation experiments show that MPC-based sensor control reduces the RMS error in the forecast by a factor of 380% as compared to uniform sampling. The paths of multiple UUVs were simultaneously

  1. In silico models for predicting vector control chemicals targeting Aedes aegypti

    PubMed Central

    Devillers, J.; Lagneau, C.; Lattes, A.; Garrigues, J.C.; Clémenté, M.M.; Yébakima, A.

    2014-01-01

    Human arboviral diseases have emerged or re-emerged in numerous countries worldwide due to a number of factors including the lack of progress in vaccine development, lack of drugs, insecticide resistance in mosquitoes, climate changes, societal behaviours, and economical constraints. Thus, Aedes aegypti is the main vector of the yellow fever and dengue fever flaviviruses and is also responsible for several recent outbreaks of the chikungunya alphavirus. As for the other mosquito species, the A. aegypti control relies heavily on the use of insecticides. However, because of increasing resistance to the different families of insecticides, reduction of Aedes populations is becoming increasingly difficult. Despite the unquestionable utility of insecticides in fighting mosquito populations, there are very few new insecticides developed and commercialized for vector control. This is because the high cost of the discovery of an insecticide is not counterbalanced by the ‘low profitability’ of the vector control market. Fortunately, the use of quantitative structure–activity relationship (QSAR) modelling allows the reduction of time and cost in the discovery of new chemical structures potentially active against mosquitoes. In this context, the goal of the present study was to review all the existing QSAR models on A. aegypti. The homology and pharmacophore models were also reviewed. Specific attention was paid to show the variety of targets investigated in Aedes in relation to the physiology and ecology of the mosquito as well as the diversity of the chemical structures which have been proposed, encompassing man-made and natural substances. PMID:25275884

  2. Prediction and Control of Number of Cells in Microdroplets by Stochastic Modeling

    PubMed Central

    Ceyhan, Elvan; Xu, Feng; Gurkan, Umut Atakan; Emre, Ahmet Emrehan; Turali, Emine Sumeyra; El Assal, Rami; Acikgenc, Ali; Wu, Chung-an Max; Demirci, Utkan

    2012-01-01

    Manipulation and encapsulation of cells in microdroplets has found many applications in various fields such as clinical diagnostics, pharmaceutical research, and regenerative medicine. The control over the number of cells in individual droplets in such applications is important especially for microfluidic applications. There is a growing need for modeling approaches that enables control over cells within individual droplets. In this study, we developed statistical models based on negative binomial regression to determine the dependence of number of cells per droplet on three main factors: the cell concentration in the ejection fluid, droplet size, and cell size. These models were based on experimental data obtained by using a microdroplet generator, where the presented statistical models estimated the number of cells encapsulated in droplets. We also propose a stochastic model for the total volume of cells per droplet. The statistical and stochastic models introduced in this study are adaptable to various cell types and cell encapsulation technologies such as microfluidic and acoustic methods that require reliable control over number of cells per droplet provided that setting or interaction of the variables is similar to ours. PMID:23034772

  3. Predicting healthcare employees' participation in an office redesign program: Attitudes, norms and behavioral control

    PubMed Central

    Mohr, David C; Lukas, Carol VanDeusen; Meterko, Mark

    2008-01-01

    Background The study examined the extent to which components based on a modified version of the theory of planned behavior explained employee participation in a new clinical office program designed to reduce patient waiting times in primary care clinics. Methods We regressed extent of employee participation on attitudes about the program, group norms, and perceived behavioral control along with individual and clinic characteristics using a hierarchical linear mixed model. Results Perceived group norms were one of the best predictors of employee participation. Attitudes about the program were also significant, but to a lesser degree. Behavioral control, however, was not a significant predictor. Respondents with at least one year of clinic tenure, or who were team leaders, first line supervisor, or managers had greater participation rates. Analysis at the clinic level indicated clinics with scores in the highest quartile clinic scores on group norms, attitudes, and behavioral control scores were significantly higher on levels of overall participation than clinics in the lowest quartile. Conclusion Findings suggest that establishing strong norms and values may influence employee participation in a change program in a group setting. Supervisory level was also significant with greater responsibility being associated with greater participation. PMID:18976505

  4. Predicting behaviour from perceived behavioural control: tests of the accuracy assumption of the theory of planned behaviour.

    PubMed

    Sheeran, Paschal; Trafimow, David; Armitage, Christopher J

    2003-09-01

    The theory of planned behaviour assumes that the accuracy of perceived behavioural control (PBC) determines the strength of the PBC-behaviour relationship. However, this assumption has never been formally tested. The present research developed and validated a proxy measure of actual control (PMAC) in order to test the assumption. In two studies, participants completed measures of intention and PBC, and subsequently completed measures of behaviour and the PMAC. Validity of the PMAC was established by findings showing; (a). that the PMAC moderated the intention-behaviour relation, and (b). that PMAC scores did not reflect attributions for participants' failure to enact their stated intentions. Accuracy was operationalized as the difference between PBC and PMAC scores. Consistent with theoretical expectations, several analyses indicated that greater accuracy of PBC was associated with improved prediction of behaviour by PBC. PMID:14567844

  5. Predictive Methods for Real-Time Control of Flood Operation of a Multireservoir System: Methodology and Comparative Study

    NASA Astrophysics Data System (ADS)

    Niewiadomska-Szynkiewicz, Ewa; Malinowski, Krzysztof; Karbowski, Andrzej

    1996-04-01

    Predictive methods for real-time flood operation of water systems consisting of reservoirs located in parallel on tributaries to the main river are presented and discussed. The aspect of conflicting individual goals of the local decision units and other objectives important from an overall point of view is taken into account. The particular attention is focused on hierarchical control structure which provides framework for organization of an on-line reservoir management problem. The important factor involved in flood control the uncertainty with respect to future inflows is taken into consideration. A case study of the upper Vistula river basin system in the southern part of Poland is presented. Simulation results based on 11 historical floods are briefly described and discussed.

  6. Breakup and then makeup: a predictive model of how cilia self-regulate hardness for posture control

    NASA Astrophysics Data System (ADS)

    Bandyopadhyay, Promode R.; Hansen, Joshua C.

    2013-06-01

    Functioning as sensors and propulsors, cilia are evolutionarily conserved organelles having a highly organized internal structure. How a paramecium's cilium produces off-propulsion-plane curvature during its return stroke for symmetry breaking and drag reduction is not known. We explain these cilium deformations by developing a torsional pendulum model of beat frequency dependence on viscosity and an olivo-cerebellar model of self-regulation of posture control. The phase dependence of cilia torsion is determined, and a bio-physical model of hardness control with predictive features is offered. Crossbridge links between the central microtubule pair harden the cilium during the power stroke; this stroke's end is a critical phase during which ATP molecules soften the crossbridge-microtubule attachment at the cilium inflection point where torsion is at its maximum. A precipitous reduction in hardness ensues, signaling the start of ATP hydrolysis that re-hardens the cilium. The cilium attractor basin could be used as reference for perturbation sensing.

  7. Optical system design and experimental evaluation of a coherent Doppler wind Lidar system for the predictive control of wind turbine

    NASA Astrophysics Data System (ADS)

    Shinohara, Leilei; Tauscher, Julian Asche; Beuth, Thorsten; Heussner, Nico; Fox, Maik; Babu, Harsha Umesh; Stork, Wilhelm

    2014-09-01

    The control of wind turbine blade pitch systems by Lidar assisted wind speed prediction has been proposed to increase the electric power generation and reduce the mechanical fatigue load on wind turbines. However, the sticking point of such Lidar systems is the price. Hence, our objective is to develop a more cost efficient Lidar system to support the pitch control of horizontal axis wind turbines and therefore to reduce the material requirement, lower the operation and maintenance costs and decrease the cost of wind energy in the long term. Compared to the state of the art Lidar systems, a laser with a shorter coherence length and a corresponding fiber delay line is introduced for reducing the costs. In this paper we present the experimental evaluation of different sending and receiving optics designs for such a system from a free space laboratory setup.

  8. Energy-Efficient Control with Harvesting Predictions for Solar-Powered Wireless Sensor Networks.

    PubMed

    Zou, Tengyue; Lin, Shouying; Feng, Qijie; Chen, Yanlian

    2016-01-01

    Wireless sensor networks equipped with rechargeable batteries are useful for outdoor environmental monitoring. However, the severe energy constraints of the sensor nodes present major challenges for long-term applications. To achieve sustainability, solar cells can be used to acquire energy from the environment. Unfortunately, the energy supplied by the harvesting system is generally intermittent and considerably influenced by the weather. To improve the energy efficiency and extend the lifetime of the networks, we propose algorithms for harvested energy prediction using environmental shadow detection. Thus, the sensor nodes can adjust their scheduling plans accordingly to best suit their energy production and residual battery levels. Furthermore, we introduce clustering and routing selection methods to optimize the data transmission, and a Bayesian network is used for warning notifications of bottlenecks along the path. The entire system is implemented on a real-time Texas Instruments CC2530 embedded platform, and the experimental results indicate that these mechanisms sustain the networks' activities in an uninterrupted and efficient manner. PMID:26742042

  9. Energy-Efficient Control with Harvesting Predictions for Solar-Powered Wireless Sensor Networks

    PubMed Central

    Zou, Tengyue; Lin, Shouying; Feng, Qijie; Chen, Yanlian

    2016-01-01

    Wireless sensor networks equipped with rechargeable batteries are useful for outdoor environmental monitoring. However, the severe energy constraints of the sensor nodes present major challenges for long-term applications. To achieve sustainability, solar cells can be used to acquire energy from the environment. Unfortunately, the energy supplied by the harvesting system is generally intermittent and considerably influenced by the weather. To improve the energy efficiency and extend the lifetime of the networks, we propose algorithms for harvested energy prediction using environmental shadow detection. Thus, the sensor nodes can adjust their scheduling plans accordingly to best suit their energy production and residual battery levels. Furthermore, we introduce clustering and routing selection methods to optimize the data transmission, and a Bayesian network is used for warning notifications of bottlenecks along the path. The entire system is implemented on a real-time Texas Instruments CC2530 embedded platform, and the experimental results indicate that these mechanisms sustain the networks’ activities in an uninterrupted and efficient manner. PMID:26742042

  10. Age at diagnosis predicts deterioration in glycaemic control among children and adolescents with type 1 diabetes

    PubMed Central

    Clements, Mark A; Lind, Marcus; Raman, Sripriya; Patton, Susana R; Lipska, Kasia J; Fridlington, Amanda G; Tang, Fengming; Jones, Phil G; Wu, Yue; Spertus, John A; Kosiborod, Mikhail

    2014-01-01

    Background Poor glycemic control early in the course of type 1 diabetes mellitus (T1DM) increases the risk for microvascular complications. However, predictors of deteriorating control after diagnosis have not been described, making it difficult to identify high-risk patients and proactively provide aggressive interventions. Objective We examined whether diagnostic age, gender, and race were associated with deteriorating glycemic control during the first 5 years after diagnosis. Participants 2218 pediatric patients with T1DM. Methods We conducted a longitudinal cohort study of pediatric patients with T1DM from the Midwest USA, 1993–2009, evaluating within-patient glycated hemoglobin (HbA1c) trajectories constructed from all available HbA1c values within 5 years of diagnosis. Results 52.6% of patients were male; 86.1% were non-Hispanic Caucasian. The mean diagnostic age was 9.0±4.1 years. The mean number of HbA1c values/year/participant was 2.4±0.9. HbA1c trajectories differed markedly across age groups, with older patients experiencing greater deterioration than their younger counterparts (p<0.001). HbA1c trajectories, stratified by age, varied markedly by race (p for race×diagnostic age <0.001). Non-Hispanic African-American patients experienced higher initial HbA1c (8.7% vs 7.6% (71.6 vs 59.6 mmol/mol); p<0.001), and greater deterioration in HbA1c than non-Hispanic Caucasian patients across diagnostic ages (rise of 2.04% vs 0.99% per year (22.3 vs 10.8 mmol/mol/year); p<0.0001). Conclusions Older diagnostic age and black race are major risk factors for deterioration in glycemic control early in the course of T1DM. These findings can inform efforts to explore the reasons behind these differences and develop preventive interventions for high-risk patients. PMID:25452876

  11. Chance-constrained model predictive control applied to inventory management in hospitalary pharmacy.

    PubMed

    Maestre, Jose Maria; Ocampo-Martinez, Carlos

    2014-01-01

    This extended abstract addresses the preliminary results of applying uncertainty handling strategies and advanced control techniques to the inventary management of hospitality pharmacy. Inventory management is one of the main tasks that a pharmacy department has to carry out in a hospital. It is a complex problem because it requires to establish a tradeoff between contradictory optimization criteria. The final goal of the proposed research is to update the inventory management system of hospitals such that it is possible to reduce the average inventory while maintaining preestablished clinical guarantees. PMID:25488247

  12. Progress in analytical methods to predict and control azimuthal combustion instability modes in annular chambers

    NASA Astrophysics Data System (ADS)

    Bauerheim, M.; Nicoud, F.; Poinsot, T.

    2016-02-01

    Longitudinal low-frequency thermoacoustic unstable modes in combustion chambers have been intensively studied experimentally, numerically, and theoretically, leading to significant progress in both understanding and controlling these acoustic modes. However, modern annular gas turbines may also exhibit azimuthal modes, which are much less studied and feature specific mode structures and dynamic behaviors, leading to more complex situations. Moreover, dealing with 10-20 burners mounted in the same chamber limits the use of high fidelity simulations or annular experiments to investigate these modes because of their complexity and costs. Consequently, for such circumferential acoustic modes, theoretical tools have been developed to uncover underlying phenomena controlling their stability, nature, and dynamics. This review presents recent progress in this field. First, Galerkin and network models are described with their pros and cons in both the temporal and frequency framework. Then, key features of such acoustic modes are unveiled, focusing on their specificities such as symmetry breaking, non-linear modal coupling, forcing by turbulence. Finally, recent works on uncertainty quantifications, guided by theoretical studies and applied to annular combustors, are presented. The objective is to provide a global view of theoretical research on azimuthal modes to highlight their complexities and potential.

  13. Predicted Performance of On-Off Systems for Precise Satellite Attitude Control

    NASA Technical Reports Server (NTRS)

    Brown, Stuart C.

    1961-01-01

    An investigation has been made of the use of on-off reaction jets for precision attitude control of a satellite. Since a symmetrical vehicle is assumed, only single-axis control needs to be considered. The responses to initial disturbances and also limit-cycle characteristics for several systems have been evaluated. Calculated results indicate that realistic values of settling time and fuel consumption for the example considered can be obtained. The performance of a given system depends on the characteristics of the error detector used. In cases where the detector output was saturated for a relatively low error input, the settling time deteriorated when a lead network was used to provide damping. This deterioration could be eliminated if a separate rate signal to produce vehicle rate limiting were available. As an alternate approach, two systems were investigated which used a timed sequence of torques and could operate with a detector output of very small linear range. Although the performance of these systems was poorer than that of the lead network system without detector saturation, the performance was better than that of the lead network system with low values of detector saturation. The effects on limit-cycle characteristics of hysteresis, lead network constants, dead zone, and thrust time delays were also investigated.

  14. Prevalence and predictive factors of osteoporosis in systemic sclerosis patients: a case-control study

    PubMed Central

    Marot, Mathilde; Valéry, Antoine; Esteve, Eric; Bens, Guido; Müller, Adelheid; Rist, Stéphanie; Toumi, Hechmi; Lespessailles, Eric

    2015-01-01

    Purpose Investigate the prevalence of osteoporosis in patients with systemic sclerosis (SSc) and describe alterations of bone tissue with High-Resolution peripheral Quantitative Computed Tomography (HR-pQCT). Methods Thirty-three patients and 33 controls matched on age, body mass index (BMI) and menopause were included. Bone mineral density (BMD) was measured at the lumbar spine (LS), femoral neck (FN) and total hip (TH) by dual energy X-ray absorptiometry. Volumetric BMD (vBMD) and bone microarchitecture were measured by HR-pQCT at tibia and radius. Results In patients, BMI was significantly lower, the prevalence of osteoporosis was significantly higher and HR-pQCT analysis showed a significant alteration of the trabecular compartment with a decrease in trabecular vBMD on both sites than in controls. In multivariate analysis, a low lean body mass, presence of anticentromere antibodies and older age were identified as independent factors for decreased BMD at LS (r²=0.43), FN (r²=0.61) and TH (r²=0.73). History or current digital ulcers were also identified as an independent factor for microarchitecture alteration. Conclusion In patients an increased prevalence of osteoporosis was found and HR-pQCT showed impaired trabecular bone compartment. Also, low lean body mass, high age, digital ulcers and ACAs were identified as independent risk factors for bone damage. PMID:25944694

  15. Model predictive control of two-step nitrification and its validation via short-cut nitrification tests.

    PubMed

    Sui, Jun; Luo, Fan; Li, Jie

    2016-10-01

    Short-cut nitrification (SCN) is shown to be an attractive technology due to its savings in aeration and external carbon source addition cost. However, the shortage of excluding nitrite nitrogen as a model state in an Activated Sludge Model limits the model predictive control of biological nitrogen removal via SCN. In this paper, a two-step kinetic model was developed based on the introduction of pH and temperature as process controller, and it was implemented in an SBR reactor. The simulation results for optimizing operating conditions showed that with increasing of dissolved oxygen (DO) the rate of ammonia oxidation and nitrite accumulation firstly increased in order to achieve a SCN process. By further increasing DO, the SCN process can be transformed into a complete nitrification process. In addition, within a certain range, increasing sludge retention time and aeration time are beneficial to the accumulation of nitrite. The implementation results in the SBR reactor showed that the data predicted by the kinetic model are in agreement with the data obtained, which indicate that the two-step kinetic model is appropriate to simulate the ammonia removal and nitrite production kinetics. PMID:26901147

  16. Direct Methods for Predicting Movement Biomechanics Based Upon Optimal Control Theory with Implementation in OpenSim.

    PubMed

    Porsa, Sina; Lin, Yi-Chung; Pandy, Marcus G

    2016-08-01

    The aim of this study was to compare the computational performances of two direct methods for solving large-scale, nonlinear, optimal control problems in human movement. Direct shooting and direct collocation were implemented on an 8-segment, 48-muscle model of the body (24 muscles on each side) to compute the optimal control solution for maximum-height jumping. Both algorithms were executed on a freely-available musculoskeletal modeling platform called OpenSim. Direct collocation converged to essentially the same optimal solution up to 249 times faster than direct shooting when the same initial guess was assumed (3.4 h of CPU time for direct collocation vs. 35.3 days for direct shooting). The model predictions were in good agreement with the time histories of joint angles, ground reaction forces and muscle activation patterns measured for subjects jumping to their maximum achievable heights. Both methods converged to essentially the same solution when started from the same initial guess, but computation time was sensitive to the initial guess assumed. Direct collocation demonstrates exceptional computational performance and is well suited to performing predictive simulations of movement using large-scale musculoskeletal models. PMID:26715209

  17. Prediction of 7-year psychopathology from mother-infant joint attention behaviours: a nested case–control study

    PubMed Central

    2013-01-01

    Background To investigate whether later diagnosis of psychiatric disorder can be predicted from analysis of mother-infant joint attention (JA) behaviours in social-communicative interaction at 12 months. Method Using data from a large contemporary birth cohort, we examined 159 videos of a mother-infant interaction for joint attention behaviour when children were aged one year, sampled from within the Avon Longitudinal Study of Parents and Children (ALSPAC) cohort. Fifty-three of the videos involved infants who were later considered to have a psychiatric disorder at seven years and 106 were same aged controls. Psychopathologies included in the case group were disruptive behaviour disorders, oppositional-conduct disorder, attention-deficit/hyperactivity disorder, pervasive development disorder, anxiety and depressive disorders. Psychiatric diagnoses were obtained using the Development and Wellbeing Assessment when the children were seven years old. Results None of the three JA behaviours (shared look rate, shared attention rate and shared attention intensity) showed a significant association with the primary outcome of case–control status. Only shared look rate predicted any of the exploratory sub-diagnosis outcomes and was found to be positively associated with later oppositional-conduct disorders (OR [95% CI]: 1.5 [1.0, 2.3]; p = 0.041). Conclusions JA behaviours did not, in general, predict later psychopathology. However, shared look was positively associated with later oppositional-conduct disorders. This suggests that some features of JA may be early markers of later psychopathology. Further investigation will be required to determine whether any JA behaviours can be used to screen for families in need of intervention. PMID:24063312

  18. The influence of the local effect model parameters on the prediction of the tumor control probability for prostate cancer

    NASA Astrophysics Data System (ADS)

    Chanrion, M.-A.; Sauerwein, W.; Jelen, U.; Wittig, A.; Engenhart-Cabillic, R.; Beuve, M.

    2014-06-01

    In carbon ion beams, biological effects vary along the ion track; hence, to quantify them, specific radiobiological models are needed. One of them, the local effect model (LEM), in particular version I (LEM I), is implemented in treatment planning systems (TPS) clinically used in European particle therapy centers. From the physical properties of the specific ion radiation, the LEM calculates the survival probabilities of the cell or tissue type under study, provided that some determinant input parameters are initially defined. Mathematical models can be used to predict, for instance, the tumor control probability (TCP), and then evaluate treatment outcomes. This work studies the influence of the LEM I input parameters on the TCP predictions in the specific case of prostate cancer. Several published input parameters and their combinations were tested. Their influence on the dose distributions calculated for a water phantom and for a patient geometry was evaluated using the TPS TRiP98. Changing input parameters induced clinically significant modifications of the mean dose (up to a factor of 3.5), spatial dose distribution, and TCP predictions (up to factor of 2.6 for D50). TCP predictions were found to be more sensitive to the parameter threshold dose (Dt) than to the biological parameters α and β. Additionally, an analytical expression was derived for correlating α, β and Dt, and this has emphasized the importance of \\frac{D_t}{\\alpha /\\beta }. The improvement of radiobiological models for particle TPS will only be achieved when more patient outcome data with well-defined patient groups, fractionation schemes and well-defined end-points are available.

  19. Channel-Reach Morphology in Formerly Glaciated, Mountain Streams: Controls and Prediction

    NASA Astrophysics Data System (ADS)

    Hassan, M. A.; Brardinoni, F.

    2006-12-01

    The spatial distribution of channel types in mountain drainage basins of coastal British Columbia is examined. Using field- and GIS-based data we show that the local channel slope and degree of colluvial-alluvial coupling imposed by the glacial valley morphology dictate the spatial organization of channel-reach morphology. In particular, the glacially-induced channel long profile generates characteristic sequences of channel reaches (with repetitions and inversions) that depart from the downstream succession distinctive of unglaciated mountain streams. For example, the presence of one hanging valley in the river long profile produces and separates two full successions of channel types a headmost one characterized by an ephemeral/seasonal hydrologic regime, and a downstream one, where water runoff is perennial. Exploratory scatter plots indicate that slope, shear stress, and relative roughness ensure best separation between reach types. At a confirmatory level, highest prediction of channel types is achieved by discriminant functions containing the same three variates. Success rates, depending on whether or not boulder-cascade reaches are grouped with step-pools, vary between 89% and 76%. Notwithstanding the glacially-inherited slope and the transient geomorphic dynamics of this landscape, similar to the case of unglaciated mountain streams, channel types are chiefly segregated by local slope (albeit characterized by significantly higher ranges), and to a lesser extent by shear stress and relative roughness. This outcome, while adding considerable strength to prior empirical knowledge, indicates that first-order physical conditions at which distinct channel states form are insensitive to very different landscape structures, hence histories.

  20. Environmental changes impacting Echinococcus transmission: research to support predictive surveillance and control.

    PubMed

    Atkinson, Jo-An M; Gray, Darren J; Clements, Archie C A; Barnes, Tamsin S; McManus, Donald P; Yang, Yu R

    2013-03-01

    Echinococcosis, resulting from infection with tapeworms Echinococcus granulosus and E. multilocularis, has a global distribution with 2-3 million people affected and 200,000 new cases diagnosed annually. Costs of treatment for humans and economic losses to the livestock industry have been estimated to exceed $2 billion. These figures are likely to be an underestimation given the challenges with its early detection and the lack of mandatory official reporting policies in most countries. Despite this global burden, echinococcosis remains a neglected zoonosis. The importance of environmental factors in influencing the transmission intensity and distribution of Echinococcus spp. is increasingly being recognized. With the advent of climate change and the influence of global population expansion, food insecurity and land-use changes, questions about the potential impact of changing temperature, rainfall patterns, increasing urbanization, deforestation, grassland degradation and overgrazing on zoonotic disease transmission are being raised. This study is the first to comprehensively review how climate change and anthropogenic environmental factors contribute to the transmission of echinococcosis mediated by changes in animal population dynamics, spatial overlap of competent hosts and the creation of improved conditions for egg survival. We advocate rigorous scientific research to establish the causal link between specific environmental variables and echinococcosis in humans and the incorporation of environmental, animal and human data collection within a sentinel site surveillance network that will complement satellite remote-sensing information. Identifying the environmental determinants of transmission risk to humans will be vital for the design of more accurate predictive models to guide cost-effective pre-emptive public health action against echinococcosis. PMID:23504826