Minimum flow unit installation at the South Edwards Hydro Plant

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bernhardt, P.; Bates, D.

1995-12-31

Niagara Mohawk Power Corp. owns and operates the 3.3 MW South Edwards Hydro Plant in Northern New York. The FERC license for this plant requires a minimum flow release in the bypass region of the river. NMPC submitted a license amendment to the FERC to permit the addition of a minimum flow unit to take advantage of this flow. The amendment was accepted, permitting the installation of the 236 kw, 60 cfs unit to proceed. The unit was installed and commissioned in 1994.

Exploratory Investigation of Early Biomarkers for Chronic Fatigue in Prostate Cancer Patients Following Radiation Therapy

PubMed Central

Feng, Li Rebekah; Wolff, Brian S.; Lukkahatai, Nada; Espina, Alexandra; Saligan, Leorey N.

2016-01-01

Background Fatigue is one of the most debilitating side effects of cancer therapy. Identifying biomarkers early during cancer therapy may help us understand the biologic underpinnings of the persistence of fatigue following therapy. Objective We aimed to identify early biomarkers of fatigue by examining correlations of levels of cytokines during external beam radiation therapy (EBRT) with persistence of fatigue one year following treatment completion in men with non-metastatic prostate cancer (NM-PC). Methods A sample of 34 men with NM-PC scheduled to receive EBRT were followed at baseline (T1), midpoint of EBRT (T2), and one year following EBRT (T3). Demographic and clinical data were obtained by chart review. The Functional Assessment of Cancer Therapy-Fatigue (FACT-F) was administered to measure fatigue levels. Plasma cytokine levels were determined at T1 and T2 using the Bio-Rad Bio-Plex Cytokine Assay Kits. Results Significant correlations were observed between levels of IL-3, IL-8, IL-9, IL-10, IL-16, IP10, IFNα2, IFNγ, and SDF1α at T2 with worsening of fatigue from T1 to T3. Conclusions Immunological changes prior to chronic fatigue development may reflect the long term response to radiation therapy-induced damage. Implications for Practice Early biomarkers for chronic fatigue related to cancer therapy will help advance our understanding of the etiology of this distressing symptom and will help nurses identify patients at risk for developing chronic fatigue after cancer treatment. This information will also aide in patient education, as well as symptom management. PMID:27105468

Biomass power for rural development. Technical progress report, July 1--September 30, 1997

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neuhauser, E.

The focus of the DOE/USDA sponsored biomass power for rural development project is to develop commercial energy crops for power generation by the year 2000. The New York based Salix Consortium project is a multi-partner endeavor, implemented in three stages. Phase-1, Final Design and Project Development, will conclude with the preparation of construction and/or operating permits, feedstock production plans, and contracts ready for signature. Field trials of willow (Salix) have been initiated at several locations in New York (Tully, Lockport, King Ferry, La Fayette, Massena, and Himrod) and co-firing tests are underway at Greenidge Station (NYSEG) and Dunkirk Station (NMPC).more » Phase-2 of the project will focus on scale-up of willow crop acreage, construction of co-firing facilities at Dunkirk Station (NMPC), and final modifications for Greenidge Station. Cofiring willow is also under consideration for GPU`s Seward Station where testing is underway. There will be an evaluation of the energy crop as part of the gasification trials occurring at BED`s McNeill power station. Phase-3 will represent fullscale commercialization of the energy crop and power generation on a sustainable basis. During the third quarter of 1997, much of the Consortium`s effort has focused on outreach activities, continued feedstock development, fuel supply planning, and fuel contract development, and preparation for 1998 scale-up activities. The Consortium also submitted a Phase-1 extension proposal during this period. A few of the more important milestones are outlined below. The fourth quarter of 1997 is expected to be dominated by Phase-II proposal efforts and planning for 1998 activities.« less

Olympic Village thermal energy storage experiment. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fernandes, R.A.; Saylor, C.M.

Four thermal energy storage (TES) systems were operated in identical dormitory-style buildings of the Raybrook Correctional Facility, formerly the housing for the athletes at the 1980 Winter Olympic Games in Lake Placid, New York. The objectives of the project were to assess the ability of these TES systems to be controlled so as to modify load profiles favorably, and to assess the ability to maintain comfortable indoor conditions under those control strategies. Accordingly, the test was designed to evaluate the effect on load profiles of appropriate control algorithms for the TES systems, collect comprehensive TES operating data, and identify neededmore » research and development to improve the effectiveness of the TES systems. The four similar dormitory buildings were used to compare electric slab heating on grade, ceramic brick storage heating, pressurized-hot-water heating, and heat pumps with hot-water storage. In a fifth similar building, a conventional (non-TES) forced air electric resistance heat system was used. The four buildings with TES systems also had electric resistance heating for backup. A remote computer-based monitoring and control system was used to implement the control algorithms and to collect data from the site. For a 25% TES saturation of electric heat customers on the NMPC system, production costs were reduced by up to $2,235,000 for the New York Power Pool. The winter peak load was reduced by up to 223 MW. The control schedules developed were successful in reducing on-peak energy consumption while maintaining indoor conditions as close to the comfort level as possible considering the test environment.« less

Some Like It Hot: Heat Resistance of Escherichia coli in Food

PubMed Central

Li, Hui; Gänzle, Michael

2016-01-01

Heat treatment and cooking are common interventions for reducing the numbers of vegetative cells and eliminating pathogenic microorganisms in food. Current cooking method requires the internal temperature of beef patties to reach 71°C. However, some pathogenic Escherichia coli such as the beef isolate E. coli AW 1.7 are extremely heat resistant, questioning its inactivation by current heat interventions in beef processing. To optimize the conditions of heat treatment for effective decontaminations of pathogenic E. coli strains, sufficient estimations, and explanations are necessary on mechanisms of heat resistance of target strains. The heat resistance of E. coli depends on the variability of strains and properties of food formulations including salt and water activity. Heat induces alterations of E. coli cells including membrane, cytoplasm, ribosome and DNA, particularly on proteins including protein misfolding and aggregations. Resistant systems of E. coli act against these alterations, mainly through gene regulations of heat response including EvgA, heat shock proteins, σE and σS, to re-fold of misfolded proteins, and achieve antagonism to heat stress. Heat resistance can also be increased by expression of key proteins of membrane and stabilization of membrane fluidity. In addition to the contributions of the outer membrane porin NmpC and overcome of osmotic stress from compatible solutes, the new identified genomic island locus of heat resistant performs a critical role to these highly heat resistant strains. This review aims to provide an overview of current knowledge on heat resistance of E. coli, to better understand its related mechanisms and explore more effective applications of heat interventions in food industry. PMID:27857712

Biomass power for rural development. Technical progress report, May 1, 1996--December 31, 1996

DOE Office of Scientific and Technical Information (OSTI.GOV)

Neuhauser, E.

Developing commercial energy crops for power generation by the year 2000 is the focus of the DOE/USDA sponsored Biomass Power for Rural Development project. The New York based Salix Consortium project is a multi-partner endeavor, implemented in three stages. Phase-I, Final Design and Project Development, will conclude with the preparation of construction and/or operating permits, feedstock production plans, and contracts ready for signature. Field trials of willow (Salix) have been initiated at several locations in New York (Tully, Lockport, King Ferry, La Facette, Massena, and Himrod) and co-firing tests are underway at Greenidge Station (NYSEG). Phase-II of the project willmore » focus on scale-up of willow crop acreage, construction of co-firing facilities at Dunkirk Station (NMPC), and final modifications for Greenidge Station. There will be testing of the energy crop as part of the gasification trials expected to occur at BED`s McNeill power station and potentially at one of GPU`s facilities. Phase-III will represent full-scale commercialization of the energy crop and power generation on a sustainable basis. Willow has been selected as the energy crop of choice for many reasons. Willow is well suited to the climate of the Northeastern United States, and initial field trials have demonstrated that the yields required for the success of the project are obtainable. Like other energy crops, willow has rural development benefits and could serve to diversify local crop production, provide new sources of income for participating growers, and create new jobs. Willow could be used to put a large base of idle acreage back into crop production. Additionally, the willow coppicing system integrates well with current farm operations and utilizes agricultural practices that are already familiar to farmers.« less

Simulation analysis of adaptive cruise prediction control

NASA Astrophysics Data System (ADS)

Zhang, Li; Cui, Sheng Min

2017-09-01

Predictive control is suitable for multi-variable and multi-constraint system control.In order to discuss the effect of predictive control on the vehicle longitudinal motion, this paper establishes the expected spacing model by combining variable pitch spacing and the of safety distance strategy. The model predictive control theory and the optimization method based on secondary planning are designed to obtain and track the best expected acceleration trajectory quickly. Simulation models are established including predictive and adaptive fuzzy control. Simulation results show that predictive control can realize the basic function of the system while ensuring the safety. The application of predictive and fuzzy adaptive algorithm in cruise condition indicates that the predictive control effect is better.

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.

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.

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.

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.

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.

Dynamic Simulation of Human Gait Model With Predictive Capability.

PubMed

Sun, Jinming; Wu, Shaoli; Voglewede, Philip A

2018-03-01

In this paper, it is proposed that the central nervous system (CNS) controls human gait using a predictive control approach in conjunction with classical feedback control instead of exclusive classical feedback control theory that controls based on past error. To validate this proposition, a dynamic model of human gait is developed using a novel predictive approach to investigate the principles of the CNS. The model developed includes two parts: a plant model that represents the dynamics of human gait and a controller that represents the CNS. The plant model is a seven-segment, six-joint model that has nine degrees-of-freedom (DOF). The plant model is validated using data collected from able-bodied human subjects. The proposed controller utilizes model predictive control (MPC). MPC uses an internal model to predict the output in advance, compare the predicted output to the reference, and optimize the control input so that the predicted error is minimal. To decrease the complexity of the model, two joints are controlled using a proportional-derivative (PD) controller. The developed predictive human gait model is validated by simulating able-bodied human gait. The simulation results show that the developed model is able to simulate the kinematic output close to experimental data.

Finite element based model predictive control for active vibration suppression of a one-link flexible manipulator.

PubMed

Dubay, Rickey; Hassan, Marwan; Li, Chunying; Charest, Meaghan

2014-09-01

This paper presents a unique approach for active vibration control of a one-link flexible manipulator. The method combines a finite element model of the manipulator and an advanced model predictive controller to suppress vibration at its tip. This hybrid methodology improves significantly over the standard application of a predictive controller for vibration control. The finite element model used in place of standard modelling in the control algorithm provides a more accurate prediction of dynamic behavior, resulting in enhanced control. Closed loop control experiments were performed using the flexible manipulator, instrumented with strain gauges and piezoelectric actuators. In all instances, experimental and simulation results demonstrate that the finite element based predictive controller provides improved active vibration suppression in comparison with using a standard predictive control strategy. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

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.

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.

Effect of accuracy of wind power prediction on power system operator

NASA Technical Reports Server (NTRS)

Schlueter, R. A.; Sigari, G.; Costi, T.

1985-01-01

This research project proposed a modified unit commitment that schedules connection and disconnection of generating units in response to load. A modified generation control is also proposed that controls steam units under automatic generation control, fast responding diesels, gas turbines and hydro units under a feedforward control, and wind turbine array output under a closed loop array control. This modified generation control and unit commitment require prediction of trend wind power variation one hour ahead and the prediction of error in this trend wind power prediction one half hour ahead. An improved meter for predicting trend wind speed variation is developed. Methods for accurately simulating the wind array power from a limited number of wind speed prediction records was developed. Finally, two methods for predicting the error in the trend wind power prediction were developed. This research provides a foundation for testing and evaluating the modified unit commitment and generation control that was developed to maintain operating reliability at a greatly reduced overall production cost for utilities with wind generation capacity.

Predictive Control of Networked Multiagent Systems via Cloud Computing.

PubMed

Liu, Guo-Ping

2017-01-18

This paper studies the design and analysis of networked multiagent predictive control systems via cloud computing. A cloud predictive control scheme for networked multiagent systems (NMASs) is proposed to achieve consensus and stability simultaneously and to compensate for network delays actively. The design of the cloud predictive controller for NMASs is detailed. The analysis of the cloud predictive control scheme gives the necessary and sufficient conditions of stability and consensus of closed-loop networked multiagent control systems. The proposed scheme is verified to characterize the dynamical behavior and control performance of NMASs through simulations. The outcome provides a foundation for the development of cooperative and coordinative control of NMASs and its applications.

A Hierarchical Model Predictive Tracking Control for Independent Four-Wheel Driving/Steering Vehicles with Coaxial Steering Mechanism

NASA Astrophysics Data System (ADS)

Itoh, Masato; Hagimori, Yuki; Nonaka, Kenichiro; Sekiguchi, Kazuma

2016-09-01

In this study, we apply a hierarchical model predictive control to omni-directional mobile vehicle, and improve the tracking performance. We deal with an independent four-wheel driving/steering vehicle (IFWDS) equipped with four coaxial steering mechanisms (CSM). The coaxial steering mechanism is a special one composed of two steering joints on the same axis. In our previous study with respect to IFWDS with ideal steering, we proposed a model predictive tracking control. However, this method did not consider constraints of the coaxial steering mechanism which causes delay of steering. We also proposed a model predictive steering control considering constraints of this mechanism. In this study, we propose a hierarchical system combining above two control methods for IFWDS. An upper controller, which deals with vehicle kinematics, runs a model predictive tracking control, and a lower controller, which considers constraints of coaxial steering mechanism, runs a model predictive steering control which tracks the predicted steering angle optimized an upper controller. We verify the superiority of this method by comparing this method with the previous method.

Concurrent and longitudinal associations of peers' acceptance with emotion and effortful control in kindergarten

PubMed Central

Hernández, Maciel M.; Eisenberg, Nancy; Valiente, Carlos; Diaz, Anjolii; VanSchyndel, Sarah K.; Berger, Rebecca H.; Terrell, Nathan; Silva, Kassondra M.; Spinrad, Tracy L.; Southworth, Jody

2015-01-01

The purpose of the study was to evaluate bidirectional associations between peer acceptance and both emotion and effortful control during kindergarten (N = 301). In both the fall and spring semesters, we obtained peer nominations of acceptance, measures of positive and negative emotion based on naturalistic observations in school (i.e., classroom, lunch/recess), and observers’ reports of effortful control (i.e., inhibitory control, attention focusing) and emotions (i.e., positive, negative). In structural equation panel models, peer acceptance in fall predicted higher effortful control in spring. Effortful control in fall did not predict peer acceptance in spring. Negative emotion predicted lower peer acceptance across time for girls but not for boys. Peer acceptance did not predict negative or positive emotion over time. In addition, we tested interactions between positive or negative emotion and effortful control predicting peer acceptance. Positive emotion predicted higher peer acceptance for children low in effortful control. PMID:28348445

A system identification approach for developing model predictive controllers of antibody quality attributes in cell culture processes

PubMed Central

Schmitt, John; Beller, Justin; Russell, Brian; Quach, Anthony; Hermann, Elizabeth; Lyon, David; Breit, Jeffrey

2017-01-01

As the biopharmaceutical industry evolves to include more diverse protein formats and processes, more robust control of Critical Quality Attributes (CQAs) is needed to maintain processing flexibility without compromising quality. Active control of CQAs has been demonstrated using model predictive control techniques, which allow development of processes which are robust against disturbances associated with raw material variability and other potentially flexible operating conditions. Wide adoption of model predictive control in biopharmaceutical cell culture processes has been hampered, however, in part due to the large amount of data and expertise required to make a predictive model of controlled CQAs, a requirement for model predictive control. Here we developed a highly automated, perfusion apparatus to systematically and efficiently generate predictive models using application of system identification approaches. We successfully created a predictive model of %galactosylation using data obtained by manipulating galactose concentration in the perfusion apparatus in serialized step change experiments. We then demonstrated the use of the model in a model predictive controller in a simulated control scenario to successfully achieve a %galactosylation set point in a simulated fed‐batch culture. The automated model identification approach demonstrated here can potentially be generalized to many CQAs, and could be a more efficient, faster, and highly automated alternative to batch experiments for developing predictive models in cell culture processes, and allow the wider adoption of model predictive control in biopharmaceutical processes. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:1647–1661, 2017 PMID:28786215

Sustained sensorimotor control as intermittent decisions about prediction errors: computational framework and application to ground vehicle steering.

PubMed

Markkula, Gustav; Boer, Erwin; Romano, Richard; Merat, Natasha

2018-06-01

A conceptual and computational framework is proposed for modelling of human sensorimotor control and is exemplified for the sensorimotor task of steering a car. The framework emphasises control intermittency and extends on existing models by suggesting that the nervous system implements intermittent control using a combination of (1) motor primitives, (2) prediction of sensory outcomes of motor actions, and (3) evidence accumulation of prediction errors. It is shown that approximate but useful sensory predictions in the intermittent control context can be constructed without detailed forward models, as a superposition of simple prediction primitives, resembling neurobiologically observed corollary discharges. The proposed mathematical framework allows straightforward extension to intermittent behaviour from existing one-dimensional continuous models in the linear control and ecological psychology traditions. Empirical data from a driving simulator are used in model-fitting analyses to test some of the framework's main theoretical predictions: it is shown that human steering control, in routine lane-keeping and in a demanding near-limit task, is better described as a sequence of discrete stepwise control adjustments, than as continuous control. Results on the possible roles of sensory prediction in control adjustment amplitudes, and of evidence accumulation mechanisms in control onset timing, show trends that match the theoretical predictions; these warrant further investigation. The results for the accumulation-based model align with other recent literature, in a possibly converging case against the type of threshold mechanisms that are often assumed in existing models of intermittent control.

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.

Muscle Synergies May Improve Optimization Prediction of Knee Contact Forces During Walking

PubMed Central

Walter, Jonathan P.; Kinney, Allison L.; Banks, Scott A.; D'Lima, Darryl D.; Besier, Thor F.; Lloyd, David G.; Fregly, Benjamin J.

2014-01-01

The ability to predict patient-specific joint contact and muscle forces accurately could improve the treatment of walking-related disorders. Muscle synergy analysis, which decomposes a large number of muscle electromyographic (EMG) signals into a small number of synergy control signals, could reduce the dimensionality and thus redundancy of the muscle and contact force prediction process. This study investigated whether use of subject-specific synergy controls can improve optimization prediction of knee contact forces during walking. To generate the predictions, we performed mixed dynamic muscle force optimizations (i.e., inverse skeletal dynamics with forward muscle activation and contraction dynamics) using data collected from a subject implanted with a force-measuring knee replacement. Twelve optimization problems (three cases with four subcases each) that minimized the sum of squares of muscle excitations were formulated to investigate how synergy controls affect knee contact force predictions. The three cases were: (1) Calibrate+Match where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously matched, (2) Precalibrate+Predict where experimental knee contact forces were predicted using precalibrated muscle model parameters values from the first case, and (3) Calibrate+Predict where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously predicted, all while matching inverse dynamic loads at the hip, knee, and ankle. The four subcases used either 44 independent controls or five synergy controls with and without EMG shape tracking. For the Calibrate+Match case, all four subcases closely reproduced the measured medial and lateral knee contact forces (R2 ≥ 0.94, root-mean-square (RMS) error < 66 N), indicating sufficient model fidelity for contact force prediction. For the Precalibrate+Predict and Calibrate+Predict cases, synergy controls yielded better contact force predictions (0.61 < R2 < 0.90, 83 N < RMS error < 161 N) than did independent controls (-0.15 < R2 < 0.79, 124 N < RMS error < 343 N) for corresponding subcases. For independent controls, contact force predictions improved when precalibrated model parameter values or EMG shape tracking was used. For synergy controls, contact force predictions were relatively insensitive to how model parameter values were calibrated, while EMG shape tracking made lateral (but not medial) contact force predictions worse. For the subject and optimization cost function analyzed in this study, use of subject-specific synergy controls improved the accuracy of knee contact force predictions, especially for lateral contact force when EMG shape tracking was omitted, and reduced prediction sensitivity to uncertainties in muscle model parameter values. PMID:24402438

Muscle synergies may improve optimization prediction of knee contact forces during walking.

PubMed

Walter, Jonathan P; Kinney, Allison L; Banks, Scott A; D'Lima, Darryl D; Besier, Thor F; Lloyd, David G; Fregly, Benjamin J

2014-02-01

The ability to predict patient-specific joint contact and muscle forces accurately could improve the treatment of walking-related disorders. Muscle synergy analysis, which decomposes a large number of muscle electromyographic (EMG) signals into a small number of synergy control signals, could reduce the dimensionality and thus redundancy of the muscle and contact force prediction process. This study investigated whether use of subject-specific synergy controls can improve optimization prediction of knee contact forces during walking. To generate the predictions, we performed mixed dynamic muscle force optimizations (i.e., inverse skeletal dynamics with forward muscle activation and contraction dynamics) using data collected from a subject implanted with a force-measuring knee replacement. Twelve optimization problems (three cases with four subcases each) that minimized the sum of squares of muscle excitations were formulated to investigate how synergy controls affect knee contact force predictions. The three cases were: (1) Calibrate+Match where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously matched, (2) Precalibrate+Predict where experimental knee contact forces were predicted using precalibrated muscle model parameters values from the first case, and (3) Calibrate+Predict where muscle model parameter values were calibrated and experimental knee contact forces were simultaneously predicted, all while matching inverse dynamic loads at the hip, knee, and ankle. The four subcases used either 44 independent controls or five synergy controls with and without EMG shape tracking. For the Calibrate+Match case, all four subcases closely reproduced the measured medial and lateral knee contact forces (R2 ≥ 0.94, root-mean-square (RMS) error < 66 N), indicating sufficient model fidelity for contact force prediction. For the Precalibrate+Predict and Calibrate+Predict cases, synergy controls yielded better contact force predictions (0.61 < R2 < 0.90, 83 N < RMS error < 161 N) than did independent controls (-0.15 < R2 < 0.79, 124 N < RMS error < 343 N) for corresponding subcases. For independent controls, contact force predictions improved when precalibrated model parameter values or EMG shape tracking was used. For synergy controls, contact force predictions were relatively insensitive to how model parameter values were calibrated, while EMG shape tracking made lateral (but not medial) contact force predictions worse. For the subject and optimization cost function analyzed in this study, use of subject-specific synergy controls improved the accuracy of knee contact force predictions, especially for lateral contact force when EMG shape tracking was omitted, and reduced prediction sensitivity to uncertainties in muscle model parameter values.

Predictive displays for a process-control schematic interface.

PubMed

Yin, Shanqing; Wickens, Christopher D; Helander, Martin; Laberge, Jason C

2015-02-01

Our objective was to examine the extent to which increasing precision of predictive (rate of change) information in process control will improve performance on a simulated process-control task. Predictive displays have been found to be useful in process control (as well as aviation and maritime industries). However, authors of prior research have not examined the extent to which predictive value is increased by increasing predictor resolution, nor has such research tied potential improvements to changes in process control strategy. Fifty nonprofessional participants each controlled a simulated chemical mixture process (honey mixer simulation) that simulated the operations found in process control. Participants in each of five groups controlled with either no predictor or a predictor ranging in the resolution of prediction of the process. Increasing detail resolution generally increased the benefit of prediction over the control condition although not monotonically so. The best overall performance, combining quality and predictive ability, was obtained by the display of intermediate resolution. The two displays with the lowest resolution were clearly inferior. Predictors with higher resolution are of value but may trade off enhanced sensitivity to variable change (lower-resolution discrete state predictor) with smoother control action (higher-resolution continuous predictors). The research provides guidelines to the process-control industry regarding displays that can most improve operator performance.

A system identification approach for developing model predictive controllers of antibody quality attributes in cell culture processes.

PubMed

Downey, Brandon; Schmitt, John; Beller, Justin; Russell, Brian; Quach, Anthony; Hermann, Elizabeth; Lyon, David; Breit, Jeffrey

2017-11-01

As the biopharmaceutical industry evolves to include more diverse protein formats and processes, more robust control of Critical Quality Attributes (CQAs) is needed to maintain processing flexibility without compromising quality. Active control of CQAs has been demonstrated using model predictive control techniques, which allow development of processes which are robust against disturbances associated with raw material variability and other potentially flexible operating conditions. Wide adoption of model predictive control in biopharmaceutical cell culture processes has been hampered, however, in part due to the large amount of data and expertise required to make a predictive model of controlled CQAs, a requirement for model predictive control. Here we developed a highly automated, perfusion apparatus to systematically and efficiently generate predictive models using application of system identification approaches. We successfully created a predictive model of %galactosylation using data obtained by manipulating galactose concentration in the perfusion apparatus in serialized step change experiments. We then demonstrated the use of the model in a model predictive controller in a simulated control scenario to successfully achieve a %galactosylation set point in a simulated fed-batch culture. The automated model identification approach demonstrated here can potentially be generalized to many CQAs, and could be a more efficient, faster, and highly automated alternative to batch experiments for developing predictive models in cell culture processes, and allow the wider adoption of model predictive control in biopharmaceutical processes. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers Biotechnol. Prog., 33:1647-1661, 2017. © 2017 The Authors Biotechnology Progress published by Wiley Periodicals, Inc. on behalf of American Institute of Chemical Engineers.

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.

Model predictive control for spacecraft rendezvous in elliptical orbit

NASA Astrophysics Data System (ADS)

Li, Peng; Zhu, Zheng H.

2018-05-01

This paper studies the control of spacecraft rendezvous with attitude stable or spinning targets in an elliptical orbit. The linearized Tschauner-Hempel equation is used to describe the motion of spacecraft and the problem is formulated by model predictive control. The control objective is to maximize control accuracy and smoothness simultaneously to avoid unexpected change or overshoot of trajectory for safe rendezvous. It is achieved by minimizing the weighted summations of control errors and increments. The effects of two sets of horizons (control and predictive horizons) in the model predictive control are examined in terms of fuel consumption, rendezvous time and computational effort. The numerical results show the proposed control strategy is effective.

Robust current control-based generalized predictive control with sliding mode disturbance compensation for PMSM drives.

PubMed

Liu, Xudong; Zhang, Chenghui; Li, Ke; Zhang, Qi

2017-11-01

This paper addresses the current control of permanent magnet synchronous motor (PMSM) for electric drives with model uncertainties and disturbances. A generalized predictive current control method combined with sliding mode disturbance compensation is proposed to satisfy the requirement of fast response and strong robustness. Firstly, according to the generalized predictive control (GPC) theory based on the continuous time model, a predictive current control method is presented without considering the disturbance, which is convenient to be realized in the digital controller. In fact, it's difficult to derive the exact motor model and parameters in the practical system. Thus, a sliding mode disturbance compensation controller is studied to improve the adaptiveness and robustness of the control system. The designed controller attempts to combine the merits of both predictive control and sliding mode control, meanwhile, the controller parameters are easy to be adjusted. Lastly, the proposed controller is tested on an interior PMSM by simulation and experiment, and the results indicate that it has good performance in both current tracking and disturbance rejection. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

An improved predictive functional control method with application to PMSM systems

NASA Astrophysics Data System (ADS)

Li, Shihua; Liu, Huixian; Fu, Wenshu

2017-01-01

In common design of prediction model-based control method, usually disturbances are not considered in the prediction model as well as the control design. For the control systems with large amplitude or strong disturbances, it is difficult to precisely predict the future outputs according to the conventional prediction model, and thus the desired optimal closed-loop performance will be degraded to some extent. To this end, an improved predictive functional control (PFC) method is developed in this paper by embedding disturbance information into the system model. Here, a composite prediction model is thus obtained by embedding the estimated value of disturbances, where disturbance observer (DOB) is employed to estimate the lumped disturbances. So the influence of disturbances on system is taken into account in optimisation procedure. Finally, considering the speed control problem for permanent magnet synchronous motor (PMSM) servo system, a control scheme based on the improved PFC method is designed to ensure an optimal closed-loop performance even in the presence of disturbances. Simulation and experimental results based on a hardware platform are provided to confirm the effectiveness of the proposed algorithm.

Motor prediction in Brain-Computer Interfaces for controlling mobile robots.

PubMed

Geng, Tao; Gan, John Q

2008-01-01

EEG-based Brain-Computer Interface (BCI) can be regarded as a new channel for motor control except that it does not involve muscles. Normal neuromuscular motor control has two fundamental components: (1) to control the body, and (2) to predict the consequences of the control command, which is called motor prediction. In this study, after training with a specially designed BCI paradigm based on motor imagery, two subjects learnt to predict the time course of some features of the EEG signals. It is shown that, with this newly-obtained motor prediction skill, subjects can use motor imagery of feet to directly control a mobile robot to avoid obstacles and reach a small target in a time-critical scenario.

Modeling pilot interaction with automated digital avionics systems: Guidance and control algorithms for contour and nap-of-the-Earth flight

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1990-01-01

A collection of technical papers are presented that cover modeling pilot interaction with automated digital avionics systems and guidance and control algorithms for contour and nap-of-the-earth flight. The titles of the papers presented are as follows: (1) Automation effects in a multiloop manual control system; (2) A qualitative model of human interaction with complex dynamic systems; (3) Generalized predictive control of dynamic systems; (4) An application of generalized predictive control to rotorcraft terrain-following flight; (5) Self-tuning generalized predictive control applied to terrain-following flight; and (6) Precise flight path control using a predictive algorithm.

Model predictive control of the solid oxide fuel cell stack temperature with models based on experimental data

NASA Astrophysics Data System (ADS)

Pohjoranta, Antti; Halinen, Matias; Pennanen, Jari; Kiviaho, Jari

2015-03-01

Generalized predictive control (GPC) is applied to control the maximum temperature in a solid oxide fuel cell (SOFC) stack and the temperature difference over the stack. GPC is a model predictive control method and the models utilized in this work are ARX-type (autoregressive with extra input), multiple input-multiple output, polynomial models that were identified from experimental data obtained from experiments with a complete SOFC system. The proposed control is evaluated by simulation with various input-output combinations, with and without constraints. A comparison with conventional proportional-integral-derivative (PID) control is also made. It is shown that if only the stack maximum temperature is controlled, a standard PID controller can be used to obtain output performance comparable to that obtained with the significantly more complex model predictive controller. However, in order to control the temperature difference over the stack, both the stack minimum and the maximum temperature need to be controlled and this cannot be done with a single PID controller. In such a case the model predictive controller provides a feasible and effective solution.

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.

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.

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.

On the comparison of stochastic model predictive control strategies applied to a hydrogen-based microgrid

NASA Astrophysics Data System (ADS)

Velarde, P.; Valverde, L.; Maestre, J. M.; Ocampo-Martinez, C.; Bordons, C.

2017-03-01

In this paper, a performance comparison among three well-known stochastic model predictive control approaches, namely, multi-scenario, tree-based, and chance-constrained model predictive control is presented. To this end, three predictive controllers have been designed and implemented in a real renewable-hydrogen-based microgrid. The experimental set-up includes a PEM electrolyzer, lead-acid batteries, and a PEM fuel cell as main equipment. The real experimental results show significant differences from the plant components, mainly in terms of use of energy, for each implemented technique. Effectiveness, performance, advantages, and disadvantages of these techniques are extensively discussed and analyzed to give some valid criteria when selecting an appropriate stochastic predictive controller.

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.

Model predictive control of P-time event graphs

NASA Astrophysics Data System (ADS)

Hamri, H.; Kara, R.; Amari, S.

2016-12-01

This paper deals with model predictive control of discrete event systems modelled by P-time event graphs. First, the model is obtained by using the dater evolution model written in the standard algebra. Then, for the control law, we used the finite-horizon model predictive control. For the closed-loop control, we used the infinite-horizon model predictive control (IH-MPC). The latter is an approach that calculates static feedback gains which allows the stability of the closed-loop system while respecting the constraints on the control vector. The problem of IH-MPC is formulated as a linear convex programming subject to a linear matrix inequality problem. Finally, the proposed methodology is applied to a transportation system.

Model predictive control design for polytopic uncertain systems by synthesising multi-step prediction scenarios

NASA Astrophysics Data System (ADS)

Lu, Jianbo; Xi, Yugeng; Li, Dewei; Xu, Yuli; Gan, Zhongxue

2018-01-01

A common objective of model predictive control (MPC) design is the large initial feasible region, low online computational burden as well as satisfactory control performance of the resulting algorithm. It is well known that interpolation-based MPC can achieve a favourable trade-off among these different aspects. However, the existing results are usually based on fixed prediction scenarios, which inevitably limits the performance of the obtained algorithms. So by replacing the fixed prediction scenarios with the time-varying multi-step prediction scenarios, this paper provides a new insight into improvement of the existing MPC designs. The adopted control law is a combination of predetermined multi-step feedback control laws, based on which two MPC algorithms with guaranteed recursive feasibility and asymptotic stability are presented. The efficacy of the proposed algorithms is illustrated by a numerical example.

Improved LTVMPC design for steering control of autonomous vehicle

NASA Astrophysics Data System (ADS)

Velhal, Shridhar; Thomas, Susy

2017-01-01

An improved linear time varying model predictive control for steering control of autonomous vehicle running on slippery road is presented. Control strategy is designed such that the vehicle will follow the predefined trajectory with highest possible entry speed. In linear time varying model predictive control, nonlinear vehicle model is successively linearized at each sampling instant. This linear time varying model is used to design MPC which will predict the future horizon. By incorporating predicted input horizon in each successive linearization the effectiveness of controller has been improved. The tracking performance using steering with front wheel and braking at four wheels are presented to illustrate the effectiveness of the proposed method.

Tailored high-resolution numerical weather forecasts for energy efficient predictive building control

NASA Astrophysics Data System (ADS)

Stauch, V. J.; Gwerder, M.; Gyalistras, D.; Oldewurtel, F.; Schubiger, F.; Steiner, P.

2010-09-01

The high proportion of the total primary energy consumption by buildings has increased the public interest in the optimisation of buildings' operation and is also driving the development of novel control approaches for the indoor climate. In this context, the use of weather forecasts presents an interesting and - thanks to advances in information and predictive control technologies and the continuous improvement of numerical weather prediction (NWP) models - an increasingly attractive option for improved building control. Within the research project OptiControl (www.opticontrol.ethz.ch) predictive control strategies for a wide range of buildings, heating, ventilation and air conditioning (HVAC) systems, and representative locations in Europe are being investigated with the aid of newly developed modelling and simulation tools. Grid point predictions for radiation, temperature and humidity of the high-resolution limited area NWP model COSMO-7 (see www.cosmo-model.org) and local measurements are used as disturbances and inputs into the building system. The control task considered consists in minimizing energy consumption whilst maintaining occupant comfort. In this presentation, we use the simulation-based OptiControl methodology to investigate the impact of COSMO-7 forecasts on the performance of predictive building control and the resulting energy savings. For this, we have selected building cases that were shown to benefit from a prediction horizon of up to 3 days and therefore, are particularly suitable for the use of numerical weather forecasts. We show that the controller performance is sensitive to the quality of the weather predictions, most importantly of the incident radiation on differently oriented façades. However, radiation is characterised by a high temporal and spatial variability in part caused by small scale and fast changing cloud formation and dissolution processes being only partially represented in the COSMO-7 grid point predictions. On the other hand, buildings are affected by particularly local weather conditions at the building site. To overcome this discrepancy, we make use of local measurements to statistically adapt the COSMO-7 model output to the meteorological conditions at the building. For this, we have developed a general correction algorithm that exploits systematic properties of the COSMO-7 prediction error and explicitly estimates the degree of temporal autocorrelation using online recursive estimation. The resulting corrected predictions are improved especially for the first few hours being the most crucial for the predictive controller and, ultimately for the reduction of primary energy consumption using predictive control. The use of numerical weather forecasts in predictive building automation is one example in a wide field of weather dependent advanced energy saving technologies. Our work particularly highlights the need for the development of specifically tailored weather forecast products by (statistical) postprocessing in order to meet the requirements of specific applications.

Improved fuzzy PID controller design using predictive functional control structure.

PubMed

Wang, Yuzhong; Jin, Qibing; Zhang, Ridong

2017-11-01

In conventional PID scheme, the ensemble control performance may be unsatisfactory due to limited degrees of freedom under various kinds of uncertainty. To overcome this disadvantage, a novel PID control method that inherits the advantages of fuzzy PID control and the predictive functional control (PFC) is presented and further verified on the temperature model of a coke furnace. Based on the framework of PFC, the prediction of the future process behavior is first obtained using the current process input signal. Then, the fuzzy PID control based on the multi-step prediction is introduced to acquire the optimal control law. Finally, the case study on a temperature model of a coke furnace shows the effectiveness of the fuzzy PID control scheme when compared with conventional PID control and fuzzy self-adaptive PID control. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Life Extending Control. [mechanical fatigue in reusable rocket engines

NASA Technical Reports Server (NTRS)

Lorenzo, Carl F.; Merrill, Walter C.

1991-01-01

The concept of Life Extending Control is defined. Life is defined in terms of mechanical fatigue life. A brief description is given of the current approach to life prediction using a local, cyclic, stress-strain approach for a critical system component. An alternative approach to life prediction based on a continuous functional relationship to component performance is proposed. Based on cyclic life prediction, an approach to life extending control, called the Life Management Approach, is proposed. A second approach, also based on cyclic life prediction, called the implicit approach, is presented. Assuming the existence of the alternative functional life prediction approach, two additional concepts for Life Extending Control are presented.

Life extending control: A concept paper

NASA Technical Reports Server (NTRS)

Lorenzo, Carl F.; Merrill, Walter C.

1991-01-01

The concept of Life Extending Control is defined. Life is defined in terms of mechanical fatigue life. A brief description is given of the current approach to life prediction using a local, cyclic, stress-strain approach for a critical system component. An alternative approach to life prediction based on a continuous functional relationship to component performance is proposed.Base on cyclic life prediction an approach to Life Extending Control, called the Life Management Approach is proposed. A second approach, also based on cyclic life prediction, called the Implicit Approach, is presented. Assuming the existence of the alternative functional life prediction approach, two additional concepts for Life Extending Control are presented.

Preschool Inhibitory Control Predicts ADHD Group Status and Inhibitory Weakness in School.

PubMed

Jacobson, Lisa A; Schneider, Heather; Mahone, E Mark

2017-12-26

Discriminative utility of performance measures of inhibitory control was examined in preschool children with and without ADHD to determine whether performance measures added to diagnostic prediction and to prediction of informant-rated day-to-day executive function. Children ages 4-5 years (N = 105, 61% boys; 54 ADHD, medication-naïve) were assessed using performance measures (Auditory Continuous Performance Test for Preschoolers-Commission errors, Conflicting Motor Response Test, NEPSY Statue) and caregiver (parent, teacher) ratings of inhibition (Behavior Rating Inventory of Executive Function-Preschool version). Performance measures and parent and teacher reports of inhibitory control significantly and uniquely predicted ADHD group status; however, performance measures did not add to prediction of group status beyond parent reports. Performance measures did significantly predict classroom inhibitory control (teacher ratings), over and above parent reports of inhibitory control. Performance measures of inhibitory control may be adequate predictors of ADHD status and good predictors of young children's classroom inhibitory control, demonstrating utility as components of clinical assessments. © The Author(s) 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Plint, Trevor; Lessard, Benoît H.; Bender, Timothy P.

In this study, we have assessed the potential application of group 13 and 14 metal and metalloid phthalocyanines ((X){sub n}-MPcs) and their axially substituted derivatives as hole-transporting layers in organic light emitting diodes (OLEDs). OLEDs studied herein have the generic structure of glass/ITO/(N,N′-di(1-naphthyl)-N,N′-diphenyl-(1,1′-biphenyl)-4,4′-diamine (NPB) or (X){sub n}-MPc)(50 nm)/Alq{sub 3} (60 nm)/LiF (1 nm)/Al (80 nm), where X is an axial substituent group. OLEDs using chloro aluminum phthalocyanine (Cl-AlPc) showed good peak luminance values of 2620 ± 113 cd/m{sup 2} at 11 V. To our knowledge, Cl-AlPc has not previously been shown to work as a hole transport material (HTL) in OLEDs. Conversely, the di-chlorides of silicon, germanium, andmore » tin phthalocyanine (Cl{sub 2}-SiPc, Cl{sub 2}-GePc, and Cl{sub 2}-SnPc, respectively) showed poor performance compared to Cl-AlPc, having peak luminances of only 38 ± 4 cd/m{sup 2} (12 V), 23 ± 1 cd/m{sup 2} (8.5 V), and 59 ± 5 cd/m{sup 2} (13.5 V), respectively. However, by performing a simple axial substitution of the chloride groups of Cl{sub 2}-SiPc with pentafluorophenoxy groups, the resulting bis(pentafluorophenoxy) silicon phthalocyanine (F{sub 10}-SiPc) containing OLED had a peak luminance of 5141 ± 941 cd/m{sup 2} (10 V), a two order of magnitude increase over its chlorinated precursor. This material showed OLED characteristics approaching those of a baseline OLED based on the well-studied triarylamine NPB. Attempts to attach the pentafluorophenoxy axial group to both SnPc and GePc were hindered by synthetic difficulties and low thermal stability, respectively. In light of the performance improvements observed by simple axial substitution of SiPc in OLEDs, the use of axially substituted MPcs in organic electronic devices remains of continuing interest to us and potentially the field in general.« less

Power maximization of a point absorber wave energy converter using improved model predictive control

NASA Astrophysics Data System (ADS)

Milani, Farideh; Moghaddam, Reihaneh Kardehi

2017-08-01

This paper considers controlling and maximizing the absorbed power of wave energy converters for irregular waves. With respect to physical constraints of the system, a model predictive control is applied. Irregular waves' behavior is predicted by Kalman filter method. Owing to the great influence of controller parameters on the absorbed power, these parameters are optimized by imperialist competitive algorithm. The results illustrate the method's efficiency in maximizing the extracted power in the presence of unknown excitation force which should be predicted by Kalman filter.

Limb Dominance Results from Asymmetries in Predictive and Impedance Control Mechanisms

PubMed Central

Yadav, Vivek; Sainburg, Robert L.

2014-01-01

Handedness is a pronounced feature of human motor behavior, yet the underlying neural mechanisms remain unclear. We hypothesize that motor lateralization results from asymmetries in predictive control of task dynamics and in control of limb impedance. To test this hypothesis, we present an experiment with two different force field environments, a field with a predictable magnitude that varies with the square of velocity, and a field with a less predictable magnitude that varies linearly with velocity. These fields were designed to be compatible with controllers that are specialized in predicting limb and task dynamics, and modulating position and velocity dependent impedance, respectively. Because the velocity square field does not change the form of the equations of motion for the reaching arm, we reasoned that a forward dynamic-type controller should perform well in this field, while control of linear damping and stiffness terms should be less effective. In contrast, the unpredictable linear field should be most compatible with impedance control, but incompatible with predictive dynamics control. We measured steady state final position accuracy and 3 trajectory features during exposure to these fields: Mean squared jerk, Straightness, and Movement time. Our results confirmed that each arm made straighter, smoother, and quicker movements in its compatible field. Both arms showed similar final position accuracies, which were achieved using more extensive corrective sub-movements when either arm performed in its incompatible field. Finally, each arm showed limited adaptation to its incompatible field. Analysis of the dependence of trajectory errors on field magnitude suggested that dominant arm adaptation occurred by prediction of the mean field, thus exploiting predictive mechanisms for adaptation to the unpredictable field. Overall, our results support the hypothesis that motor lateralization reflects asymmetries in specific motor control mechanisms associated with predictive control of limb and task dynamics, and modulation of limb impedance. PMID:24695543

Discovering Pediatric Asthma Phenotypes on the Basis of Response to Controller Medication Using Machine Learning.

PubMed

Ross, Mindy K; Yoon, Jinsung; van der Schaar, Auke; van der Schaar, Mihaela

2018-01-01

Pediatric asthma has variable underlying inflammation and symptom control. Approaches to addressing this heterogeneity, such as clustering methods to find phenotypes and predict outcomes, have been investigated. However, clustering based on the relationship between treatment and clinical outcome has not been performed, and machine learning approaches for long-term outcome prediction in pediatric asthma have not been studied in depth. Our objectives were to use our novel machine learning algorithm, predictor pursuit (PP), to discover pediatric asthma phenotypes on the basis of asthma control in response to controller medications, to predict longitudinal asthma control among children with asthma, and to identify features associated with asthma control within each discovered pediatric phenotype. We applied PP to the Childhood Asthma Management Program study data (n = 1,019) to discover phenotypes on the basis of asthma control between assigned controller therapy groups (budesonide vs. nedocromil). We confirmed PP's ability to discover phenotypes using the Asthma Clinical Research Network/Childhood Asthma Research and Education network data. We next predicted children's asthma control over time and compared PP's performance with that of traditional prediction methods. Last, we identified clinical features most correlated with asthma control in the discovered phenotypes. Four phenotypes were discovered in both datasets: allergic not obese (A + /O - ), obese not allergic (A - /O + ), allergic and obese (A + /O + ), and not allergic not obese (A - /O - ). Of the children with well-controlled asthma in the Childhood Asthma Management Program dataset, we found more nonobese children treated with budesonide than with nedocromil (P = 0.015) and more obese children treated with nedocromil than with budesonide (P = 0.008). Within the obese group, more A + /O + children's asthma was well controlled with nedocromil than with budesonide (P = 0.022) or with placebo (P = 0.011). The PP algorithm performed significantly better (P < 0.001) than traditional machine learning algorithms for both short- and long-term asthma control prediction. Asthma control and bronchodilator response were the features most predictive of short-term asthma control, regardless of type of controller medication or phenotype. Bronchodilator response and serum eosinophils were the most predictive features of asthma control, regardless of type of controller medication or phenotype. Advanced statistical machine learning approaches can be powerful tools for discovery of phenotypes based on treatment response and can aid in asthma control prediction in complex medical conditions such as asthma.

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.

Inferential modeling and predictive feedback control in real-time motion compensation using the treatment couch during radiotherapy

NASA Astrophysics Data System (ADS)

Qiu, Peng; D'Souza, Warren D.; McAvoy, Thomas J.; Liu, K. J. Ray

2007-09-01

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 feedback control system. Our results show that, with the tumor motion unknown but inferred by skin-based markers through the PLS model, the predictive feedback control system was able to effectively compensate intra-fraction motion.

Happiness as a motivator: positive affect predicts primary control striving for career and educational goals.

PubMed

Haase, Claudia M; Poulin, Michael J; Heckhausen, Jutta

2012-08-01

What motivates individuals to invest time and effort and overcome obstacles (i.e., strive for primary control) when pursuing important goals? We propose that positive affect predicts primary control striving for career and educational goals, and we explore the mediating role of control beliefs. In Study 1, positive affect predicted primary control striving for career goals in a two-wave longitudinal study of a U.S. sample. In Study 2, positive affect predicted primary control striving for career and educational goals and objective career outcomes in a six-wave longitudinal study of a German sample. Control beliefs partially mediated the longitudinal associations with primary control striving. Thus, when individuals experience positive affect, they become more motivated to invest time and effort, and overcome obstacles when pursuing their goals, in part because they believe they have more control over attaining their goals.

Improved model predictive control of resistive wall modes by error field estimator in EXTRAP T2R

NASA Astrophysics Data System (ADS)

Setiadi, A. C.; Brunsell, P. R.; Frassinetti, L.

2016-12-01

Many implementations of a model-based approach for toroidal plasma have shown better control performance compared to the conventional type of feedback controller. One prerequisite of model-based control is the availability of a control oriented model. This model can be obtained empirically through a systematic procedure called system identification. Such a model is used in this work to design a model predictive controller to stabilize multiple resistive wall modes in EXTRAP T2R reversed-field pinch. Model predictive control is an advanced control method that can optimize the future behaviour of a system. Furthermore, this paper will discuss an additional use of the empirical model which is to estimate the error field in EXTRAP T2R. Two potential methods are discussed that can estimate the error field. The error field estimator is then combined with the model predictive control and yields better radial magnetic field suppression.

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.

Comparison of predictive control methods for high consumption industrial furnace.

PubMed

Stojanovski, Goran; Stankovski, Mile

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.

Growth in Temperament and Parenting as Predictors of Adjustment During Children’s Transition to Adolescence

PubMed Central

Lengua, Liliana J.

2014-01-01

The author examined relations among demographic risk (income, maternal education, single-parent status), growth in temperament (fear, irritability, effortful control), and parenting (rejection, inconsistent discipline) across 3 years and the prediction of children’s adjustment problems in a community sample (N = 190; ages 8–12 years at Time 1). Family income was related to higher initial levels of fear, irritability, rejection, and inconsistency and lower effortful control but was not related to changes in these variables. Higher initial rejection predicted increases in child fear and irritability. Higher initial fear predicted decreases in rejection and inconsistency. Higher initial irritability predicted increases in inconsistency, and higher initial effortful control predicted decreases in rejection. When growth of parenting and temperament were considered simultaneously, increases in effortful control and decreases in fear and irritability predicted lower Time 3 internalizing and externalizing problems. Increases in rejection and inconsistent discipline predicted higher Time 3 externalizing, although sometimes the effect appeared to be indirect through temperament. The findings suggest that temperament and parenting predict changes in each other and predict adjustment during the transition to adolescence. PMID:16953689

Muscle Synergies Facilitate Computational Prediction of Subject-Specific Walking Motions

PubMed Central

Meyer, Andrew J.; Eskinazi, Ilan; Jackson, Jennifer N.; Rao, Anil V.; Patten, Carolynn; Fregly, Benjamin J.

2016-01-01

Researchers have explored a variety of neurorehabilitation approaches to restore normal walking function following a stroke. However, there is currently no objective means for prescribing and implementing treatments that are likely to maximize recovery of walking function for any particular patient. As a first step toward optimizing neurorehabilitation effectiveness, this study develops and evaluates a patient-specific synergy-controlled neuromusculoskeletal simulation framework that can predict walking motions for an individual post-stroke. The main question we addressed was whether driving a subject-specific neuromusculoskeletal model with muscle synergy controls (5 per leg) facilitates generation of accurate walking predictions compared to a model driven by muscle activation controls (35 per leg) or joint torque controls (5 per leg). To explore this question, we developed a subject-specific neuromusculoskeletal model of a single high-functioning hemiparetic subject using instrumented treadmill walking data collected at the subject’s self-selected speed of 0.5 m/s. The model included subject-specific representations of lower-body kinematic structure, foot–ground contact behavior, electromyography-driven muscle force generation, and neural control limitations and remaining capabilities. Using direct collocation optimal control and the subject-specific model, we evaluated the ability of the three control approaches to predict the subject’s walking kinematics and kinetics at two speeds (0.5 and 0.8 m/s) for which experimental data were available from the subject. We also evaluated whether synergy controls could predict a physically realistic gait period at one speed (1.1 m/s) for which no experimental data were available. All three control approaches predicted the subject’s walking kinematics and kinetics (including ground reaction forces) well for the model calibration speed of 0.5 m/s. However, only activation and synergy controls could predict the subject’s walking kinematics and kinetics well for the faster non-calibration speed of 0.8 m/s, with synergy controls predicting the new gait period the most accurately. When used to predict how the subject would walk at 1.1 m/s, synergy controls predicted a gait period close to that estimated from the linear relationship between gait speed and stride length. These findings suggest that our neuromusculoskeletal simulation framework may be able to bridge the gap between patient-specific muscle synergy information and resulting functional capabilities and limitations. PMID:27790612

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. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive adjustment of interval predictive control based on combined model and application in shell brand petroleum distillation tower

NASA Astrophysics Data System (ADS)

Sun, Chao; Zhang, Chunran; Gu, Xinfeng; Liu, Bin

2017-10-01

Constraints of the optimization objective are often unable to be met when predictive control is applied to industrial production process. Then, online predictive controller will not find a feasible solution or a global optimal solution. To solve this problem, based on Back Propagation-Auto Regressive with exogenous inputs (BP-ARX) combined control model, nonlinear programming method is used to discuss the feasibility of constrained predictive control, feasibility decision theorem of the optimization objective is proposed, and the solution method of soft constraint slack variables is given when the optimization objective is not feasible. Based on this, for the interval control requirements of the controlled variables, the slack variables that have been solved are introduced, the adaptive weighted interval predictive control algorithm is proposed, achieving adaptive regulation of the optimization objective and automatically adjust of the infeasible interval range, expanding the scope of the feasible region, and ensuring the feasibility of the interval optimization objective. Finally, feasibility and effectiveness of the algorithm is validated through the simulation comparative experiments.

Profile control simulations and experiments on TCV: a controller test environment and results using a model-based predictive controller

NASA Astrophysics Data System (ADS)

Maljaars, E.; Felici, F.; Blanken, T. C.; Galperti, C.; Sauter, O.; de Baar, M. R.; Carpanese, F.; Goodman, T. P.; Kim, D.; Kim, S. H.; Kong, M.; Mavkov, B.; Merle, A.; Moret, J. M.; Nouailletas, R.; Scheffer, M.; Teplukhina, A. A.; Vu, N. M. T.; The EUROfusion MST1-team; The TCV-team

2017-12-01

The successful performance of a model predictive profile controller is demonstrated in simulations and experiments on the TCV tokamak, employing a profile controller test environment. Stable high-performance tokamak operation in hybrid and advanced plasma scenarios requires control over the safety factor profile (q-profile) and kinetic plasma parameters such as the plasma beta. This demands to establish reliable profile control routines in presently operational tokamaks. We present a model predictive profile controller that controls the q-profile and plasma beta using power requests to two clusters of gyrotrons and the plasma current request. The performance of the controller is analyzed in both simulation and TCV L-mode discharges where successful tracking of the estimated inverse q-profile as well as plasma beta is demonstrated under uncertain plasma conditions and the presence of disturbances. The controller exploits the knowledge of the time-varying actuator limits in the actuator input calculation itself such that fast transitions between targets are achieved without overshoot. A software environment is employed to prepare and test this and three other profile controllers in parallel in simulations and experiments on TCV. This set of tools includes the rapid plasma transport simulator RAPTOR and various algorithms to reconstruct the plasma equilibrium and plasma profiles by merging the available measurements with model-based predictions. In this work the estimated q-profile is merely based on RAPTOR model predictions due to the absence of internal current density measurements in TCV. These results encourage to further exploit model predictive profile control in experiments on TCV and other (future) tokamaks.

Robust model predictive control for satellite formation keeping with eccentricity/inclination vector separation

NASA Astrophysics Data System (ADS)

Lim, Yeerang; Jung, Youeyun; Bang, Hyochoong

2018-05-01

This study presents model predictive formation control based on an eccentricity/inclination vector separation strategy. Alternative collision avoidance can be accomplished by using eccentricity/inclination vectors and adding a simple goal function term for optimization process. Real-time control is also achievable with model predictive controller based on convex formulation. Constraint-tightening approach is address as well improve robustness of the controller, and simulation results are presented to verify performance enhancement for the proposed approach.

Predictive models of glucose control: roles for glucose-sensing neurones.

PubMed

Kosse, C; Gonzalez, A; Burdakov, D

2015-01-01

The brain can be viewed as a sophisticated control module for stabilizing blood glucose. A review of classical behavioural evidence indicates that central circuits add predictive (feedforward/anticipatory) control to the reactive (feedback/compensatory) control by peripheral organs. The brain/cephalic control is constructed and engaged, via associative learning, by sensory cues predicting energy intake or expenditure (e.g. sight, smell, taste, sound). This allows rapidly measurable sensory information (rather than slowly generated internal feedback signals, e.g. digested nutrients) to control food selection, glucose supply for fight-or-flight responses or preparedness for digestion/absorption. Predictive control is therefore useful for preventing large glucose fluctuations. We review emerging roles in predictive control of two classes of widely projecting hypothalamic neurones, orexin/hypocretin (ORX) and melanin-concentrating hormone (MCH) cells. Evidence is cited that ORX neurones (i) are activated by sensory cues (e.g. taste, sound), (ii) drive hepatic production, and muscle uptake, of glucose, via sympathetic nerves, (iii) stimulate wakefulness and exploration via global brain projections and (iv) are glucose-inhibited. MCH neurones are (i) glucose-excited, (ii) innervate learning and reward centres to promote synaptic plasticity, learning and memory and (iii) are critical for learning associations useful for predictive control (e.g. using taste to predict nutrient value of food). This evidence is unified into a model for predictive glucose control. During associative learning, inputs from some glucose-excited neurones may promote connections between the 'fast' senses and reward circuits, constructing neural shortcuts for efficient action selection. In turn, glucose-inhibited neurones may engage locomotion/exploration and coordinate the required fuel supply. Feedback inhibition of the latter neurones by glucose would ensure that glucose fluxes they stimulate (from liver, into muscle) are balanced. Estimating nutrient challenges from indirect sensory cues may become more difficult when the cues become complex and variable (e.g. like human foods today). Consequent errors of predictive glucose control may contribute to obesity and diabetes. © 2014 The Authors. Acta Physiologica published by John Wiley & Sons Ltd on behalf of Scandinavian Physiological Society.

Life extending control for rocket engines

NASA Technical Reports Server (NTRS)

Lorenzo, C. F.; Saus, J. R.; Ray, A.; Carpino, M.; Wu, M.-K.

1992-01-01

The concept of life extending control is defined. A brief discussion of current fatigue life prediction methods is given and the need for an alternative life prediction model based on a continuous functional relationship is established. Two approaches to life extending control are considered: (1) the implicit approach which uses cyclic fatigue life prediction as a basis for control design; and (2) the continuous life prediction approach which requires a continuous damage law. Progress on an initial formulation of a continuous (in time) fatigue model is presented. Finally, nonlinear programming is used to develop initial results for life extension for a simplified rocket engine (model).

A combined-slip predictive control of vehicle stability with experimental verification

NASA Astrophysics Data System (ADS)

Jalali, Milad; Hashemi, Ehsan; Khajepour, Amir; Chen, Shih-ken; Litkouhi, Bakhtiar

2018-02-01

In this paper, a model predictive vehicle stability controller is designed based on a combined-slip LuGre tyre model. Variations in the lateral tyre forces due to changes in tyre slip ratios are considered in the prediction model of the controller. It is observed that the proposed combined-slip controller takes advantage of the more accurate tyre model and can adjust tyre slip ratios based on lateral forces of the front axle. This results in an interesting closed-loop response that challenges the notion of braking only the wheels on one side of the vehicle in differential braking. The performance of the proposed controller is evaluated in software simulations and is compared to a similar pure-slip controller. Furthermore, experimental tests are conducted on a rear-wheel drive electric Chevrolet Equinox equipped with differential brakes to evaluate the closed-loop response of the model predictive control controller.

Prediction based active ramp metering control strategy with mobility and safety assessment

NASA Astrophysics Data System (ADS)

Fang, Jie; Tu, Lili

2018-04-01

Ramp metering is one of the most direct and efficient motorway traffic flow management measures so as to improve traffic conditions. However, owing to short of traffic conditions prediction, in earlier studies, the impact on traffic flow dynamics of the applied RM control was not quantitatively evaluated. In this study, a RM control algorithm adopting Model Predictive Control (MPC) framework to predict and assess future traffic conditions, which taking both the current traffic conditions and the RM-controlled future traffic states into consideration, was presented. The designed RM control algorithm targets at optimizing the network mobility and safety performance. The designed algorithm is evaluated in a field-data-based simulation. Through comparing the presented algorithm controlled scenario with the uncontrolled scenario, it was proved that the proposed RM control algorithm can effectively relieve the congestion of traffic network with no significant compromises in safety aspect.

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.

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.

Adaptive vibration control of structures under earthquakes

NASA Astrophysics Data System (ADS)

Lew, Jiann-Shiun; Juang, Jer-Nan; Loh, Chin-Hsiung

2017-04-01

techniques, for structural vibration suppression under earthquakes. Various control strategies have been developed to protect structures from natural hazards and improve the comfort of occupants in buildings. However, there has been little development of adaptive building control with the integration of real-time system identification and control design. Generalized predictive control, which combines the process of real-time system identification and the process of predictive control design, has received widespread acceptance and has been successfully applied to various test-beds. This paper presents a formulation of the predictive control scheme for adaptive vibration control of structures under earthquakes. Comprehensive simulations are performed to demonstrate and validate the proposed adaptive control technique for earthquake-induced vibration of a building.

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.

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.

Using self-reported and objective measures of self-control to predict exercise and academic behaviors among first-year university students.

PubMed

Stork, Matthew J; Graham, Jeffrey D; Bray, Steven R; Martin Ginis, Kathleen A

2017-07-01

Thirty students (mean age = 18 ± 0.5 years) completed self-report (Self-Control Scale) and objective (isometric handgrip squeeze performance) measures of self-control, provided their exercise and academic (study/schoolwork) plans for the next month, and then logged these behaviors over the subsequent 4-week period. Trait self-control predicted exercise and academic behavior. Handgrip squeeze performance predicted academic behavior and adherence to academic plans. Further, regression analysis revealed that trait self-control and handgrip performance explained significant variance in academic behavior. These findings provide a new understanding of how different self-control measures can be used to predict first-year students' participation in, and adherence to, exercise and academic behaviors concurrently.

Changes in Predictive Task Switching with Age and with Cognitive Load.

PubMed

Levy-Tzedek, Shelly

2017-01-01

Predictive control of movement is more efficient than feedback-based control, and is an important skill in everyday life. We tested whether the ability to predictively control movements of the upper arm is affected by age and by cognitive load. A total of 63 participants were tested in two experiments. In both experiments participants were seated, and controlled a cursor on a computer screen by flexing and extending their dominant arm. In Experiment 1, 20 young adults and 20 older adults were asked to continuously change the frequency of their horizontal arm movements, with the goal of inducing an abrupt switch between discrete movements (at low frequencies) and rhythmic movements (at high frequencies). We tested whether that change was performed based on a feed-forward (predictive) or on a feedback (reactive) control. In Experiment 2, 23 young adults performed the same task, while being exposed to a cognitive load half of the time via a serial subtraction task. We found that both aging and cognitive load diminished, on average, the ability of participants to predictively control their movements. Five older adults and one young adult under a cognitive load were not able to perform the switch between rhythmic and discrete movement (or vice versa). In Experiment 1, 40% of the older participants were able to predictively control their movements, compared with 70% in the young group. In Experiment 2, 48% of the participants were able to predictively control their movements with a cognitively loading task, compared with 70% in the no-load condition. The ability to predictively change a motor plan in anticipation of upcoming changes may be an important component in performing everyday functions, such as safe driving and avoiding falls.

Relationships of personality factors to perceived stress, depression, and oral lichen planus severity.

PubMed

Mohamadi Hasel, Kurosh; Besharat, Mohamad Ali; Abdolhoseini, Amir; Alaei Nasab, Somaye; Niknam, Seyran

2013-06-01

  The objective of this study is to examine relationships of hardiness and big five personality factors to depression, perceived stress, and oral lichen planus (OLP) severity. Sixty Iranian patients with oral lichen planus completed measures of perceived stress, hardiness, big five, and depression. Linear regressions revealed that control and challenge significantly predicted least perceived stress. On the contrary, big five factor of neuroticism predicted more perceived stress. Furthermore, control, commitment, and extraversion negatively predicted depression levels, but neuroticism positively predicted depression levels. Additionally, more levels of the challenge factor predicted fewer OLP scores while more levels of perceived stress predicted more OLP scores. The components of control challenge and neuroticism factors had a significant role in predicting perceived stress. On the other hand, the components of control and commitment and extraversion factors had a prominent role in predicting depression in patients with OLP, so personality constructs may have an effective role in triggering experience of stress, depression, and OLP itself. Additionally, interventions that enhance individual protective factors may be beneficial in reducing stress and depression in some severe diseases.

Regulatory focus affects predictions of the future.

PubMed

Guo, Tieyuan; Spina, Roy

2015-02-01

This research investigated how regulatory focus might influence trend-reversal predictions. We hypothesized that compared with promotion focus, prevention focus hinders sense of control, which in turn predicts more trend-reversal developments. Studies 1 and 3 revealed that participants expected trend-reversal developments to be more likely to occur when they focused on prevention than when they focused on promotion. Study 2 extended the findings by including a control condition, and revealed that participants expected trend-reversal developments to be more likely to occur in the prevention condition than in the promotion and control conditions. Studies 4 and 5 revealed that participants' chronic prevention focus predicted a low sense of control (Study 4), and that promotion focus predicted a high sense of control (Studies 4 and 5). Furthermore, participants with a high sense of control expected trend-reversal developments to be less likely to occur. Thus, the results provided converging evidence for the hypothesis. © 2014 by the Society for Personality and Social Psychology, Inc.

Fourier transform wavefront control with adaptive prediction of the atmosphere.

PubMed

Poyneer, Lisa A; Macintosh, Bruce A; Véran, Jean-Pierre

2007-09-01

Predictive Fourier control is a temporal power spectral density-based adaptive method for adaptive optics that predicts the atmosphere under the assumption of frozen flow. The predictive controller is based on Kalman filtering and a Fourier decomposition of atmospheric turbulence using the Fourier transform reconstructor. It provides a stable way to compensate for arbitrary numbers of atmospheric layers. For each Fourier mode, efficient and accurate algorithms estimate the necessary atmospheric parameters from closed-loop telemetry and determine the predictive filter, adjusting as conditions change. This prediction improves atmospheric rejection, leading to significant improvements in system performance. For a 48x48 actuator system operating at 2 kHz, five-layer prediction for all modes is achievable in under 2x10(9) floating-point operations/s.

Learning to predict is spared in mild cognitive impairment due to Alzheimer's disease.

PubMed

Baker, Rosalind; Bentham, Peter; Kourtzi, Zoe

2015-10-01

Learning the statistics of the environment is critical for predicting upcoming events. However, little is known about how we translate previous knowledge about scene regularities to sensory predictions. Here, we ask whether patients with mild cognitive impairment due to Alzheimer's disease (MCI-AD) that are known to have spared implicit but impaired explicit recognition memory are able to learn temporal regularities and predict upcoming events. We tested the ability of MCI-AD patients and age-matched controls to predict the orientation of a test stimulus following exposure to sequences of leftwards or rightwards oriented gratings. Our results demonstrate that exposure to temporal sequences without feedback facilitates the ability to predict an upcoming stimulus in both MCI-AD patients and controls. Further, we show that executive cognitive control may account for individual variability in predictive learning. That is, we observed significant positive correlations of performance in attentional and working memory tasks with post-training performance in the prediction task. Taken together, these results suggest a mediating role of circuits involved in cognitive control (i.e. frontal circuits) that may support the ability for predictive learning in MCI-AD.

Basic Research on Adaptive Model Algorithmic Control

DTIC Science & Technology

1985-12-01

Control Conference. Richalet, J., A. Rault, J.L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial...pp.977-982. Richalet, J., A. Rault, J. L. Testud and J. Papon (1978). Model predictive heuristic control: applications to industrial processes

The effects of self-control, gang membership, and parental attachment/identification on police contacts among Latino and African American youths.

PubMed

Flexon, Jamie L; Greenleaf, Richard G; Lurigio, Arthur J

2012-04-01

This study assessed the correlates of self-control and police contact in a sample of Chicago public high school students. The investigation examined the effects of parental attachment/identification, family structure, and peer association on self-control and the effects of parental attachment/identification, family structure, peer association, and self-control on police contact. Differences between African American and Latino youth on the predictors of the two dependent measures were tested in separate regression models. Weak parental attachment/identification and gang affiliation (peer association) predicted low self-control among all students. Among African American youth, only weak maternal attachment/identification predicted low self-control; both weak maternal attachment/identification and gang affiliation predicted low self-control among Latino youth. Gang affiliation predicted police stops (delinquency) among African Americans but not among Latinos. However, both African American and Latino students with lower self-control were more likely to be stopped by the police than those with higher self-control.

Recursive Deadbeat Controller Design

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan; Phan, Minh Q.

1997-01-01

This paper presents a recursive algorithm for a deadbeat predictive controller design. The method combines together the concepts of system identification and deadbeat controller designs. It starts with the multi-step output prediction equation and derives the control force in terms of past input and output time histories. The formulation thus derived satisfies simultaneously system identification and deadbeat controller design requirements. As soon as the coefficient matrices are identified satisfying the output prediction equation, no further work is required to compute the deadbeat control gain matrices. The method can be implemented recursively just as any typical recursive system identification techniques.

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.

Elementary Students' Effortful Control and Academic Achievement: The Mediating Role of Teacher-Student Relationship Quality

PubMed Central

Hernández, Maciel M.; Valiente, Carlos; Eisenberg, Nancy; Berger, Rebecca H.; Spinrad, Tracy L.; VanSchyndel, Sarah K.; Silva, Kassondra M.; Southworth, Jody; Thompson, Marilyn S.

2017-01-01

This study evaluated the association between effortful control in kindergarten and academic achievement one year later (N = 301), and whether teacher–student closeness and conflict in kindergarten mediated the association. Parents, teachers, and observers reported on children's effortful control, and teachers reported on their perceived levels of closeness and conflict with students. Students completed the passage comprehension and applied problems subtests of the Woodcock–Johnson tests of achievement, as well as a behavioral measure of effortful control. Analytical models predicting academic achievement were estimated using a structural equation model framework. Effortful control positively predicted academic achievement even when controlling for prior achievement and other covariates. Mediation hypotheses were tested in a separate model; effortful control positively predicted teacher–student closeness and strongly, negatively predicted teacher–student conflict. Teacher–student closeness and effortful control, but not teacher–student conflict, had small, positive associations with academic achievement. Effortful control also indirectly predicted higher academic achievement through its positive effect on teacher–student closeness and via its positive relation to early academic achievement. The findings suggest that teacher–student closeness is one mechanism by which effortful control is associated with academic achievement. Effortful control was also a consistent predictor of academic achievement, beyond prior achievement levels and controlling for teacher–student closeness and conflict, with implications for intervention programs on fostering regulation and achievement concurrently. PMID:28684888

Elementary Students' Effortful Control and Academic Achievement: The Mediating Role of Teacher-Student Relationship Quality.

PubMed

Hernández, Maciel M; Valiente, Carlos; Eisenberg, Nancy; Berger, Rebecca H; Spinrad, Tracy L; VanSchyndel, Sarah K; Silva, Kassondra M; Southworth, Jody; Thompson, Marilyn S

This study evaluated the association between effortful control in kindergarten and academic achievement one year later ( N = 301), and whether teacher-student closeness and conflict in kindergarten mediated the association. Parents, teachers, and observers reported on children's effortful control, and teachers reported on their perceived levels of closeness and conflict with students. Students completed the passage comprehension and applied problems subtests of the Woodcock-Johnson tests of achievement, as well as a behavioral measure of effortful control. Analytical models predicting academic achievement were estimated using a structural equation model framework. Effortful control positively predicted academic achievement even when controlling for prior achievement and other covariates. Mediation hypotheses were tested in a separate model; effortful control positively predicted teacher-student closeness and strongly, negatively predicted teacher-student conflict. Teacher-student closeness and effortful control, but not teacher-student conflict, had small, positive associations with academic achievement. Effortful control also indirectly predicted higher academic achievement through its positive effect on teacher-student closeness and via its positive relation to early academic achievement. The findings suggest that teacher-student closeness is one mechanism by which effortful control is associated with academic achievement. Effortful control was also a consistent predictor of academic achievement, beyond prior achievement levels and controlling for teacher-student closeness and conflict, with implications for intervention programs on fostering regulation and achievement concurrently.

Initial Evaluations of LoC Prediction Algorithms Using the NASA Vertical Motion Simulator

NASA Technical Reports Server (NTRS)

Krishnakumar, Kalmanje; Stepanyan, Vahram; Barlow, Jonathan; Hardy, Gordon; Dorais, Greg; Poolla, Chaitanya; Reardon, Scott; Soloway, Donald

2014-01-01

Flying near the edge of the safe operating envelope is an inherently unsafe proposition. Edge of the envelope here implies that small changes or disturbances in system state or system dynamics can take the system out of the safe envelope in a short time and could result in loss-of-control events. This study evaluated approaches to predicting loss-of-control safety margins as the aircraft gets closer to the edge of the safe operating envelope. The goal of the approach is to provide the pilot aural, visual, and tactile cues focused on maintaining the pilot's control action within predicted loss-of-control boundaries. Our predictive architecture combines quantitative loss-of-control boundaries, an adaptive prediction method to estimate in real-time Markov model parameters and associated stability margins, and a real-time data-based predictive control margins estimation algorithm. The combined architecture is applied to a nonlinear transport class aircraft. Evaluations of various feedback cues using both test and commercial pilots in the NASA Ames Vertical Motion-base Simulator (VMS) were conducted in the summer of 2013. The paper presents results of this evaluation focused on effectiveness of these approaches and the cues in preventing the pilots from entering a loss-of-control event.

Control and prediction components of movement planning in stuttering vs. nonstuttering adults

PubMed Central

Daliri, Ayoub; Prokopenko, Roman A.; Flanagan, J. Randall; Max, Ludo

2014-01-01

Purpose Stuttering individuals show speech and nonspeech sensorimotor deficiencies. To perform accurate movements, the sensorimotor system needs to generate appropriate control signals and correctly predict their sensory consequences. Using a reaching task, we examined the integrity of these control and prediction components, separately, for movements unrelated to the speech motor system. Method Nine stuttering and nine nonstuttering adults made fast reaching movements to visual targets while sliding an object under the index finger. To quantify control, we determined initial direction error and end-point error. To quantify prediction, we calculated the correlation between vertical and horizontal forces applied to the object—an index of how well vertical force (preventing slip) anticipated direction-dependent variations in horizontal force (moving the object). Results Directional and end-point error were significantly larger for the stuttering group. Both groups performed similarly in scaling vertical force with horizontal force. Conclusions The stuttering group's reduced reaching accuracy suggests limitations in generating control signals for voluntary movements, even for non-orofacial effectors. Typical scaling of vertical force with horizontal force suggests an intact ability to predict the consequences of planned control signals. Stuttering may be associated with generalized deficiencies in planning control signals rather than predicting the consequences of those signals. PMID:25203459

Missile Guidance Law Based on Robust Model Predictive Control Using Neural-Network Optimization.

PubMed

Li, Zhijun; Xia, Yuanqing; Su, Chun-Yi; Deng, Jun; Fu, Jun; He, Wei

2015-08-01

In this brief, the utilization of robust model-based predictive control is investigated for the problem of missile interception. Treating the target acceleration as a bounded disturbance, novel guidance law using model predictive control is developed by incorporating missile inside constraints. The combined model predictive approach could be transformed as a constrained quadratic programming (QP) problem, which may be solved using a linear variational inequality-based primal-dual neural network over a finite receding horizon. Online solutions to multiple parametric QP problems are used so that constrained optimal control decisions can be made in real time. Simulation studies are conducted to illustrate the effectiveness and performance of the proposed guidance control law for missile interception.

Control, Filtering and Prediction for Phased Arrays in Directed Energy Systems

DTIC Science & Technology

2016-04-30

adaptive optics. 15. SUBJECT TERMS control, filtering, prediction, system identification, adaptive optics, laser beam pointing, target tracking, phase... laser beam control; furthermore, wavefront sensors are plagued by the difficulty of maintaining the required alignment and focusing in dynamic mission...developed new methods for filtering, prediction and system identification in adaptive optics for high energy laser systems including phased arrays. The

Prediction algorithms for urban traffic control

DOT National Transportation Integrated Search

1979-02-01

The objectives of this study are to 1) review and assess the state-of-the-art of prediction algorithms for urban traffic control in terms of their accuracy and application, and 2) determine the prediction accuracy obtainable by examining the performa...

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 responses be known for a particular input and modeled plant. These responses are used in the error prediction controller. An analysis was done on the general dynamic behavior that results from including a digital error predictor in a control loop and these were compared to those including the near-ideal Neural Network error predictor. This analysis was done for a second and third order system.

Choosing the appropriate forecasting model for predictive parameter control.

PubMed

Aleti, Aldeida; Moser, Irene; Meedeniya, Indika; Grunske, Lars

2014-01-01

All commonly used stochastic optimisation algorithms have to be parameterised to perform effectively. Adaptive parameter control (APC) is an effective method used for this purpose. APC repeatedly adjusts parameter values during the optimisation process for optimal algorithm performance. The assignment of parameter values for a given iteration is based on previously measured performance. In recent research, time series prediction has been proposed as a method of projecting the probabilities to use for parameter value selection. In this work, we examine the suitability of a variety of prediction methods for the projection of future parameter performance based on previous data. All considered prediction methods have assumptions the time series data has to conform to for the prediction method to provide accurate projections. Looking specifically at parameters of evolutionary algorithms (EAs), we find that all standard EA parameters with the exception of population size conform largely to the assumptions made by the considered prediction methods. Evaluating the performance of these prediction methods, we find that linear regression provides the best results by a very small and statistically insignificant margin. Regardless of the prediction method, predictive parameter control outperforms state of the art parameter control methods when the performance data adheres to the assumptions made by the prediction method. When a parameter's performance data does not adhere to the assumptions made by the forecasting method, the use of prediction does not have a notable adverse impact on the algorithm's performance.

Towards feasible and effective predictive wavefront control for adaptive optics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Poyneer, L A; Veran, J

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.

Model Predictive Control Based Motion Drive Algorithm for a Driving Simulator

NASA Astrophysics Data System (ADS)

Rehmatullah, Faizan

In this research, we develop a model predictive control based motion drive algorithm for the driving simulator at Toronto Rehabilitation Institute. Motion drive algorithms exploit the limitations of the human vestibular system to formulate a perception of motion within the constrained workspace of a simulator. In the absence of visual cues, the human perception system is unable to distinguish between acceleration and the force of gravity. The motion drive algorithm determines control inputs to displace the simulator platform, and by using the resulting inertial forces and angular rates, creates the perception of motion. By using model predictive control, we can optimize the use of simulator workspace for every maneuver while simulating the vehicle perception. With the ability to handle nonlinear constraints, the model predictive control allows us to incorporate workspace limitations.

Lysophosphatidic Acid and Apolipoprotein A1 Predict Increased Risk of Developing World Trade Center Lung Injury: A Nested Case-Control Study

PubMed Central

Tsukiji, Jun; Cho, Soo Jung; Echevarria, Ghislaine C.; Kwon, Sophia; Joseph, Phillip; Schenck, Edward J.; Naveed, Bushra; Prezant, David J.; Rom, William N.; Schmidt, Ann Marie; Weiden, Michael D.; Nolan, Anna

2014-01-01

Rationale Metabolic syndrome, inflammatory and vascular injury markers measured in serum after WTC exposures predict abnormal FEV1. We hypothesized that elevated LPA levels predict FEV1

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.

Study on model current predictive control method of PV grid- connected inverters systems with voltage sag

NASA Astrophysics Data System (ADS)

Jin, N.; Yang, F.; Shang, S. Y.; Tao, T.; Liu, J. S.

2016-08-01

According to the limitations of the LVRT technology of traditional photovoltaic inverter existed, this paper proposes a low voltage ride through (LVRT) control method based on model current predictive control (MCPC). This method can effectively improve the photovoltaic inverter output characteristics and response speed. The MCPC method of photovoltaic grid-connected inverter designed, the sum of the absolute value of the predictive current and the given current error is adopted as the cost function with the model predictive control method. According to the MCPC, the optimal space voltage vector is selected. Photovoltaic inverter has achieved automatically switches of priority active or reactive power control of two control modes according to the different operating states, which effectively improve the inverter capability of LVRT. The simulation and experimental results proves that the proposed method is correct and effective.

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. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Combined Adaptive Neural Network and Nonlinear Model Predictive Control for Multirate Networked Industrial Process Control.

PubMed

Wang, Tong; Gao, Huijun; Qiu, Jianbin

2016-02-01

This paper investigates the multirate networked industrial process control problem in double-layer architecture. First, the output tracking problem for sampled-data nonlinear plant at device layer with sampling period T(d) is investigated using adaptive neural network (NN) control, and it is shown that the outputs of subsystems at device layer can track the decomposed setpoints. Then, the outputs and inputs of the device layer subsystems are sampled with sampling period T(u) at operation layer to form the index prediction, which is used to predict the overall performance index at lower frequency. Radial basis function NN is utilized as the prediction function due to its approximation ability. Then, considering the dynamics of the overall closed-loop system, nonlinear model predictive control method is proposed to guarantee the system stability and compensate the network-induced delays and packet dropouts. Finally, a continuous stirred tank reactor system is given in the simulation part to demonstrate the effectiveness of the proposed method.

Predicting changes in hypertension control using electronic health records from a chronic disease management program

PubMed Central

Sun, Jimeng; McNaughton, Candace D; Zhang, Ping; Perer, Adam; Gkoulalas-Divanis, Aris; Denny, Joshua C; Kirby, Jacqueline; Lasko, Thomas; Saip, Alexander; Malin, Bradley A

2014-01-01

Objective Common chronic diseases such as hypertension are costly and difficult to manage. Our ultimate goal is to use data from electronic health records to predict the risk and timing of deterioration in hypertension control. Towards this goal, this work predicts the transition points at which hypertension is brought into, as well as pushed out of, control. Method In a cohort of 1294 patients with hypertension enrolled in a chronic disease management program at the Vanderbilt University Medical Center, patients are modeled as an array of features derived from the clinical domain over time, which are distilled into a core set using an information gain criteria regarding their predictive performance. A model for transition point prediction was then computed using a random forest classifier. Results The most predictive features for transitions in hypertension control status included hypertension assessment patterns, comorbid diagnoses, procedures and medication history. The final random forest model achieved a c-statistic of 0.836 (95% CI 0.830 to 0.842) and an accuracy of 0.773 (95% CI 0.766 to 0.780). Conclusions This study achieved accurate prediction of transition points of hypertension control status, an important first step in the long-term goal of developing personalized hypertension management plans. PMID:24045907

Predicting changes in hypertension control using electronic health records from a chronic disease management program.

PubMed

Sun, Jimeng; McNaughton, Candace D; Zhang, Ping; Perer, Adam; Gkoulalas-Divanis, Aris; Denny, Joshua C; Kirby, Jacqueline; Lasko, Thomas; Saip, Alexander; Malin, Bradley A

2014-01-01

Common chronic diseases such as hypertension are costly and difficult to manage. Our ultimate goal is to use data from electronic health records to predict the risk and timing of deterioration in hypertension control. Towards this goal, this work predicts the transition points at which hypertension is brought into, as well as pushed out of, control. In a cohort of 1294 patients with hypertension enrolled in a chronic disease management program at the Vanderbilt University Medical Center, patients are modeled as an array of features derived from the clinical domain over time, which are distilled into a core set using an information gain criteria regarding their predictive performance. A model for transition point prediction was then computed using a random forest classifier. The most predictive features for transitions in hypertension control status included hypertension assessment patterns, comorbid diagnoses, procedures and medication history. The final random forest model achieved a c-statistic of 0.836 (95% CI 0.830 to 0.842) and an accuracy of 0.773 (95% CI 0.766 to 0.780). This study achieved accurate prediction of transition points of hypertension control status, an important first step in the long-term goal of developing personalized hypertension management plans.

B-52 control configured vehicles: Flight test results

NASA Technical Reports Server (NTRS)

Arnold, J. I.; Murphy, F. B.

1976-01-01

Recently completed B-52 Control Configured Vehicles (CCV) flight testing is summarized, and results are compared to analytical predictions. Results are presented for five CCV system concepts: ride control, maneuver load control, flutter mode control, augmented stability, and fatigue reduction. Test results confirm analytical predictions and show that CCV system concepts achieve performance goals when operated individually or collectively.

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.

Differing Air Traffic Controller Responses to Similar Trajectory Prediction Errors

NASA Technical Reports Server (NTRS)

Mercer, Joey; Hunt-Espinosa, Sarah; Bienert, Nancy; Laraway, Sean

2016-01-01

A Human-In-The-Loop simulation was conducted in January of 2013 in the Airspace Operations Laboratory at NASA's Ames Research Center. The simulation airspace included two en route sectors feeding the northwest corner of Atlanta's Terminal Radar Approach Control. The focus of this paper is on how uncertainties in the study's trajectory predictions impacted the controllers ability to perform their duties. Of particular interest is how the controllers interacted with the delay information displayed in the meter list and data block while managing the arrival flows. Due to wind forecasts with 30-knot over-predictions and 30-knot under-predictions, delay value computations included errors of similar magnitude, albeit in opposite directions. However, when performing their duties in the presence of these errors, did the controllers issue clearances of similar magnitude, albeit in opposite directions?

Using VAPEPS for noise control on Space Station Freedom

NASA Technical Reports Server (NTRS)

Badilla, Gloria; Bergen, Thomas; Scharton, Terry

1991-01-01

Noise environmental control is an important design consideration for Space Station Freedom (SSF), both for crew safety and productivity. Acoustic noise requirements are established to eliminate fatigue and potential hearing loss by crew members from long-term exposure and to facilitate speech communication. VAPEPS (VibroAcoustic Payload Environment Prediction System) is currently being applied to SSF for prediction of the on-orbit noise and vibration environments induced in the 50 to 10,000 Hz frequency range. Various sources such as fans, pumps, centrifuges, exercise equipment, and other mechanical devices are used in the analysis. The predictions will be used in design tradeoff studies and to provide confidence that requirements will be met. Preliminary predictions show that the required levels will be exceeded unless substantial noise control measures are incorporated in the SSF design. Predicted levels for an SSF design without acoustic control treatments exceed requirements by 25 dB in some one-third octave frequency bands.

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.

Enhanced pid vs model predictive control applied to bldc motor

NASA Astrophysics Data System (ADS)

Gaya, M. S.; Muhammad, Auwal; Aliyu Abdulkadir, Rabiu; Salim, S. N. S.; Madugu, I. S.; Tijjani, Aminu; Aminu Yusuf, Lukman; Dauda Umar, Ibrahim; Khairi, M. T. M.

2018-01-01

BrushLess Direct Current (BLDC) motor is a multivariable and highly complex nonlinear system. Variation of internal parameter values with environment or reference signal increases the difficulty in controlling the BLDC effectively. Advanced control strategies (like model predictive control) often have to be integrated to satisfy the control desires. Enhancing or proper tuning of a conventional algorithm results in achieving the desired performance. This paper presents a performance comparison of Enhanced PID and Model Predictive Control (MPC) applied to brushless direct current motor. The simulation results demonstrated that the PSO-PID is slightly better than the PID and MPC in tracking the trajectory of the reference signal. The proposed scheme could be useful algorithms for the system.

Extended active disturbance rejection controller

NASA Technical Reports Server (NTRS)

Tian, Gang (Inventor); Gao, Zhiqiang (Inventor)

2012-01-01

Multiple designs, systems, methods and processes for controlling a system or plant using an extended active disturbance rejection control (ADRC) based controller are presented. The extended ADRC controller accepts sensor information from the plant. The sensor information is used in conjunction with an extended state observer in combination with a predictor that estimates and predicts the current state of the plant and a co-joined estimate of the system disturbances and system dynamics. The extended state observer estimates and predictions are used in conjunction with a control law that generates an input to the system based in part on the extended state observer estimates and predictions as well as a desired trajectory for the plant to follow.

Extended Active Disturbance Rejection Controller

NASA Technical Reports Server (NTRS)

Gao, Zhiqiang (Inventor); Tian, Gang (Inventor)

2016-01-01

Multiple designs, systems, methods and processes for controlling a system or plant using an extended active disturbance rejection control (ADRC) based controller are presented. The extended ADRC controller accepts sensor information from the plant. The sensor information is used in conjunction with an extended state observer in combination with a predictor that estimates and predicts the current state of the plant and a co-joined estimate of the system disturbances and system dynamics. The extended state observer estimates and predictions are used in conjunction with a control law that generates an input to the system based in part on the extended state observer estimates and predictions as well as a desired trajectory for the plant to follow.

Extended Active Disturbance Rejection Controller

NASA Technical Reports Server (NTRS)

Tian, Gang (Inventor); Gao, Zhiqiang (Inventor)

2014-01-01

Multiple designs, systems, methods and processes for controlling a system or plant using an extended active disturbance rejection control (ADRC) based controller are presented. The extended ADRC controller accepts sensor information from the plant. The sensor information is used in conjunction with an extended state observer in combination with a predictor that estimates and predicts the current state of the plant and a co-joined estimate of the system disturbances and system dynamics. The extended state observer estimates and predictions are used in conjunction with a control law that generates an input to the system based in part on the extended state observer estimates and predictions as well as a desired trajectory for the plant to follow.

Model Predictive Control of LCL Three-level Photovoltaic Grid-connected Inverter

NASA Astrophysics Data System (ADS)

Liang, Cheng; Tian, Engang; Pang, Baobing; Li, Juan; Yang, Yang

2018-05-01

In this paper, neutral point clamped three-level inverter circuit is analyzed to establish a mathematical model of the three-level inverter in the αβ coordinate system. The causes and harms of the midpoint potential imbalance problem are described. The paper use the method of model predictive control to control the entire inverter circuit[1]. The simulation model of the inverter system is built in Matlab/Simulink software. It is convenient to control the grid-connected current, suppress the unbalance of the midpoint potential and reduce the switching frequency by changing the weight coefficient in the cost function. The superiority of the model predictive control in the control method of the inverter system is verified.

Network control principles predict neuron function in the Caenorhabditis elegans connectome

PubMed Central

Chew, Yee Lian; Walker, Denise S.; Schafer, William R.; Barabási, Albert-László

2017-01-01

Recent studies on the controllability of complex systems offer a powerful mathematical framework to systematically explore the structure-function relationship in biological, social and technological networks1–3. Despite theoretical advances, we lack direct experimental proof of the validity of these widely used control principles. Here we fill this gap by applying a control framework to the connectome of the nematode C. elegans4–6, allowing us to predict the involvement of each C. elegans neuron in locomotor behaviours. We predict that control of the muscles or motor neurons requires twelve neuronal classes, which include neuronal groups previously implicated in locomotion by laser ablation7–13, as well as one previously uncharacterised neuron, PDB. We validate this prediction experimentally, finding that the ablation of PDB leads to a significant loss of dorsoventral polarity in large body bends. Importantly, control principles also allow us to investigate the involvement of individual neurons within each neuronal class. For example, we predict that, within the class of DD motor neurons, only three (DD04, DD05, or DD06) should affect locomotion when ablated individually. This prediction is also confirmed, with single-cell ablations of DD04 or DD05, but not DD02 or DD03, specifically affecting posterior body movements. Our predictions are robust to deletions of weak connections, missing connections, and rewired connections in the current connectome, indicating the potential applicability of this analytical framework to larger and less well-characterised connectomes. PMID:29045391

Network control principles predict neuron function in the Caenorhabditis elegans connectome

NASA Astrophysics Data System (ADS)

Yan, Gang; Vértes, Petra E.; Towlson, Emma K.; Chew, Yee Lian; Walker, Denise S.; Schafer, William R.; Barabási, Albert-László

2017-10-01

Recent studies on the controllability of complex systems offer a powerful mathematical framework to systematically explore the structure-function relationship in biological, social, and technological networks. Despite theoretical advances, we lack direct experimental proof of the validity of these widely used control principles. Here we fill this gap by applying a control framework to the connectome of the nematode Caenorhabditis elegans, allowing us to predict the involvement of each C. elegans neuron in locomotor behaviours. We predict that control of the muscles or motor neurons requires 12 neuronal classes, which include neuronal groups previously implicated in locomotion by laser ablation, as well as one previously uncharacterized neuron, PDB. We validate this prediction experimentally, finding that the ablation of PDB leads to a significant loss of dorsoventral polarity in large body bends. Importantly, control principles also allow us to investigate the involvement of individual neurons within each neuronal class. For example, we predict that, within the class of DD motor neurons, only three (DD04, DD05, or DD06) should affect locomotion when ablated individually. This prediction is also confirmed; single cell ablations of DD04 or DD05 specifically affect posterior body movements, whereas ablations of DD02 or DD03 do not. Our predictions are robust to deletions of weak connections, missing connections, and rewired connections in the current connectome, indicating the potential applicability of this analytical framework to larger and less well-characterized connectomes.

Network control principles predict neuron function in the Caenorhabditis elegans connectome.

PubMed

Yan, Gang; Vértes, Petra E; Towlson, Emma K; Chew, Yee Lian; Walker, Denise S; Schafer, William R; Barabási, Albert-László

2017-10-26

Recent studies on the controllability of complex systems offer a powerful mathematical framework to systematically explore the structure-function relationship in biological, social, and technological networks. Despite theoretical advances, we lack direct experimental proof of the validity of these widely used control principles. Here we fill this gap by applying a control framework to the connectome of the nematode Caenorhabditis elegans, allowing us to predict the involvement of each C. elegans neuron in locomotor behaviours. We predict that control of the muscles or motor neurons requires 12 neuronal classes, which include neuronal groups previously implicated in locomotion by laser ablation, as well as one previously uncharacterized neuron, PDB. We validate this prediction experimentally, finding that the ablation of PDB leads to a significant loss of dorsoventral polarity in large body bends. Importantly, control principles also allow us to investigate the involvement of individual neurons within each neuronal class. For example, we predict that, within the class of DD motor neurons, only three (DD04, DD05, or DD06) should affect locomotion when ablated individually. This prediction is also confirmed; single cell ablations of DD04 or DD05 specifically affect posterior body movements, whereas ablations of DD02 or DD03 do not. Our predictions are robust to deletions of weak connections, missing connections, and rewired connections in the current connectome, indicating the potential applicability of this analytical framework to larger and less well-characterized connectomes.

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…

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…

Multi-objective optimization for model predictive control.

PubMed

Wojsznis, Willy; Mehta, Ashish; Wojsznis, Peter; Thiele, Dirk; Blevins, Terry

2007-06-01

This paper presents a technique of multi-objective optimization for Model Predictive Control (MPC) where the optimization has three levels of the objective function, in order of priority: handling constraints, maximizing economics, and maintaining control. The greatest weights are assigned dynamically to control or constraint variables that are predicted to be out of their limits. The weights assigned for economics have to out-weigh those assigned for control objectives. Control variables (CV) can be controlled at fixed targets or within one- or two-sided ranges around the targets. Manipulated Variables (MV) can have assigned targets too, which may be predefined values or current actual values. This MV functionality is extremely useful when economic objectives are not defined for some or all the MVs. To achieve this complex operation, handle process outputs predicted to go out of limits, and have a guaranteed solution for any condition, the technique makes use of the priority structure, penalties on slack variables, and redefinition of the constraint and control model. An engineering implementation of this approach is shown in the MPC embedded in an industrial control system. The optimization and control of a distillation column, the standard Shell heavy oil fractionator (HOF) problem, is adequately achieved with this MPC.

Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abbas, Nikhar; Tom, Nathan M

2017-06-03

Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalmanmore » filter and autoregressive model to evaluate model predictive control performance.« less

Utilization of Model Predictive Control to Balance Power Absorption Against Load Accumulation: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Abbas, Nikhar; Tom, Nathan

Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalmanmore » filter and autoregressive model to evaluate model predictive control performance.« less

Active control strategy for the running attitude of high-speed train under strong crosswind condition

NASA Astrophysics Data System (ADS)

Li, Decang; Meng, Jianjun; Bai, Huan; Xu, Ruxun

2018-07-01

This paper focuses on the safety of high-speed trains under strong crosswind conditions. A new active control strategy is proposed based on the adaptive predictive control theory. The new control strategy aims at adjusting the attitudes of a train by controlling the new-type intelligent giant magnetostrictive actuator (GMA). It combined adaptive control with dynamic matrix control; parameters of predictive controller was real-time adjusted by online distinguishing to enhance the robustness of the control algorithm. On this basis, a correction control algorithm is also designed to regulate the parameters of predictive controller based on the step response of a controlled objective. Finally, the simulation results show that the proposed control strategy can adjust the running attitudes of high-speed trains under strong crosswind conditions; they also indicate that the new active control strategy is effective and applicable in improving the safety performance of a train based on a host-target computer technology provided by Matlab/Simulink.

Early Predictors of Middle School Fraction Knowledge

PubMed Central

Bailey, Drew H.; Siegler, Robert S.; Geary, David C.

2014-01-01

Recent findings that earlier fraction knowledge predicts later mathematics achievement raise the question of what predicts later fraction knowledge. Analyses of longitudinal data indicated that whole number magnitude knowledge in first grade predicted knowledge of fraction magnitudes in middle school, controlling for whole number arithmetic proficiency, domain general cognitive abilities, parental income and education, race, and gender. Similarly, knowledge of whole number arithmetic in first grade predicted knowledge of fraction arithmetic in middle school, controlling for whole number magnitude knowledge in first grade and the other control variables. In contrast, neither type of early whole number knowledge uniquely predicted middle school reading achievement. We discuss the implications of these findings for theories of numerical development and for improving mathematics learning. PMID:24576209

Prediction of Safety Stock Using Fuzzy Time Series (FTS) and Technology of Radio Frequency Identification (RFID) for Stock Control at Vendor Managed Inventory (VMI)

NASA Astrophysics Data System (ADS)

Mashuri, Chamdan; Suryono; Suseno, Jatmiko Endro

2018-02-01

This research was conducted by prediction of safety stock using Fuzzy Time Series (FTS) and technology of Radio Frequency Identification (RFID) for stock control at Vendor Managed Inventory (VMI). Well-controlled stock influenced company revenue and minimized cost. It discussed about information system of safety stock prediction developed through programming language of PHP. Input data consisted of demand got from automatic, online and real time acquisition using technology of RFID, then, sent to server and stored at online database. Furthermore, data of acquisition result was predicted by using algorithm of FTS applying universe of discourse defining and fuzzy sets determination. Fuzzy set result was continued to division process of universe of discourse in order to be to final step. Prediction result was displayed at information system dashboard developed. By using 60 data from demand data, prediction score was 450.331 and safety stock was 135.535. Prediction result was done by error deviation validation using Mean Square Percent Error of 15%. It proved that FTS was good enough in predicting demand and safety stock for stock control. For deeper analysis, researchers used data of demand and universe of discourse U varying at FTS to get various result based on test data used.

Depressive Symptoms in Adolescence: Longitudinal Links with Maternal Empathy and Psychological Control.

PubMed

Werner, Lente L A A; der Graaff, Jolien Van; Meeus, Wim H J; Branje, Susan J T

2016-08-01

Building on self-determination theory (Deci and Ryan in Psychological Inquiry, 11, 227-268. doi: 10.1207/S15327965PLI1104_01 , 2000), the aim of the current study was to examine the role of maternal affective and cognitive empathy in predicting adolescents' depressive symptoms, through mothers' psychological control use. Less empathic mothers may be less sensitive to adolescents' need for psychological autonomy, and thus prone to violating this need using psychological control, which may in turn predict adolescents' depressive symptoms. Moreover, according to interpersonal theory of depression (Coyne in Journal of Abnormal Psychology, 85, 186-193. doi: 10.1037/0021-843x.85.2.186 , 1976), adolescents' depressive symptoms may elicit rejecting responses, such as mothers' psychological control. For six waves, 497 adolescents (57 % boys, M age T1 = 13.03) annually completed questionnaires on depressive symptoms and maternal psychological control, while mothers reported on their empathy. Cross-lagged path analyses showed that throughout adolescence, both mothers' affective and cognitive empathy indirectly predicted boys' and girls' depressive symptoms, through psychological control. Additionally, depressive symptoms predicted psychological control for boys, and early adolescent girls. These results highlight the importance of (1) mothers' affective and cognitive empathy in predicting adolescents' depressive symptoms, and (2) taking gender into account when examining adolescent-effects.

Perceived Academic Control and Academic Emotions Predict Undergraduate University Student Success: Examining Effects on Dropout Intention and Achievement.

PubMed

Respondek, Lisa; Seufert, Tina; Stupnisky, Robert; Nett, Ulrike E

2017-01-01

The present study addressed concerns over the high risk of university students' academic failure. It examined how perceived academic control and academic emotions predict undergraduate students' academic success, conceptualized as both low dropout intention and high achievement (indicated by GPA). A cross-sectional survey was administered to 883 undergraduate students across all disciplines of a German STEM orientated university. The study additionally compared freshman students ( N = 597) vs. second-year students ( N = 286). Using structural equation modeling, for the overall sample of undergraduate students we found that perceived academic control positively predicted enjoyment and achievement, as well as negatively predicted boredom and anxiety. The prediction of dropout intention by perceived academic control was fully mediated via anxiety. When taking perceived academic control into account, we found no specific impact of enjoyment or boredom on the intention to dropout and no specific impact of all three academic emotions on achievement. The multi-group analysis showed, however, that perceived academic control, enjoyment, and boredom among second-year students had a direct relationship with dropout intention. A major contribution of the present study was demonstrating the important roles of perceived academic control and anxiety in undergraduate students' academic success. Concerning corresponding institutional support and future research, the results suggested distinguishing incoming from advanced undergraduate students.

The Science and Practice of Self-Control.

PubMed

Duckworth, Angela L; Seligman, Martin E P

2017-09-01

In 2005, we discovered that self-control "outdoes" talent in predicting academic success during adolescence. Since then, a surfeit of longitudinal evidence has affirmed the importance of self-control to achieving everyday goals that conflict with momentary temptations. In parallel, research that has "lumped" self-control with other facets of Big Five conscientiousness has shown the superior predictive power of this broad family of individual differences for diverse life outcomes. Self-control can also be "split" from related traits that in certain contexts demonstrate superior predictive power for achievement. Most important, both the "lumping" and "splitting" traditions have enhanced our understanding of the underlying mechanisms and antecedents of self-control. Collectively, progress over the past decade and a half suggests a bright future for the science and practice of self-control.

Level and change in perceived control predict 19-year mortality: findings from the Americans' changing lives study.

PubMed

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

2013-10-01

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 Lives Study (House et al., 1990; N = 2,840, M age at T2: 56.32 years, range: 28-99, 64% women), we examined the extent to which mean levels and rates of change in perceived control over 16 years predict all-cause mortality over a 19-year follow-up period. Shared growth-survival models revealed that higher levels of and more positive changes in perceived control were associated with longer survival times, independent of sociodemographic correlates. We found that level effects of control were accounted for by well-being and health factors, whereas the change effects of control were not. Analyses also indicated an age-differential pattern, with the predictive effects of both levels and trajectories of control declining in old age. We discuss possible pathways through which perceived control operates to facilitate key health outcomes and consider how their malleability and effectiveness may change with increasing age.

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

Relations of Effortful Control, Reactive Undercontrol, and Anger to Chinese Children’s Adjustment

PubMed Central

Eisenberg, Nancy; Ma, Yue; Chang, Lei; Zhou, Qing; West, Stephen G.; Aiken, Leona

2006-01-01

The purpose of the study was to examine the zero-order and unique relations of effortful attentional and behavioral regulation, reactive impulsivity, and anger/frustration to Chinese first and second graders’ internalizing and externalizing symptoms, as well as the prediction of adjustment from the interaction of anger/frustration and effortful control or impulsivity. A parent and teacher reported on children’s anger/frustration, effortful control, and impulsivity; parents reported on children’s internalizing symptoms; and teachers and peers reported on children’s externalizing symptoms. Children were classified as relatively high on externalizing (or comorbid), internalizing, or nondisordered. High impulsivity and teacher-reported anger/frustration, and low effortful control, were associated with externalizing problems whereas low effortful control and high parent-reported anger were predictive of internalizing problems. Unique prediction from effortful and reactive control was obtained and these predictors (especially when reported by teachers) often interacted with anger/frustration when predicting problem behavior classification. PMID:17459176

Perceived parenting dimensions and identity styles: exploring the socialization of adolescents' processing of identity-relevant information.

PubMed

Smits, Ilse; Soenens, Bart; Luyckx, Koen; Duriez, Bart; Berzonsky, Michael; Goossens, Luc

2008-04-01

This study examined the relationships between crucial dimensions of perceived parenting (support, behavioral control, and psychological control) and the three identity styles defined by Berzonsky [Berzonsky, M. D. (1990). Self-construction over the life span: A process perspective on identity formation. Advances in Personal Construct Psychology, 1, 155-186.]. Each identity style was hypothesized to relate to a specific pattern of perceived parenting dimensions. Hypotheses were examined in a sample of middle and late adolescents (n=674). An information-oriented style was positively predicted by parental support. Contrary to expectations, however, an information-oriented style was also positively predicted by psychological control. A normative identity style was positively predicted by support and behavioral control. In line with expectations, a diffuse-avoidant identity style was positively predicted by psychological control and negatively by maternal (but not paternal) behavioral control. Findings are discussed in light of the literature on the socialization of identity formation and directions for future research are outlined.

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

USDA-ARS?s Scientific Manuscript database

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 ...

The Minimal Control Principle Predicts Strategy Shifts in the Abstract Decision Making Task

ERIC Educational Resources Information Center

Taatgen, Niels A.

2011-01-01

The minimal control principle (Taatgen, 2007) predicts that people strive for problem-solving strategies that require as few internal control states as possible. In an experiment with the Abstract Decision Making task (ADM task; Joslyn & Hunt, 1998) the reward structure was manipulated to make either a low-control strategy or a high-strategy…

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.

Acceleration feedback improves balancing against reflex delay

PubMed Central

Insperger, Tamás; Milton, John; Stépán, Gábor

2013-01-01

A model for human postural balance is considered in which the time-delayed feedback depends on position, velocity and acceleration (proportional–derivative–acceleration (PDA) feedback). It is shown that a PDA controller is equivalent to a predictive controller, in which the prediction is based on the most recent information of the state, but the control input is not involved into the prediction. A PDA controller is superior to the corresponding proportional–derivative controller in the sense that the PDA controller can stabilize systems with approximately 40 per cent larger feedback delays. The addition of a sensory dead zone to account for the finite thresholds for detection by sensory receptors results in highly intermittent, complex oscillations that are a typical feature of human postural sway. PMID:23173196

Nonlinear model predictive control of a wave energy converter based on differential flatness parameterisation

NASA Astrophysics Data System (ADS)

Li, Guang

2017-01-01

This paper presents a fast constrained optimization approach, which is tailored for nonlinear model predictive control of wave energy converters (WEC). The advantage of this approach relies on its exploitation of the differential flatness of the WEC model. This can reduce the dimension of the resulting nonlinear programming problem (NLP) derived from the continuous constrained optimal control of WEC using pseudospectral method. The alleviation of computational burden using this approach helps to promote an economic implementation of nonlinear model predictive control strategy for WEC control problems. The method is applicable to nonlinear WEC models, nonconvex objective functions and nonlinear constraints, which are commonly encountered in WEC control problems. Numerical simulations demonstrate the efficacy of this approach.

Job Design and Ethnic Differences in Working Women’s Physical Activity

PubMed Central

Grzywacz, Joseph G.; Crain, A. Lauren; Martinson, Brian C.; Quandt, Sara A.

2014-01-01

Objective To document the role job control and schedule control play in shaping women’s physical activity, and how it delineates educational and racial variability in associations of job and social control with physical activity. Methods Prospective data were obtained from a community-based sample of working women (N = 302). Validated instruments measured job control and schedule control. Steps per day were assessed using New Lifestyles 800 activity monitors. Results Greater job control predicted more steps per day, whereas greater schedule control predicted fewer steps. Small indirect associations between ethnicity and physical activity were observed among women with a trade school degree or less but not for women with a college degree. Conclusions Low job control created barriers to physical activity among working women with a trade school degree or less. Greater schedule control predicted less physical activity, suggesting women do not use time “created” by schedule flexibility for personal health enhancement. PMID:24034681

Job design and ethnic differences in working women's physical activity.

PubMed

Grzywacz, Joseph G; Crain, A Lauren; Martinson, Brian C; Quandt, Sara A

2014-01-01

To document the role job control and schedule control play in shaping women's physical activity, and how it delineates educational and racial variability in associations of job and social control with physical activity. Prospective data were obtained from a community-based sample of working women (N = 302). Validated instruments measured job control and schedule control. Steps per day were assessed using New Lifestyles 800 activity monitors. Greater job control predicted more steps per day, whereas greater schedule control predicted fewer steps. Small indirect associations between ethnicity and physical activity were observed among women with a trade school degree or less but not for women with a college degree. Low job control created barriers to physical activity among working women with a trade school degree or less. Greater schedule control predicted less physical activity, suggesting women do not use time "created" by schedule flexibility for personal health enhancement.

Forward and Inverse Predictive Model for the Trajectory Tracking Control of a Lower Limb Exoskeleton for Gait Rehabilitation: Simulation modelling analysis

NASA Astrophysics Data System (ADS)

Zakaria, M. A.; Majeed, A. P. P. A.; Taha, Z.; Alim, M. M.; Baarath, K.

2018-03-01

The movement of a lower limb exoskeleton requires a reasonably accurate control method to allow for an effective gait therapy session to transpire. Trajectory tracking is a nontrivial means of passive rehabilitation technique to correct the motion of the patients’ impaired limb. This paper proposes an inverse predictive model that is coupled together with the forward kinematics of the exoskeleton to estimate the behaviour of the system. A conventional PID control system is used to converge the required joint angles based on the desired input from the inverse predictive model. It was demonstrated through the present study, that the inverse predictive model is capable of meeting the trajectory demand with acceptable error tolerance. The findings further suggest the ability of the predictive model of the exoskeleton to predict a correct joint angle command to the system.

Neural network based automatic limit prediction and avoidance system and method

NASA Technical Reports Server (NTRS)

Calise, Anthony J. (Inventor); Prasad, Jonnalagadda V. R. (Inventor); Horn, Joseph F. (Inventor)

2001-01-01

A method for performance envelope boundary cueing for a vehicle control system comprises the steps of formulating a prediction system for a neural network and training the neural network to predict values of limited parameters as a function of current control positions and current vehicle operating conditions. The method further comprises the steps of applying the neural network to the control system of the vehicle, where the vehicle has capability for measuring current control positions and current vehicle operating conditions. The neural network generates a map of current control positions and vehicle operating conditions versus the limited parameters in a pre-determined vehicle operating condition. The method estimates critical control deflections from the current control positions required to drive the vehicle to a performance envelope boundary. Finally, the method comprises the steps of communicating the critical control deflection to the vehicle control system; and driving the vehicle control system to provide a tactile cue to an operator of the vehicle as the control positions approach the critical control deflections.

REVIEW: Widespread access to predictive models in the motor system: a short review

NASA Astrophysics Data System (ADS)

Davidson, Paul R.; Wolpert, Daniel M.

2005-09-01

Recent behavioural and computational studies suggest that access to internal predictive models of arm and object dynamics is widespread in the sensorimotor system. Several systems, including those responsible for oculomotor and skeletomotor control, perceptual processing, postural control and mental imagery, are able to access predictions of the motion of the arm. A capacity to make and use predictions of object dynamics is similarly widespread. Here, we review recent studies looking at the predictive capacity of the central nervous system which reveal pervasive access to forward models of the environment.

Informal Control Networks and Adolescent Orientations Toward Alcohol Use.

ERIC Educational Resources Information Center

Johnson, Kirk Alan

1986-01-01

Investigated the roles parental and peer informal control structures play in predicting adolescent alcohol use and abuse, using data from high school students (N=345). Suggests that "youth world" and "adult world" control structures are predictive of adolescents' orientations toward alcohol, though generally in different…

Detecting Controller Malfunctions in Electromagnetic Environments. Part 1; Modeling and Estimation of Nominal System Function

NASA Technical Reports Server (NTRS)

Weinstein, Bernice

1999-01-01

A strategy for detecting control law calculation errors in critical flight control computers during laboratory validation testing is presented. This paper addresses Part I of the detection strategy which involves the use of modeling of the aircraft control laws and the design of Kalman filters to predict the correct control commands. Part II of the strategy which involves the use of the predicted control commands to detect control command errors is presented in the companion paper.

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…

A Novel Approach to Adaptive Flow Separation Control

DTIC Science & Technology

2016-09-03

particular, it considers control of flow separation over a NACA-0025 airfoil using microjet actuators and develops Adaptive Sampling Based Model...Predictive Control ( Adaptive SBMPC), a novel approach to Nonlinear Model Predictive Control that applies the Minimal Resource Allocation Network...Distribution Unlimited UU UU UU UU 03-09-2016 1-May-2013 30-Apr-2016 Final Report: A Novel Approach to Adaptive Flow Separation Control The views, opinions

Effects of external loads on balance control during upright stance: experimental results and model-based predictions.

PubMed

Qu, Xingda; Nussbaum, Maury A

2009-01-01

The purpose of this study was to identify the effects of external loads on balance control during upright stance, and to examine the ability of a new balance control model to predict these effects. External loads were applied to 12 young, healthy participants, and effects on balance control were characterized by center-of-pressure (COP) based measures. Several loading conditions were studied, involving combinations of load mass (10% and 20% of individual body mass) and height (at or 15% of stature above the whole-body COM). A balance control model based on an optimal control strategy was used to predict COP time series. It was assumed that a given individual would adopt the same neural optimal control mechanisms, identified in a no-load condition, under diverse external loading conditions. With the application of external loads, COP mean velocity in the anterior-posterior direction and RMS distance in the medial-lateral direction increased 8.1% and 10.4%, respectively. Predicted COP mean velocity and RMS distance in the anterior-posterior direction also increased with external loading, by 11.1% and 2.9%, respectively. Both experimental COP data and model-based predictions provided the same general conclusion, that application of larger external loads and loads more superior to the whole body center of mass lead to less effective postural control and perhaps a greater risk of loss of balance or falls. Thus, it can be concluded that the assumption about consistency in control mechanisms was partially supported, and it is the mechanical changes induced by external loads that primarily affect balance control.

Cooperative airframe/propulsion control for supersonic cruise aircraft

NASA Technical Reports Server (NTRS)

Schweikhard, W. G.; Berry, D. T.

1974-01-01

Interactions between propulsion systems and flight controls have emerged as a major control problem on supersonic cruise aircraft. This paper describes the nature and causes of these interactions and the approaches to predicting and solving the problem. Integration of propulsion and flight control systems appears to be the most promising solution if the interaction effects can be adequately predicted early in the vehicle design. Significant performance, stability, and control improvements may be realized from a cooperative control system.

Application of real-time machine learning to myoelectric prosthesis control: A case series in adaptive switching.

PubMed

Edwards, Ann L; Dawson, Michael R; Hebert, Jacqueline S; Sherstan, Craig; Sutton, Richard S; Chan, K Ming; Pilarski, Patrick M

2016-10-01

Myoelectric prostheses currently used by amputees can be difficult to control. Machine learning, and in particular learned predictions about user intent, could help to reduce the time and cognitive load required by amputees while operating their prosthetic device. The goal of this study was to compare two switching-based methods of controlling a myoelectric arm: non-adaptive (or conventional) control and adaptive control (involving real-time prediction learning). Case series study. We compared non-adaptive and adaptive control in two different experiments. In the first, one amputee and one non-amputee subject controlled a robotic arm to perform a simple task; in the second, three able-bodied subjects controlled a robotic arm to perform a more complex task. For both tasks, we calculated the mean time and total number of switches between robotic arm functions over three trials. Adaptive control significantly decreased the number of switches and total switching time for both tasks compared with the conventional control method. Real-time prediction learning was successfully used to improve the control interface of a myoelectric robotic arm during uninterrupted use by an amputee subject and able-bodied subjects. Adaptive control using real-time prediction learning has the potential to help decrease both the time and the cognitive load required by amputees in real-world functional situations when using myoelectric prostheses. © The International Society for Prosthetics and Orthotics 2015.

Comparison of simulator fidelity model predictions with in-simulator evaluation data

NASA Technical Reports Server (NTRS)

Parrish, R. V.; Mckissick, B. T.; Ashworth, B. R.

1983-01-01

A full factorial in simulator experiment of a single axis, multiloop, compensatory pitch tracking task is described. The experiment was conducted to provide data to validate extensions to an analytic, closed loop model of a real time digital simulation facility. The results of the experiment encompassing various simulation fidelity factors, such as visual delay, digital integration algorithms, computer iteration rates, control loading bandwidths and proprioceptive cues, and g-seat kinesthetic cues, are compared with predictions obtained from the analytic model incorporating an optimal control model of the human pilot. The in-simulator results demonstrate more sensitivity to the g-seat and to the control loader conditions than were predicted by the model. However, the model predictions are generally upheld, although the predicted magnitudes of the states and of the error terms are sometimes off considerably. Of particular concern is the large sensitivity difference for one control loader condition, as well as the model/in-simulator mismatch in the magnitude of the plant states when the other states match.

An introduction to high speed aircraft noise prediction

NASA Technical Reports Server (NTRS)

Wilson, Mark R.

1992-01-01

The Aircraft Noise Prediction Program's High Speed Research prediction system (ANOPP-HSR) is introduced. This mini-manual is an introduction which gives a brief overview of the ANOPP system and the components of the HSR prediction method. ANOPP information resources are given. Twelve of the most common ANOPP-HSR control statements are described. Each control statement's purpose and format are stated and relevant examples are provided. More detailed examples of the use of the control statements are presented in the manual along with ten ANOPP-HSR templates. The purpose of the templates is to provide the user with working ANOPP-HSR programs which can be modified to serve particular prediction requirements. Also included in this manual is a brief discussion of common errors and how to solve these problems. The appendices include the following useful information: a summary of all ANOPP-HSR functional research modules, a data unit directory, a discussion of one of the more complex control statements, and input data unit and table examples.

Descent advisor preliminary field test

NASA Technical Reports Server (NTRS)

Green, Steven M.; Vivona, Robert A.; Sanford, Beverly

1995-01-01

A field test of the Descent Advisor (DA) automation tool was conducted at the Denver Air Route Traffic Control Center in September 1994. DA is being developed to assist Center controllers in the efficient management and control of arrival traffic. DA generates advisories, based on trajectory predictions, to achieve accurate meter-fix arrival times in a fuel efficient manner while assisting the controller with the prediction and resolution of potential conflicts. The test objectives were to evaluate the accuracy of DA trajectory predictions for conventional- and flight-management-system-equipped jet transports, to identify significant sources of trajectory prediction error, and to investigate procedural and training issues (both air and ground) associated with DA operations. Various commercial aircraft (97 flights total) and a Boeing 737-100 research aircraft participated in the test. Preliminary results from the primary test set of 24 commercial flights indicate a mean DA arrival time prediction error of 2.4 sec late with a standard deviation of 13.1 sec. This paper describes the field test and presents preliminary results for the commercial flights.

Model predictive and reallocation problem for CubeSat fault recovery and attitude control

NASA Astrophysics Data System (ADS)

Franchi, Loris; Feruglio, Lorenzo; Mozzillo, Raffaele; Corpino, Sabrina

2018-01-01

In recent years, thanks to the increase of the know-how on machine-learning techniques and the advance of the computational capabilities of on-board processing, expensive computing algorithms, such as Model Predictive Control, have begun to spread in space applications even on small on-board processor. The paper presents an algorithm for an optimal fault recovery of a 3U CubeSat, developed in MathWorks Matlab & Simulink environment. This algorithm involves optimization techniques aiming at obtaining the optimal recovery solution, and involves a Model Predictive Control approach for the attitude control. The simulated system is a CubeSat in Low Earth Orbit: the attitude control is performed with three magnetic torquers and a single reaction wheel. The simulation neglects the errors in the attitude determination of the satellite, and focuses on the recovery approach and control method. The optimal recovery approach takes advantage of the properties of magnetic actuation, which gives the possibility of the redistribution of the control action when a fault occurs on a single magnetic torquer, even in absence of redundant actuators. In addition, the paper presents the results of the implementation of Model Predictive approach to control the attitude of the satellite.

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.

SEIZURE PREDICTION: THE FOURTH INTERNATIONAL WORKSHOP

PubMed Central

Zaveri, Hitten P.; Frei, Mark G.; Arthurs, Susan; Osorio, Ivan

2010-01-01

The recently convened Fourth International Workshop on Seizure Prediction (IWSP4) brought together a diverse international group of investigators, from academia and industry, including epileptologists, neurosurgeons, neuroscientists, computer scientists, engineers, physicists, and mathematicians who are conducting interdisciplinary research on the prediction and control of seizures. IWSP4 allowed the presentation and discussion of results, an exchange of ideas, an assessment of the status of seizure prediction, control and related fields and the fostering of collaborative projects. PMID:20674508

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. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

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. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Controlling chaos faster.

PubMed

Bick, Christian; Kolodziejski, Christoph; Timme, Marc

2014-09-01

Predictive feedback control is an easy-to-implement method to stabilize unknown unstable periodic orbits in chaotic dynamical systems. Predictive feedback control is severely limited because asymptotic convergence speed decreases with stronger instabilities which in turn are typical for larger target periods, rendering it harder to effectively stabilize periodic orbits of large period. Here, we study stalled chaos control, where the application of control is stalled to make use of the chaotic, uncontrolled dynamics, and introduce an adaptation paradigm to overcome this limitation and speed up convergence. This modified control scheme is not only capable of stabilizing more periodic orbits than the original predictive feedback control but also speeds up convergence for typical chaotic maps, as illustrated in both theory and application. The proposed adaptation scheme provides a way to tune parameters online, yielding a broadly applicable, fast chaos control that converges reliably, even for periodic orbits of large period.

Event-rate and delta inflation when evaluating mortality as a primary outcome from randomized controlled trials of nutritional interventions during critical illness: a systematic review.

PubMed

Summers, Matthew J; Chapple, Lee-anne S; McClave, Stephen A; Deane, Adam M

2016-04-01

There is a lack of high-quality evidence that proves that nutritional interventions during critical illness reduce mortality. We evaluated whether power calculations for randomized controlled trials (RCTs) of nutritional interventions that used mortality as the primary outcome were realistic, and whether overestimation was systematic in the studies identified to determine whether this was due to overestimates of event rate or delta. A systematic review of the literature between 2005 and 2015 was performed to identify RCTs of nutritional interventions administered to critically ill adults that had mortality as the primary outcome. Predicted event rate (predicted mortality during the control), predicted mortality during intervention, predicted delta (predicted difference between mortality during the control and intervention), actual event rate (observed mortality during control), observed mortality during intervention, and actual delta (difference between observed mortality during the control and intervention) were recorded. The event-rate gap (predicted event rate minus observed event rate), the delta gap (predicted delta minus observed delta), and the predicted number needed to treat were calculated. Data are shown as median (range). Fourteen articles were extracted, with power calculations provided for 10 studies. The predicted event rate was 29.9% (20.0–52.4%), and the predicted delta was 7.9% (3.0–20.0%). If the study hypothesis was proven correct then, on the basis of the power calculations, the number needed to treat would have been 12.7 (5.0–33.3) patients. The actual event rate was 25.3% (6.1–50.0%), the observed mortality during the intervention was 24.4% (6.3–39.7%), and the actual delta was 0.5% (−10.2–10.3%), such that the event-rate gap was 2.6% (−3.9–23.7%) and delta gap was 7.5% (3.2–25.2%). Overestimates of delta occur frequently in RCTs of nutritional interventions in the critically ill that are powered to determine a mortality benefit. Delta inflation may explain the number of "negative" studies in this field of research.

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.

Control surface hinge moment prediction using computational fluid dynamics

NASA Astrophysics Data System (ADS)

Simpson, Christopher David

The following research determines the feasibility of predicting control surface hinge moments using various computational methods. A detailed analysis is conducted using a 2D GA(W)-1 airfoil with a 20% plain flap. Simple hinge moment prediction methods are tested, including empirical Datcom relations and XFOIL. Steady-state and time-accurate turbulent, viscous, Navier-Stokes solutions are computed using Fun3D. Hinge moment coefficients are computed. Mesh construction techniques are discussed. An adjoint-based mesh adaptation case is also evaluated. An NACA 0012 45-degree swept horizontal stabilizer with a 25% elevator is also evaluated using Fun3D. Results are compared with experimental wind-tunnel data obtained from references. Finally, the costs of various solution methods are estimated. Results indicate that while a steady-state Navier-Stokes solution can accurately predict control surface hinge moments for small angles of attack and deflection angles, a time-accurate solution is necessary to accurately predict hinge moments in the presence of flow separation. The ability to capture the unsteady vortex shedding behavior present in moderate to large control surface deflections is found to be critical to hinge moment prediction accuracy. Adjoint-based mesh adaptation is shown to give hinge moment predictions similar to a globally-refined mesh for a steady-state 2D simulation.

Perceived Academic Control and Academic Emotions Predict Undergraduate University Student Success: Examining Effects on Dropout Intention and Achievement

PubMed Central

Respondek, Lisa; Seufert, Tina; Stupnisky, Robert; Nett, Ulrike E.

2017-01-01

The present study addressed concerns over the high risk of university students' academic failure. It examined how perceived academic control and academic emotions predict undergraduate students' academic success, conceptualized as both low dropout intention and high achievement (indicated by GPA). A cross-sectional survey was administered to 883 undergraduate students across all disciplines of a German STEM orientated university. The study additionally compared freshman students (N = 597) vs. second-year students (N = 286). Using structural equation modeling, for the overall sample of undergraduate students we found that perceived academic control positively predicted enjoyment and achievement, as well as negatively predicted boredom and anxiety. The prediction of dropout intention by perceived academic control was fully mediated via anxiety. When taking perceived academic control into account, we found no specific impact of enjoyment or boredom on the intention to dropout and no specific impact of all three academic emotions on achievement. The multi-group analysis showed, however, that perceived academic control, enjoyment, and boredom among second-year students had a direct relationship with dropout intention. A major contribution of the present study was demonstrating the important roles of perceived academic control and anxiety in undergraduate students' academic success. Concerning corresponding institutional support and future research, the results suggested distinguishing incoming from advanced undergraduate students. PMID:28326043

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.

Dynamics and control of quadcopter using linear model predictive control approach

NASA Astrophysics Data System (ADS)

Islam, M.; Okasha, M.; Idres, M. M.

2017-12-01

This paper investigates the dynamics and control of a quadcopter using the Model Predictive Control (MPC) approach. The dynamic model is of high fidelity and nonlinear, with six degrees of freedom that include disturbances and model uncertainties. The control approach is developed based on MPC to track different reference trajectories ranging from simple ones such as circular to complex helical trajectories. In this control technique, a linearized model is derived and the receding horizon method is applied to generate the optimal control sequence. Although MPC is computer expensive, it is highly effective to deal with the different types of nonlinearities and constraints such as actuators’ saturation and model uncertainties. The MPC parameters (control and prediction horizons) are selected by trial-and-error approach. Several simulation scenarios are performed to examine and evaluate the performance of the proposed control approach using MATLAB and Simulink environment. Simulation results show that this control approach is highly effective to track a given reference trajectory.

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

Adaptive MPC based on MIMO ARX-Laguerre model.

PubMed

Ben Abdelwahed, Imen; Mbarek, Abdelkader; Bouzrara, Kais

2017-03-01

This paper proposes a method for synthesizing an adaptive predictive controller using a reduced complexity model. This latter is given by the projection of the ARX model on Laguerre bases. The resulting model is entitled MIMO ARX-Laguerre and it is characterized by an easy recursive representation. The adaptive predictive control law is computed based on multi-step-ahead finite-element predictors, identified directly from experimental input/output data. The model is tuned in each iteration by an online identification algorithms of both model parameters and Laguerre poles. The proposed approach avoids time consuming numerical optimization algorithms associated with most common linear predictive control strategies, which makes it suitable for real-time implementation. The method is used to synthesize and test in numerical simulations adaptive predictive controllers for the CSTR process benchmark. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

A predictive control framework for optimal energy extraction of wind farms

NASA Astrophysics Data System (ADS)

Vali, M.; van Wingerden, J. W.; Boersma, S.; Petrović, V.; Kühn, M.

2016-09-01

This paper proposes an adjoint-based model predictive control for optimal energy extraction of wind farms. It employs the axial induction factor of wind turbines to influence their aerodynamic interactions through the wake. The performance index is defined here as the total power production of the wind farm over a finite prediction horizon. A medium-fidelity wind farm model is utilized to predict the inflow propagation in advance. The adjoint method is employed to solve the formulated optimization problem in a cost effective way and the first part of the optimal solution is implemented over the control horizon. This procedure is repeated at the next controller sample time providing the feedback into the optimization. The effectiveness and some key features of the proposed approach are studied for a two turbine test case through simulations.

A reinforcement sensitivity model of affective and behavioral dysregulation in marijuana use and associated problems.

PubMed

Emery, Noah N; Simons, Jeffrey S

2017-08-01

This study tested a model linking sensitivity to punishment (SP) and reward (SR) to marijuana use and problems via affect lability and poor control. A 6-month prospective design was used in a sample of 2,270 young-adults (64% female). The hypothesized SP × SR interaction did not predict affect lability or poor control, but did predict use likelihood at baseline. At low levels of SR, SP was associated with an increased likelihood of abstaining, which was attenuated as SR increased. SP and SR displayed positive main effects on both affect lability and poor control. Affect lability and poor control, in turn, mediated effects on the marijuana outcomes. Poor control predicted both increased marijuana use and, controlling for use level, greater intensity of problems. Affect lability predicted greater intensity of problems, but was not associated with use level. There were few prospective effects. SR consistently predicted greater marijuana use and problems. SP however, exhibited both risk and protective pathways. Results indicate that SP is associated with a decreased likelihood of marijuana use. However, once use is initiated SP is associated with increased risk of problems, in part, due to its effects on both affect and behavioral dysregulation. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Measured vs. Predicted Pedestal Pressure During RMP ELM Control in DIII-D

NASA Astrophysics Data System (ADS)

Zywicki, Bailey; Fenstermacher, Max; Groebner, Richard; Meneghini, Orso

2017-10-01

From database analysis of DIII-D plasmas with Resonant Magnetic Perturbations (RMPs) for ELM control, we will compare the experimental pedestal pressure (p_ped) to EPED code predictions and present the dependence of any p_ped differences from EPED on RMP parameters not included in the EPED model e.g. RMP field strength, toroidal and poloidal spectrum etc. The EPED code, based on Peeling-Ballooning and Kinetic Ballooning instability constraints, will also be used by ITER to predict the H-mode p_ped without RMPs. ITER plans to use RMPs as an effective ELM control method. The need to control ELMs in ITER is of the utmost priority, as it directly correlates to the lifetime of the plasma facing components. An accurate means of determining the impact of RMP ELM control on the p_ped is needed, because the device fusion power is strongly dependent on p_ped. With this new collection of data, we aim to provide guidance to predictions of the ITER pedestal during RMP ELM control that can be incorporated in a future predictive code. Work supported in part by US DoE under the Science Undergraduate Laboratory Internship (SULI) program and under DE-FC02-04ER54698, and DE-AC52-07NA27344.

A Discrete-Time Average Model Based Predictive Control for Quasi-Z-Source Inverter

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, Yushan; Abu-Rub, Haitham; Xue, Yaosuo

A discrete-time average model-based predictive control (DTA-MPC) is proposed for a quasi-Z-source inverter (qZSI). As a single-stage inverter topology, the qZSI regulates the dc-link voltage and the ac output voltage through the shoot-through (ST) duty cycle and the modulation index. Several feedback strategies have been dedicated to produce these two control variables, among which the most popular are the proportional–integral (PI)-based control and the conventional model-predictive control (MPC). However, in the former, there are tradeoffs between fast response and stability; the latter is robust, but at the cost of high calculation burden and variable switching frequency. Moreover, they require anmore » elaborated design or fine tuning of controller parameters. The proposed DTA-MPC predicts future behaviors of the ST duty cycle and modulation signals, based on the established discrete-time average model of the quasi-Z-source (qZS) inductor current, the qZS capacitor voltage, and load currents. The prediction actions are applied to the qZSI modulator in the next sampling instant, without the need of other controller parameters’ design. A constant switching frequency and significantly reduced computations are achieved with high performance. Transient responses and steady-state accuracy of the qZSI system under the proposed DTA-MPC are investigated and compared with the PI-based control and the conventional MPC. Simulation and experimental results verify the effectiveness of the proposed approach for the qZSI.« less

A Discrete-Time Average Model Based Predictive Control for Quasi-Z-Source Inverter

DOE PAGES

Liu, Yushan; Abu-Rub, Haitham; Xue, Yaosuo; ...

2017-12-25

A discrete-time average model-based predictive control (DTA-MPC) is proposed for a quasi-Z-source inverter (qZSI). As a single-stage inverter topology, the qZSI regulates the dc-link voltage and the ac output voltage through the shoot-through (ST) duty cycle and the modulation index. Several feedback strategies have been dedicated to produce these two control variables, among which the most popular are the proportional–integral (PI)-based control and the conventional model-predictive control (MPC). However, in the former, there are tradeoffs between fast response and stability; the latter is robust, but at the cost of high calculation burden and variable switching frequency. Moreover, they require anmore » elaborated design or fine tuning of controller parameters. The proposed DTA-MPC predicts future behaviors of the ST duty cycle and modulation signals, based on the established discrete-time average model of the quasi-Z-source (qZS) inductor current, the qZS capacitor voltage, and load currents. The prediction actions are applied to the qZSI modulator in the next sampling instant, without the need of other controller parameters’ design. A constant switching frequency and significantly reduced computations are achieved with high performance. Transient responses and steady-state accuracy of the qZSI system under the proposed DTA-MPC are investigated and compared with the PI-based control and the conventional MPC. Simulation and experimental results verify the effectiveness of the proposed approach for the qZSI.« less

Improved disturbance rejection for predictor-based control of MIMO linear systems with input delay

NASA Astrophysics Data System (ADS)

Shi, Shang; Liu, Wenhui; Lu, Junwei; Chu, Yuming

2018-02-01

In this paper, we are concerned with the predictor-based control of multi-input multi-output (MIMO) linear systems with input delay and disturbances. By taking the future values of disturbances into consideration, a new improved predictive scheme is proposed. Compared with the existing predictive schemes, our proposed predictive scheme can achieve a finite-time exact state prediction for some smooth disturbances including the constant disturbances, and a better disturbance attenuation can also be achieved for a large class of other time-varying disturbances. The attenuation of mismatched disturbances for second-order linear systems with input delay is also investigated by using our proposed predictor-based controller.

Control of Uncertain Systems under Constraints: Switching Horizon Predictive Control of Persistently Disturbed Input-Saturated Plants

DTIC Science & Technology

2006-12-01

on at any time from a family of candidate feedback-gains so as to control a discrete- time input-saturated LTI system possibly subject to persistent... times robustness Mosca, E. (2006) Control of Uncertain Systems under Constraints: Switching Horizon Predictive Control of Persistently Disturbed...feedback controls u = f(x̂) (3) so as to ensure, under suitable conditions, stability in the noiseless case as well as finite l∞-induced gain of the

Predicting Minimum Control Speed on the Ground (VMCG) and Minimum Control Airspeed (VMCA) of Engine Inoperative Flight Using Aerodynamic Database and Propulsion Database Generators

NASA Astrophysics Data System (ADS)

Hadder, Eric Michael

There are many computer aided engineering tools and software used by aerospace engineers to design and predict specific parameters of an airplane. These tools help a design engineer predict and calculate such parameters such as lift, drag, pitching moment, takeoff range, maximum takeoff weight, maximum flight range and much more. However, there are very limited ways to predict and calculate the minimum control speeds of an airplane in engine inoperative flight. There are simple solutions, as well as complicated solutions, yet there is neither standard technique nor consistency throughout the aerospace industry. To further complicate this subject, airplane designers have the option of using an Automatic Thrust Control System (ATCS), which directly alters the minimum control speeds of an airplane. This work addresses this issue with a tool used to predict and calculate the Minimum Control Speed on the Ground (VMCG) as well as the Minimum Control Airspeed (VMCA) of any existing or design-stage airplane. With simple line art of an airplane, a program called VORLAX is used to generate an aerodynamic database used to calculate the stability derivatives of an airplane. Using another program called Numerical Propulsion System Simulation (NPSS), a propulsion database is generated to use with the aerodynamic database to calculate both VMCG and VMCA. This tool was tested using two airplanes, the Airbus A320 and the Lockheed Martin C130J-30 Super Hercules. The A320 does not use an Automatic Thrust Control System (ATCS), whereas the C130J-30 does use an ATCS. The tool was able to properly calculate and match known values of VMCG and VMCA for both of the airplanes. The fact that this tool was able to calculate the known values of VMCG and VMCA for both airplanes means that this tool would be able to predict the VMCG and VMCA of an airplane in the preliminary stages of design. This would allow design engineers the ability to use an Automatic Thrust Control System (ATCS) as part of the design of an airplane and still have the ability to predict the VMCG and VMCA of the airplane.

Implicit but not explicit self-esteem predicts future depressive symptomatology.

PubMed

Franck, Erik; De Raedt, Rudi; De Houwer, Jan

2007-10-01

To date, research on the predictive validity of implicit self-esteem for depressive relapse is very sparse. In the present study, we assessed implicit self-esteem using the Name Letter Preference Task and explicit self-esteem using the Rosenberg self-esteem scale in a group of currently depressed patients, formerly depressed individuals, and never depressed controls. In addition, we examined the predictive validity of explicit, implicit, and the interaction of explicit and implicit self-esteem in predicting future symptoms of depression in formerly depressed individuals and never depressed controls. The results showed that currently depressed individuals reported a lower explicit self-esteem as compared to formerly depressed individuals and never depressed controls. In line with previous research, all groups showed a positive implicit self-esteem not different from each other. Furthermore, after controlling for initial depressive symptomatology, implicit but not explicit self-esteem significantly predicted depressive symptoms at six months follow-up. Although implicit self-esteem assessed with the Name Letter Preference Test was not different between formerly depressed individuals and never depressed controls, the findings suggest it is an interesting variable in the study of vulnerability for depression relapse.

Class-Related Emotions in Secondary Physical Education: A Control-Value Theory Approach

ERIC Educational Resources Information Center

Simonton, Kelly L.; Garn, Alex C.; Solmon, Melinda Ann

2017-01-01

Purpose: Grounded in control-value theory, a model of students' achievement emotions in physical education (PE) was investigated. Methods: A path analysis tested hypotheses that students' (N = 529) perceptions of teacher responsiveness, assertiveness, and clarity predict control and value beliefs which, in turn, predict enjoyment and boredom.…

NATO IST 124 Experimentation Instructions

DTIC Science & Technology

2016-11-10

more reliable and predictable network performance through adaptive and efficient control schemes . This report provides guidance and instructions for...tactical heterogeneous networks for more reliable and predictable network performance through adaptive and efficient control schemes . This report

Control of Systems With Slow Actuators Using Time Scale Separation

NASA Technical Reports Server (NTRS)

Stepanyan, Vehram; Nguyen, Nhan

2009-01-01

This paper addresses the problem of controlling a nonlinear plant with a slow actuator using singular perturbation method. For the known plant-actuator cascaded system the proposed scheme achieves tracking of a given reference model with considerably less control demand than would otherwise result when using conventional design techniques. This is the consequence of excluding the small parameter from the actuator dynamics via time scale separation. The resulting tracking error is within the order of this small parameter. For the unknown system the adaptive counterpart is developed based on the prediction model, which is driven towards the reference model by the control design. It is proven that the prediction model tracks the reference model with an error proportional to the small parameter, while the prediction error converges to zero. The resulting closed-loop system with all prediction models and adaptive laws remains stable. The benefits of the approach are demonstrated in simulation studies and compared to conventional control approaches.

Mothers' and Fathers' Worry and Over-Control: One Step Closer to Understanding Early Adolescent Social Anxiety.

PubMed

Van Zalk, Nejra; Tillfors, Maria; Trost, Kari

2018-05-05

This study investigated the links between parental worry, parental over-control and adolescent social anxiety in parent-adolescent dyads. Using a longitudinal sample of adolescents (M age  = 14.28) and their parents (224 mother-daughter, 234 mother-son, 51 father-daughter, and 47 father-son dyads), comparisons were conducted using cross-lagged path models across two time points. We used adolescent reports of social anxiety and feelings of being overly controlled by parents, and mother and father self-reports of worries. Our results show that boys' social anxiety predicted higher perceived parental overcontrol, whereas girls' social anxiety predicted higher paternal worry over time. In addition, girls' reports of feeling overly controlled by parents predicted higher maternal worry but lower paternal worry over time. For boys, feeling overly controlled predicted less social anxiety instead. The study illustrates how mothers and fathers might differ in their behaviors and concerns regarding their children's social anxiety and feelings of overcontrol.

Optimal strategy analysis based on robust predictive control for inventory system with random demand

NASA Astrophysics Data System (ADS)

Saputra, Aditya; Widowati, Sutrisno

2017-12-01

In this paper, the optimal strategy for a single product single supplier inventory system with random demand is analyzed by using robust predictive control with additive random parameter. We formulate the dynamical system of this system as a linear state space with additive random parameter. To determine and analyze the optimal strategy for the given inventory system, we use robust predictive control approach which gives the optimal strategy i.e. the optimal product volume that should be purchased from the supplier for each time period so that the expected cost is minimal. A numerical simulation is performed with some generated random inventory data. We simulate in MATLAB software where the inventory level must be controlled as close as possible to a set point decided by us. From the results, robust predictive control model provides the optimal strategy i.e. the optimal product volume that should be purchased and the inventory level was followed the given set point.

Prediction of outcome of bright light treatment in patients with seasonal affective disorder: Discarding the early response, confirming a higher atypical balance, and uncovering a higher body mass index at baseline as predictors of endpoint outcome.

PubMed

Dimitrova, Tzvetelina D; Reeves, Gloria M; Snitker, Soren; Lapidus, Manana; Sleemi, Aamar R; Balis, Theodora G; Manalai, Partam; Tariq, Muhammad M; Cabassa, Johanna A; Karim, Naila N; Johnson, Mary A; Langenberg, Patricia; Rohan, Kelly J; Miller, Michael; Stiller, John W; Postolache, Teodor T

2017-11-01

We tested the hypothesis that the early improvement in mood after the first hour of bright light treatment compared to control dim-red light would predict the outcome at six weeks of bright light treatment for depressed mood in patients with Seasonal Affective Disorder (SAD). We also analyzed the value of Body Mass Index (BMI) and atypical symptoms of depression at baseline in predicting treatment outcome. Seventy-eight adult participants were enrolled. The first treatment was controlled crossover, with randomized order, and included one hour of active bright light treatment and one hour of control dim-red light, with one-hour washout. Depression was measured on the Structured Interview Guide for the Hamilton Rating Scale for Depression-SAD version (SIGH-SAD). The predictive association of depression scores changes after the first session. BMI and atypical score balance with treatment outcomes at endpoint were assessed using multivariable linear and logistic regressions. No significant prediction by changes in depression scores after the first session was found. However, higher atypical balance scores and BMI positively predicted treatment outcome. Absence of a control intervention for the six-weeks of treatment (only the first session in the laboratory was controlled). Exclusion of patients with comorbid substance abuse, suicidality and bipolar I disorder, and patients on antidepressant medications, reducing the generalizability of the study. Prediction of outcome by early response to light treatment was not replicated, and the previously reported prediction of baseline atypical balance was confirmed. BMI, a parameter routinely calculated in primary care, was identified as a novel predictor, and calls for replication and then exploration of possible mediating mechanisms. Published by Elsevier B.V.

Induced optimism as mental rehearsal to decrease depressive predictive certainty.

PubMed

Miranda, Regina; Weierich, Mariann; Khait, Valerie; Jurska, Justyna; Andersen, Susan M

2017-03-01

The present study examined whether practice in making optimistic future-event predictions would result in change in the hopelessness-related cognitions that characterize depression. Individuals (N = 170) with low, mild, and moderate-to-severe depressive symptoms were randomly assigned to a condition in which they practiced making optimistic future-event predictions or to a control condition in which they viewed the same stimuli but practiced determining whether a given phrase contained an adjective. Overall, individuals in the induced optimism condition showed increases in optimistic predictions, relative to the control condition, as a result of practice, but only individuals with moderate-to-severe symptoms of depression who practiced making optimistic future-event predictions showed decreases in depressive predictive certainty, relative to the control condition. In addition, they showed gains in efficiency in making optimistic predictions over the practice blocks, as assessed by response time. There was no difference in depressed mood by practice condition. Mental rehearsal might be one way of changing the hopelessness-related cognitions that characterize depression. Copyright © 2016 Elsevier Ltd. All rights reserved.

Role of parenting style in achieving metabolic control in adolescents with type 1 diabetes.

PubMed

Shorer, Maayan; David, Ravit; Schoenberg-Taz, Michal; Levavi-Lavi, Ifat; Phillip, Moshe; Meyerovitch, Joseph

2011-08-01

To examine the role of parenting style in achieving metabolic control and treatment adherence in adolescents with type 1 diabetes. Parents of 100 adolescents with type 1 diabetes completed assessments of their parenting style and sense of helplessness. Parents and patients rated patient adherence to the treatment regimen. Glycemic control was evaluated by HbA(1c) values. An authoritative paternal parenting style predicted better glycemic control and adherence in the child; a permissive maternal parenting style predicted poor adherence. A higher sense of helplessness in both parents predicted worse glycemic control and lesser adherence to treatment. Parental sense of helplessness was a significant predictor of diabetes control after correcting for other confounders (patient age, sex, and treatment method). An authoritative nonhelpless parenting style is associated with better diabetes control in adolescents. Paternal involvement is important in adolescent diabetes management. These results have implications for psychological interventions.

Model predictive control based on reduced order models applied to belt conveyor system.

PubMed

Chen, Wei; Li, Xin

2016-11-01

In the paper, a model predictive controller based on reduced order model is proposed to control belt conveyor system, which is an electro-mechanics complex system with long visco-elastic body. Firstly, in order to design low-degree controller, the balanced truncation method is used for belt conveyor model reduction. Secondly, MPC algorithm based on reduced order model for belt conveyor system is presented. Because of the error bound between the full-order model and reduced order model, two Kalman state estimators are applied in the control scheme to achieve better system performance. Finally, the simulation experiments are shown that balanced truncation method can significantly reduce the model order with high-accuracy and model predictive control based on reduced-model performs well in controlling the belt conveyor system. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Model Predictive Flight Control System with Full State Observer using H∞ Method

NASA Astrophysics Data System (ADS)

Sanwale, Jitu; Singh, Dhan Jeet

2018-03-01

This paper presents the application of the model predictive approach to design a flight control system (FCS) for longitudinal dynamics of a fixed wing aircraft. Longitudinal dynamics is derived for a conventional aircraft. Open loop aircraft response analysis is carried out. Simulation studies are illustrated to prove the efficacy of the proposed model predictive controller using H ∞ state observer. The estimation criterion used in the {H}_{∞} observer design is to minimize the worst possible effects of the modelling errors and additive noise on the parameter estimation.

Neural network-based run-to-run controller using exposure and resist thickness adjustment

NASA Astrophysics Data System (ADS)

Geary, Shane; Barry, Ronan

2003-06-01

This paper describes the development of a run-to-run control algorithm using a feedforward neural network, trained using the backpropagation training method. The algorithm is used to predict the critical dimension of the next lot using previous lot information. It is compared to a common prediction algorithm - the exponentially weighted moving average (EWMA) and is shown to give superior prediction performance in simulations. The manufacturing implementation of the final neural network showed significantly improved process capability when compared to the case where no run-to-run control was utilised.

Self-regulating the effortful "social dos".

PubMed

Cortes, Kassandra; Kammrath, Lara K; Scholer, Abigail A; Peetz, Johanna

2014-03-01

In the current research, we explored differences in the self-regulation of the personal dos (i.e., engaging in active and effortful behaviors that benefit the self) and in the self-regulation of the social dos (engaging in those same effortful behaviors to benefit someone else). In 6 studies, we examined whether the same trait self-control abilities that predict task persistence on personal dos would also predict task persistence on social dos. That is, would the same behavior, such as persisting through a tedious and attentionally demanding task, show different associations with trait self-control when it is framed as benefitting the self versus someone else? In Studies 1-3, we directly compared the personal and social dos and found that trait self-control predicted self-reported and behavioral personal dos but not social dos, even when the behaviors were identical and when the incentives were matched. Instead, trait agreeableness--a trait linked to successful self-regulation within the social domain--predicted the social dos. Trait self-control did not predict the social dos even when task difficulty increased (Study 4), but it did predict the social don'ts, consistent with past research (Studies 5-6). The current studies provide support for the importance of distinguishing different domains of self-regulated behaviors and suggest that social dos can be successfully performed through routes other than traditional self-control abilities. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Can overt diabetes mellitus be predicted by an early A1C value in gestational diabetics?

PubMed

Granada, Catalina; Forbes, Joanna; Sangi-Haghpeykar, Haleh; Davidson, Christina

2014-01-01

To test the hypothesis that a hemoglobin A1C value (A1C) in early pregnancy is predictive of overt diabetes mellitus (DM) postpartum in women with gestational diabetes (GDM). In this case-control analysis of women with an early pregnancy diagnosis of GDM, we estimated the association between an early pregnancy A1C and subsequent diagnosis of DM. Women with a normal postpartum diabetic screen (controls) were compared against those with confirmed postpartum DM (cases). Ability of A1C levels to predict DM was examined via logistic regression analysis and corresponding receiver operating characteristic values. During the 10-year study period 166 women met the inclusion criteria: 140 (84%) had normal postpartum testing (controls), and 26 (16%) were diagnosed with DM (cases). The mean A1C value was significantly higher among cases than controls (6.7 vs. 5.6, p < 0.0001, SD 1.3-5). Cases had A1Cs ranging from 5.5- 11.7%, while controls had A1Cs ranging from 4.3-7.8%. The best discriminatory cut point for postpartum DM was an A1C > 5.9% (sensitivity 81%, specificity 83%, positive predictive value 47%, negative predictive value Our findings suggest that an elevated early pregnancy A1C may be predictive of overt DM. Larger studies are needed to further validate this association.

What No Child Left Behind Leaves Behind: The Roles of IQ and Self-Control in Predicting Standardized Achievement Test Scores and Report Card Grades

PubMed Central

Duckworth, Angela L.; Quinn, Patrick D.; Tsukayama, Eli

2013-01-01

The increasing prominence of standardized testing to assess student learning motivated the current investigation. We propose that standardized achievement test scores assess competencies determined more by intelligence than by self-control, whereas report card grades assess competencies determined more by self-control than by intelligence. In particular, we suggest that intelligence helps students learn and solve problems independent of formal instruction, whereas self-control helps students study, complete homework, and behave positively in the classroom. Two longitudinal, prospective studies of middle school students support predictions from this model. In both samples, IQ predicted changes in standardized achievement test scores over time better than did self-control, whereas self-control predicted changes in report card grades over time better than did IQ. As expected, the effect of self-control on changes in report card grades was mediated in Study 2 by teacher ratings of homework completion and classroom conduct. In a third study, ratings of middle school teachers about the content and purpose of standardized achievement tests and report card grades were consistent with the proposed model. Implications for pedagogy and public policy are discussed. PMID:24072936

Early Adolescent Relationship Predictors of Emerging Adult Outcomes: Youth with and without Type 1 Diabetes

PubMed Central

Helgeson, Vicki S.; Palladino, Dianne K.; Reynolds, Kerry A.; Becker, Dorothy; Escobar, Oscar; Siminerio, Linda

2013-01-01

Background Emerging adulthood is a high-risk period for mental health problems and risk behaviors for youth generally and for physical health problems among those with type 1 diabetes. Purpose To examine whether adolescents’ relationships with parents and friends predict health and risk behaviors during emerging adulthood. Method Youth with and without diabetes were enrolled at average age 12 and followed for 7 years. Parent and friend relationship variables, measured during adolescence, were used to predict emerging adulthood outcomes: depression, risk behavior, and, for those with diabetes, diabetes outcomes. Results Parent relationship quality predicted decreased depressive symptoms and, for those with diabetes, decreased alcohol use. Parent control predicted increased smoking, reduced college attendance, and, for control participants, increased depressive symptoms. For those with diabetes, parent control predicted decreased depressive symptoms and better self-care. Friend relationship variables predicted few outcomes. Conclusions Adolescent parent relationships remain an important influence on emerging adults’ lives. PMID:24178509

Aircraft Trajectories Computation-Prediction-Control (La Trajectoire de l’Avion Calcul-Prediction-Controle). Volume 2

DTIC Science & Technology

1990-05-01

faire atterrir las a~ronefs sans recourir de faqon systimatique aux attentes habituelles; un de leurs coll~gues ayant contribu6 At la recherche de la...applicable to or usable for the management of the flows of aircraft and the control of individual flights, the integration of control phases over...February 1976. AIR TRAFFIC MANAGEMENT : Civil/Military Systems and Technologies Guidance and Control Symposium, Copenhagen, Denmark, 9-12 October 1979. AGARD

Longitudinal Analysis of Depressive Symptoms and Glycemic Control in Type 2 Diabetes

PubMed Central

Aikens, James E.; Perkins, Denise White; Lipton, Bonnie; Piette, John D.

2009-01-01

OBJECTIVE To compare whether depressive symptoms are more strongly related to subsequent or prior glycemic control in type 2 diabetes and to test whether patient characteristics modify these longitudinal associations. RESEARCH DESIGN AND METHODS On two occasions separated by 6 months, depressive symptoms and glycemic control were assessed in 253 adults with type 2 diabetes. Regression analyses examined depressive symptoms as both a predictor and outcome of glycemic control and tested whether medication regimen (e.g., insulin versus oral drugs) was an effect modifier before and after adjusting for baseline levels of the outcome being predicted. RESULTS Depressive symptom severity predicted poor glycemic control 6 months later (P = 0.018) but not after baseline glycemic control was taken into account (P = 0.361). Although baseline glycemic control did not generally predict depressive symptoms 6 months later (P = 0.558), it significantly interacted with regimen (P = 0.008). Specifically, glycemic control predicted depressive symptoms among patients prescribed insulin (β = 0.31, P = 0.002) but not among those prescribed oral medication alone (β = −0.10, P = 0.210). Classifying depression dichotomously produced similar but weaker findings. CONCLUSIONS Depressive symptoms do not necessarily lead to worsened glycemic control. In contrast, insulin-treated patients in poor glycemic control are at moderate risk for worsening of depressive symptoms. These patients should be carefully monitored to determine whether depression treatment should be initiated or intensified. PMID:19389814

Visuo-motor coordination ability predicts performance with brain-computer interfaces controlled by modulation of sensorimotor rhythms (SMR)

PubMed Central

Hammer, Eva M.; Kaufmann, Tobias; Kleih, Sonja C.; Blankertz, Benjamin; Kübler, Andrea

2014-01-01

Modulation of sensorimotor rhythms (SMR) was suggested as a control signal for brain-computer interfaces (BCI). Yet, there is a population of users estimated between 10 to 50% not able to achieve reliable control and only about 20% of users achieve high (80–100%) performance. Predicting performance prior to BCI use would facilitate selection of the most feasible system for an individual, thus constitute a practical benefit for the user, and increase our knowledge about the correlates of BCI control. In a recent study, we predicted SMR-BCI performance from psychological variables that were assessed prior to the BCI sessions and BCI control was supported with machine-learning techniques. We described two significant psychological predictors, namely the visuo-motor coordination ability and the ability to concentrate on the task. The purpose of the current study was to replicate these results thereby validating these predictors within a neurofeedback based SMR-BCI that involved no machine learning.Thirty-three healthy BCI novices participated in a calibration session and three further neurofeedback training sessions. Two variables were related with mean SMR-BCI performance: (1) a measure for the accuracy of fine motor skills, i.e., a trade for a person’s visuo-motor control ability; and (2) subject’s “attentional impulsivity”. In a linear regression they accounted for almost 20% in variance of SMR-BCI performance, but predictor (1) failed significance. Nevertheless, on the basis of our prior regression model for sensorimotor control ability we could predict current SMR-BCI performance with an average prediction error of M = 12.07%. In more than 50% of the participants, the prediction error was smaller than 10%. Hence, psychological variables played a moderate role in predicting SMR-BCI performance in a neurofeedback approach that involved no machine learning. Future studies are needed to further consolidate (or reject) the present predictors. PMID:25147518

Model Predictive Control-based Power take-off Control of an Oscillating Water Column Wave Energy Conversion System

NASA Astrophysics Data System (ADS)

Rajapakse, G.; Jayasinghe, S. G.; Fleming, A.; Shahnia, F.

2017-07-01

Australia’s extended coastline asserts abundance of wave and tidal power. The predictability of these energy sources and their proximity to cities and towns make them more desirable. Several tidal current turbine and ocean wave energy conversion projects have already been planned in the coastline of southern Australia. Some of these projects use air turbine technology with air driven turbines to harvest the energy from an oscillating water column. This study focuses on the power take-off control of a single stage unidirectional oscillating water column air turbine generator system, and proposes a model predictive control-based speed controller for the generator-turbine assembly. The proposed method is verified with simulation results that show the efficacy of the controller in extracting power from the turbine while maintaining the speed at the desired level.

Predictive and Reactive Grip Force Responses to Rapid Load Increases in People With Multiple Sclerosis.

PubMed

Allgöwer, Kathrin; Kern, Claudia; Hermsdörfer, Joachim

2017-03-01

To determine the effects of multiple sclerosis (MS) on predictive and reactive grip force control in a catching task and on clinical tests of hand function. Case-control study with matched-pairs control group. University prevention and rehabilitation center. Participants (N=30) consisted of people with multiple sclerosis (PwMS) (n=15) and healthy controls (n=15), matched for sex, age, and hand dominance. Not applicable. Performance on the Expanded Disability Status Scale (EDSS), Nine-Hole Peg Test (9-HPT), Jebsen-Taylor Hand Function Test (JTHFT), and 2-point discrimination (2PD) was evaluated. To analyze grip force control, blindfolded subjects held a receptacle equipped with grip force and acceleration sensors in their hand. In a catching task, a weight was dropped from (1) the experimenter's hand unexpectedly into the receptacle (reactive force control); and (2) from the subject's opposite hand (predictive force control). Grip forces and time lags were analyzed. PwMS (mean EDSS ± SD, 4.2±1.86) had impairments in the 9-HPT and JTHFT (P<.001). The 2PD did not differ significantly between PwMS and controls. During reactive force control (catching task 1), PwMS showed significantly higher grip forces immediately after impact (P<.05), and a significant prolongation of the time from grip force increase until reaching the peak of grip force (P<.001). PwMS and controls did not differ during predictive force control (catching task 2; P>.1). Exaggerated grip force responses and alterations of timing after an unpredictable perturbation, combined with preserved grip force control during predictable conditions, is a characteristic pattern of fine motor control deficits in MS. Measures of reactive grip force responses may be used to complement neurologic assessments. Further studies exploring the usefulness of these measures should be performed in a broader community of PwMS. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Unscented Kalman Filter-Trained Neural Networks for Slip Model Prediction

PubMed Central

Li, Zhencai; Wang, Yang; Liu, Zhen

2016-01-01

The purpose of this work is to investigate the accurate trajectory tracking control of a wheeled mobile robot (WMR) based on the slip model prediction. Generally, a nonholonomic WMR may increase the slippage risk, when traveling on outdoor unstructured terrain (such as longitudinal and lateral slippage of wheels). In order to control a WMR stably and accurately under the effect of slippage, an unscented Kalman filter and neural networks (NNs) are applied to estimate the slip model in real time. This method exploits the model approximating capabilities of nonlinear state–space NN, and the unscented Kalman filter is used to train NN’s weights online. The slip parameters can be estimated and used to predict the time series of deviation velocity, which can be used to compensate control inputs of a WMR. The results of numerical simulation show that the desired trajectory tracking control can be performed by predicting the nonlinear slip model. PMID:27467703

Anticipatory Monitoring and Control of Complex Systems using a Fuzzy based Fusion of Support Vector Regressors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miltiadis Alamaniotis; Vivek Agarwal

This paper places itself in the realm of anticipatory systems and envisions monitoring and control methods being capable of making predictions over system critical parameters. Anticipatory systems allow intelligent control of complex systems by predicting their future state. In the current work, an intelligent model aimed at implementing anticipatory monitoring and control in energy industry is presented and tested. More particularly, a set of support vector regressors (SVRs) are trained using both historical and observed data. The trained SVRs are used to predict the future value of the system based on current operational system parameter. The predicted values are thenmore » inputted to a fuzzy logic based module where the values are fused to obtain a single value, i.e., final system output prediction. The methodology is tested on real turbine degradation datasets. The outcome of the approach presented in this paper highlights the superiority over single support vector regressors. In addition, it is shown that appropriate selection of fuzzy sets and fuzzy rules plays an important role in improving system performance.« less

Descent Advisor Preliminary Field Test

NASA Technical Reports Server (NTRS)

Green, Steven M.; Vivona, Robert A.; Sanford, Beverly

1995-01-01

A field test of the Descent Advisor (DA) automation tool was conducted at the Denver Air Route Traffic Control Center in September 1994. DA is being developed to assist Center controllers in the efficient management and control of arrival traffic. DA generates advisories, based on trajectory predictions, to achieve accurate meter-fix arrival times in a fuel efficient manner while assisting the controller with the prediction and resolution of potential conflicts. The test objectives were: (1) to evaluate the accuracy of DA trajectory predictions for conventional and flight-management system equipped jet transports, (2) to identify significant sources of trajectory prediction error, and (3) to investigate procedural and training issues (both air and ground) associated with DA operations. Various commercial aircraft (97 flights total) and a Boeing 737-100 research aircraft participated in the test. Preliminary results from the primary test set of 24 commercial flights indicate a mean DA arrival time prediction error of 2.4 seconds late with a standard deviation of 13.1 seconds. This paper describes the field test and presents preliminary results for the commercial flights.

Predicting spillover risk to non-target plants pre-release: Bikasha collaris a potential biological control agent of Chinese tallowtree (Triadica sebifera)

USDA-ARS?s Scientific Manuscript database

Quarantine host range tests accurately predict direct risk of biological control agents to non-target species. However, a well-known indirect effect of biological control of weeds releases is spillover damage to non-target species. Spillover damage may occur when the population of agents achieves ou...

Fuzzy Integration of Support Vector Regression Models for Anticipatory Control of Complex Energy Systems

DOE PAGES

Alamaniotis, Miltiadis; Agarwal, Vivek

2014-04-01

Anticipatory control systems are a class of systems whose decisions are based on predictions for the future state of the system under monitoring. Anticipation denotes intelligence and is an inherent property of humans that make decisions by projecting in future. Likewise, artificially intelligent systems equipped with predictive functions may be utilized for anticipating future states of complex systems, and therefore facilitate automated control decisions. Anticipatory control of complex energy systems is paramount to their normal and safe operation. In this paper a new intelligent methodology integrating fuzzy inference with support vector regression is introduced. Our proposed methodology implements an anticipatorymore » system aiming at controlling energy systems in a robust way. Initially a set of support vector regressors is adopted for making predictions over critical system parameters. Furthermore, the predicted values are fed into a two stage fuzzy inference system that makes decisions regarding the state of the energy system. The inference system integrates the individual predictions into a single one at its first stage, and outputs a decision together with a certainty factor computed at its second stage. The certainty factor is an index of the significance of the decision. The proposed anticipatory control system is tested on a real world set of data obtained from a complex energy system, describing the degradation of a turbine. Results exhibit the robustness of the proposed system in controlling complex energy systems.« less

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. (c) 2015 APA, all rights reserved).

A Two-Time Scale Decentralized Model Predictive Controller Based on Input and Output Model

PubMed Central

Niu, Jian; Zhao, Jun; Xu, Zuhua; Qian, Jixin

2009-01-01

A decentralized model predictive controller applicable for some systems which exhibit different dynamic characteristics in different channels was presented in this paper. These systems can be regarded as combinations of a fast model and a slow model, the response speeds of which are in two-time scale. Because most practical models used for control are obtained in the form of transfer function matrix by plant tests, a singular perturbation method was firstly used to separate the original transfer function matrix into two models in two-time scale. Then a decentralized model predictive controller was designed based on the two models derived from the original system. And the stability of the control method was proved. Simulations showed that the method was effective. PMID:19834542

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

Application of model predictive control for optimal operation of wind turbines

NASA Astrophysics Data System (ADS)

Yuan, Yuan; Cao, Pei; Tang, J.

2017-04-01

For large-scale wind turbines, reducing maintenance cost is a major challenge. Model predictive control (MPC) is a promising approach to deal with multiple conflicting objectives using the weighed sum approach. In this research, model predictive control method is applied to wind turbine to find an optimal balance between multiple objectives, such as the energy capture, loads on turbine components, and the pitch actuator usage. The actuator constraints are integrated into the objective function at the control design stage. The analysis is carried out in both the partial load region and full load region, and the performances are compared with those of a baseline gain scheduling PID controller. The application of this strategy achieves enhanced balance of component loads, the average power and actuator usages in partial load region.

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.

Cognitive reappraisal and secondary control coping: associations with working memory, positive and negative affect, and symptoms of anxiety/depression.

PubMed

Andreotti, Charissa; Thigpen, Jennifer E; Dunn, Madeleine J; Watson, Kelly; Potts, Jennifer; Reising, Michelle M; Robinson, Kristen E; Rodriguez, Erin M; Roubinov, Danielle; Luecken, Linda; Compas, Bruce E

2013-01-01

The current study examined the relations of measures of cognitive reappraisal and secondary control coping with working memory abilities, positive and negative affect, and symptoms of anxiety and depression in young adults (N=124). Results indicate significant relations between working memory abilities and reports of secondary control coping and between reports of secondary control coping and cognitive reappraisal. Associations were also found between measures of secondary control coping and cognitive reappraisal and positive and negative affect and symptoms of depression and anxiety. Further, the findings suggest that reports of cognitive reappraisal may be more strongly predictive of positive affect whereas secondary control coping may be more strongly predictive of negative affect and symptoms of depression and anxiety. Overall, the results suggest that current measures of secondary control coping and cognitive reappraisal capture related but distinct constructs and suggest that the assessment of working memory may be more strongly related to secondary control coping in predicting individual differences in distress.

Looking beyond patients: Can parents' quality of life predict asthma control in children?

PubMed

Cano-Garcinuño, Alfredo; Mora-Gandarillas, Isabel; Bercedo-Sanz, Alberto; Callén-Blecua, María Teresa; Castillo-Laita, José Antonio; Casares-Alonso, Irene; Forns-Serrallonga, Dolors; Tauler-Toro, Eulàlia; Alonso-Bernardo, Luz María; García-Merino, Águeda; Moneo-Hernández, Isabel; Cortés-Rico, Olga; Carvajal-Urueña, Ignacio; Morell-Bernabé, Juan José; Martín-Ibáñez, Itziar; Rodríguez-Fernández-Oliva, Carmen Rosa; Asensi-Monzó, María Teresa; Fernández-Carazo, Carmen; Murcia-García, José; Durán-Iglesias, Catalina; Montón-Álvarez, José Luis; Domínguez-Aurrecoechea, Begoña; Praena-Crespo, Manuel

2016-07-01

Social and family factors may influence the probability of achieving asthma control in children. Parents' quality of life has been insufficiently explored as a predictive factor linked to the probability of achieving disease control in asthmatic children. Determine whether the parents' quality of life predicts medium-term asthma control in children. Longitudinal study of children between 4 and 14 years of age, with active asthma. The parents' quality of life was evaluated using the specific IFABI-R instrument, in which scores were higher for poorer quality of life. Its association with asthma control measures in the child 16 weeks later was analyzed using multivariate methods, adjusting the effect for disease, child and family factors. The data from 452 children were analyzed (median age 9.6 years, 63.3% males). The parents' quality of life was predictive for asthma control; each point increase on the initial IFABI-R score was associated with an adjusted odds ratio (95% confidence interval) of 0.56 (0.37-0.86) for good control of asthma on the second visit, 2.58 (1.62-4.12) for asthma exacerbation, 2.12 (1.33-3.38) for an unscheduled visit to the doctor, and 2.46 (1.18-5.13) for going to the emergency room. The highest quartile for the IFABI-R score had a sensitivity of 34.5% and a specificity of 82.2% to predict poorly controlled asthma. Parents' poorer quality of life is related to poor, medium-term asthma control in children. Assessing the parents' quality of life could aid disease management decisions. Pediatr Pulmonol. 2016;51:670-677. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

The relationship between high residential density in student dormitories and anxiety, binge eating and Internet addiction: a study of Chinese college students.

PubMed

Tao, Zhuoli; Wu, Gao; Wang, Zeyuan

2016-01-01

Although various studies have indicated that high residential density may affect health and psychological outcomes, to our knowledge, there have been no studies regarding the predictive nature of crowded living conditions on binge eating and the use of the Internet as coping strategies. A total of 1048 Chinese college students (540 males and 508 females) were randomly selected and asked to complete a battery of questionnaires that included the Zung's Self-Rating Anxiety Scale, the Internet Addiction Test, and Rosenbaum's Self-Control Scale. Binge eating behaviors and compensatory behaviors were also reported, and variables about residential density were measured. Among female participants, binge eating scores were significantly predicted by anxiety caused by high-density living conditions (P = 0.008), and similarly, the frequency of compensatory behaviors was significantly predicted by anxiety caused by high-density living conditions (P = 0.000) and self-control (P = 0.003). Furthermore, the Internet Addiction Test scores were significantly predicted by the anxiety caused by high -density living conditions (P = 0.000) and self-control (P = 0.000). Among male participants, not only were the binge eating scores significantly predicted by the anxiety caused by high-density living conditions (P = 0.000) and self-control (P = 0.000), but the frequency of compensatory behaviors was also significantly predicted by the anxiety caused by high-density living conditions (P = 0.000) and self-control (P = 0.01). Furthermore, Internet Addiction Test scores were significantly predicted by anxiety caused by high-density living conditions (P = 0.000) and self-control (P = 0.000). It was further found that for both genders, subjective factors such as self-control, and the anxiety caused by high-density living conditions had a stronger impact on Internet addiction than objective factors, such as the size of the student's dormitory room. Moreover, self-control was found to act as a moderator in the relationship between anxiety and Internet addiction among male participants. Binge eating and Internet use could be considered coping strategies for Chinese college students facing high residential density in their dormitories.

A model for prediction of STOVL ejector dynamics

NASA Technical Reports Server (NTRS)

Drummond, Colin K.

1989-01-01

A semi-empirical control-volume approach to ejector modeling for transient performance prediction is presented. This new approach is motivated by the need for a predictive real-time ejector sub-system simulation for Short Take-Off Verticle Landing (STOVL) integrated flight and propulsion controls design applications. Emphasis is placed on discussion of the approximate characterization of the mixing process central to thrust augmenting ejector operation. The proposed ejector model suggests transient flow predictions are possible with a model based on steady-flow data. A practical test case is presented to illustrate model calibration.

Visual anticipation biases conscious decision making but not bottom-up visual processing.

PubMed

Mathews, Zenon; Cetnarski, Ryszard; Verschure, Paul F M J

2014-01-01

Prediction plays a key role in control of attention but it is not clear which aspects of prediction are most prominent in conscious experience. An evolving view on the brain is that it can be seen as a prediction machine that optimizes its ability to predict states of the world and the self through the top-down propagation of predictions and the bottom-up presentation of prediction errors. There are competing views though on whether prediction or prediction errors dominate the formation of conscious experience. Yet, the dynamic effects of prediction on perception, decision making and consciousness have been difficult to assess and to model. We propose a novel mathematical framework and a psychophysical paradigm that allows us to assess both the hierarchical structuring of perceptual consciousness, its content and the impact of predictions and/or errors on conscious experience, attention and decision-making. Using a displacement detection task combined with reverse correlation, we reveal signatures of the usage of prediction at three different levels of perceptual processing: bottom-up fast saccades, top-down driven slow saccades and consciousnes decisions. Our results suggest that the brain employs multiple parallel mechanism at different levels of perceptual processing in order to shape effective sensory consciousness within a predicted perceptual scene. We further observe that bottom-up sensory and top-down predictive processes can be dissociated through cognitive load. We propose a probabilistic data association model from dynamical systems theory to model the predictive multi-scale bias in perceptual processing that we observe and its role in the formation of conscious experience. We propose that these results support the hypothesis that consciousness provides a time-delayed description of a task that is used to prospectively optimize real time control structures, rather than being engaged in the real-time control of behavior itself.

Prediction of the Aerodynamic Characteristics of Cruciform Missiles Including Effects of Roll Angle and Control Deflection

DTIC Science & Technology

1986-08-01

CHARACTERISTICS OF CRU.CIFORM MISSILES INCLUDING EFFECTS OF ROLL ANGLE AND CONTROL DEFLECTION N by Daniel J. Lesieutre Michael R. Mendenhall Susana M. Nazario...ANGLE AND CONTROL DEFLECTION Daniel J. Lesieutre Michael R. Mendenhal. Susana M. Nazario Nielsen Engineering & Research, Inc.00 Mountain View, CA 94043...Lo PREDICTION OF THE AERODYNAMIC CHARACTERISTICS OF CRU.CIFORM MISSILES - INCLUDING EFFECTS OF ROLL ANGLE AND CONTROL DEFLECTION by Daniel J

Cell Fate Reprogramming by Control of Intracellular Network Dynamics

PubMed Central

Zañudo, Jorge G. T.; Albert, Réka

2015-01-01

Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell’s fate, such as disease therapeutics and stem cell reprogramming. Here we develop a novel network control framework that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our approach drives any initial state to the target state with 100% effectiveness and needs to be applied only transiently for the network to reach and stay in the desired state. We illustrate our method’s potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of helper T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments. PMID:25849586

On Application of Model Predictive Control to Power Converter with Switching

NASA Astrophysics Data System (ADS)

Zanma, Tadanao; Fukuta, Junichi; Doki, Shinji; Ishida, Muneaki; Okuma, Shigeru; Matsumoto, Takashi; Nishimori, Eiji

This paper concerns a DC-DC converter control. In DC-DC converters, there exist both continuous components such as inductance, conductance and resistance and discrete ones, IGBT and MOSFET as semiconductor switching elements. Such a system can be regarded as a hybrid dynamical system. Thus, this paper presents a dc-dc control technique based on the model predictive control. Specifically, a case in which the load of the dc-dc converter changes from active to sleep is considered. In the case, a control method which makes the output voltage follow to the reference quickly in transition, and the switching frequency be constant in steady state. In addition, in applying the model predictive control to power electronics circuits, the switching characteristic of the device and the restriction condition for protection are also considered. The effectiveness of the proposed method is illustrated by comparing a conventional method through some simulation results.

Self-control across species (Columba livia, Homo sapiens, and Rattus norvegicus).

PubMed

Tobin, H; Logue, A W

1994-06-01

Data from six previous studies of self-control behavior were compared against predictions made by the matching law and by molar maximization. The studies involved pigeons (Columba livia), rats (Rattus norvegicus), and 3-year-old, 5-year-old, and adult humans (Homo sapiens) who had received food as the reinforcer, and adult humans who had received points exchangeable for money as the reinforcer. Neither theory proved to be an accurate or better predictor for all groups. In contrast to the predictions of these theories, self-control was shown to vary according to species, human age group, and reinforcer quality. When the reinforcer was food, the self-control of different species was found to be negatively correlated with metabolic rate; that is, larger species showed greater self-control. These results suggest that allometric scaling may prove useful in describing and predicting species differences in self-control.

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. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Class Anxiety in Secondary Education: Exploring Structural Relations with Perceived Control, Engagement, Disaffection, and Performance.

PubMed

González, Antonio; Faílde Garrido, José María; Rodríguez Castro, Yolanda; Carrera Rodríguez, María Victoria

2015-09-14

The aim of this study was to assess the relationships between class-related anxiety with perceived control, teacher-reported behavioral engagement, behavioral disaffection, and academic performance. Participants were 355 compulsory secondary students (9th and 10th grades; Mean age = 15.2 years; SD = 1.8 years). Structural equation models revealed performance was predicted by perceived control, anxiety, disaffection, and engagement. Perceived control predicted anxiety, disaffection, and engagement. Anxiety predicted disaffection and engagement, and partially mediated the effects from control on disaffection (β = -.277, p < .005; CI = -.378, -.197) and engagement (β = .170, p < .002; CI = .103 .258). The negative association between anxiety and performance was mediated by engagement and disaffection (β = -.295, p < .002; CI = -.439, -.182). Anxiety, engagement, and disaffection mediated the effects of control on performance (β = .352, p < .003; CI = .279, .440). The implications of these results are discussed in the light of current theory and educational interventions.

Prediction-based sampled-data H∞ controller design for attitude stabilisation of a rigid spacecraft with disturbances

NASA Astrophysics Data System (ADS)

Zhu, Baolong; Zhang, Zhiping; Zhou, Ding; Ma, Jie; Li, Shunli

2017-08-01

This paper investigates the H∞ control problem of the attitude stabilisation of a rigid spacecraft with external disturbances using prediction-based sampled-data control strategy. Aiming to achieve a 'virtual' closed-loop system, a type of parameterised sampled-data controller is designed by introducing a prediction mechanism. The resultant closed-loop system is equivalent to a hybrid system featured by a continuous-time and an impulsive differential system. By using a time-varying Lyapunov functional, a generalised bounded real lemma (GBRL) is first established for a kind of impulsive differential system. Based on this GBRL and Lyapunov functional approach, a sufficient condition is derived to guarantee the closed-loop system to be asymptotically stable and to achieve a prescribed H∞ performance. In addition, the controller parameter tuning is cast into a convex optimisation problem. Simulation and comparative results are provided to illustrate the effectiveness of the developed control scheme.

Design and experiment of vehicular charger AC/DC system based on predictive control algorithm

NASA Astrophysics Data System (ADS)

He, Guangbi; Quan, Shuhai; Lu, Yuzhang

2018-06-01

For the car charging stage rectifier uncontrollable system, this paper proposes a predictive control algorithm of DC/DC converter based on the prediction model, established by the state space average method and its prediction model, obtained by the optimal mathematical description of mathematical calculation, to analysis prediction algorithm by Simulink simulation. The design of the structure of the car charging, at the request of the rated output power and output voltage adjustable control circuit, the first stage is the three-phase uncontrolled rectifier DC voltage Ud through the filter capacitor, after by using double-phase interleaved buck-boost circuit with wide range output voltage required value, analyzing its working principle and the the parameters for the design and selection of components. The analysis of current ripple shows that the double staggered parallel connection has the advantages of reducing the output current ripple and reducing the loss. The simulation experiment of the whole charging circuit is carried out by software, and the result is in line with the design requirements of the system. Finally combining the soft with hardware circuit to achieve charging of the system according to the requirements, experimental platform proved the feasibility and effectiveness of the proposed predictive control algorithm based on the car charging of the system, which is consistent with the simulation results.

Incremental Validity of Biographical Data in the Prediction of En Route Air Traffic Control Specialist Technical Skills

DOT National Transportation Integrated Search

2012-07-01

Previous research demonstrated that an empirically-keyed, response-option scored biographical data (biodata) : scale predicted supervisory ratings of air traffic control specialist (ATCS) job performance (Dean & Broach, : 2011). This research f...

Predictive Eco-Cruise Control (ECC) system : model development, modeling and potential benefits.

DOT National Transportation Integrated Search

2013-02-01

The research develops a reference model of a predictive eco-cruise control (ECC) system that intelligently modulates vehicle speed within a pre-set speed range to minimize vehicle fuel consumption levels using roadway topographic information. The stu...

Toward autonomous spacecraft

NASA Technical Reports Server (NTRS)

Fogel, L. J.; Calabrese, P. G.; Walsh, M. J.; Owens, A. J.

1982-01-01

Ways in which autonomous behavior of spacecraft can be extended to treat situations wherein a closed loop control by a human may not be appropriate or even possible are explored. Predictive models that minimize mean least squared error and arbitrary cost functions are discussed. A methodology for extracting cyclic components for an arbitrary environment with respect to usual and arbitrary criteria is developed. An approach to prediction and control based on evolutionary programming is outlined. A computer program capable of predicting time series is presented. A design of a control system for a robotic dense with partially unknown physical properties is presented.

Predictive control of hollow-fiber bioreactors for the production of monoclonal antibodies.

PubMed

Dowd, J E; Weber, I; Rodriguez, B; Piret, J M; Kwok, K E

1999-05-20

The selection of medium feed rates for perfusion bioreactors represents a challenge for process optimization, particularly in bioreactors that are sampled infrequently. When the present and immediate future of a bioprocess can be adequately described, predictive control can minimize deviations from set points in a manner that can maximize process consistency. Predictive control of perfusion hollow-fiber bioreactors was investigated in a series of hybridoma cell cultures that compared operator control to computer estimation of feed rates. Adaptive software routines were developed to estimate the current and predict the future glucose uptake and lactate production of the bioprocess at each sampling interval. The current and future glucose uptake rates were used to select the perfusion feed rate in a designed response to deviations from the set point values. The routines presented a graphical user interface through which the operator was able to view the up-to-date culture performance and assess the model description of the immediate future culture performance. In addition, fewer samples were taken in the computer-estimated cultures, reducing labor and analytical expense. The use of these predictive controller routines and the graphical user interface decreased the glucose and lactate concentration variances up to sevenfold, and antibody yields increased by 10% to 43%. Copyright 1999 John Wiley & Sons, Inc.

Development of a Clinical Tool to Predict Home Death of a Discharged Cancer Patient in Japan: a Case-Control Study.

PubMed

Fukui, Sakiko; Morita, Tatsuya; Yoshiuchi, Kazuhiro

2017-08-01

The aim of this study was to investigate the predictive value of a clinical tool to predict whether discharged cancer patients die at home, comparing groups of case who died at home and control who died in hospitals or other facilities. We conducted a nationwide case-control study to identify the determinants of home death for a discharged cancer patient. We randomly selected nurses in charge of 2000 home-visit nursing agencies from all 5813 agencies in Japan by referring to the nationwide databases in January 2013. The nurses were asked to report variables of their patients' place of death, patients' and caregivers' clinical statuses, and their preferences for home death. We used logistic regression analysis and developed a clinical tool to accurately predict it and investigated their predictive values. We identified 466 case and 478 control patients. Five predictive variables of home death were obtained: patients' and caregivers' preferences for home death [OR (95% CI) 2.66 (1.99-3.55)], availability of visiting physicians [2.13 (1.67-2.70)], 24-h contact between physicians and nurses [1.68 (1.30-2.18)], caregivers' experiences of deathwatch at home [1.41 (1.13-1.75)], and patients' insights as to their own prognosis [1.23 (1.02-1.50)]. We calculated the scores predicting home death for each variable (range 6-28). When using a cutoff point of 16, home death was predicted with a sensitivity of 0.72 and a specificity of 0.81 with the Harrell's c-statistic of 0.84. This simple clinical tool for healthcare professionals can help predict whether a discharged patient is likely to die at home.

Effects of Parenting Style upon Psychological Well-Being of Young Adults: Exploring the Relations among Parental Care, Locus of Control and Depression.

ERIC Educational Resources Information Center

Taris, Toon W.; Bok, Inge A.

1997-01-01

Used structural equation model to explore relationship between parenting style and Dutch young adult offsprings' depression and locus of control. Found that loving, caring parenting styles predicted lower depression levels. A loving, caring upbringing provided by fathers predicted a shift toward an internal locus of control, but a similar…

Coordinated control of active and reactive power of distribution network with distributed PV cluster via model predictive control

NASA Astrophysics Data System (ADS)

Ji, Yu; Sheng, Wanxing; Jin, Wei; Wu, Ming; Liu, Haitao; Chen, Feng

2018-02-01

A coordinated optimal control method of active and reactive power of distribution network with distributed PV cluster based on model predictive control is proposed in this paper. The method divides the control process into long-time scale optimal control and short-time scale optimal control with multi-step optimization. The models are transformed into a second-order cone programming problem due to the non-convex and nonlinear of the optimal models which are hard to be solved. An improved IEEE 33-bus distribution network system is used to analyse the feasibility and the effectiveness of the proposed control method

Detection of visual events along the apparent motion trace in patients with paranoid schizophrenia.

PubMed

Sanders, Lia Lira Olivier; Muckli, Lars; de Millas, Walter; Lautenschlager, Marion; Heinz, Andreas; Kathmann, Norbert; Sterzer, Philipp

2012-07-30

Dysfunctional prediction in sensory processing has been suggested as a possible causal mechanism in the development of delusions in patients with schizophrenia. Previous studies in healthy subjects have shown that while the perception of apparent motion can mask visual events along the illusory motion trace, such motion masking is reduced when events are spatio-temporally compatible with the illusion, and, therefore, predictable. Here we tested the hypothesis that this specific detection advantage for predictable target stimuli on the apparent motion trace is reduced in patients with paranoid schizophrenia. Our data show that, although target detection along the illusory motion trace is generally impaired, both patients and healthy control participants detect predictable targets more often than unpredictable targets. Patients had a stronger motion masking effect when compared to controls. However, patients showed the same advantage in the detection of predictable targets as healthy control subjects. Our findings reveal stronger motion masking but intact prediction of visual events along the apparent motion trace in patients with paranoid schizophrenia and suggest that the sensory prediction mechanism underlying apparent motion is not impaired in paranoid schizophrenia. Copyright © 2012. Published by Elsevier Ireland Ltd.

Trajectory Orientation: A Technology-Enabled Concept Requiring a Shift in Controller Roles and Responsibilities

NASA Technical Reports Server (NTRS)

Leiden, Ken; Green, Steven

2000-01-01

The development of a decision support tool (DST) for the en-route domain with accurate conflict prediction time horizons of 20 minutes has introduced an interesting problem. A 20 minute time horizon for conflict prediction often results in the predicted conflict occurring one or more sectors downstream from the sector controller who "owns" (i-e., is responsible for the safe separation of aircraft) one or both of the aircraft in the conflict pair. Based on current roles and responsibilities of today's en route controllers, the upstream controller would not resolve this conflict. In most cases, the downstream controller would wait until the conflicting aircraft entered higher sector before resolving the conflict. This results in a delay of several minutes from the time when the conflict was initially predicted. This delay is inefficient from both a controller workload and user's cost of operations perspective. Trajectory orientation, a new concept for facilitating an efficient, conflict-free flight path across several sectors while conforming to metering or miles-in-trail spacing, is proposed as an alternative to today's sector-oriented method. This concept necessitates a fundamental shift in thinking about inter-sector coordination. Instead of operating independently, with the main focus on protecting their internal airspace, controllers would work cooperatively, depending on each other for well-planned, conflict-free flow of aircraft. To support the trajectory orientation concept, a long time horizon (15 to 20 minutes) for conflict prediction and resolution would most likely be a primary requirement. In addition, new tools, such as controller-pilot data link will be identified to determine their necessity and applicability for trajectory orientation. Finally, with significant controller participation from selected Air Route Traffic Control Centers, potential shifts in R-side/D-side roles and responsibilities as well as the creation of a new controller position for multi-sector planning will be examined to determine the most viable solutions.

Patients with Mild Alzheimer's Disease Fail When Using Their Working Memory: Evidence from the Eye Tracking Technique.

PubMed

Fernández, Gerardo; Manes, Facundo; Politi, Luis E; Orozco, David; Schumacher, Marcela; Castro, Liliana; Agamennoni, Osvaldo; Rotstein, Nora P

2016-01-01

Patients with Alzheimer's disease (AD) develop progressive language, visuoperceptual, attentional, and oculomotor changes that can have an impact on their reading comprehension. However, few studies have examined reading behavior in AD, and none have examined the contribution of predictive cueing in reading performance. For this purpose we analyzed the eye movement behavior of 35 healthy readers (Controls) and 35 patients with probable AD during reading of regular and high-predictable sentences. The cloze predictability of words N - 1, and N + 1 exerted an influence on the reader's gaze duration. The predictabilities of preceding words in high-predictable sentences served as task-appropriate cues that were used by Control readers. In contrast, these effects were not present in AD patients. In Controls, changes in predictability significantly affected fixation duration along the sentence; noteworthy, these changes did not affect fixation durations in AD patients. Hence, only in healthy readers did predictability of upcoming words influence fixation durations via memory retrieval. Our results suggest that Controls used stored information of familiar texts for enhancing their reading performance and imply that contextual-word predictability, whose processing is proposed to require memory retrieval, only affected reading behavior in healthy subjects. In AD patients, this loss reveals impairments in brain areas such as those corresponding to working memory and memory retrieval. These findings might be relevant for expanding the options for the early detection and monitoring in the early stages of AD. Furthermore, evaluation of eye movements during reading could provide a new tool for measuring drug impact on patients' behavior.

Application of indoor noise prediction in the real world

NASA Astrophysics Data System (ADS)

Lewis, David N.

2002-11-01

Predicting indoor noise in industrial workrooms is an important part of the process of designing industrial plants. Predicted levels are used in the design process to determine compliance with occupational-noise regulations, and to estimate levels inside the walls in order to predict community noise radiated from the building. Once predicted levels are known, noise-control strategies can be developed. In this paper an overview of over 20 years of experience is given with the use of various prediction approaches to manage noise in Unilever plants. This work has applied empirical and ray-tracing approaches separately, and in combination, to design various packaging and production plants and other facilities. The advantages of prediction methods in general, and of the various approaches in particular, will be discussed. A case-study application of prediction methods to the optimization of noise-control measures in a food-packaging plant will be presented. Plans to acquire a simplified prediction model for use as a company noise-screening tool will be discussed.

The effect of deviance predictability on mismatch negativity in schizophrenia patients.

PubMed

Horacek, Magdalena; Kärgel, Christian; Scherbaum, Norbert; Müller, Bernhard W

2016-03-23

Mismatch negativity (MMN) is an electrophysiological index of prediction error processing and recently has been considered an endophenotype marker in schizophrenia. While the prediction error is a core concept in the MMN generation, predictability of deviance occurrence has rarely been assessed in MMN research and in schizophrenia patients. We investigated the MMN to 12% temporally predictable or unpredictable duration decrement deviant stimuli in two runs in 29 healthy controls and 31 schizophrenia patients. We analyzed MMN amplitudes and latencies and its associations with clinical symptoms at electrode Fz. With a stimulus onset asynchronicity of 500 ms in the regular predictable condition, a deviant occurred every 4s while it varied randomly in the unpredictable condition. In the random condition we found diminished MMN amplitudes in patients which normalized in the regular deviance condition, resulting in an analysis of variance main effect of predictability and a predictability x group interaction. Deviance predictability did not affect the MMN of control subjects and we found no relevant results with regard to MMN latencies. Our results indicate that MMN amplitudes in patients normalize to the level of the control subjects in the case of a temporally fixed regular deviant. In schizophrenia patients the detection of deviance is basically intact. However, the temporal uncertainty of deviance occurrence may be of substantial relevance to the highly replicated MMN deficit in schizophrenia patients. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

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.

Contextualizing Gay-Straight Alliances: Student, Advisor, and Structural Factors Related to Positive Youth Development Among Members

PubMed Central

Poteat, V. Paul; Yoshikawa, Hirokazu; Calzo, Jerel P.; Gray, Mary L.; DiGiovanni, Craig. D.; Lipkin, Arthur; Mundy-Shephard, Adrienne; Perrotti, Jeff; Scheer, Jillian R.; Shaw, Mathew P.

2014-01-01

Gay-Straight Alliances (GSAs) may promote resilience. Yet, what GSA components predict wellbeing? Among 146 youth and advisors in 13 GSAs (58% lesbian, gay, bisexual, or questioning; 64% white; 38% received free/reduced-cost lunch), student (demographics, victimization, attendance frequency, leadership, support, control), advisor (years served, training, control) and contextual factors (overall support or advocacy, outside support for the GSA) that predicted purpose, mastery, and self-esteem were tested. In multilevel models, GSA support predicted all outcomes. Racial/ethnic minority youth reported greater wellbeing, yet lower support. Youth in GSAs whose advisors served longer and perceived more control and were in more supportive school contexts reported healthier outcomes. GSA advocacy also predicted purpose. Ethnographic notes elucidated complex associations and variability in how GSAs operated. PMID:25176579

On the incremental validity of irrational beliefs to predict subjective well-being while controlling for personality factors.

PubMed

Spörrle, Matthias; Strobel, Maria; Tumasjan, Andranik

2010-11-01

This research examines the incremental validity of irrational thinking as conceptualized by Albert Ellis to predict diverse aspects of subjective well-being while controlling for the influence of personality factors. Rational-emotive behavior therapy (REBT) argues that irrational beliefs result in maladaptive emotions leading to reduced well-being. Although there is some early scientific evidence for this relation, it has never been investigated whether this connection would still persist when statistically controlling for the Big Five personality factors, which were consistently found to be important determinants of well-being. Regression analyses revealed significant incremental validity of irrationality over personality factors when predicting life satisfaction, but not when predicting subjective happiness. Results are discussed with respect to conceptual differences between these two aspects of subjective well-being.

Adaptive two-degree-of-freedom PI for speed control of permanent magnet synchronous motor based on fractional order GPC.

PubMed

Qiao, Wenjun; Tang, Xiaoqi; Zheng, Shiqi; Xie, Yuanlong; Song, Bao

2016-09-01

In this paper, an adaptive two-degree-of-freedom (2Dof) proportional-integral (PI) controller is proposed for the speed control of permanent magnet synchronous motor (PMSM). Firstly, an enhanced just-in-time learning technique consisting of two novel searching engines is presented to identify the model of the speed control system in a real-time manner. Secondly, a general formula is given to predict the future speed reference which is unavailable at the interval of two bus-communication cycles. Thirdly, the fractional order generalized predictive control (FOGPC) is introduced to improve the control performance of the servo drive system. Based on the identified model parameters and predicted speed reference, the optimal control law of FOGPC is derived. Finally, the designed 2Dof PI controller is auto-tuned by matching with the optimal control law. Simulations and real-time experimental results on the servo drive system of PMSM are provided to illustrate the effectiveness of the proposed strategy. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Implicit and explicit attitudes predict smoking cessation: moderating effects of experienced failure to control smoking and plans to quit.

PubMed

Chassin, Laurie; Presson, Clark C; Sherman, Steven J; Seo, Dong-Chul; Macy, Jonathan T

2010-12-01

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. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

Implementation of model predictive control for resistive wall mode stabilization on EXTRAP T2R

NASA Astrophysics Data System (ADS)

Setiadi, A. C.; Brunsell, P. R.; Frassinetti, L.

2015-10-01

A model predictive control (MPC) method for stabilization of the resistive wall mode (RWM) in the EXTRAP T2R reversed-field pinch is presented. The system identification technique is used to obtain a linearized empirical model of EXTRAP T2R. MPC employs the model for prediction and computes optimal control inputs that satisfy performance criterion. The use of a linearized form of the model allows for compact formulation of MPC, implemented on a millisecond timescale, that can be used for real-time control. The design allows the user to arbitrarily suppress any selected Fourier mode. The experimental results from EXTRAP T2R show that the designed and implemented MPC successfully stabilizes the RWM.

Costs and benefits linked to developments in cognitive control.

PubMed

Blackwell, Katharine A; Munakata, Yuko

2014-03-01

Developing cognitive control over one's thoughts, emotions, and actions is a fundamental process that predicts important life outcomes. Such control begins in infancy, and shifts during development from a predominantly reactive form (e.g. retrieving task-relevant information when needed) to an increasingly proactive form (e.g. maintaining task-relevant information in anticipation of needing it). While such developments are generally viewed as adaptive, cognitive abilities can also involve trade-offs, such that the benefits of developing increasingly proactive control may come with associated costs. In two experiments, we test for such cognitive trade-offs in children who are transitioning to proactive control. We find that proactive control predicts expected benefits in children's working memory, but is also associated with predicted costs in disproportionately slowing children under conditions of distraction. These findings highlight unique advantages and disadvantages of proactive and reactive control, and suggest caution in attempting to alter their balance during development. © 2013 John Wiley & Sons Ltd.

Multivariable model predictive control design of reactive distillation column for Dimethyl Ether production

NASA Astrophysics Data System (ADS)

Wahid, A.; Putra, I. G. E. P.

2018-03-01

Dimethyl ether (DME) as an alternative clean energy has attracted a growing attention in the recent years. DME production via reactive distillation has potential for capital cost and energy requirement savings. However, combination of reaction and distillation on a single column makes reactive distillation process a very complex multivariable system with high non-linearity of process and strong interaction between process variables. This study investigates a multivariable model predictive control (MPC) based on two-point temperature control strategy for the DME reactive distillation column to maintain the purities of both product streams. The process model is estimated by a first order plus dead time model. The DME and water purity is maintained by controlling a stage temperature in rectifying and stripping section, respectively. The result shows that the model predictive controller performed faster responses compared to conventional PI controller that are showed by the smaller ISE values. In addition, the MPC controller is able to handle the loop interactions well.

Comparisons of Predictions of the XB-70-1 Longitudinal Stability and Control Derivatives with Flight Results for Six Flight Conditions

NASA Technical Reports Server (NTRS)

Wolowicz, C. H.; Yancey, R. B.

1973-01-01

Preliminary correlations of flight-determined and predicted stability and control characteristics of the XB-70-1 reported in NASA TN D-4578 were subject to uncertainties in several areas which necessitated a review of prediction techniques particularly for the longitudinal characteristics. Reevaluation and updating of the original predictions, including aeroelastic corrections, for six specific flight-test conditions resulted in improved correlations of static pitch stability with flight data. The original predictions for the pitch-damping derivative, on the other hand, showed better correlation with flight data than the updated predictions. It appears that additional study is required in the application of aeroelastic corrections to rigid model wind-tunnel data and the theoretical determination of dynamic derivatives for this class of aircraft.

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.

Absolute Stability Analysis of a Phase Plane Controlled Spacecraft

NASA Technical Reports Server (NTRS)

Jang, Jiann-Woei; Plummer, Michael; Bedrossian, Nazareth; Hall, Charles; Jackson, Mark; Spanos, Pol

2010-01-01

Many aerospace attitude control systems utilize phase plane control schemes that include nonlinear elements such as dead zone and ideal relay. To evaluate phase plane control robustness, stability margin prediction methods must be developed. Absolute stability is extended to predict stability margins and to define an abort condition. A constrained optimization approach is also used to design flex filters for roll control. The design goal is to optimize vehicle tracking performance while maintaining adequate stability margins. Absolute stability is shown to provide satisfactory stability constraints for the optimization.

Predictive display design for the vehicles with time delay in dynamic response

NASA Astrophysics Data System (ADS)

Efremov, A. V.; Tiaglik, M. S.; Irgaleev, I. H.; Efremov, E. V.

2018-02-01

The two ways for the improvement of flying qualities are considered: the predictive display (PD) and the predictive display integrated with the flight control system (FCS). The both ways allow to transforming the controlled element dynamics in the crossover frequency range, to improve the accuracy of tracking and to suppress the effect of time delay in the vehicle response too. The technique for optimization of the predictive law is applied to the landing task. The results of the mathematical modeling and experimental investigations carried out for this task are considered in the paper.

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.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Arumugasamy, Senthil Kumar; Ahmad, Z.

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 spacemore » 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.« less

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.

Parent Prediction of Child Mood and Emotional Resilience: The Role of Parental Responsiveness and Psychological Control

PubMed Central

Boughton, Kristy L.; Lumley, Margaret N.

2011-01-01

Research consistently shows low to moderate agreement between parent and child reports of child mood, suggesting that parents are not always the best predictors of child emotional functioning. This study examines parental responsiveness and psychological control for improving prediction of early adolescent mood and emotional resilience beyond parent report of child emotional functioning. Participants were 268 early adolescents administered measures of depression symptoms, emotional resilience, and perceptions of parenting. Parents of participating youth completed measures of youth emotional functioning. Parental responsiveness and psychological control each emerged as family variables that may be of value for predicting child emotional functioning beyond parent reports. Specifically, responsiveness explained significant variance in child depression and resilience after accounting for parent reports, while parental psychological control increased prediction of child mood alone. Results generally suggest that parenting behaviours may be an important consideration when children and parents provide discrepant reports of child emotional well-being. Conceptual and clinical implications of these results are discussed. PMID:22110912

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 age 4…

Self-Control, Social Factors, and Delinquency: A Test of the General Theory of Crime among Adolescents in Hong Kong

ERIC Educational Resources Information Center

Cheung, Nicole W. T.; Cheung, Yuet W.

2008-01-01

The objectives of this study were to test the predictive power of self-control theory for delinquency in a Chinese context, and to explore if social factors as predicted in social bonding theory, differential association theory, general strain theory, and labeling theory have effects on delinquency in the presence of self-control. Self-report data…

Early Urinary Markers of Diabetic Kidney Disease: A Nested Case-Control Study From the Diabetes Control and Complications Trial (DCCT)

PubMed Central

Kern, Elizabeth O; Erhard, Penny; Sun, Wanjie; Genuth, Saul; Weiss, Miriam F

2010-01-01

Background Urinary markers were tested as predictors of macroalbuminuria or microalbuminuria in type 1 diabetes. Study Design Nested case:control of participants in the Diabetes Control and Complications Trial (DCCT) Setting & Participants Eighty-seven cases of microalbuminuria were matched to 174 controls in a 1:2 ratio, while 4 cases were matched to 4 controls in a 1:1 ratio, resulting in 91 cases and 178 controls for microalbuminuria. Fifty-five cases of macroalbuminuria were matched to 110 controls in a 1:2 ratio. Controls were free of micro/macroalbuminuria when their matching case first developed micro/macroalbuminuria. Predictors Urinary N-acetyl-β-D-glucosaminidase, pentosidine, AGE fluorescence, albumin excretion rate (AER) Outcomes Incident microalbuminuria (two consecutive annual AER > 40 but <= 300 mg/day), or macroalbuminuria (AER > 300 mg/day) Measurements Stored urine samples from DCCT entry, and 1–9 years later when macroalbuminuria or microalbuminuria occurred, were measured for the lysosomal enzyme, N-acetyl-β-D-glucosaminidase, and the advanced glycosylation end-products (AGEs) pentosidine and AGE-fluorescence. AER and adjustor variables were obtained from the DCCT. Results Sub-microalbuminuric levels of AER at baseline independently predicted microalbuminuria (adjusted OR 1.83; p<.001) and macroalbuminuria (adjusted OR 1.82; p<.001). Baseline N-acetyl-β-D-glucosaminidase independently predicted macroalbuminuria (adjusted OR 2.26; p<.001), and microalbuminuria (adjusted OR 1.86; p<.001). Baseline pentosidine predicted macroalbuminuria (adjusted OR 6.89; p=.002). Baseline AGE fluorescence predicted microalbuminuria (adjusted OR 1.68; p=.02). However, adjusted for N-acetyl-β-D-glucosaminidase, pentosidine and AGE-fluorescence lost predictive association with macroalbuminuria and microalbuminuria, respectively. Limitations Use of angiotensin converting-enzyme inhibitors was not directly ascertained, although their use was proscribed during the DCCT. Conclusions Early in type 1 diabetes, repeated measurements of AER and urinary NAG may identify individuals susceptible to future diabetic nephropathy. Combining the two markers may yield a better predictive model than either one alone. Renal tubule stress may be more severe, reflecting abnormal renal tubule processing of AGE-modified proteins, among individuals susceptible to diabetic nephropathy. PMID:20138413

SU-E-T-630: Predictive Modeling of Mortality, Tumor Control, and Normal Tissue Complications After Stereotactic Body Radiotherapy for Stage I Non-Small Cell Lung Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lindsay, WD; Oncora Medical, LLC, Philadelphia, PA; Berlind, CG

Purpose: While rates of local control have been well characterized after stereotactic body radiotherapy (SBRT) for stage I non-small cell lung cancer (NSCLC), less data are available characterizing survival and normal tissue toxicities, and no validated models exist assessing these parameters after SBRT. We evaluate the reliability of various machine learning techniques when applied to radiation oncology datasets to create predictive models of mortality, tumor control, and normal tissue complications. Methods: A dataset of 204 consecutive patients with stage I non-small cell lung cancer (NSCLC) treated with stereotactic body radiotherapy (SBRT) at the University of Pennsylvania between 2009 and 2013more » was used to create predictive models of tumor control, normal tissue complications, and mortality in this IRB-approved study. Nearly 200 data fields of detailed patient- and tumor-specific information, radiotherapy dosimetric measurements, and clinical outcomes data were collected. Predictive models were created for local tumor control, 1- and 3-year overall survival, and nodal failure using 60% of the data (leaving the remainder as a test set). After applying feature selection and dimensionality reduction, nonlinear support vector classification was applied to the resulting features. Models were evaluated for accuracy and area under ROC curve on the 81-patient test set. Results: Models for common events in the dataset (such as mortality at one year) had the highest predictive power (AUC = .67, p < 0.05). For rare occurrences such as radiation pneumonitis and local failure (each occurring in less than 10% of patients), too few events were present to create reliable models. Conclusion: Although this study demonstrates the validity of predictive analytics using information extracted from patient medical records and can most reliably predict for survival after SBRT, larger sample sizes are needed to develop predictive models for normal tissue toxicities and more advanced machine learning methodologies need be consider in the future.« less

Applied Distributed Model Predictive Control for Energy Efficient Buildings and Ramp Metering

NASA Astrophysics Data System (ADS)

Koehler, Sarah Muraoka

Industrial large-scale control problems present an interesting algorithmic design challenge. A number of controllers must cooperate in real-time on a network of embedded hardware with limited computing power in order to maximize system efficiency while respecting constraints and despite communication delays. Model predictive control (MPC) can automatically synthesize a centralized controller which optimizes an objective function subject to a system model, constraints, and predictions of disturbance. Unfortunately, the computations required by model predictive controllers for large-scale systems often limit its industrial implementation only to medium-scale slow processes. Distributed model predictive control (DMPC) enters the picture as a way to decentralize a large-scale model predictive control problem. The main idea of DMPC is to split the computations required by the MPC problem amongst distributed processors that can compute in parallel and communicate iteratively to find a solution. Some popularly proposed solutions are distributed optimization algorithms such as dual decomposition and the alternating direction method of multipliers (ADMM). However, these algorithms ignore two practical challenges: substantial communication delays present in control systems and also problem non-convexity. This thesis presents two novel and practically effective DMPC algorithms. The first DMPC algorithm is based on a primal-dual active-set method which achieves fast convergence, making it suitable for large-scale control applications which have a large communication delay across its communication network. In particular, this algorithm is suited for MPC problems with a quadratic cost, linear dynamics, forecasted demand, and box constraints. We measure the performance of this algorithm and show that it significantly outperforms both dual decomposition and ADMM in the presence of communication delay. The second DMPC algorithm is based on an inexact interior point method which is suited for nonlinear optimization problems. The parallel computation of the algorithm exploits iterative linear algebra methods for the main linear algebra computations in the algorithm. We show that the splitting of the algorithm is flexible and can thus be applied to various distributed platform configurations. The two proposed algorithms are applied to two main energy and transportation control problems. The first application is energy efficient building control. Buildings represent 40% of energy consumption in the United States. Thus, it is significant to improve the energy efficiency of buildings. The goal is to minimize energy consumption subject to the physics of the building (e.g. heat transfer laws), the constraints of the actuators as well as the desired operating constraints (thermal comfort of the occupants), and heat load on the system. In this thesis, we describe the control systems of forced air building systems in practice. We discuss the "Trim and Respond" algorithm which is a distributed control algorithm that is used in practice, and show that it performs similarly to a one-step explicit DMPC algorithm. Then, we apply the novel distributed primal-dual active-set method and provide extensive numerical results for the building MPC problem. The second main application is the control of ramp metering signals to optimize traffic flow through a freeway system. This application is particularly important since urban congestion has more than doubled in the past few decades. The ramp metering problem is to maximize freeway throughput subject to freeway dynamics (derived from mass conservation), actuation constraints, freeway capacity constraints, and predicted traffic demand. In this thesis, we develop a hybrid model predictive controller for ramp metering that is guaranteed to be persistently feasible and stable. This contrasts to previous work on MPC for ramp metering where such guarantees are absent. We apply a smoothing method to the hybrid model predictive controller and apply the inexact interior point method to this nonlinear non-convex ramp metering problem.

Analysis and experimental evaluation of shunt active power filter for power quality improvement based on predictive direct power control.

PubMed

Aissa, Oualid; Moulahoum, Samir; Colak, Ilhami; Babes, Badreddine; Kabache, Nadir

2017-10-12

This paper discusses the use of the concept of classical and predictive direct power control for shunt active power filter function. These strategies are used to improve the active power filter performance by compensation of the reactive power and the elimination of the harmonic currents drawn by non-linear loads. A theoretical analysis followed by a simulation using MATLAB/Simulink software for the studied techniques has been established. Moreover, two test benches have been carried out using the dSPACE card 1104 for the classic and predictive DPC control to evaluate the studied methods in real time. Obtained results are presented and compared in this paper to confirm the superiority of the predictive technique. To overcome the pollution problems caused by the consumption of fossil fuels, renewable energies are the alternatives recommended to ensure green energy. In the same context, the tested predictive filter can easily be supplied by a renewable energy source that will give its impact to enhance the power quality.

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 transmission loss if not controlled appropriately. Inductive loads which operate with lagging power factor consume VARs, thus load compensation techniques by capacitor bank employment locally supply VARs needed by the load. Capacitors are highly unreliable components due to their failure modes and aging inherent. Approximately 60% of power electronic devices failure such as voltage-source inverter based static synchronous compensator (STATCOM) is due to the use of aluminum electrolytic DC capacitors. Therefore, a capacitor-less VAR compensation is desired. This dissertation also investigates a STATCOM capacitor-less reactive power compensation that uses only inductors combined with predictive controlled matrix converter.

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.

Results of an integrated structure/control law design sensitivity analysis

NASA Technical Reports Server (NTRS)

Gilbert, Michael G.

1989-01-01

A design sensitivity analysis method for Linear Quadratic Cost, Gaussian (LQG) optimal control laws, which predicts change in the optimal control law due to changes in fixed problem parameters using analytical sensitivity equations is discussed. Numerical results of a design sensitivity analysis for a realistic aeroservoelastic aircraft example are presented. In this example, the sensitivity of the optimally controlled aircraft's response to various problem formulation and physical aircraft parameters is determined. These results are used to predict the aircraft's new optimally controlled response if the parameter was to have some other nominal value during the control law design process. The sensitivity results are validated by recomputing the optimal control law for discrete variations in parameters, computing the new actual aircraft response, and comparing with the predicted response. These results show an improvement in sensitivity accuracy for integrated design purposes over methods which do not include changes in the optimal control law. Use of the analytical LQG sensitivity expressions is also shown to be more efficient than finite difference methods for the computation of the equivalent sensitivity information.

Emotional processing and self-control in adolescents with type 1 diabetes.

PubMed

Hughes, Amy E; Berg, Cynthia A; Wiebe, Deborah J

2012-09-01

This study examined whether emotional processing (understanding emotions), self-control (regulation of thoughts, emotions, and behavior), and their interaction predicted HbA1c for adolescents with type 1 diabetes over and above diabetes-specific constructs. Self-report measures of self-control, emotional processing, self-efficacy for diabetes management, diabetes-specific negative affect, and adherence, and HbA1c from medical records were obtained from 137 adolescents with type 1 diabetes (M age = 13.48 years). Emotional processing interacted with self-control to predict HbA1c, such that when adolescents had both low emotional processing and low self-control, HbA1c was poorest. Also, both high emotional processing and self-control buffered negative effects of low capacity in the other in relation to HbA1c. The interaction of emotional processing × self-control predicted HbA1c over diabetes-specific self-efficacy, negative affect, and adherence. These findings suggest the importance of emotional processing and self-control for health outcomes in adolescents with diabetes.

Emotional Processing and Self-Control in Adolescents With Type 1 Diabetes

PubMed Central

Hughes, Amy E.; Wiebe, Deborah J.

2012-01-01

Objective This study examined whether emotional processing (understanding emotions), self-control (regulation of thoughts, emotions, and behavior), and their interaction predicted HbA1c for adolescents with type 1 diabetes over and above diabetes-specific constructs. Methods Self-report measures of self-control, emotional processing, self-efficacy for diabetes management, diabetes-specific negative affect, and adherence, and HbA1c from medical records were obtained from 137 adolescents with type 1 diabetes (M age = 13.48 years). Results Emotional processing interacted with self-control to predict HbA1c, such that when adolescents had both low emotional processing and low self-control, HbA1c was poorest. Also, both high emotional processing and self-control buffered negative effects of low capacity in the other in relation to HbA1c. The interaction of emotional processing × self-control predicted HbA1c over diabetes-specific self-efficacy, negative affect, and adherence. Conclusions These findings suggest the importance of emotional processing and self-control for health outcomes in adolescents with diabetes. PMID:22523404

Model predictive controller design for boost DC-DC converter using T-S fuzzy cost function

NASA Astrophysics Data System (ADS)

Seo, Sang-Wha; Kim, Yong; Choi, Han Ho

2017-11-01

This paper proposes a Takagi-Sugeno (T-S) fuzzy method to select cost function weights of finite control set model predictive DC-DC converter control algorithms. The proposed method updates the cost function weights at every sample time by using T-S type fuzzy rules derived from the common optimal control engineering knowledge that a state or input variable with an excessively large magnitude can be penalised by increasing the weight corresponding to the variable. The best control input is determined via the online optimisation of the T-S fuzzy cost function for all the possible control input sequences. This paper implements the proposed model predictive control algorithm in real time on a Texas Instruments TMS320F28335 floating-point Digital Signal Processor (DSP). Some experimental results are given to illuminate the practicality and effectiveness of the proposed control system under several operating conditions. The results verify that our method can yield not only good transient and steady-state responses (fast recovery time, small overshoot, zero steady-state error, etc.) but also insensitiveness to abrupt load or input voltage parameter variations.

Reynolds-Averaged Navier-Stokes Analysis of Zero Efflux Flow Control over a Hump Model

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.

2006-01-01

The unsteady flow over a hump model with zero efflux oscillatory flow control is modeled computationally using the unsteady Reynolds-averaged Navier-Stokes equations. Three different turbulence models produce similar results, and do a reasonably good job predicting the general character of the unsteady surface pressure coefficients during the forced cycle. However, the turbulent shear stresses are underpredicted in magnitude inside the separation bubble, and the computed results predict too large a (mean) separation bubble compared with experiment. These missed predictions are consistent with earlier steady-state results using no-flow-control and steady suction, from a 2004 CFD validation workshop for synthetic jets.

Reynolds-Averaged Navier-Stokes Analysis of Zero Efflux Flow Control Over a Hump Model

NASA Technical Reports Server (NTRS)

Rumsey, Christopher L.

2006-01-01

The unsteady flow over a hump model with zero efflux oscillatory flow control is modeled computationally using the unsteady Reynolds-averaged Navier-Stokes equations. Three different turbulence models produce similar results, and do a reasonably good job predicting the general character of the unsteady surface pressure coefficients during the forced cycle. However, the turbulent shear stresses are underpredicted in magnitude inside the separation bubble, and the computed results predict too large a (mean) separation bubble compared with experiment. These missed predictions are consistent with earlier steady-state results using no-flow-control and steady suction, from a 2004 CFD validation workshop for synthetic jets.

Cell fate reprogramming by control of intracellular network dynamics

NASA Astrophysics Data System (ADS)

Zanudo, Jorge G. T.; Albert, Reka

Identifying control strategies for biological networks is paramount for practical applications that involve reprogramming a cell's fate, such as disease therapeutics and stem cell reprogramming. Although the topic of controlling the dynamics of a system has a long history in control theory, most of this work is not directly applicable to intracellular networks. Here we present a network control method that integrates the structural and functional information available for intracellular networks to predict control targets. Formulated in a logical dynamic scheme, our control method takes advantage of certain function-dependent network components and their relation to steady states in order to identify control targets, which are guaranteed to drive any initial state to the target state with 100% effectiveness and need to be applied only transiently for the system to reach and stay in the desired state. We illustrate our method's potential to find intervention targets for cancer treatment and cell differentiation by applying it to a leukemia signaling network and to the network controlling the differentiation of T cells. We find that the predicted control targets are effective in a broad dynamic framework. Moreover, several of the predicted interventions are supported by experiments. This work was supported by NSF Grant PHY 1205840.

Closed-loop control of artificial pancreatic Beta -cell in type 1 diabetes mellitus using model predictive iterative learning control.

PubMed

Wang, Youqing; Dassau, Eyal; Doyle, Francis J

2010-02-01

A novel combination of iterative learning control (ILC) and model predictive control (MPC), referred to here as model predictive iterative learning control (MPILC), is proposed for glycemic control in type 1 diabetes mellitus. MPILC exploits two key factors: frequent glucose readings made possible by continuous glucose monitoring technology; and the repetitive nature of glucose-meal-insulin dynamics with a 24-h cycle. The proposed algorithm can learn from an individual's lifestyle, allowing the control performance to be improved from day to day. After less than 10 days, the blood glucose concentrations can be kept within a range of 90-170 mg/dL. Generally, control performance under MPILC is better than that under MPC. The proposed methodology is robust to random variations in meal timings within +/-60 min or meal amounts within +/-75% of the nominal value, which validates MPILC's superior robustness compared to run-to-run control. Moreover, to further improve the algorithm's robustness, an automatic scheme for setpoint update that ensures safe convergence is proposed. Furthermore, the proposed method does not require user intervention; hence, the algorithm should be of particular interest for glycemic control in children and adolescents.

Impact of active controls technology on structural integrity

NASA Technical Reports Server (NTRS)

Noll, Thomas; Austin, Edward; Donley, Shawn; Graham, George; Harris, Terry

1991-01-01

This paper summarizes the findings of The Technical Cooperation Program to assess the impact of active controls technology on the structural integrity of aeronautical vehicles and to evaluate the present state-of-the-art for predicting the loads caused by a flight-control system modification and the resulting change in the fatigue life of the flight vehicle. The potential for active controls to adversely affect structural integrity is described, and load predictions obtained using two state-of-the-art analytical methods are given.

Modelling and model predictive control for a bicycle-rider system

NASA Astrophysics Data System (ADS)

Chu, T. D.; Chen, C. K.

2018-01-01

This study proposes a bicycle-rider control model based on model predictive control (MPC). First, a bicycle-rider model with leaning motion of the rider's upper body is developed. The initial simulation data of the bicycle rider are then used to identify the linear model of the system in state-space form for MPC design. Control characteristics of the proposed controller are assessed by simulating the roll-angle tracking control. In this riding task, the MPC uses steering and leaning torques as the control inputs to control the bicycle along a reference roll angle. The simulation results in different cases have demonstrated the applicability and performance of the MPC for bicycle-rider modelling.

A Wavelet Neural Network Optimal Control Model for Traffic-Flow Prediction in Intelligent Transport Systems

NASA Astrophysics Data System (ADS)

Huang, Darong; Bai, Xing-Rong

Based on wavelet transform and neural network theory, a traffic-flow prediction model, which was used in optimal control of Intelligent Traffic system, is constructed. First of all, we have extracted the scale coefficient and wavelet coefficient from the online measured raw data of traffic flow via wavelet transform; Secondly, an Artificial Neural Network model of Traffic-flow Prediction was constructed and trained using the coefficient sequences as inputs and raw data as outputs; Simultaneous, we have designed the running principium of the optimal control system of traffic-flow Forecasting model, the network topological structure and the data transmitted model; Finally, a simulated example has shown that the technique is effectively and exactly. The theoretical results indicated that the wavelet neural network prediction model and algorithms have a broad prospect for practical application.

Level of self-esteem and contingencies of self-worth: unique effects on academic, social, and financial problems in college students.

PubMed

Crocker, Jennifer; Luhtanen, Riia K

2003-06-01

The unique effects of level of self-esteem and contingencies of self-worth assessed prior to college on academic, social, and financial problems experienced during the freshman year were examined in a longitudinal study of 642 college students. Low self-esteem predicted social problems, even controlling for demographic and personality variables (neuroticism, agreeableness, and social desirability), but did not predict academic or financial problems with other variables controlled. Academic competence contingency predicted academic and financial problems and appearance contingency predicted financial problems, even after controlling for relevant personality variables. We conclude that contingencies of self-worth uniquely contribute to academic and financial difficulties experienced by college freshmen beyond level of self-esteem and other personality variables. Low self-esteem, on the other hand, appears to uniquely contribute to later social difficulties.

Predicting forage intake by grazing beef cattle

USDA-ARS?s Scientific Manuscript database

The control of feed intake by ruminants is complex, and developing a cohesive theory of intake control in ruminants continues to be a challenge. Because our understanding of factors that regulate intake by cattle is inadequate, predicting feed intake, even under the best of circumstances, is diffic...

A predictive pilot model for STOL aircraft landing

NASA Technical Reports Server (NTRS)

Kleinman, D. L.; Killingsworth, W. R.

1974-01-01

An optimal control approach has been used to model pilot performance during STOL flare and landing. The model is used to predict pilot landing performance for three STOL configurations, each having a different level of automatic control augmentation. Model predictions are compared with flight simulator data. It is concluded that the model can be effective design tool for studying analytically the effects of display modifications, different stability augmentation systems, and proposed changes in the landing area geometry.

Incremental Validity of Biographical Data in the Prediction of En Route Air Traffic Control Specialist Technical Skills

DTIC Science & Technology

2012-07-01

Incremental Validity of Biographical Data in the Prediction of En Route Air Traffic Control Specialist Technical Skills Dana Broach Civil Aerospace...Medical Institute Federal Aviation Administration Oklahoma City, OK 73125 July 2012 Final Report DOT/FAA/AM- 12 /8 Office of Aerospace Medicine...FAA/AM- 12 /8 4. Title and Subtitle 5. Report Date July 2012 Incremental Validity of Biographical Data in the Prediction of En Route Air

Prediction Study on Anti-Slide Control of Railway Vehicle Based on RBF Neural Networks

NASA Astrophysics Data System (ADS)

Yang, Lijun; Zhang, Jimin

While railway vehicle braking, Anti-slide control system will detect operating status of each wheel-sets e.g. speed difference and deceleration etc. Once the detected value on some wheel-set is over pre-defined threshold, brake effort on such wheel-set will be adjusted automatically to avoid blocking. Such method takes effect on guarantee safety operation of vehicle and avoid wheel-set flatness, however it cannot adapt itself to the rail adhesion variation. While wheel-sets slide, the operating status is chaotic time series with certain law, and can be predicted with the law and experiment data in certain time. The predicted values can be used as the input reference signals of vehicle anti-slide control system, to judge and control the slide status of wheel-sets. In this article, the RBF neural networks is taken to predict wheel-set slide status in multi-step with weight vector adjusted based on online self-adaptive algorithm, and the center & normalizing parameters of active function of the hidden unit of RBF neural networks' hidden layer computed with K-means clustering algorithm. With multi-step prediction simulation, the predicted signal with appropriate precision can be used by anti-slide system to trace actively and adjust wheel-set slide tendency, so as to adapt to wheel-rail adhesion variation and reduce the risk of wheel-set blocking.

Machine Learning EEG to Predict Cognitive Functioning and Processing Speed Over a 2-Year Period in Multiple Sclerosis Patients and Controls.

PubMed

Kiiski, Hanni; Jollans, Lee; Donnchadha, Seán Ó; Nolan, Hugh; Lonergan, Róisín; Kelly, Siobhán; O'Brien, Marie Claire; Kinsella, Katie; Bramham, Jessica; Burke, Teresa; Hutchinson, Michael; Tubridy, Niall; Reilly, Richard B; Whelan, Robert

2018-05-01

Event-related potentials (ERPs) show promise to be objective indicators of cognitive functioning. The aim of the study was to examine if ERPs recorded during an oddball task would predict cognitive functioning and information processing speed in Multiple Sclerosis (MS) patients and controls at the individual level. Seventy-eight participants (35 MS patients, 43 healthy age-matched controls) completed visual and auditory 2- and 3-stimulus oddball tasks with 128-channel EEG, and a neuropsychological battery, at baseline (month 0) and at Months 13 and 26. ERPs from 0 to 700 ms and across the whole scalp were transformed into 1728 individual spatio-temporal datapoints per participant. A machine learning method that included penalized linear regression used the entire spatio-temporal ERP to predict composite scores of both cognitive functioning and processing speed at baseline (month 0), and months 13 and 26. The results showed ERPs during the visual oddball tasks could predict cognitive functioning and information processing speed at baseline and a year later in a sample of MS patients and healthy controls. In contrast, ERPs during auditory tasks were not predictive of cognitive performance. These objective neurophysiological indicators of cognitive functioning and processing speed, and machine learning methods that can interrogate high-dimensional data, show promise in outcome prediction.

Convolutional neural networks for prostate cancer recurrence prediction

NASA Astrophysics Data System (ADS)

Kumar, Neeraj; Verma, Ruchika; Arora, Ashish; Kumar, Abhay; Gupta, Sanchit; Sethi, Amit; Gann, Peter H.

2017-03-01

Accurate prediction of the treatment outcome is important for cancer treatment planning. We present an approach to predict prostate cancer (PCa) recurrence after radical prostatectomy using tissue images. We used a cohort whose case vs. control (recurrent vs. non-recurrent) status had been determined using post-treatment follow up. Further, to aid the development of novel biomarkers of PCa recurrence, cases and controls were paired based on matching of other predictive clinical variables such as Gleason grade, stage, age, and race. For this cohort, tissue resection microarray with up to four cores per patient was available. The proposed approach is based on deep learning, and its novelty lies in the use of two separate convolutional neural networks (CNNs) - one to detect individual nuclei even in the crowded areas, and the other to classify them. To detect nuclear centers in an image, the first CNN predicts distance transform of the underlying (but unknown) multi-nuclear map from the input HE image. The second CNN classifies the patches centered at nuclear centers into those belonging to cases or controls. Voting across patches extracted from image(s) of a patient yields the probability of recurrence for the patient. The proposed approach gave 0.81 AUC for a sample of 30 recurrent cases and 30 non-recurrent controls, after being trained on an independent set of 80 case-controls pairs. If validated further, such an approach might help in choosing between a combination of treatment options such as active surveillance, radical prostatectomy, radiation, and hormone therapy. It can also generalize to the prediction of treatment outcomes in other cancers.

TankSIM: A Cryogenic Tank Performance Prediction Program

NASA Technical Reports Server (NTRS)

Bolshinskiy, L. G.; Hedayat, A.; Hastings, L. J.; Moder, J. P.; Schnell, A. R.; Sutherlin, S. G.

2015-01-01

Accurate prediction of the thermodynamic state of the cryogenic propellants in launch vehicle tanks is necessary for mission planning and successful execution. Cryogenic propellant storage and transfer in space environments requires that tank pressure be controlled. The pressure rise rate is determined by the complex interaction of external heat leak, fluid temperature stratification, and interfacial heat and mass transfer. If the required storage duration of a space mission is longer than the period in which the tank pressure reaches its allowable maximum, an appropriate pressure control method must be applied. Therefore, predictions of the pressurization rate and performance of pressure control techniques in cryogenic tanks are required for development of cryogenic fluid long-duration storage technology and planning of future space exploration missions. This paper describes an analytical tool, Tank System Integrated Model (TankSIM), which can be used for modeling pressure control and predicting the behavior of cryogenic propellant for long-term storage for future space missions. It is written in the FORTRAN 90 language and can be compiled with any Visual FORTRAN compiler. A thermodynamic vent system (TVS) is used to achieve tank pressure control. Utilizing TankSIM, the following processes can be modeled: tank self-pressurization, boiloff, ullage venting, and mixing. Details of the TankSIM program and comparisons of its predictions with test data for liquid hydrogen and liquid methane will be presented in the final paper.

Patient-specific dosimetric endpoints based treatment plan quality control in radiotherapy.

PubMed

Song, Ting; Staub, David; Chen, Mingli; Lu, Weiguo; Tian, Zhen; Jia, Xun; Li, Yongbao; Zhou, Linghong; Jiang, Steve B; Gu, Xuejun

2015-11-07

In intensity modulated radiotherapy (IMRT), the optimal plan for each patient is specific due to unique patient anatomy. To achieve such a plan, patient-specific dosimetric goals reflecting each patient's unique anatomy should be defined and adopted in the treatment planning procedure for plan quality control. This study is to develop such a personalized treatment plan quality control tool by predicting patient-specific dosimetric endpoints (DEs). The incorporation of patient specific DEs is realized by a multi-OAR geometry-dosimetry model, capable of predicting optimal DEs based on the individual patient's geometry. The overall quality of a treatment plan is then judged with a numerical treatment plan quality indicator and characterized as optimal or suboptimal. Taking advantage of clinically available prostate volumetric modulated arc therapy (VMAT) treatment plans, we built and evaluated our proposed plan quality control tool. Using our developed tool, six of twenty evaluated plans were identified as sub-optimal plans. After plan re-optimization, these suboptimal plans achieved better OAR dose sparing without sacrificing the PTV coverage, and the dosimetric endpoints of the re-optimized plans agreed well with the model predicted values, which validate the predictability of the proposed tool. In conclusion, the developed tool is able to accurately predict optimally achievable DEs of multiple OARs, identify suboptimal plans, and guide plan optimization. It is a useful tool for achieving patient-specific treatment plan quality control.

Working memory capacity as controlled attention in tactical decision making.

PubMed

Furley, Philip A; Memmert, Daniel

2012-06-01

The controlled attention theory of working memory capacity (WMC, Engle 2002) suggests that WMC represents a domain free limitation in the ability to control attention and is predictive of an individual's capability of staying focused, avoiding distraction and impulsive errors. In the present paper we test the predictive power of WMC in computer-based sport decision-making tasks. Experiment 1 demonstrated that high-WMC athletes were better able at focusing their attention on tactical decision making while blocking out irrelevant auditory distraction. Experiment 2 showed that high-WMC athletes were more successful at adapting their tactical decision making according to the situation instead of relying on prepotent inappropriate decisions. The present results provide additional but also unique support for the controlled attention theory of WMC by demonstrating that WMC is predictive of controlling attention in complex settings among different modalities and highlight the importance of working memory in tactical decision making.

Work, family and life-course fit

PubMed Central

Moen, Phyllis; Kelly, Erin; Huang, Qinlei

2008-01-01

This study moves from “work-family” to a multi-dimensional “life-course fit” construct (employees’ cognitive assessments of resources, resource deficits, and resource demands), using a combined work-family, demands-control and ecology of the life course framing. It examined (1) impacts of job and home ecological systems on fit dimensions, and (2) whether control over work time predicted and mediated life-course fit outcomes. Using cluster analysis of survey data on a sample of 917 white-collar employees from Best Buy headquarters, we identified four job ecologies (corresponding to the job demands-job control model) and five home ecologies (theorizing an analogous home demands-home control model). Job and home ecologies predicted fit dimensions in an additive, not interactive, fashion. Employees’ work-time control predicted every life-course fit dimension and partially mediated effects of job ecologies, organizational tenure, and job category. PMID:19430546

Validation and comparison of clinical prediction rules for invasive candidiasis in intensive care unit patients: a matched case-control study

PubMed Central

2011-01-01

Introduction Due to the increasing prevalence and severity of invasive candidiasis, investigators have developed clinical prediction rules to identify patients who may benefit from antifungal prophylaxis or early empiric therapy. The aims of this study were to validate and compare the Paphitou and Ostrosky-Zeichner clinical prediction rules in ICU patients in a 689-bed academic medical center. Methods We conducted a retrospective matched case-control study from May 2003 to June 2008 to evaluate the sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of each rule. Cases included adults with ICU stays of at least four days and invasive candidiasis matched to three controls by age, gender and ICU admission date. The clinical prediction rules were applied to cases and controls via retrospective chart review to evaluate the success of the rules in predicting invasive candidiasis. Paphitou's rule included diabetes, total parenteral nutrition (TPN) and dialysis with or without antibiotics. Ostrosky-Zeichner's rule included antibiotics or central venous catheter plus at least two of the following: surgery, immunosuppression, TPN, dialysis, corticosteroids and pancreatitis. Conditional logistic regression was performed to evaluate the rules. Discriminative power was evaluated by area under the receiver operating characteristic curve (AUC ROC). Results A total of 352 patients were included (88 cases and 264 controls). The incidence of invasive candidiasis among adults with an ICU stay of at least four days was 2.3%. The prediction rules performed similarly, exhibiting low PPVs (0.041 to 0.054), high NPVs (0.983 to 0.990) and AUC ROCs (0.649 to 0.705). A new prediction rule (Nebraska Medical Center rule) was developed with PPVs, NPVs and AUC ROCs of 0.047, 0.994 and 0.770, respectively. Conclusions Based on low PPVs and high NPVs, the rules are most useful for identifying patients who are not likely to develop invasive candidiasis, potentially preventing unnecessary antifungal use, optimizing patient ICU care and facilitating the design of forthcoming antifungal clinical trials. PMID:21846332

Development and External Validation of a Melanoma Risk Prediction Model Based on Self-assessed Risk Factors.

PubMed

Vuong, Kylie; Armstrong, Bruce K; Weiderpass, Elisabete; Lund, Eiliv; Adami, Hans-Olov; Veierod, Marit B; Barrett, Jennifer H; Davies, John R; Bishop, D Timothy; Whiteman, David C; Olsen, Catherine M; Hopper, John L; Mann, Graham J; Cust, Anne E; McGeechan, Kevin

2016-08-01

Identifying individuals at high risk of melanoma can optimize primary and secondary prevention strategies. To develop and externally validate a risk prediction model for incident first-primary cutaneous melanoma using self-assessed risk factors. We used unconditional logistic regression to develop a multivariable risk prediction model. Relative risk estimates from the model were combined with Australian melanoma incidence and competing mortality rates to obtain absolute risk estimates. A risk prediction model was developed using the Australian Melanoma Family Study (629 cases and 535 controls) and externally validated using 4 independent population-based studies: the Western Australia Melanoma Study (511 case-control pairs), Leeds Melanoma Case-Control Study (960 cases and 513 controls), Epigene-QSkin Study (44 544, of which 766 with melanoma), and Swedish Women's Lifestyle and Health Cohort Study (49 259 women, of which 273 had melanoma). We validated model performance internally and externally by assessing discrimination using the area under the receiver operating curve (AUC). Additionally, using the Swedish Women's Lifestyle and Health Cohort Study, we assessed model calibration and clinical usefulness. The risk prediction model included hair color, nevus density, first-degree family history of melanoma, previous nonmelanoma skin cancer, and lifetime sunbed use. On internal validation, the AUC was 0.70 (95% CI, 0.67-0.73). On external validation, the AUC was 0.66 (95% CI, 0.63-0.69) in the Western Australia Melanoma Study, 0.67 (95% CI, 0.65-0.70) in the Leeds Melanoma Case-Control Study, 0.64 (95% CI, 0.62-0.66) in the Epigene-QSkin Study, and 0.63 (95% CI, 0.60-0.67) in the Swedish Women's Lifestyle and Health Cohort Study. Model calibration showed close agreement between predicted and observed numbers of incident melanomas across all deciles of predicted risk. In the external validation setting, there was higher net benefit when using the risk prediction model to classify individuals as high risk compared with classifying all individuals as high risk. The melanoma risk prediction model performs well and may be useful in prevention interventions reliant on a risk assessment using self-assessed risk factors.

Changes in Gene Expression Predicting Local Control in Cervical Cancer: Results from Radiation Therapy Oncology Group 0128

PubMed Central

Weidhaas, Joanne B.; Li, Shu-Xia; Winter, Kathryn; Ryu, Janice; Jhingran, Anuja; Miller, Bridgette; Dicker, Adam P.; Gaffney, David

2009-01-01

Purpose To evaluate the potential of gene expression signatures to predict response to treatment in locally advanced cervical cancer treated with definitive chemotherapy and radiation. Experimental Design Tissue biopsies were collected from patients participating in Radiation Therapy Oncology Group (RTOG) 0128, a phase II trial evaluating the benefit of celecoxib in addition to cisplatin chemotherapy and radiation for locally advanced cervical cancer. Gene expression profiling was done and signatures of pretreatment, mid-treatment (before the first implant), and “changed” gene expression patterns between pre- and mid-treatment samples were determined. The ability of the gene signatures to predict local control versus local failure was evaluated. Two-group t test was done to identify the initial gene set separating these end points. Supervised classification methods were used to enrich the gene sets. The results were further validated by leave-one-out and 2-fold cross-validation. Results Twenty-two patients had suitable material from pretreatment samples for analysis, and 13 paired pre- and mid-treatment samples were obtained. The changed gene expression signatures between the pre- and mid-treatment biopsies predicted response to treatment, separating patients with local failures from those who achieved local control with a seven-gene signature. The in-sample prediction rate, leave-one-out prediction rate, and 2-fold prediction rate are 100% for this seven-gene signature. This signature was enriched for cell cycle genes. Conclusions Changed gene expression signatures during therapy in cervical cancer can predict outcome as measured by local control. After further validation, such findings could be applied to direct additional therapy for cervical cancer patients treated with chemotherapy and radiation. PMID:19509178

A discriminant analysis prediction model of non-syndromic cleft lip with or without cleft palate based on risk factors.

PubMed

Li, Huixia; Luo, Miyang; Luo, Jiayou; Zheng, Jianfei; Zeng, Rong; Du, Qiyun; Fang, Junqun; Ouyang, Na

2016-11-23

A risk prediction model of non-syndromic cleft lip with or without cleft palate (NSCL/P) was established by a discriminant analysis to predict the individual risk of NSCL/P in pregnant women. A hospital-based case-control study was conducted with 113 cases of NSCL/P and 226 controls without NSCL/P. The cases and the controls were obtained from 52 birth defects' surveillance hospitals in Hunan Province, China. A questionnaire was administered in person to collect the variables relevant to NSCL/P by face to face interviews. Logistic regression models were used to analyze the influencing factors of NSCL/P, and a stepwise Fisher discriminant analysis was subsequently used to construct the prediction model. In the univariate analysis, 13 influencing factors were related to NSCL/P, of which the following 8 influencing factors as predictors determined the discriminant prediction model: family income, maternal occupational hazards exposure, premarital medical examination, housing renovation, milk/soymilk intake in the first trimester of pregnancy, paternal occupational hazards exposure, paternal strong tea drinking, and family history of NSCL/P. The model had statistical significance (lambda = 0.772, chi-square = 86.044, df = 8, P < 0.001). Self-verification showed that 83.8 % of the participants were correctly predicted to be NSCL/P cases or controls with a sensitivity of 74.3 % and a specificity of 88.5 %. The area under the receiver operating characteristic curve (AUC) was 0.846. The prediction model that was established using the risk factors of NSCL/P can be useful for predicting the risk of NSCL/P. Further research is needed to improve the model, and confirm the validity and reliability of the model.

An intelligent system with EMG-based joint angle estimation for telemanipulation.

PubMed

Suryanarayanan, S; Reddy, N P; Gupta, V

1996-01-01

Bio-control of telemanipulators is being researched as an alternate control strategy. This study investigates the use of surface EMG from the biceps to predict joint angle during flexion of the arm that can be used to control an anthropomorphic telemanipulator. An intelligent system based on neural networks and fuzzy logic has been developed to use the processed surface EMG signal and predict the joint angle. The system has been tested on various angles of flexion-extension of the arm and at several speeds of flexion-extension. Preliminary results show the RMS error between the predicted angle and the actual angle to be less than 3% during training and less than 15% during testing. The technique of direct bio-control using EMG has the potential as an interface for telemanipulation applications.

Life extending control: An interdisciplinary engineering thrust

NASA Technical Reports Server (NTRS)

Lorenzo, Carl F.; Merrill, Walter C.

1991-01-01

The concept of Life Extending Control (LEC) is introduced. Possible extensions to the cyclic damage prediction approach are presented based on the identification of a model from elementary forms. Several candidate elementary forms are presented. These extensions will result in a continuous or differential form of the damage prediction model. Two possible approaches to the LEC based on the existing cyclic damage prediction method, the measured variables LEC and the estimated variables LEC, are defined. Here, damage estimates or measurements would be used directly in the LEC. A simple hydraulic actuator driven position control system example is used to illustrate the main ideas behind LEC. Results from a simple hydraulic actuator example demonstrate that overall system performance (dynamic plus life) can be maximized by accounting for component damage in the control design.

Intermittent control: a computational theory of human control.

PubMed

Gawthrop, Peter; Loram, Ian; Lakie, Martin; Gollee, Henrik

2011-02-01

The paradigm of continuous control using internal models has advanced understanding of human motor control. However, this paradigm ignores some aspects of human control, including intermittent feedback, serial ballistic control, triggered responses and refractory periods. It is shown that event-driven intermittent control provides a framework to explain the behaviour of the human operator under a wider range of conditions than continuous control. Continuous control is included as a special case, but sampling, system matched hold, an intermittent predictor and an event trigger allow serial open-loop trajectories using intermittent feedback. The implementation here may be described as "continuous observation, intermittent action". Beyond explaining unimodal regulation distributions in common with continuous control, these features naturally explain refractoriness and bimodal stabilisation distributions observed in double stimulus tracking experiments and quiet standing, respectively. Moreover, given that human control systems contain significant time delays, a biological-cybernetic rationale favours intermittent over continuous control: intermittent predictive control is computationally less demanding than continuous predictive control. A standard continuous-time predictive control model of the human operator is used as the underlying design method for an event-driven intermittent controller. It is shown that when event thresholds are small and sampling is regular, the intermittent controller can masquerade as the underlying continuous-time controller and thus, under these conditions, the continuous-time and intermittent controller cannot be distinguished. This explains why the intermittent control hypothesis is consistent with the continuous control hypothesis for certain experimental conditions.

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.

Generalized role for the cerebellum in encoding internal models: evidence from semantic processing.

PubMed

Moberget, Torgeir; Gullesen, Eva Hilland; Andersson, Stein; Ivry, Richard B; Endestad, Tor

2014-02-19

The striking homogeneity of cerebellar microanatomy is strongly suggestive of a corresponding uniformity of function. Consequently, theoretical models of the cerebellum's role in motor control should offer important clues regarding cerebellar contributions to cognition. One such influential theory holds that the cerebellum encodes internal models, neural representations of the context-specific dynamic properties of an object, to facilitate predictive control when manipulating the object. The present study examined whether this theoretical construct can shed light on the contribution of the cerebellum to language processing. We reasoned that the cerebellum might perform a similar coordinative function when the context provided by the initial part of a sentence can be highly predictive of the end of the sentence. Using functional MRI in humans we tested two predictions derived from this hypothesis, building on previous neuroimaging studies of internal models in motor control. First, focal cerebellar activation-reflecting the operation of acquired internal models-should be enhanced when the linguistic context leads terminal words to be predictable. Second, more widespread activation should be observed when such predictions are violated, reflecting the processing of error signals that can be used to update internal models. Both predictions were confirmed, with predictability and prediction violations associated with increased blood oxygenation level-dependent signal in the posterior cerebellum (Crus I/II). Our results provide further evidence for cerebellar involvement in predictive language processing and suggest that the notion of cerebellar internal models may be extended to the language domain.

Perceived Control and Social Activity in Midlife and Older Age: A Reciprocal Association? Findings From the German Ageing Survey.

PubMed

Curtis, Rachel G; Huxhold, Oliver; Windsor, Tim D

2018-06-14

Perceived control may promote social activity in older adults because individuals with greater perceived control have greater confidence in their ability to achieve outcomes and are more likely to choose difficult activities, show persistence, and employ strategies to overcome challenges. Cross-sectional research has linked perceived control with social activity in life span and older adult samples but provides little insight into the direction of influence. We examined reciprocal associations between perceived control and social activity in order to establish temporal sequencing, which is one prerequisite for determining potential causation. Participants were 14,126 midlife and older adults from the German Ageing Survey. Using cross-lagged autoregressive modeling with age as the time metric (40-87 years), we examined reciprocal 3-year lagged associations between perceived control and social activity, while controlling for concurrent associations. Perceived control significantly predicted social activity 3 years later. Reciprocally, social activity significantly predicted perceived control 3 years later. The influence of perceived control on social activity was greater than the influence of social activity on perceived control. The finding that perceived control significantly predicts future social activity has potential implications for developing interventions aimed at promoting social activity in midlife and older adults.

The Influence of Parental Control and Parent-Child Relational Qualities on Adolescent Internet Addiction: A 3-Year Longitudinal Study in Hong Kong

PubMed Central

Shek, Daniel T. L.; Zhu, Xiaoqin; Ma, Cecilia M. S.

2018-01-01

This study investigated how parental behavioral control, parental psychological control, and parent-child relational qualities predicted the initial level and rate of change in adolescent internet addiction (IA) across the junior high school years. The study also investigated the concurrent and longitudinal effects of different parenting factors on adolescent IA. Starting from the 2009/2010 academic year, 3,328 Grade 7 students (Mage = 12.59 ± 0.74 years) from 28 randomly selected secondary schools in Hong Kong responded on a yearly basis to a questionnaire measuring multiple constructs including socio-demographic characteristics, perceived parenting characteristics, and IA. Individual growth curve (IGC) analyses showed that adolescent IA slightly decreased during junior high school years. While behavioral control of both parents was negatively related to the initial level of adolescent IA, only paternal behavioral control showed a significant positive relationship with the rate of linear change in IA, suggesting that higher paternal behavioral control predicted a slower decrease in IA. In addition, fathers' and mothers' psychological control was positively associated with the initial level of adolescent IA, but increase in maternal psychological control predicted a faster drop in IA. Finally, parent-child relational qualities negatively and positively predicted the initial level and the rate of change in IA, respectively. When all parenting factors were considered simultaneously, multiple regression analyses revealed that paternal behavioral control and psychological control as well as maternal psychological control and mother-child relational quality were significant concurrent predictors of adolescent IA at Wave 2 and Wave 3. Regarding the longitudinal predicting effects, paternal psychological control and mother-child relational quality at Wave 1 were the two most robust predictors of later adolescent IA at Wave 2 and Wave 3. The above findings underscore the importance of the parent-child subsystem qualities in influencing adolescent IA in the junior high school years. In particular, these findings shed light on the different impacts of fathering and mothering which are neglected in the scientific literature. While the findings based on the levels of IA are consistent with the existing theoretical models, findings on the rate of change are novel. PMID:29765349

The Influence of Parental Control and Parent-Child Relational Qualities on Adolescent Internet Addiction: A 3-Year Longitudinal Study in Hong Kong.

PubMed

Shek, Daniel T L; Zhu, Xiaoqin; Ma, Cecilia M S

2018-01-01

This study investigated how parental behavioral control, parental psychological control, and parent-child relational qualities predicted the initial level and rate of change in adolescent internet addiction (IA) across the junior high school years. The study also investigated the concurrent and longitudinal effects of different parenting factors on adolescent IA. Starting from the 2009/2010 academic year, 3,328 Grade 7 students ( M age = 12.59 ± 0.74 years) from 28 randomly selected secondary schools in Hong Kong responded on a yearly basis to a questionnaire measuring multiple constructs including socio-demographic characteristics, perceived parenting characteristics, and IA. Individual growth curve (IGC) analyses showed that adolescent IA slightly decreased during junior high school years. While behavioral control of both parents was negatively related to the initial level of adolescent IA, only paternal behavioral control showed a significant positive relationship with the rate of linear change in IA, suggesting that higher paternal behavioral control predicted a slower decrease in IA. In addition, fathers' and mothers' psychological control was positively associated with the initial level of adolescent IA, but increase in maternal psychological control predicted a faster drop in IA. Finally, parent-child relational qualities negatively and positively predicted the initial level and the rate of change in IA, respectively. When all parenting factors were considered simultaneously, multiple regression analyses revealed that paternal behavioral control and psychological control as well as maternal psychological control and mother-child relational quality were significant concurrent predictors of adolescent IA at Wave 2 and Wave 3. Regarding the longitudinal predicting effects, paternal psychological control and mother-child relational quality at Wave 1 were the two most robust predictors of later adolescent IA at Wave 2 and Wave 3. The above findings underscore the importance of the parent-child subsystem qualities in influencing adolescent IA in the junior high school years. In particular, these findings shed light on the different impacts of fathering and mothering which are neglected in the scientific literature. While the findings based on the levels of IA are consistent with the existing theoretical models, findings on the rate of change are novel.

Aircraft Trajectories Computation-Prediction-Control. Volume 1 (La Trajectoire de l’Avion Calcul-Prediction-Controle)

DTIC Science & Technology

1990-03-01

knowledge covering problems of this type is called calculus of variations or optimal control theory (Refs. 1-8). As stated before, appli - cations occur...to the optimality conditions and the feasibility equations of Problem (GP), respectively. Clearly, after the transformation (26) is applied , the...trajectories, the primal sequential gradient-restoration algorithm (PSGRA) is applied to compute optimal trajectories for aeroassisted orbital transfer

Further Investigation of Receding Horizion-Based Controllers and Neural Network-Based Systems

NASA Technical Reports Server (NTRS)

Kelkar, Atul G.; Haley, Pamela J. (Technical Monitor)

2000-01-01

This report provides a comprehensive summary of the research work performed over the entire duration of the co-operative research agreement between NASA Langley Research Center and Kansas State University. This summary briefly lists the findings and also suggests possible future directions for the continuation of the subject research in the area of Generalized Predictive Control (GPC) and Network Based Generalized Predictive Control (NGPC).

Three-compartment model for contaminant accumulation by semipermeable membrane devices

USGS Publications Warehouse

Gale, Robert W.

1998-01-01

Passive sampling of dissolved hydrophobic contaminants with lipid (triolein)-containing semipermeable membrane devices (SPMDs) has been gaining acceptance for environmental monitoring. Understanding of the accumulation process has employed a simple polymer film-control model of uptake by the polymer-enclosed lipid, while aqueous film control has been only briefly discussed. A more complete three-compartment model incorporating both aqueous film (turbulent-diffusive) and polymer film (diffusive) mass transfer is developed here and is fit to data from accumulation studies conducted in constant-concentration, flow-through dilutors. This model predicts aqueous film control of the whole device for moderate to high Kow compounds, rather than polymer film control. Uptake rates for phenanthrene and 2,2‘,5,5‘-tetrachlorobiphenyl were about 4.8 and 4.2 L/day/standard SPMD, respectively. Maximum 28 day SPMD concentration factors of 30 000 are predicted for solutes with log Kow values of >5.5. Effects of varying aqueous and polymer film thicknesses and solute diffusivities in the polymer film are modeled, and overall accumulation by the whole device is predicted to remain under aqueous film control, although accumulation in the triolein may be subject to polymer film control. The predicted half-life and integrative response of SPMDs to pulsed concentration events is proportional to log KSPMD.

Real-time and simultaneous control of artificial limbs based on pattern recognition algorithms.

PubMed

Ortiz-Catalan, Max; Håkansson, Bo; Brånemark, Rickard

2014-07-01

The prediction of simultaneous limb motions is a highly desirable feature for the control of artificial limbs. In this work, we investigate different classification strategies for individual and simultaneous movements based on pattern recognition of myoelectric signals. Our results suggest that any classifier can be potentially employed in the prediction of simultaneous movements if arranged in a distributed topology. On the other hand, classifiers inherently capable of simultaneous predictions, such as the multi-layer perceptron (MLP), were found to be more cost effective, as they can be successfully employed in their simplest form. In the prediction of individual movements, the one-vs-one (OVO) topology was found to improve classification accuracy across different classifiers and it was therefore used to benchmark the benefits of simultaneous control. As opposed to previous work reporting only offline accuracy, the classification performance and the resulting controllability are evaluated in real time using the motion test and target achievement control (TAC) test, respectively. We propose a simultaneous classification strategy based on MLP that outperformed a top classifier for individual movements (LDA-OVO), thus improving the state-of-the-art classification approach. Furthermore, all the presented classification strategies and data collected in this study are freely available in BioPatRec, an open source platform for the development of advanced prosthetic control strategies.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Adigun, Babatunde John; Fensin, Michael Lorne; Galloway, Jack D.

Our burnup study examined the effect of a predicted critical control rod position on the nuclide predictability of several axial and radial locations within a 4×4 graphite moderated gas cooled reactor fuel cluster geometry. To achieve this, a control rod position estimator (CRPE) tool was developed within the framework of the linkage code Monteburns between the transport code MCNP and depletion code CINDER90, and four methodologies were proposed within the tool for maintaining criticality. Two of the proposed methods used an inverse multiplication approach - where the amount of fissile material in a set configuration is slowly altered until criticalitymore » is attained - in estimating the critical control rod position. Another method carried out several MCNP criticality calculations at different control rod positions, then used a linear fit to estimate the critical rod position. The final method used a second-order polynomial fit of several MCNP criticality calculations at different control rod positions to guess the critical rod position. The results showed that consistency in prediction of power densities as well as uranium and plutonium isotopics was mutual among methods within the CRPE tool that predicted critical position consistently well. Finall, while the CRPE tool is currently limited to manipulating a single control rod, future work could be geared toward implementing additional criticality search methodologies along with additional features.« less

Quality by control: Towards model predictive control of mammalian cell culture bioprocesses.

PubMed

Sommeregger, Wolfgang; Sissolak, Bernhard; Kandra, Kulwant; von Stosch, Moritz; Mayer, Martin; Striedner, Gerald

2017-07-01

The industrial production of complex biopharmaceuticals using recombinant mammalian cell lines is still mainly built on a quality by testing approach, which is represented by fixed process conditions and extensive testing of the end-product. In 2004 the FDA launched the process analytical technology initiative, aiming to guide the industry towards advanced process monitoring and better understanding of how critical process parameters affect the critical quality attributes. Implementation of process analytical technology into the bio-production process enables moving from the quality by testing to a more flexible quality by design approach. The application of advanced sensor systems in combination with mathematical modelling techniques offers enhanced process understanding, allows on-line prediction of critical quality attributes and subsequently real-time product quality control. In this review opportunities and unsolved issues on the road to a successful quality by design and dynamic control implementation are discussed. A major focus is directed on the preconditions for the application of model predictive control for mammalian cell culture bioprocesses. Design of experiments providing information about the process dynamics upon parameter change, dynamic process models, on-line process state predictions and powerful software environments seem to be a prerequisite for quality by control realization. © 2017 The Authors. Biotechnology Journal published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Drinking without thinking: an implicit measure of alcohol motivation predicts failure to control alcohol use.

PubMed

Ostafin, Brian D; Marlatt, G Alan; Greenwald, Anthony G

2008-11-01

Addiction is characterized by dyscontrol - substance use despite intentions to restrain. Using a sample of at-risk drinkers, the present study examined whether an implicit measure of alcohol motivation (the Implicit Association Test [IAT]; Greenwald, A.G., McGhee, D.E., & Schwartz, J.L.K. (1998). Measuring individual differences in implicit cognition: the Implicit Association Test. Journal of Personality and Social Psychology, 74, 1464-1480) would predict dyscontrol of alcohol use. Participants completed an IAT and, to elicit motivation to restrain alcohol use, were instructed that greater consumption in a taste test would impair performance on a later task for which they could win a prize. All participants viewed aversive slides and then completed a thought-listing task. Participants either exerted self-control by suppressing negative affect and thoughts regarding the slides or did not exert self-control. Post-manipulation, the groups did not differ in mood, urge to drink or motivation to restrain consumption. During the subsequent taste test, participants whose self-control resources were depleted consumed more alcohol than did those in the control group. Additionally, the IAT, but not an explicit measure of alcohol motivation, more strongly predicted alcohol use when self-control resources were depleted. The results indicate that the IAT may have utility in predicting dyscontrolled alcohol use.

Reference governors for controlled belt restraint systems

NASA Astrophysics Data System (ADS)

van der Laan, E. P.; Heemels, W. P. M. H.; Luijten, H.; Veldpaus, F. E.; Steinbuch, M.

2010-07-01

Today's restraint systems typically include a number of airbags, and a three-point seat belt with load limiter and pretensioner. For the class of real-time controlled restraint systems, the restraint actuator settings are continuously manipulated during the crash. This paper presents a novel control strategy for these systems. The control strategy developed here is based on a combination of model predictive control and reference management, in which a non-linear device - a reference governor (RG) - is added to a primal closed-loop controlled system. This RG determines an optimal setpoint in terms of injury reduction and constraint satisfaction by solving a constrained optimisation problem. Prediction of the vehicle motion, required to predict future constraint violation, is included in the design and is based on past crash data, using linear regression techniques. Simulation results with MADYMO models show that, with ideal sensors and actuators, a significant reduction (45%) of the peak chest acceleration can be achieved, without prior knowledge of the crash. Furthermore, it is shown that the algorithms are sufficiently fast to be implemented online.

Nonlinear predictive control of a boiler-turbine unit: A state-space approach with successive on-line model linearisation and quadratic optimisation.

PubMed

Ławryńczuk, Maciej

2017-03-01

This paper details development of a Model Predictive Control (MPC) algorithm for a boiler-turbine unit, which is a nonlinear multiple-input multiple-output process. The control objective is to follow set-point changes imposed on two state (output) variables and to satisfy constraints imposed on three inputs and one output. In order to obtain a computationally efficient control scheme, the state-space model is successively linearised on-line for the current operating point and used for prediction. In consequence, the future control policy is easily calculated from a quadratic optimisation problem. For state estimation the extended Kalman filter is used. It is demonstrated that the MPC strategy based on constant linear models does not work satisfactorily for the boiler-turbine unit whereas the discussed algorithm with on-line successive model linearisation gives practically the same trajectories as the truly nonlinear MPC controller with nonlinear optimisation repeated at each sampling instant. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Robust predictive control with optimal load tracking for critical applications. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tse, J.; Bentsman, J.; Miller, N.

1994-09-01

This report derives a multi-input multi-output (MIMO) version of a two-degree-of-freedom receding-horizon control law based on mixed H{sub 2}/H{infinity} minimization. First, the integrand in the frequency domain representation of the MIMO performance criterion is decomposed into disturbance and reference spectra. Then the controller is derived which minimizes the peak of the disturbance spectrum and the integral of the reference spectrum on the unit circle. The resulting two-degree-of-freedom MIMO control strategy, referred to as the minimax predictive multivariable control (MPC), is shown to have worst-case-disturbance-rejection and robust-stability properties superior to those of purely H{sub 2}-optimal controllers, such as Generalized Predictive Controlmore » (GPC), for identical horizons. An attractive feature of the receding horizon structure of MPC is that it can, in ways similar to GPC, directly incorporate input constraints and pre-programmed reference inputs, which are nontrivial tasks in the standard H{infinity} design.« less

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.

The role of cardiac vagal tone and inhibitory control in pre-schoolers' listening comprehension.

PubMed

Scrimin, Sara; Patron, Elisabetta; Florit, Elena; Palomba, Daniela; Mason, Lucia

2017-12-01

This study investigated the role of basal cardiac activity and inhibitory control at the beginning of the school year in predicting oral comprehension at the end of the year in pre-schoolers. Forty-three, 4-year-olds participated in the study. At the beginning of the school year children's electrocardiogram at rest was registered followed by the assessment of inhibitory control as well as verbal working memory and verbal ability. At the end of the year all children were administered a listening comprehension ability measure. A stepwise regression showed a significant effect of basal cardiac vagal tone in predicting listening comprehension together with inhibitory control and verbal ability. These results are among the first to show the predictive role of basal cardiac vagal tone and inhibitory control in pre-schoolers' oral text comprehension, and offer new insight into the association between autonomic regulation of the heart, inhibitory control, and cognitive activity at a young age. © 2017 Wiley Periodicals, Inc.

Neurocognitive Models of Medical Decision-Making Capacity in Traumatic Brain Injury Across Injury Severity.

PubMed

Triebel, Kristen L; Novack, Thomas A; Kennedy, Richard; Martin, Roy C; Dreer, Laura E; Raman, Rema; Marson, Daniel C

2016-01-01

To identify neurocognitive predictors of medical decision-making capacity (MDC) in participants with mild and moderate/severe traumatic brain injury (TBI). Academic medical center. Sixty adult controls and 104 adults with TBI (49 mild, 55 moderate/severe) evaluated within 6 weeks of injury. Prospective cross-sectional study. Participants completed the Capacity to Consent to Treatment Instrument to assess MDC and a neuropsychological test battery. We used factor analysis to reduce the battery test measures into 4 cognitive composite scores (verbal memory, verbal fluency, academic skills, and processing speed/executive function). We identified cognitive predictors of the 3 most clinically relevant Capacity to Consent to Treatment Instrument consent standards (appreciation, reasoning, and understanding). In controls, academic skills (word reading, arithmetic) and verbal memory predicted understanding; verbal fluency predicted reasoning; and no predictors emerged for appreciation. In the mild TBI group, verbal memory predicted understanding and reasoning, whereas academic skills predicted appreciation. In the moderate/severe TBI group, verbal memory and academic skills predicted understanding; academic skills predicted reasoning; and academic skills and verbal fluency predicted appreciation. Verbal memory was a predictor of MDC in controls and persons with mild and moderate/severe TBI. In clinical practice, impaired verbal memory could serve as a "red flag" for diminished consent capacity in persons with recent TBI.

Maintaining a Critical Spectra within Monteburns for a Gas-Cooled Reactor Array by Way of Control Rod Manipulation

DOE PAGES

Adigun, Babatunde John; Fensin, Michael Lorne; Galloway, Jack D.; ...

2016-10-01

Our burnup study examined the effect of a predicted critical control rod position on the nuclide predictability of several axial and radial locations within a 4×4 graphite moderated gas cooled reactor fuel cluster geometry. To achieve this, a control rod position estimator (CRPE) tool was developed within the framework of the linkage code Monteburns between the transport code MCNP and depletion code CINDER90, and four methodologies were proposed within the tool for maintaining criticality. Two of the proposed methods used an inverse multiplication approach - where the amount of fissile material in a set configuration is slowly altered until criticalitymore » is attained - in estimating the critical control rod position. Another method carried out several MCNP criticality calculations at different control rod positions, then used a linear fit to estimate the critical rod position. The final method used a second-order polynomial fit of several MCNP criticality calculations at different control rod positions to guess the critical rod position. The results showed that consistency in prediction of power densities as well as uranium and plutonium isotopics was mutual among methods within the CRPE tool that predicted critical position consistently well. Finall, while the CRPE tool is currently limited to manipulating a single control rod, future work could be geared toward implementing additional criticality search methodologies along with additional features.« less

Predicting tree mortality following gypsy moth defoliation

Treesearch

D.E. Fosbroke; R.R. Hicks; K.W. Gottschalk

1991-01-01

Appropriate application of gypsy moth control strategies requires an accurate prediction of the distribution and intensity of tree mortality prior to defoliation. This prior information is necessary to better target investments in control activities where they are needed. This poster lays the groundwork for developing hazard-rating systems for forests of the...

Factors of Predicted Learning Disorders and their Interaction with Attentional and Perceptual Training Procedures.

ERIC Educational Resources Information Center

Friar, John T.

Two factors of predicted learning disorders were investigated: (1) inability to maintain appropriate classroom behavior (BEH), (2) perceptual discrimination deficit (PERC). Three groups of first-graders (BEH, PERC, normal control) were administered measures of impulse control, distractability, auditory discrimination, and visual discrimination.…

State-of-the-Art Review : Prediction and Control of Groundborne Noise and Vibration from Rail Transit Trains

DOT National Transportation Integrated Search

1983-12-01

This report provides a comprehensive review of the state-of-the-art in the prediction and control of groundborne noise and vibration. Various types of impact criteria are reviewed for groundborne noise and vibration, building damage, and soil settlem...

Visual anticipation biases conscious decision making but not bottom-up visual processing

PubMed Central

Mathews, Zenon; Cetnarski, Ryszard; Verschure, Paul F. M. J.

2015-01-01

Prediction plays a key role in control of attention but it is not clear which aspects of prediction are most prominent in conscious experience. An evolving view on the brain is that it can be seen as a prediction machine that optimizes its ability to predict states of the world and the self through the top-down propagation of predictions and the bottom-up presentation of prediction errors. There are competing views though on whether prediction or prediction errors dominate the formation of conscious experience. Yet, the dynamic effects of prediction on perception, decision making and consciousness have been difficult to assess and to model. We propose a novel mathematical framework and a psychophysical paradigm that allows us to assess both the hierarchical structuring of perceptual consciousness, its content and the impact of predictions and/or errors on conscious experience, attention and decision-making. Using a displacement detection task combined with reverse correlation, we reveal signatures of the usage of prediction at three different levels of perceptual processing: bottom-up fast saccades, top-down driven slow saccades and consciousnes decisions. Our results suggest that the brain employs multiple parallel mechanism at different levels of perceptual processing in order to shape effective sensory consciousness within a predicted perceptual scene. We further observe that bottom-up sensory and top-down predictive processes can be dissociated through cognitive load. We propose a probabilistic data association model from dynamical systems theory to model the predictive multi-scale bias in perceptual processing that we observe and its role in the formation of conscious experience. We propose that these results support the hypothesis that consciousness provides a time-delayed description of a task that is used to prospectively optimize real time control structures, rather than being engaged in the real-time control of behavior itself. PMID:25741290

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.

Cue-Reactive Rationality, Visual Imagery and Volitional Control Predict Cue-Reactive Urge to Gamble in Poker-Machine Gamblers.

PubMed

Clark, Gavin I; Rock, Adam J; McKeith, Charles F A; Coventry, William L

2017-09-01

Poker-machine gamblers have been demonstrated to report increases in the urge to gamble following exposure to salient gambling cues. However, the processes which contribute to this urge to gamble remain to be understood. The present study aimed to investigate whether changes in the conscious experience of visual imagery, rationality and volitional control (over one's thoughts, images and attention) predicted changes in the urge to gamble following exposure to a gambling cue. Thirty-one regular poker-machine gamblers who reported at least low levels of problem gambling on the Problem Gambling Severity Index (PGSI), were recruited to complete an online cue-reactivity experiment. Participants completed the PGSI, the visual imagery, rationality and volitional control subscales of the Phenomenology of Consciousness Inventory (PCI), and a visual analogue scale (VAS) assessing urge to gamble. Participants completed the PCI subscales and VAS at baseline, following a neutral video cue and following a gambling video cue. Urge to gamble was found to significantly increase from neutral cue to gambling cue (while controlling for baseline urge) and this increase was predicted by PGSI score. After accounting for the effects of problem-gambling severity, cue-reactive visual imagery, rationality and volitional control significantly improved the prediction of cue-reactive urge to gamble. The small sample size and limited participant characteristic data restricts the generalizability of the findings. Nevertheless, this is the first study to demonstrate that changes in the subjective experience of visual imagery, volitional control and rationality predict changes in the urge to gamble from neutral to gambling cue. The results suggest that visual imagery, rationality and volitional control may play an important role in the experience of the urge to gamble in poker-machine gamblers.

An assessment of discriminatory power of office blood pressure measurements in predicting optimal ambulatory blood pressure control in people with type 2 diabetes.

PubMed

Kengne, Andre Pascal; Libend, Christelle Nong; Dzudie, Anastase; Menanga, Alain; Dehayem, Mesmin Yefou; Kingue, Samuel; Sobngwi, Eugene

2014-01-01

Ambulatory blood pressure (BP) measurements (ABPM) predict health outcomes better than office BP, and are recommended for assessing BP control, particularly in high-risk patients. We assessed the performance of office BP in predicting optimal ambulatory BP control in sub-Saharan Africans with type 2 diabetes (T2DM). Participants were a random sample of 51 T2DM patients (25 men) drug-treated for hypertension, receiving care in a referral diabetes clinic in Yaounde, Cameroon. A quality control group included 46 non-diabetic individuals with hypertension. Targets for BP control were systolic (and diastolic) BP. Mean age of diabetic participants was 60 years (standard deviation: 10) and median duration of diabetes was 6 years (min-max: 0-29). Correlation coefficients between each office-based variable and the 24-h ABPM equivalent (diabetic vs. non-diabetic participants) were 0.571 and 0.601 for systolic (SBP), 0.520 and 0.539 for diastolic (DBP), 0.631 and 0.549 for pulse pressure (PP), and 0.522 and 0.583 for mean arterial pressure (MAP). The c-statistic for the prediction of optimal ambulatory control from office-BP in diabetic participants was 0.717 for SBP, 0.494 for DBP, 0.712 for PP, 0.582 for MAP, and 0.721 for either SBP + DBP or PP + MAP. Equivalents in diabetes-free participants were 0.805, 0.763, 0.695, 0.801 and 0.813. Office DBP was ineffective in discriminating optimal ambulatory BP control in diabetic patients, and did not improve predictions based on office SBP alone. Targeting ABPM to those T2DM patients who are already at optimal office-based SBP would likely be more cost effective in this setting.

Cognitive demand and predictive adaptational responses in dynamic stability control.

PubMed

Bohm, Sebastian; Mersmann, Falk; Bierbaum, Stefanie; Dietrich, Ralf; Arampatzis, Adamantios

2012-09-21

We studied the effects of a concurrent cognitive task on predictive motor control, a feedforward mechanism of dynamic stability control, during disturbed gait in young and old adults. Thirty-two young and 27 elderly male healthy subjects participated and were randomly assigned to either control or dual task groups. By means of a covered exchangeable element the surface condition on a gangway could be altered to induce gait perturbations. The experimental protocol included a baseline on hard surface and an adaptation phase with twelve trials on soft surface. After the first, sixth and last soft surface trial, the surface condition was changed to hard (H1-3), to examine after-effects and, thus, to quantify predictive motor control. Dynamic stability was assessed using the 'margin of stability (MoS)' as a criterion for the stability state of the human body (extrapolated center of mass concept). In H1-3 the young participants significantly increased the MoS at touchdown of the disturbed leg compared to baseline. The magnitude and the rate of these after-effects were unaffected by the dual task condition. The old participants presented a trend to after-effects (i.e., increase of MoS) in H3 but only under the dual task condition.In conclusion, the additional cognitive demand did not compromise predictive motor control during disturbed walking in the young and old participants. In contrast to the control group, the old dual task group featured a trend to predictive motor adjustments, which may be a result of a higher state of attention or arousal due to the dual task paradigm. Copyright © 2012 Elsevier Ltd. All rights reserved.

Predictors of change in depressive symptoms from preschool to first grade.

PubMed

Reinfjell, Trude; Kårstad, Silja Berg; Berg-Nielsen, Turid Suzanne; Luby, Joan L; Wichstrøm, Lars

2016-11-01

Children's depressive symptoms in the transition from preschool to school are rarely investigated. We therefore tested whether children's temperament (effortful control and negative affect), social skills, child psychopathology, environmental stressors (life events), parental accuracy of predicting their child's emotion understanding (parental accuracy), parental emotional availability, and parental depression predict changes in depressive symptoms from preschool to first grade. Parents of a community sample of 995 4-year-olds were interviewed using the Preschool Age Psychiatric Assessment. The children and parents were reassessed when the children started first grade (n = 795). The results showed that DSM-5 defined depressive symptoms increased. Child temperamental negative affect and parental depression predicted increased, whereas social skills predicted decreased, depressive symptoms. However, such social skills were only protective among children with low and medium effortful control. Further, high parental accuracy proved protective among children with low effortful control and high negative affect. Thus, interventions that treat parental depression may be important for young children. Children with low effortful control and high negative affect may especially benefit from having parents who accurately perceive their emotional understanding. Efforts to enhance social skills may prove particularly important for children with low or medium effortful control.

Internal health locus of control predicts willingness to track health behaviors online and with smartphone applications.

PubMed

Bennett, Brooke L; Goldstein, Carly M; Gathright, Emily C; Hughes, Joel W; Latner, Janet D

2017-12-01

Given rising technology use across all demographic groups, digital interventions offer a potential strategy for increasing access to health information and care. Research is lacking on identifying individual differences that impact willingness to use digital interventions, which may affect patient engagement. Health locus of control, the amount of control an individual believes they have over their own health, may predict willingness to use mobile health (mHealth) applications ('apps') and online trackers. A cross-sectional study (n = 276) was conducted to assess college students' health locus of control beliefs and willingness to use health apps and online trackers. Internal and powerful other health locus of control beliefs predicted willingness to use health apps and online trackers while chance health locus of control beliefs did not. Individuals with internal and powerful other health locus of control beliefs are more willing than those with chance health locus of control beliefs to utilize a form of technology to monitor or change health behaviors. Health locus of control is an easy-to-assess patient characteristic providers can measure to identify which patients are more likely to utilize mHealth apps and online trackers.

A balance of activity in brain control and reward systems predicts self-regulatory outcomes

PubMed Central

Chen, Pin-Hao A.; Huckins, Jeremy F.; Hofmann, Wilhelm; Kelley, William M.; Heatherton, Todd F.

2017-01-01

Abstract Previous neuroimaging work has shown that increased reward-related activity following exposure to food cues is predictive of self-control failure. The balance model suggests that self-regulation failures result from an imbalance in reward and executive control mechanisms. However, an open question is whether the relative balance of activity in brain systems associated with executive control (vs reward) supports self-regulatory outcomes when people encounter tempting cues in daily life. Sixty-nine chronic dieters, a population known for frequent lapses in self-control, completed a food cue-reactivity task during an fMRI scanning session, followed by a weeklong sampling of daily eating behaviors via ecological momentary assessment. We related participants’ food cue activity in brain systems associated with executive control and reward to real-world eating patterns. Specifically, a balance score representing the amount of activity in brain regions associated with self-regulatory control, relative to automatic reward-related activity, predicted dieters’ control over their eating behavior during the following week. This balance measure may reflect individual self-control capacity and be useful for examining self-regulation success in other domains and populations. PMID:28158874

A balance of activity in brain control and reward systems predicts self-regulatory outcomes.

PubMed

Lopez, Richard B; Chen, Pin-Hao A; Huckins, Jeremy F; Hofmann, Wilhelm; Kelley, William M; Heatherton, Todd F

2017-05-01

Previous neuroimaging work has shown that increased reward-related activity following exposure to food cues is predictive of self-control failure. The balance model suggests that self-regulation failures result from an imbalance in reward and executive control mechanisms. However, an open question is whether the relative balance of activity in brain systems associated with executive control (vs reward) supports self-regulatory outcomes when people encounter tempting cues in daily life. Sixty-nine chronic dieters, a population known for frequent lapses in self-control, completed a food cue-reactivity task during an fMRI scanning session, followed by a weeklong sampling of daily eating behaviors via ecological momentary assessment. We related participants' food cue activity in brain systems associated with executive control and reward to real-world eating patterns. Specifically, a balance score representing the amount of activity in brain regions associated with self-regulatory control, relative to automatic reward-related activity, predicted dieters' control over their eating behavior during the following week. This balance measure may reflect individual self-control capacity and be useful for examining self-regulation success in other domains and populations. © The Author (2017). Published by Oxford University Press.

Correlation of the Hubble Space Telescope (HST) Space Telescope Imaging Spectrometer (STIS) On-Orbit Data with Pre-launch Predictions and Ground Contamination Controls

NASA Technical Reports Server (NTRS)

Hansen, Patricia A.

2003-01-01

The Hubble Space Telescope (HST) Space Telescope Imaging Spectrograph (STIS) was deployed on-orbit in February 1997. The contamination program for STIS was stringently controlled as the five-year end-of-life deposition was set at 158, per optical element. Contamination was controlled through materials selection, extensive vacuum outgassing certifications, cleaning techniques, and environmental controls. In addition to ground contamination controls, on-orbit contamination controls were implemented for both the HST servicing mission activities and early post-servicing mission checkout. The extensive contamination control program will be discussed and the STIS on-orbit data will be correlated with the prelaunch analytical predictions.

Topographic models for predicting malaria vector breeding habitats: potential tools for vector control managers.

PubMed

Nmor, Jephtha C; Sunahara, Toshihiko; Goto, Kensuke; Futami, Kyoko; Sonye, George; Akweywa, Peter; Dida, Gabriel; Minakawa, Noboru

2013-01-16

Identification of malaria vector breeding sites can enhance control activities. Although associations between malaria vector breeding sites and topography are well recognized, practical models that predict breeding sites from topographic information are lacking. We used topographic variables derived from remotely sensed Digital Elevation Models (DEMs) to model the breeding sites of malaria vectors. We further compared the predictive strength of two different DEMs and evaluated the predictability of various habitat types inhabited by Anopheles larvae. Using GIS techniques, topographic variables were extracted from two DEMs: 1) Shuttle Radar Topography Mission 3 (SRTM3, 90-m resolution) and 2) the Advanced Spaceborne Thermal Emission Reflection Radiometer Global DEM (ASTER, 30-m resolution). We used data on breeding sites from an extensive field survey conducted on an island in western Kenya in 2006. Topographic variables were extracted for 826 breeding sites and for 4520 negative points that were randomly assigned. Logistic regression modelling was applied to characterize topographic features of the malaria vector breeding sites and predict their locations. Model accuracy was evaluated using the area under the receiver operating characteristics curve (AUC). All topographic variables derived from both DEMs were significantly correlated with breeding habitats except for the aspect of SRTM. The magnitude and direction of correlation for each variable were similar in the two DEMs. Multivariate models for SRTM and ASTER showed similar levels of fit indicated by Akaike information criterion (3959.3 and 3972.7, respectively), though the former was slightly better than the latter. The accuracy of prediction indicated by AUC was also similar in SRTM (0.758) and ASTER (0.755) in the training site. In the testing site, both SRTM and ASTER models showed higher AUC in the testing sites than in the training site (0.829 and 0.799, respectively). The predictability of habitat types varied. Drains, foot-prints, puddles and swamp habitat types were most predictable. Both SRTM and ASTER models had similar predictive potentials, which were sufficiently accurate to predict vector habitats. The free availability of these DEMs suggests that topographic predictive models could be widely used by vector control managers in Africa to complement malaria control strategies.

What Do You Think Would Make You Happier? What Do You Think You Would Choose?*

PubMed Central

Benjamin, Daniel J.; Kimball, Miles S.; Heffetz, Ori; Rees-Jones, Alex

2011-01-01

Would people choose what they think would maximize their subjective well-being (SWB)? We present survey respondents with hypothetical scenarios and elicit both choice and predicted SWB rankings of two alternatives. While choice and predicted SWB rankings usually coincide in our data, we find systematic reversals. We identify factors—such as predicted sense of purpose, control over one’s life, family happiness, and social status—that help explain hypothetical choice controlling for predicted SWB. We explore how our findings vary by SWB measure and by scenario. Our results have implications regarding the use of SWB survey questions as a proxy for utility. PMID:23275649

A preliminary correlation of the orbiter stability and control aerodynamics from the first two Space Shuttle flights /STS-1 & 2/ with preflight predictions

NASA Technical Reports Server (NTRS)

Underwood, J. M.; Cooke, D. R.

1982-01-01

A correlation of the stability and control derivatives from flight (STS-1 & 2) with preflight predictions is presented across the Mach range from 0.9 to 25. Flight data obtained from specially designed flight test maneuvers as well as from conventional bank maneuvers generally indicate good agreement with predicted data. However, the vehicle appears to be lateral-directionally more stable than predicted in the transonic regime. Aerodynamic 'reasonableness tests' are employed to test for validity of flight data. The importance of testing multiple models in multiple wind tunnels at the same test conditions is demonstrated.

For Whom the Mind Wanders, and When, Varies Across Laboratory and Daily-Life Settings.

PubMed

Kane, Michael J; Gross, Georgina M; Chun, Charlotte A; Smeekens, Bridget A; Meier, Matt E; Silvia, Paul J; Kwapil, Thomas R

2017-09-01

Undergraduates ( N = 274) participated in a weeklong daily-life experience-sampling study of mind wandering after being assessed in the lab for executive-control abilities (working memory capacity; attention-restraint ability; attention-constraint ability; and propensity for task-unrelated thoughts, or TUTs) and personality traits. Eight times a day, electronic devices prompted subjects to report on their current thoughts and context. Working memory capacity and attention abilities predicted subjects' TUT rates in the lab, but predicted the frequency of daily-life mind wandering only as a function of subjects' momentary attempts to concentrate. This pattern replicates prior daily-life findings but conflicts with laboratory findings. Results for personality factors also revealed different associations in the lab and daily life: Only neuroticism predicted TUT rate in the lab, but only openness predicted mind-wandering rate in daily life (both predicted the content of daily-life mind wandering). Cognitive and personality factors also predicted dimensions of everyday thought other than mind wandering, such as subjective judgments of controllability of thought. Mind wandering in people's daily environments and TUTs during controlled and artificial laboratory tasks have different correlates (and perhaps causes). Thus, mind-wandering theories based solely on lab phenomena may be incomplete.

Eating on impulse: Implicit attitudes, self-regulatory resources, and trait self-control as determinants of food consumption.

PubMed

Wang, Yan; Wang, Lei; Cui, Xianghua; Fang, Yuan; Chen, Qianqiu; Wang, Ya; Qiang, Yao

2015-12-01

Self-regulatory resources and trait self-control have been found to moderate the impulse-behavior relationship. The current study investigated whether the interaction of self-regulatory resources and trait self-control moderates the association between implicit attitudes and food consumption. One hundred twenty female participants were randomly assigned to either a depletion condition in which their self-regulatory resources were reduced or a no-depletion condition. Participants' implicit attitudes for chocolate were measured with the Single Category Implicit Association Test and self-report measures of trait self-control were collected. The dependent variable was chocolate consumption in an ostensible taste and rate task. Implicit attitudes predicted chocolate consumption in depleted participants but not in non-depleted participants. However, this predictive power of implicit attitudes on eating in depleted condition disappeared in participants with high trait self-control. Thus, trait self-control and self-regulatory resources interact to moderate the prediction of implicit attitude on eating behavior. Results suggest that high trait self-control buffers the effect of self-regulatory depletion on impulsive eating. Copyright © 2015 Elsevier Ltd. All rights reserved.

Predictors of Poor Seizure Control in Children Managed at a Tertiary Care Hospital of Eastern Nepal

PubMed Central

POUDEL, Prakash; CHITLANGIA, Mohit; POKHAREL, Rita

2016-01-01

Objective Various factors have been claimed to predict outcome of afebrile seizures in children. This study was aimed to find out the predictors of poor seizure control in children at a resource limited setting. Materials & Methods This prospective study was done from July 1st, 2009 to January 31st, 2012 at B.P. Koirala Institute of Health Sciences, Nepal. Children (1 month-20 yr of age) with afebrile seizures presenting to pediatric neurology clinic were studied. Significant predictors on bivariate analysis were further analyzed with binary logistic model to find out the true predictors. Positive predictive values (PPVs) and negative predictive values (NPVs) for the true predictors were calculated. Results Out of 256 patients (male: female ratio 3:2) with afebrile seizures followed up for median duration of 27 (IQR 12-50) months, seizure was poorly controlled in 20% patients. Three factors predicted poor seizure control. They were frequent (≥1 per month) seizures at onset (OR 12.76, 95% CI 1.44-112.73, PPV 25%, NPV 98%); remote symptomatic etiology (OR 3.56, 95% CI 1.04-12.17, PPV 36%, NPV 92%); and need of more than one anticonvulsant drug (polytherapy) (OR 12.83, 95% CI 5.50-29.9, PPV 56%, NPV 96%). The strongest predictor was need of polytherapy. When all three factors were present, PPV and NPV for prediction of poor seizure control were 70% and 90% respectively. Conclusion Frequent seizures at onset, remote symptomatic etiology of seizure and need of polytherapy were associated with poor seizure control in children with afebrile seizures. PMID:27375756

Executive function predicts artificial language learning

PubMed Central

Kapa, Leah L.; Colombo, John

2017-01-01

Previous research suggests executive function (EF) advantages among bilinguals compared to monolingual peers, and these advantages are generally attributed to experience controlling two linguistic systems. However, the possibility that the relationship between bilingualism and EF might be bidirectional has not been widely considered; while experience with two languages might improve EF, better EF skills might also facilitate language learning. In the current studies, we tested whether adults’ and preschool children’s EF abilities predicted success in learning a novel artificial language. After controlling for working memory and English receptive vocabulary, adults’ artificial language performance was predicted by their inhibitory control ability (Study 1) and children’s performance was predicted by their attentional monitoring and shifting ability (Study 2). These findings provide preliminary evidence suggesting that EF processes may be employed during initial stages of language learning, particularly vocabulary acquisition, and support the possibility of a bidirectional relationship between EF and language acquisition. PMID:29129958

Distal and proximal predictors of snacking at work: A daily-survey study.

PubMed

Sonnentag, Sabine; Pundt, Alexander; Venz, Laura

2017-02-01

This study aimed at examining predictors of healthy and unhealthy snacking at work. As proximal predictors we looked at food-choice motives (health motive, affect-regulation motive); as distal predictors we included organizational eating climate, emotional eating, and self-control demands at work. We collected daily survey data from 247 employees, over a period of 2 workweeks. Multilevel structural equation modeling showed that organizational eating climate predicted health as food-choice motive, whereas emotional eating and self-control demands predicted affect regulation as food-choice motive. The health motive, in turn, predicted consuming more fruits and more cereal bars and less sweet snacks; the affect-regulation motive predicted consuming more sweet snacks. Findings highlight the importance of a health-promoting eating climate within the organization and point to the potential harm of high self-control demands at work. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Predicting Baseline for Analysis of Electricity Pricing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, T.; Lee, D.; Choi, J.

2016-05-03

To understand the impact of new pricing structure on residential electricity demands, we need a baseline model that captures every factor other than the new price. The standard baseline is a randomized control group, however, a good control group is hard to design. This motivates us to devlop data-driven approaches. We explored many techniques and designed a strategy, named LTAP, that could predict the hourly usage years ahead. The key challenge in this process is that the daily cycle of electricity demand peaks a few hours after the temperature reaching its peak. Existing methods rely on the lagged variables ofmore » recent past usages to enforce this daily cycle. These methods have trouble making predictions years ahead. LTAP avoids this trouble by assuming the daily usage profile is determined by temperature and other factors. In a comparison against a well-designed control group, LTAP is found to produce accurate predictions.« less

Adolescents' as active agents in the socialization process: legitimacy of parental authority and obligation to obey as predictors of obedience.

PubMed

Darling, Nancy; Cumsille, Patricio; Martínez, M Loreto

2007-04-01

Adolescents' agreement with parental standards and beliefs about the legitimacy of parental authority and their own obligation to obey were used to predict adolescents' obedience, controlling for parental monitoring, rules, and rule enforcement. Hierarchical linear models were used to predict both between-adolescent and within-adolescent, issue-specific differences in obedience in a sample of 703 Chilean adolescents (M age=15.0 years). Adolescents' global agreement with parents and global beliefs about their obligation to obey predicted between-adolescent obedience, controlling for parental monitoring, age, and gender. Adolescents' issue-specific agreement, legitimacy beliefs, and obligation to obey predicted issue-specific obedience, controlling for rules and parents' reports of rule enforcement. The potential of examining adolescents' agreement and beliefs about authority as a key link between parenting practices and adolescents' decisions to obey is discussed.

Method and device for predicting wavelength dependent radiation influences in thermal systems

DOEpatents

Kee, Robert J.; Ting, Aili

1996-01-01

A method and apparatus for predicting the spectral (wavelength-dependent) radiation transport in thermal systems including interaction by the radiation with partially transmitting medium. The predicted model of the thermal system is used to design and control the thermal system. The predictions are well suited to be implemented in design and control of rapid thermal processing (RTP) reactors. The method involves generating a spectral thermal radiation transport model of an RTP reactor. The method also involves specifying a desired wafer time dependent temperature profile. The method further involves calculating an inverse of the generated model using the desired wafer time dependent temperature to determine heating element parameters required to produce the desired profile. The method also involves controlling the heating elements of the RTP reactor in accordance with the heating element parameters to heat the wafer in accordance with the desired profile.

Aeroacoustics of Flight Vehicles: Theory and Practice. Volume 2: Noise Control

NASA Technical Reports Server (NTRS)

Hubbard, Harvey H. (Editor)

1991-01-01

Flight vehicles and the underlying concepts of noise generation, noise propagation, noise prediction, and noise control are studied. This volume includes those chapters that relate to flight vehicle noise control and operations: human response to aircraft noise; atmospheric propagation; theoretical models for duct acoustic propagation and radiation; design and performance of duct acoustic treatment; jet noise suppression; interior noise; flyover noise measurement and prediction; and quiet aircraft design and operational characteristics.

Homeostatic Regulation of Memory Systems and Adaptive Decisions

PubMed Central

Mizumori, Sheri JY; Jo, Yong Sang

2013-01-01

While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The “multiple memory systems of the brain” have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result in rigid and suboptimal decision making and memory as seen in addiction and neurological disease. © 2013 The Authors. Hippocampus Published by Wiley Periodicals, Inc. PMID:23929788

Homeostatic regulation of memory systems and adaptive decisions.

PubMed

Mizumori, Sheri J Y; Jo, Yong Sang

2013-11-01

While it is clear that many brain areas process mnemonic information, understanding how their interactions result in continuously adaptive behaviors has been a challenge. A homeostatic-regulated prediction model of memory is presented that considers the existence of a single memory system that is based on a multilevel coordinated and integrated network (from cells to neural systems) that determines the extent to which events and outcomes occur as predicted. The "multiple memory systems of the brain" have in common output that signals errors in the prediction of events and/or their outcomes, although these signals differ in terms of what the error signal represents (e.g., hippocampus: context prediction errors vs. midbrain/striatum: reward prediction errors). The prefrontal cortex likely plays a pivotal role in the coordination of prediction analysis within and across prediction brain areas. By virtue of its widespread control and influence, and intrinsic working memory mechanisms. Thus, the prefrontal cortex supports the flexible processing needed to generate adaptive behaviors and predict future outcomes. It is proposed that prefrontal cortex continually and automatically produces adaptive responses according to homeostatic regulatory principles: prefrontal cortex may serve as a controller that is intrinsically driven to maintain in prediction areas an experience-dependent firing rate set point that ensures adaptive temporally and spatially resolved neural responses to future prediction errors. This same drive by prefrontal cortex may also restore set point firing rates after deviations (i.e. prediction errors) are detected. In this way, prefrontal cortex contributes to reducing uncertainty in prediction systems. An emergent outcome of this homeostatic view may be the flexible and adaptive control that prefrontal cortex is known to implement (i.e. working memory) in the most challenging of situations. Compromise to any of the prediction circuits should result in rigid and suboptimal decision making and memory as seen in addiction and neurological disease. Copyright © 2013 Wiley Periodicals, Inc.

The Mechanisms for Within-Host Influenza Virus Control Affect Model-Based Assessment and Prediction of Antiviral Treatment

PubMed Central

Cao, Pengxing

2017-01-01

Models of within-host influenza viral dynamics have contributed to an improved understanding of viral dynamics and antiviral effects over the past decade. Existing models can be classified into two broad types based on the mechanism of viral control: models utilising target cell depletion to limit the progress of infection and models which rely on timely activation of innate and adaptive immune responses to control the infection. In this paper, we compare how two exemplar models based on these different mechanisms behave and investigate how the mechanistic difference affects the assessment and prediction of antiviral treatment. We find that the assumed mechanism for viral control strongly influences the predicted outcomes of treatment. Furthermore, we observe that for the target cell-limited model the assumed drug efficacy strongly influences the predicted treatment outcomes. The area under the viral load curve is identified as the most reliable predictor of drug efficacy, and is robust to model selection. Moreover, with support from previous clinical studies, we suggest that the target cell-limited model is more suitable for modelling in vitro assays or infection in some immunocompromised/immunosuppressed patients while the immune response model is preferred for predicting the infection/antiviral effect in immunocompetent animals/patients. PMID:28933757

Integrating Statistical Machine Learning in a Semantic Sensor Web for Proactive Monitoring and Control.

PubMed

Adeleke, Jude Adekunle; Moodley, Deshendran; Rens, Gavin; Adewumi, Aderemi Oluyinka

2017-04-09

Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM 2 . 5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM 2 . 5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web.

Integrating Statistical Machine Learning in a Semantic Sensor Web for Proactive Monitoring and Control

PubMed Central

Adeleke, Jude Adekunle; Moodley, Deshendran; Rens, Gavin; Adewumi, Aderemi Oluyinka

2017-01-01

Proactive monitoring and control of our natural and built environments is important in various application scenarios. Semantic Sensor Web technologies have been well researched and used for environmental monitoring applications to expose sensor data for analysis in order to provide responsive actions in situations of interest. While these applications provide quick response to situations, to minimize their unwanted effects, research efforts are still necessary to provide techniques that can anticipate the future to support proactive control, such that unwanted situations can be averted altogether. This study integrates a statistical machine learning based predictive model in a Semantic Sensor Web using stream reasoning. The approach is evaluated in an indoor air quality monitoring case study. A sliding window approach that employs the Multilayer Perceptron model to predict short term PM2.5 pollution situations is integrated into the proactive monitoring and control framework. Results show that the proposed approach can effectively predict short term PM2.5 pollution situations: precision of up to 0.86 and sensitivity of up to 0.85 is achieved over half hour prediction horizons, making it possible for the system to warn occupants or even to autonomously avert the predicted pollution situations within the context of Semantic Sensor Web. PMID:28397776

Independence and interdependence predict health and wellbeing: divergent patterns in the United States and Japan.

PubMed

Kitayama, Shinobu; Karasawa, Mayumi; Curhan, Katherine B; Ryff, Carol D; Markus, Hazel Rose

2010-01-01

A cross-cultural survey was used to examine two hypotheses designed to link culture to wellbeing and health. The first hypothesis states that people are motivated toward prevalent cultural mandates of either independence (personal control) in the United States or interdependence (relational harmony) in Japan. As predicted, Americans with compromised personal control and Japanese with strained relationships reported high perceived constraint. The second hypothesis holds that people achieve wellbeing and health through actualizing the respective cultural mandates in their modes of being. As predicted, the strongest predictor of wellbeing and health was personal control in the United States, but the absence of relational strain in Japan. All analyses controlled for age, gender, educational attainment, and personality traits. The overall pattern of findings underscores culturally distinct pathways (independent versus interdependent) in achieving the positive life outcomes.

Nonparametric method for failures diagnosis in the actuating subsystem of aircraft control system

NASA Astrophysics Data System (ADS)

Terentev, M. N.; Karpenko, S. S.; Zybin, E. Yu; Kosyanchuk, V. V.

2018-02-01

In this paper we design a nonparametric method for failures diagnosis in the aircraft control system that uses the measurements of the control signals and the aircraft states only. It doesn’t require a priori information of the aircraft model parameters, training or statistical calculations, and is based on analytical nonparametric one-step-ahead state prediction approach. This makes it possible to predict the behavior of unidentified and failure dynamic systems, to weaken the requirements to control signals, and to reduce the diagnostic time and problem complexity.

TSAFE Interface Control Document v 2.0

NASA Technical Reports Server (NTRS)

Paielli, Russell A.; Bach, Ralph E.

2013-01-01

This document specifies the data interface for TSAFE, the Tactical Separation-Assured Flight Environment. TSAFE is a research prototype of a software application program for alerting air traffic controllers to imminent conflicts in enroute airspace. It is intended for Air Route Traffic Control Centers ("Centers") in the U.S. National Airspace System. It predicts trajectories for approximately 3 minutes into the future, searches for conflicts, and sends data about predicted conflicts to the client, which uses the data to alert an air traffic controller of conflicts. TSAFE itself does not provide a graphical user interface.

Predictive IP controller for robust position control of linear servo system.

PubMed

Lu, Shaowu; Zhou, Fengxing; Ma, Yajie; Tang, Xiaoqi

2016-07-01

Position control is a typical application of linear servo system. In this paper, to reduce the system overshoot, an integral plus proportional (IP) controller is used in the position control implementation. To further improve the control performance, a gain-tuning IP controller based on a generalized predictive control (GPC) law is proposed. Firstly, to represent the dynamics of the position loop, a second-order linear model is used and its model parameters are estimated on-line by using a recursive least squares method. Secondly, based on the GPC law, an optimal control sequence is obtained by using receding horizon, then directly supplies the IP controller with the corresponding control parameters in the real operations. Finally, simulation and experimental results are presented to show the efficiency of proposed scheme. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models

EPA Science Inventory

The second phase of the MicroArray Quality Control (MAQC-II) project evaluated common practices for developing and validating microarray-based models aimed at predicting toxicological and clinical endpoints. Thirty-six teams developed classifiers for 13 endpoints - some easy, som...

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…

Analysis of baseline gene expression levels from toxicogenomics study control animals to identify sources of variation and predict responses to chemicals

EPA Science Inventory

The use of gene expression profiling to predict chemical mode of action would be enhanced by better characterization of variance due to individual, environmental, and technical factors. Meta-analysis of microarray data from untreated or vehicle-treated animals within the control ...

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…

Inclusive Education: Teachers' Intentions and Behaviour Analysed from the Viewpoint of the Theory of Planned Behaviour

ERIC Educational Resources Information Center

Yan, Zi; Sin, Kuen-fung

2014-01-01

The theory of planned behaviour (TPB) claims that behaviour can be predicted by behavioural intention and perceived behavioural control, while behavioural intention is a function of attitude towards the behaviour, subjective norm, and perceived behavioural control. This study aims at providing explanation and prediction of teachers' inclusive…

State-of-the-Art Review Prediction and Control of Groundborne Noise and Vibration from Rail Transit Trains : Annotated Bibliography

DOT National Transportation Integrated Search

1982-02-01

This interim report presents an annotated bibliography that has been compiled as part of a comprehensive review of the state-of-the-art in the prediction and control of groundborne noise and vibration created by rail transit operations. Included in t...

Low-income minority fathers' control strategies and children's regulatory skills

PubMed Central

Malin, Jenessa L.; Cabrera, Natasha J.; Karberg, Elizabeth; Aldoney, Daniela; Rowe, Meredith

2015-01-01

The current study explored the bidirectional association of children's individual characteristics, fathers' control strategies at 24-months and children's regulatory skills at pre-kindergarten (pre-K). Using a sample of low-income minority families with 2-year-olds from the Early Head Start Evaluation Research Program (n = 71) we assessed the association between child gender and vocabulary skills, fathers' control strategies at 24-months (e.g., regulatory behavior and regulatory language), and children's sustained attention and emotion regulation at pre-kindergarten. There were three main findings. First, fathers' overwhelmingly use commands (e.g., do that) to promote compliance in their 24-month old children. Second, children's vocabulary skills predict fathers' regulatory behaviors during a father-child interaction, whereas children's gender predicts fathers' regulatory language during an interaction. Third, controlling for maternal supportiveness, fathers' regulatory behaviors at 24-months predict children's sustained attention at pre-kindergarten whereas fathers' regulatory language at 24-months predicts children's emotion regulation at pre-kindergarten. Our findings highlight the importance of examining paternal contributions to children's regulatory skills. PMID:25798496

Low-income, minority fathers' control strategies and their children's regulatory skills.

PubMed

Malin, Jenessa L; Cabrera, Natasha J; Karberg, Elizabeth; Aldoney, Daniela; Rowe, Meredith L

2014-01-01

The current study explored the bidirectional association of children's individual characteristics, fathers' control strategies at 24 months, and children's regulatory skills at prekindergarten (pre-K). Using a sample of low-income, minority families with 2-year-olds from the Early Head Start Research and Evaluation Project (n = 71), we assessed the association between child gender and vocabulary skills, fathers' control strategies at 24 months (e.g., regulatory behavior and regulatory language), and children's sustained attention and emotion regulation at prekindergarten. There were three main findings. First, fathers overwhelmingly used commands (e.g., "Do that.") to promote compliance in their 24-month-old children. Second, children's vocabulary skills predicted fathers' regulatory behaviors during a father-child interaction whereas children's gender predicted fathers' regulatory language during an interaction. Third, controlling for maternal supportiveness, fathers' regulatory behaviors at 24 months predicted children's sustained attention at pre-K whereas fathers' regulatory language at 24 months predicted children's emotion regulation at pre-K. Our findings highlight the importance of examining paternal contributions to children's regulatory skills. © 2014 Michigan Association for Infant Mental Health.

The kinetics and location of intra-host HIV evolution to evade cellular immunity are predictable

NASA Astrophysics Data System (ADS)

Barton, John; Goonetilleke, Nilu; Butler, Thomas; Walker, Bruce; McMichael, Andrew; Chakraborty, Arup

Human immunodeficiency virus (HIV) evolves within infected persons to escape targeting and clearance by the host immune system, thereby preventing effective immune control of infection. Knowledge of the timing and pathways of escape that result in loss of control of the virus could aid in the design of effective strategies to overcome the challenge of viral diversification and immune escape. We combined methods from statistical physics and evolutionary dynamics to predict the course of in vivo viral sequence evolution in response to T cell-mediated immune pressure in a cohort of 17 persons with acute HIV infection. Our predictions agree well with both the location of documented escape mutations and the clinically observed time to escape. We also find that that the mutational pathways to escape depend on the viral sequence background due to epistatic interactions. The ability to predict escape pathways, and the duration over which control is maintained by specific immune responses prior to escape, could be exploited for the rational design of immunotherapeutic strategies that may enable long-term control of HIV infection.

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. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Nonprincipal plane scattering of flat plates and pattern control of horn antennas

NASA Technical Reports Server (NTRS)

Balanis, Constantine A.; Polka, Lesley A.; Liu, Kefeng

1989-01-01

Using the geometrical theory of diffraction, the traditional method of high frequency scattering analysis, the prediction of the radar cross section of a perfectly conducting, flat, rectangular plate is limited to principal planes. Part A of this report predicts the radar cross section in nonprincipal planes using the method of equivalent currents. This technique is based on an asymptotic end-point reduction of the surface radiation integrals for an infinite wedge and enables nonprincipal plane prediction. The predicted radar cross sections for both horizontal and vertical polarizations are compared to moment method results and experimental data from Arizona State University's anechoic chamber. In part B, a variational calculus approach to the pattern control of the horn antenna is outlined. The approach starts with the optimization of the aperture field distribution so that the control of the radiation pattern in a range of directions can be realized. A control functional is thus formulated. Next, a spectral analysis method is introduced to solve for the eigenfunctions from the extremal condition of the formulated functional. Solutions to the optimized aperture field distribution are then obtained.

Stability and Control CFD Investigations of a Generic 53 Degree Swept UCAV Configuration

NASA Technical Reports Server (NTRS)

Frink, Neal T.

2014-01-01

NATO STO Task Group AVT-201 on "Extended Assessment of Reliable Stability & Control Prediction Methods for NATO Air Vehicles" is studying various computational approaches to predict stability and control parameters for aircraft undergoing non-linear flight conditions. This paper contributes an assessment through correlations with wind tunnel data for the state of aerodynamic predictive capability of time-accurate RANS methodology on the group's focus configuration, a 53deg swept and twisted lambda wing UCAV, undergoing a variety of roll, pitch, and yaw motions. The vehicle aerodynamics is dominated by the complex non-linear physics of round leading-edge vortex flow separation. Correlations with experimental data are made for static longitudinal/lateral sweeps, and at varying frequencies of prescribed roll/pitch/yaw sinusoidal motion for the vehicle operating with and without control surfaces. The data and the derived understanding should prove useful to the AVT-201 team and other researchers who are developing techniques for augmenting flight simulation models from low-speed CFD predictions of aircraft traversing non-linear regions of a flight envelope.

Engineering bacterial translation initiation - Do we have all the tools we need?

PubMed

Vigar, Justin R J; Wieden, Hans-Joachim

2017-11-01

Reliable tools that allow precise and predictable control over gene expression are critical for the success of nearly all bioengineering applications. Translation initiation is the most regulated phase during protein biosynthesis, and is therefore a promising target for exerting control over gene expression. At the translational level, the copy number of a protein can be fine-tuned by altering the interaction between the translation initiation region of an mRNA and the ribosome. These interactions can be controlled by modulating the mRNA structure using numerous approaches, including small molecule ligands, RNAs, or RNA-binding proteins. A variety of naturally occurring regulatory elements have been repurposed, facilitating advances in synthetic gene regulation strategies. The pursuit of a comprehensive understanding of mechanisms governing translation initiation provides the framework for future engineering efforts. Here we outline state-of-the-art strategies used to predictably control translation initiation in bacteria. We also discuss current limitations in the field and future goals. Due to its function as the rate-determining step, initiation is the ideal point to exert effective translation regulation. Several engineering tools are currently available to rationally design the initiation characteristics of synthetic mRNAs. However, improvements are required to increase the predictability, effectiveness, and portability of these tools. Predictable and reliable control over translation initiation will allow greater predictability when designing, constructing, and testing genetic circuits. The ability to build more complex circuits predictably will advance synthetic biology and contribute to our fundamental understanding of the underlying principles of these processes. "This article is part of a Special Issue entitled "Biochemistry of Synthetic Biology - Recent Developments" Guest Editor: Dr. Ilka Heinemann and Dr. Patrick O'Donoghue. Copyright © 2017 Elsevier B.V. All rights reserved.

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. © 2014 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

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. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Predicting school adjustment from multiple perspectives on parental behaviors.

PubMed

Ratelle, Catherine F; Duchesne, Stéphane; Guay, Frédéric

2017-01-01

Past research supported the importance of parental autonomy support, involvement, and structure for student outcomes. The goal of this study was to test the contribution of these behaviors from mothers and fathers in predicting adolescents' adjustment in school using a multi-informant approach. A sample of 522 adolescents (233 boys, 389 girls), their mothers (n = 535), and fathers (n = 296) participated in the study. Results revealed that parents' self-evaluations explained additional variance in children's school adjustment, over and beyond the contribution of children's evaluation of their parents. Maternal reports on their positive behaviors (autonomy support, involvement, and structure) predicted their child's academic and emotional adjustment while their reported control predicted lower levels of these. Fathers' self-reported positive behaviors predicted academic adjustment while their control predicted lower academic and personal-emotional adjustment. These findings support the importance of multiple assessments of parental behaviors for improving the prediction of adjustment in school. Copyright © 2016 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Isothermal life prediction of composite lamina using a damage mechanics approach

NASA Technical Reports Server (NTRS)

Abuelfoutouh, Nader M.; Verrilli, Michael J.; Halford, Gary R.

1989-01-01

A method for predicting isothermal plastic fatigue life of a composite lamina is presented in which both fibers and matrix are isotropic materials. In general, the fatigue resistances of the matrix, fibers, and interfacial material must be known in order to predict composite fatigue life. Composite fatigue life is predicted using only the matrix fatigue resistance due to inelasticity micromechanisms. The effect of the fiber orientation on loading direction is accounted for while predicting composite life. The application is currently limited to isothermal cases where the internal thermal stresses that might arise from thermal strain mismatch between fibers and matrix are negligible. The theory is formulated to predict the fatigue life of a composite lamina under either load or strain control. It is applied currently to predict the life of tungsten-copper composite lamina at 260 C under tension-tension load control. The calculated life of the lamina is in good agreement with available composite low cycle fatigue data.

Loss of Control Increases Belief in Precognition and Belief in Precognition Increases Control

PubMed Central

Greenaway, Katharine H.; Louis, Winnifred R.; Hornsey, Matthew J.

2013-01-01

Every year thousands of dollars are spent on psychics who claim to “know” the future. The present research questions why, despite no evidence that humans are able to psychically predict the future, do people persist in holding irrational beliefs about precognition? We argue that believing the future is predictable increases one’s own perceived ability to exert control over future events. As a result, belief in precognition should be particularly strong when people most desire control–that is, when they lack it. In Experiment 1 (N = 87), people who were experimentally induced to feel low in control reported greater belief in precognition than people who felt high in control. Experiment 2 (N = 53) investigated whether belief in precognition increases perceived control. Consistent with this notion, providing scientific evidence that precognition is possible increased feelings of control relative to providing scientific evidence that precognition was not possible. Experiment 3 (N = 132) revealed that when control is low, believing in precognition helps people to feel in control once more. Prediction therefore acts as a compensatory mechanism in times of low control. The present research provides new insights into the psychological functions of seemingly irrational beliefs, like belief in psychic abilities. PMID:23951136

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

Trajectory control method of stratospheric airship based on the sliding mode control and prediction in wind field

NASA Astrophysics Data System (ADS)

Zhang, Jia-shi; Yang, Xi-xiang

2017-11-01

The stratospheric airship has the characteristics of large inertia, long time delay and large disturbance of wind field , so the trajectory control is very difficult .Build the lateral three degrees of freedom dynamic model which consider the wind interference , the dynamics equation is linearized by the small perturbation theory, propose a trajectory control method Combine with the sliding mode control and prediction, design the trajectory controller , takes the HAA airship as the reference to carry out simulation analysis. Results show that the improved sliding mode control with front-feedback method not only can solve well control problems of airship trajectory in wind field, but also can effectively improve the control accuracy of the traditional sliding mode control method, solved problems that using the traditional sliding mode control to control. It provides a useful reference for dynamic modeling and trajectory control of stratospheric airship.

A standardized model for predicting flap failure using indocyanine green dye

NASA Astrophysics Data System (ADS)

Zimmermann, Terence M.; Moore, Lindsay S.; Warram, Jason M.; Greene, Benjamin J.; Nakhmani, Arie; Korb, Melissa L.; Rosenthal, Eben L.

2016-03-01

Techniques that provide a non-invasive method for evaluation of intraoperative skin flap perfusion are currently available but underutilized. We hypothesize that intraoperative vascular imaging can be used to reliably assess skin flap perfusion and elucidate areas of future necrosis by means of a standardized critical perfusion threshold. Five animal groups (negative controls, n=4; positive controls, n=5; chemotherapy group, n=5; radiation group, n=5; chemoradiation group, n=5) underwent pre-flap treatments two weeks prior to undergoing random pattern dorsal fasciocutaneous flaps with a length to width ratio of 2:1 (3 x 1.5 cm). Flap perfusion was assessed via laser-assisted indocyanine green dye angiography and compared to standard clinical assessment for predictive accuracy of flap necrosis. For estimating flap-failure, clinical prediction achieved a sensitivity of 79.3% and a specificity of 90.5%. When average flap perfusion was more than three standard deviations below the average flap perfusion for the negative control group at the time of the flap procedure (144.3+/-17.05 absolute perfusion units), laser-assisted indocyanine green dye angiography achieved a sensitivity of 81.1% and a specificity of 97.3%. When absolute perfusion units were seven standard deviations below the average flap perfusion for the negative control group, specificity of necrosis prediction was 100%. Quantitative absolute perfusion units can improve specificity for intraoperative prediction of viable tissue. Using this strategy, a positive predictive threshold of flap failure can be standardized for clinical use.

Offline modeling for product quality prediction of mineral processing using modeling error PDF shaping and entropy minimization.

PubMed

Ding, Jinliang; Chai, Tianyou; Wang, Hong

2011-03-01

This paper presents a novel offline modeling for product quality prediction of mineral processing which consists of a number of unit processes in series. The prediction of the product quality of the whole mineral process (i.e., the mixed concentrate grade) plays an important role and the establishment of its predictive model is a key issue for the plantwide optimization. For this purpose, a hybrid modeling approach of the mixed concentrate grade prediction is proposed, which consists of a linear model and a nonlinear model. The least-squares support vector machine is adopted to establish the nonlinear model. The inputs of the predictive model are the performance indices of each unit process, while the output is the mixed concentrate grade. In this paper, the model parameter selection is transformed into the shape control of the probability density function (PDF) of the modeling error. In this context, both the PDF-control-based and minimum-entropy-based model parameter selection approaches are proposed. Indeed, this is the first time that the PDF shape control idea is used to deal with system modeling, where the key idea is to turn model parameters so that either the modeling error PDF is controlled to follow a target PDF or the modeling error entropy is minimized. The experimental results using the real plant data and the comparison of the two approaches are discussed. The results show the effectiveness of the proposed approaches.

Predictors of early growth in academic achievement: the head-toes-knees-shoulders task

PubMed Central

McClelland, Megan M.; Cameron, Claire E.; Duncan, Robert; Bowles, Ryan P.; Acock, Alan C.; Miao, Alicia; Pratt, Megan E.

2014-01-01

Children's behavioral self-regulation and executive function (EF; including attentional or cognitive flexibility, working memory, and inhibitory control) are strong predictors of academic achievement. The present study examined the psychometric properties of a measure of behavioral self-regulation called the Head-Toes-Knees-Shoulders (HTKS) by assessing construct validity, including relations to EF measures, and predictive validity to academic achievement growth between prekindergarten and kindergarten. In the fall and spring of prekindergarten and kindergarten, 208 children (51% enrolled in Head Start) were assessed on the HTKS, measures of cognitive flexibility, working memory (WM), and inhibitory control, and measures of emergent literacy, mathematics, and vocabulary. For construct validity, the HTKS was significantly related to cognitive flexibility, working memory, and inhibitory control in prekindergarten and kindergarten. For predictive validity in prekindergarten, a random effects model indicated that the HTKS significantly predicted growth in mathematics, whereas a cognitive flexibility task significantly predicted growth in mathematics and vocabulary. In kindergarten, the HTKS was the only measure to significantly predict growth in all academic outcomes. An alternative conservative analytical approach, a fixed effects analysis (FEA) model, also indicated that growth in both the HTKS and measures of EF significantly predicted growth in mathematics over four time points between prekindergarten and kindergarten. Results demonstrate that the HTKS involves cognitive flexibility, working memory, and inhibitory control, and is substantively implicated in early achievement, with the strongest relations found for growth in achievement during kindergarten and associations with emergent mathematics. PMID:25071619

Impact of predictive model-directed end-of-life counseling for Medicare beneficiaries.

PubMed

Hamlet, Karen S; Hobgood, Adam; Hamar, Guy Brent; Dobbs, Angela C; Rula, Elizabeth Y; Pope, James E

2010-05-01

To validate a predictive model for identifying Medicare beneficiaries who need end-of-life care planning and to determine the impact on cost and hospice care of a telephonic counseling program utilizing this predictive model in 2 Medicare Health Support (MHS) pilots. Secondary analysis of data from 2 MHS pilot programs that used a randomized controlled design. A predictive model was developed using intervention group data (N = 43,497) to identify individuals at greatest risk of death. Model output guided delivery of a telephonic intervention designed to support educated end-of-life decisions and improve end-of-life provisions. Control group participants received usual care. As a primary outcome, Medicare costs in the last 6 months of life were compared between intervention group decedents (n = 3112) and control group decedents (n = 1630). Hospice admission rates and duration of hospice care were compared as secondary measures. The predictive model was highly accurate, and more than 80% of intervention group decedents were contacted during the 12 months before death. Average Medicare costs were $1913 lower for intervention group decedents compared with control group decedents in the last 6 months of life (P = .05), for a total savings of $5.95 million. There were no significant changes in hospice admissions or mean duration of hospice care. Telephonic end-of-life counseling provided as an ancillary Medicare service, guided by a predictive model, can reach a majority of individuals needing support and can reduce costs by facilitating voluntary election of less intensive care.

Advancement in Watershed Modelling Using Dynamic Lateral and Longitudinal Sediment (Dis)connectivity Prediction

NASA Astrophysics Data System (ADS)

Mahoney, D. T.; al Aamery, N. M. H.; Fox, J.

2017-12-01

The authors find that sediment (dis)connectivity has seldom taken precedence within watershed models, and the present study advances this modeling framework and applies the modeling within a bedrock-controlled system. Sediment (dis)connectivity, defined as the detachment and transport of sediment from source to sink between geomorphic zones, is a major control on sediment transport. Given the availability of high resolution geospatial data, coupling sediment connectivity concepts within sediment prediction models offers an approach to simulate sediment sources and pathways within a watershed's sediment cascade. Bedrock controlled catchments are potentially unique due to the presence of rock outcrops causing longitudinal impedance to sediment transport pathways in turn impacting the longitudinal distribution of the energy gradient responsible for conveying sediment. Therefore, the authors were motivated by the need to formulate a sediment transport model that couples sediment (dis)connectivity knowledge to predict sediment flux for bedrock controlled catchments. A watershed-scale sediment transport model was formulated that incorporates sediment (dis)connectivity knowledge collected via field reconnaissance and predicts sediment flux through coupling with the Partheniades equation and sediment continuity model. Sediment (dis)connectivity was formulated by coupling probabilistic upland lateral connectivity prediction with instream longitudinal connectivity assessments via discretization of fluid and sediment pathways. Flux predictions from the upland lateral connectivity model served as an input to the instream longitudinal connectivity model. Disconnectivity in the instream model was simulated via the discretization of stream reaches due to barriers such as bedrock outcroppings and man-made check dams. The model was tested for a bedrock controlled catchment in Kentucky, USA for which extensive historic water and sediment flux data was available. Predicted sediment flux was validated via sediment flux measurements collected by the authors. Watershed configuration and the distribution of lateral and longitudinal impedances to sediment transport were found to have significant influence on sediment connectivity and thus sediment flux.

Multi-mode evaluation of power-maximizing cross-flow turbine controllers

DOE PAGES

Forbush, Dominic; Cavagnaro, Robert J.; Donegan, James; ...

2017-09-21

A general method for predicting and evaluating the performance of three candidate cross-flow turbine power-maximizing controllers is presented in this paper using low-order dynamic simulation, scaled laboratory experiments, and full-scale field testing. For each testing mode and candidate controller, performance metrics quantifying energy capture (ability of a controller to maximize power), variation in torque and rotation rate (related to drive train fatigue), and variation in thrust loads (related to structural fatigue) are quantified for two purposes. First, for metrics that could be evaluated across all testing modes, we considered the accuracy with which simulation or laboratory experiments could predict performancemore » at full scale. Second, we explored the utility of these metrics to contrast candidate controller performance. For these turbines and set of candidate controllers, energy capture was found to only differentiate controller performance in simulation, while the other explored metrics were able to predict performance of the full-scale turbine in the field with various degrees of success. Finally, effects of scale between laboratory and full-scale testing are considered, along with recommendations for future improvements to dynamic simulations and controller evaluation.« less

Vestibulospinal adaptation to microgravity

NASA Technical Reports Server (NTRS)

Paloski, W. H.

1998-01-01

Human balance control is known to be transiently disrupted after spaceflight; however, the mechanisms responsible for postflight postural ataxia are still under investigation. In this report, we propose a conceptual model of vestibulospinal adaptation based on theoretical adaptive control concepts and supported by the results from a comprehensive study of balance control recovery after spaceflight. The conceptual model predicts that immediately after spaceflight the balance control system of a returning astronaut does not expect to receive gravity-induced afferent inputs and that descending vestibulospinal control of balance is disrupted until the central nervous system is able to cope with the newly available vestibular otolith information. Predictions of the model are tested using data from a study of the neurosensory control of balance in astronauts immediately after landing. In that study, the mechanisms of sensorimotor balance control were assessed under normal, reduced, and/or altered (sway-referenced) visual and somatosensory input conditions. We conclude that the adaptive control model accurately describes the neurobehavioral responses to spaceflight and that similar models of altered sensory, motor, or environmental constraints are needed clinically to predict responses that patients with sensorimotor pathologies may have to various visual-vestibular or changing stimulus environments.

Multi-mode evaluation of power-maximizing cross-flow turbine controllers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Forbush, Dominic; Cavagnaro, Robert J.; Donegan, James

A general method for predicting and evaluating the performance of three candidate cross-flow turbine power-maximizing controllers is presented in this paper using low-order dynamic simulation, scaled laboratory experiments, and full-scale field testing. For each testing mode and candidate controller, performance metrics quantifying energy capture (ability of a controller to maximize power), variation in torque and rotation rate (related to drive train fatigue), and variation in thrust loads (related to structural fatigue) are quantified for two purposes. First, for metrics that could be evaluated across all testing modes, we considered the accuracy with which simulation or laboratory experiments could predict performancemore » at full scale. Second, we explored the utility of these metrics to contrast candidate controller performance. For these turbines and set of candidate controllers, energy capture was found to only differentiate controller performance in simulation, while the other explored metrics were able to predict performance of the full-scale turbine in the field with various degrees of success. Finally, effects of scale between laboratory and full-scale testing are considered, along with recommendations for future improvements to dynamic simulations and controller evaluation.« less

A negative relationship between ventral striatal loss anticipation response and impulsivity in borderline personality disorder.

PubMed

Herbort, Maike C; Soch, Joram; Wüstenberg, Torsten; Krauel, Kerstin; Pujara, Maia; Koenigs, Michael; Gallinat, Jürgen; Walter, Henrik; Roepke, Stefan; Schott, Björn H

2016-01-01

Patients with borderline personality disorder (BPD) frequently exhibit impulsive behavior, and self-reported impulsivity is typically higher in BPD patients when compared to healthy controls. Previous functional neuroimaging studies have suggested a link between impulsivity, the ventral striatal response to reward anticipation, and prediction errors. Here we investigated the striatal neural response to monetary gain and loss anticipation and their relationship with impulsivity in 21 female BPD patients and 23 age-matched female healthy controls using functional magnetic resonance imaging (fMRI). Participants performed a delayed monetary incentive task in which three categories of objects predicted a potential gain, loss, or neutral outcome. Impulsivity was assessed using the Barratt Impulsiveness Scale (BIS-11). Compared to healthy controls, BPD patients exhibited significantly reduced fMRI responses of the ventral striatum/nucleus accumbens (VS/NAcc) to both reward-predicting and loss-predicting cues. BIS-11 scores showed a significant positive correlation with the VS/NAcc reward anticipation responses in healthy controls, and this correlation, while also nominally positive, failed to reach significance in BPD patients. BPD patients, on the other hand, exhibited a significantly negative correlation between ventral striatal loss anticipation responses and BIS-11 scores, whereas this correlation was significantly positive in healthy controls. Our results suggest that patients with BPD show attenuated anticipation responses in the VS/NAcc and, furthermore, that higher impulsivity in BPD patients might be related to impaired prediction of aversive outcomes.

Utility of the theory of reasoned action and theory of planned behavior for predicting Chinese adolescent smoking.

PubMed

Guo, Qian; Johnson, C Anderson; Unger, Jennifer B; Lee, Liming; Xie, Bin; Chou, Chih-Ping; Palmer, Paula H; Sun, Ping; Gallaher, Peggy; Pentz, MaryAnn

2007-05-01

One third of smokers worldwide live in China. Identifying predictors of smoking is important for prevention program development. This study explored whether the Theory of Reasoned Action (TRA) and Theory of Planned Behavior (TPB) predict adolescent smoking in China. Data were obtained from 14,434 middle and high school students (48.6% boys, 51.4% girls) in seven geographically varied cities in China. TRA and TPB were tested by multilevel mediation modeling, and compared by multilevel analyses and likelihood ratio tests. Perceived behavioral control was tested as a main effect in TPB and a moderation effect in TRA. The mediation effects of smoking intention were supported in both models (p<0.001). TPB accounted for significantly more variance than TRA (p<0.001). Perceived behavioral control significantly interacted with attitudes and social norms in TRA (p<0.001). Therefore, TRA and TPB are applicable to China to predict adolescent smoking. TPB is superior to TRA for the prediction and TRA can better predict smoking among students with lower than higher perceived behavioral control.

A digital prediction algorithm for a single-phase boost PFC

NASA Astrophysics Data System (ADS)

Qing, Wang; Ning, Chen; Weifeng, Sun; Shengli, Lu; Longxing, Shi

2012-12-01

A novel digital control algorithm for digital control power factor correction is presented, which is called the prediction algorithm and has a feature of a higher PF (power factor) with lower total harmonic distortion, and a faster dynamic response with the change of the input voltage or load current. For a certain system, based on the current system state parameters, the prediction algorithm can estimate the track of the output voltage and the inductor current at the next switching cycle and get a set of optimized control sequences to perfectly track the trajectory of input voltage. The proposed prediction algorithm is verified at different conditions, and computer simulation and experimental results under multi-situations confirm the effectiveness of the prediction algorithm. Under the circumstances that the input voltage is in the range of 90-265 V and the load current in the range of 20%-100%, the PF value is larger than 0.998. The startup and the recovery times respectively are about 0.1 s and 0.02 s without overshoot. The experimental results also verify the validity of the proposed method.

Assessing Probabilistic Risk Assessment Approaches for Insect Biological Control Introductions.

PubMed

Kaufman, Leyla V; Wright, Mark G

2017-07-07

The introduction of biological control agents to new environments requires host specificity tests to estimate potential non-target impacts of a prospective agent. Currently, the approach is conservative, and is based on physiological host ranges determined under captive rearing conditions, without consideration for ecological factors that may influence realized host range. We use historical data and current field data from introduced parasitoids that attack an endemic Lepidoptera species in Hawaii to validate a probabilistic risk assessment (PRA) procedure for non-target impacts. We use data on known host range and habitat use in the place of origin of the parasitoids to determine whether contemporary levels of non-target parasitism could have been predicted using PRA. Our results show that reasonable predictions of potential non-target impacts may be made if comprehensive data are available from places of origin of biological control agents, but scant data produce poor predictions. Using apparent mortality data rather than marginal attack rate estimates in PRA resulted in over-estimates of predicted non-target impact. Incorporating ecological data into PRA models improved the predictive power of the risk assessments.

Assessing Probabilistic Risk Assessment Approaches for Insect Biological Control Introductions

PubMed Central

Kaufman, Leyla V.; Wright, Mark G.

2017-01-01

The introduction of biological control agents to new environments requires host specificity tests to estimate potential non-target impacts of a prospective agent. Currently, the approach is conservative, and is based on physiological host ranges determined under captive rearing conditions, without consideration for ecological factors that may influence realized host range. We use historical data and current field data from introduced parasitoids that attack an endemic Lepidoptera species in Hawaii to validate a probabilistic risk assessment (PRA) procedure for non-target impacts. We use data on known host range and habitat use in the place of origin of the parasitoids to determine whether contemporary levels of non-target parasitism could have been predicted using PRA. Our results show that reasonable predictions of potential non-target impacts may be made if comprehensive data are available from places of origin of biological control agents, but scant data produce poor predictions. Using apparent mortality data rather than marginal attack rate estimates in PRA resulted in over-estimates of predicted non-target impact. Incorporating ecological data into PRA models improved the predictive power of the risk assessments. PMID:28686180

The phantom robot - Predictive displays for teleoperation with time delay

NASA Technical Reports Server (NTRS)

Bejczy, Antal K.; Kim, Won S.; Venema, Steven C.

1990-01-01

An enhanced teleoperation technique for time-delayed bilateral teleoperator control is discussed. The control technique selected for time delay is based on the use of a high-fidelity graphics phantom robot that is being controlled in real time (without time delay) against the static task image. Thus, the motion of the phantom robot image on the monitor predicts the motion of the real robot. The real robot's motion will follow the phantom robot's motion on the monitor with the communication time delay implied in the task. Real-time high-fidelity graphics simulation of a PUMA arm is generated and overlaid on the actual camera view of the arm. A simple camera calibration technique is used for calibrated graphics overlay. A preliminary experiment is performed with the predictive display by using a very simple tapping task. The results with this simple task indicate that predictive display enhances the human operator's telemanipulation task performance significantly during free motion when there is a long time delay. It appears, however, that either two-view or stereoscopic predictive displays are necessary for general three-dimensional tasks.

Motivational state controls the prediction error in Pavlovian appetitive-aversive interactions.

PubMed

Laurent, Vincent; Balleine, Bernard W; Westbrook, R Frederick

2018-01-01

Contemporary theories of learning emphasize the role of a prediction error signal in driving learning, but the nature of this signal remains hotly debated. Here, we used Pavlovian conditioning in rats to investigate whether primary motivational and emotional states interact to control prediction error. We initially generated cues that positively or negatively predicted an appetitive food outcome. We then assessed how these cues modulated aversive conditioning when a novel cue was paired with a foot shock. We found that a positive predictor of food enhances, whereas a negative predictor of that same food impairs, aversive conditioning. Critically, we also showed that the enhancement produced by the positive predictor is removed by reducing the value of its associated food. In contrast, the impairment triggered by the negative predictor remains insensitive to devaluation of its associated food. These findings provide compelling evidence that the motivational value attributed to a predicted food outcome can directly control appetitive-aversive interactions and, therefore, that motivational processes can modulate emotional processes to generate the final error term on which subsequent learning is based. Copyright © 2017 Elsevier Inc. All rights reserved.

Prospective versus predictive control in timing of hitting a falling ball.

PubMed

Katsumata, Hiromu; Russell, Daniel M

2012-02-01

Debate exists as to whether humans use prospective or predictive control to intercept an object falling under gravity (Baurès et al. in Vis Res 47:2982-2991, 2007; Zago et al. in Vis Res 48:1532-1538, 2008). Prospective control involves using continuous information to regulate action. τ, the ratio of the size of the gap to the rate of gap closure, has been proposed as the information used in guiding interceptive actions prospectively (Lee in Ecol Psychol 10:221-250, 1998). This form of control is expected to generate movement modulation, where variability decreases over the course of an action based upon more accurate timing information. In contrast, predictive control assumes that a pre-programmed movement is triggered at an appropriate criterion timing variable. For a falling object it is commonly argued that an internal model of gravitational acceleration is used to predict the motion of the object and determine movement initiation. This form of control predicts fixed duration movements initiated at consistent time-to-contact (TTC), either across conditions (constant criterion operational timing) or within conditions (variable criterion operational timing). The current study sought to test predictive and prospective control hypotheses by disrupting continuous visual information of a falling ball and examining consistency in movement initiation and duration, and evidence for movement modulation. Participants (n = 12) batted a ball dropped from three different heights (1, 1.3 and 1.5 m), under both full-vision and partial occlusion conditions. In the occlusion condition, only the initial ball drop and the final 200 ms of ball flight to the interception point could be observed. The initiation of the swing did not occur at a consistent TTC, τ, or any other timing variable across drop heights, in contrast with previous research. However, movement onset was not impacted by occluding the ball flight for 280-380 ms. This finding indicates that humans did not need to be continuously coupled to vision of the ball to initiate the swing accurately, but instead could use predictive control based on acceleration timing information (TTC2). However, other results provide evidence for movement modulation, a characteristic of prospective control. Strong correlations between movement initiation and duration and reduced timing variability from swing onset to arrival at the interception point, both support compensatory variability. An analysis of modulation within the swing revealed that early in the swing, the movement acceleration was strongly correlated to the required mean velocity at swing onset and that later in the swing, the movement acceleration was again strongly correlated with the current required mean velocity. Rather than a consistent movement initiated at the same time, these findings show that the swing was variable but modulated for meeting the demands of each trial. A prospective model of coupling τ (bat-ball) with τ (ball-target) was found to provide a very strong linear fit for an average of 69% of the movement duration. These findings provide evidence for predictive control based on TTC2 information in initiating the swing and prospective control based on τ in guiding the bat to intercept the ball.

Models for short term malaria prediction in Sri Lanka

PubMed Central

Briët, Olivier JT; Vounatsou, Penelope; Gunawardena, Dissanayake M; Galappaththy, Gawrie NL; Amerasinghe, Priyanie H

2008-01-01

Background Malaria in Sri Lanka is unstable and fluctuates in intensity both spatially and temporally. Although the case counts are dwindling at present, given the past history of resurgence of outbreaks despite effective control measures, the control programmes have to stay prepared. The availability of long time series of monitored/diagnosed malaria cases allows for the study of forecasting models, with an aim to developing a forecasting system which could assist in the efficient allocation of resources for malaria control. Methods Exponentially weighted moving average models, autoregressive integrated moving average (ARIMA) models with seasonal components, and seasonal multiplicative autoregressive integrated moving average (SARIMA) models were compared on monthly time series of district malaria cases for their ability to predict the number of malaria cases one to four months ahead. The addition of covariates such as the number of malaria cases in neighbouring districts or rainfall were assessed for their ability to improve prediction of selected (seasonal) ARIMA models. Results The best model for forecasting and the forecasting error varied strongly among the districts. The addition of rainfall as a covariate improved prediction of selected (seasonal) ARIMA models modestly in some districts but worsened prediction in other districts. Improvement by adding rainfall was more frequent at larger forecasting horizons. Conclusion Heterogeneity of patterns of malaria in Sri Lanka requires regionally specific prediction models. Prediction error was large at a minimum of 22% (for one of the districts) for one month ahead predictions. The modest improvement made in short term prediction by adding rainfall as a covariate to these prediction models may not be sufficient to merit investing in a forecasting system for which rainfall data are routinely processed. PMID:18460204

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.

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 whole plant mass and energy exchange models allows prediction of plant carbon, energy and nitrogen exchange that fits recently collected data including plant sap flux, leaf gas exchange, eddy covariance towers and stand and watershed-scale biogeochemistry measurements. The results of our work will allow the next generation of ecosystem to regional scale coupled-biogeochemistry models to incorporate a simple plant hydraulic mechanism that will enable defensible predictions of carbon, water, energy and nutrient cycling with changing climate and land use.

Longitudinal Relations of Intrusive Parenting and Effortful Control to Ego-Resiliency During Early Childhood

PubMed Central

Taylor, Zoe E.; Eisenberg, Nancy; Spinrad, Tracy L.; Widaman, Keith F.

2012-01-01

Longitudinal relations among ego-resiliency, effortful control, and observed intrusive parenting were examined at 18, 30, and 42 months of age (Ns = 256, 230, and 210) using structural equation modeling. Intrusive parenting at 18 and 30 months negatively predicted effortful control a year later, over and above earlier levels. Effortful control at 30 months mediated the negative relation between 18-month intrusive parenting and ego-resiliency at 42 months when controlling for stability of the variables. Ego-resiliency did not predict effortful control. The findings suggest that intrusive parenting may have a negative effect on children’s personality resiliency through its effects on the abilities to regulate attention and behavior. PMID:23379965

Uncertainty and sensitivity analysis of control strategies using the benchmark simulation model No1 (BSM1).

PubMed

Flores-Alsina, Xavier; Rodriguez-Roda, Ignasi; Sin, Gürkan; Gernaey, Krist V

2009-01-01

The objective of this paper is to perform an uncertainty and sensitivity analysis of the predictions of the Benchmark Simulation Model (BSM) No. 1, when comparing four activated sludge control strategies. The Monte Carlo simulation technique is used to evaluate the uncertainty in the BSM1 predictions, considering the ASM1 bio-kinetic parameters and influent fractions as input uncertainties while the Effluent Quality Index (EQI) and the Operating Cost Index (OCI) are focused on as model outputs. The resulting Monte Carlo simulations are presented using descriptive statistics indicating the degree of uncertainty in the predicted EQI and OCI. Next, the Standard Regression Coefficients (SRC) method is used for sensitivity analysis to identify which input parameters influence the uncertainty in the EQI predictions the most. The results show that control strategies including an ammonium (S(NH)) controller reduce uncertainty in both overall pollution removal and effluent total Kjeldahl nitrogen. Also, control strategies with an external carbon source reduce the effluent nitrate (S(NO)) uncertainty increasing both their economical cost and variability as a trade-off. Finally, the maximum specific autotrophic growth rate (micro(A)) causes most of the variance in the effluent for all the evaluated control strategies. The influence of denitrification related parameters, e.g. eta(g) (anoxic growth rate correction factor) and eta(h) (anoxic hydrolysis rate correction factor), becomes less important when a S(NO) controller manipulating an external carbon source addition is implemented.

Characteristics of Perimenstrual Asthma and Its Relation to Asthma Severity and Control

PubMed Central

Rao, Chitra K.; Moore, Charity G.; Bleecker, Eugene; Busse, William W.; Calhoun, William; Castro, Mario; Chung, Kian Fan; Erzurum, Serpil C.; Israel, Elliot; Curran-Everett, Douglas

2013-01-01

Background: Although perimenstrual asthma (PMA) has been associated with severe and difficult-to-control asthma, it remains poorly characterized and understood. The objectives of this study were to identify clinical, demographic, and inflammatory factors associated with PMA and to assess the association of PMA with asthma severity and control. Methods: Women with asthma recruited to the National Heart, Lung, and Blood Institute Severe Asthma Research Program who reported PMA symptoms on a screening questionnaire were analyzed in relation to basic demographics, clinical questionnaire data, immunoinflammatory markers, and physiologic parameters. Univariate comparisons between PMA and non-PMA groups were performed. A severity-adjusted model predicting PMA was created. Additional models addressed the role of PMA in asthma control. Results: Self-identified PMA was reported in 17% of the subjects (n = 92) and associated with higher BMI, lower FVC % predicted, and higher gastroesophageal reflux disease rates. Fifty-two percent of the PMA group met criteria for severe asthma compared with 30% of the non-PMA group. In multivariable analyses controlling for severity, aspirin sensitivity and lower FVC % predicted were associated with the presence of PMA. Furthermore, after controlling for severity and confounders, PMA remained associated with more asthma symptoms and urgent health-care utilization. Conclusions: PMA is common in women with severe asthma and associated with poorly controlled disease. Aspirin sensitivity and lower FVC % predicted are associated with PMA after adjusting for multiple factors, suggesting that alterations in prostaglandins may contribute to this phenotype. PMID:23632943

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

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.

Development of a Low-Lift Chiller Controller and Simplified Precooling Control Algorithm - Final Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gayeski, N.; Armstrong, Peter; Alvira, M.

2011-11-30

KGS Buildings LLC (KGS) and Pacific Northwest National Laboratory (PNNL) have developed a simplified control algorithm and prototype low-lift chiller controller suitable for model-predictive control in a demonstration project of low-lift cooling. Low-lift cooling is a highly efficient cooling strategy conceived to enable low or net-zero energy buildings. A low-lift cooling system consists of a high efficiency low-lift chiller, radiant cooling, thermal storage, and model-predictive control to pre-cool thermal storage overnight on an optimal cooling rate trajectory. We call the properly integrated and controlled combination of these elements a low-lift cooling system (LLCS). This document is the final report formore » that project.« less

Self-controlled learning benefits: exploring contributions of self-efficacy and intrinsic motivation via path analysis.

PubMed

Ste-Marie, Diane M; Carter, Michael J; Law, Barbi; Vertes, Kelly; Smith, Victoria

2016-09-01

Research has shown learning advantages for self-controlled practice contexts relative to yoked (i.e., experimenter-imposed) contexts; yet, explanations for this phenomenon remain relatively untested. We examined, via path analysis, whether self-efficacy and intrinsic motivation are important constructs for explaining self-controlled learning benefits. The path model was created using theory-based and empirically supported relationships to examine causal links between these psychological constructs and physical performance. We hypothesised that self-efficacy and intrinsic motivation would have greater predictive power for learning under self-controlled compared to yoked conditions. Participants learned double-mini trampoline progressions, and measures of physical performance, self-efficacy and intrinsic motivation were collected over two practice days and a delayed retention day. The self-controlled group (M = 2.04, SD = .98) completed significantly more skill progressions in retention than their yoked counterparts (M = 1.3, SD = .65). The path model displayed adequate fit, and similar significant path coefficients were found for both groups wherein each variable was predominantly predicted by its preceding time point (e.g., self-efficacy time 1 predicts self-efficacy time 2). Interestingly, the model was not moderated by group; thus, failing to support the hypothesis that self-efficacy and intrinsic motivation have greater predictive power for learning under self-controlled relative to yoked conditions.

Effectiveness of a Predictive Algorithm in the Prevention of Exercise-Induced Hypoglycemia in Type 1 Diabetes.

PubMed

Abraham, Mary B; Davey, Raymond; O'Grady, Michael J; Ly, Trang T; Paramalingam, Nirubasini; Fournier, Paul A; Roy, Anirban; Grosman, Benyamin; Kurtz, Natalie; Fairchild, Janice M; King, Bruce R; Ambler, Geoffrey R; Cameron, Fergus; Jones, Timothy W; Davis, Elizabeth A

2016-09-01

Sensor-augmented pump therapy (SAPT) with a predictive algorithm to suspend insulin delivery has the potential to reduce hypoglycemia, a known obstacle in improving physical activity in patients with type 1 diabetes. The predictive low glucose management (PLGM) system employs a predictive algorithm that suspends basal insulin when hypoglycemia is predicted. The aim of this study was to determine the efficacy of this algorithm in the prevention of exercise-induced hypoglycemia under in-clinic conditions. This was a randomized, controlled cross-over study in which 25 participants performed 2 consecutive sessions of 30 min of moderate-intensity exercise while on basal continuous subcutaneous insulin infusion on 2 study days: a control day with SAPT alone and an intervention day with SAPT and PLGM. The predictive algorithm suspended basal insulin when sensor glucose was predicted to be below the preset hypoglycemic threshold in 30 min. We tested preset hypoglycemic thresholds of 70 and 80 mg/dL. The primary outcome was the requirement for hypoglycemia treatment (symptomatic hypoglycemia with plasma glucose <63 mg/dL or plasma glucose <50 mg/dL) and was compared in both control and intervention arms. Results were analyzed in 19 participants. In the intervention arm with both thresholds, only 6 participants (32%) required treatment for hypoglycemia compared with 17 participants (89%) in the control arm (P = 0.003). In participants with a 2-h pump suspension on intervention days, the plasma glucose was 84 ± 12 and 99 ± 24 mg/dL at thresholds of 70 and 80 mg/dL, respectively. SAPT with PLGM reduced the need for hypoglycemia treatment after moderate-intensity exercise in an in-clinic setting.

Tank System Integrated Model: A Cryogenic Tank Performance Prediction Program

NASA Technical Reports Server (NTRS)

Bolshinskiy, L. G.; Hedayat, A.; Hastings, L. J.; Sutherlin, S. G.; Schnell, A. R.; Moder, J. P.

2017-01-01

Accurate predictions of the thermodynamic state of the cryogenic propellants, pressurization rate, and performance of pressure control techniques in cryogenic tanks are required for development of cryogenic fluid long-duration storage technology and planning for future space exploration missions. This Technical Memorandum (TM) presents the analytical tool, Tank System Integrated Model (TankSIM), which can be used for modeling pressure control and predicting the behavior of cryogenic propellant for long-term storage for future space missions. Utilizing TankSIM, the following processes can be modeled: tank self-pressurization, boiloff, ullage venting, mixing, and condensation on the tank wall. This TM also includes comparisons of TankSIM program predictions with the test data andexamples of multiphase mission calculations.

Children's construction task performance and spatial ability: controlling task complexity and predicting mathematics performance.

PubMed

Richardson, Miles; Hunt, Thomas E; Richardson, Cassandra

2014-12-01

This paper presents a methodology to control construction task complexity and examined the relationships between construction performance and spatial and mathematical abilities in children. The study included three groups of children (N = 96); ages 7-8, 10-11, and 13-14 years. Each group constructed seven pre-specified objects. The study replicated and extended previous findings that indicated that the extent of component symmetry and variety, and the number of components for each object and available for selection, significantly predicted construction task difficulty. Results showed that this methodology is a valid and reliable technique for assessing and predicting construction play task difficulty. Furthermore, construction play performance predicted mathematical attainment independently of spatial ability.

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.

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

Perceived control and communication about sex: a study of South African families.

PubMed

Goodnight, Bradley; Salama, Christina; Grim, Elizabeth C; Anthony, Elizabeth R; Armistead, Lisa; Cook, Sarah L; Skinner, Donald; Toefy, Yoesrie

2014-01-01

Caregiver-youth communication about sex protects youth against HIV/AIDS, and caregivers who believe that sex knowledge is important are more likely to talk to their youth about sex. However, caregivers who experience barriers to communication about sex may not talk to their youth about sex even if the caregiver believes that sex education is important. The Theory of Planned Behaviour predicts that an actor has perceived control is necessary for behavioural change. This study therefore hypothesised that caregivers' perceived control moderates the relationship between caregiver attitudes about youth sex knowledge and caregiver-youth communication about sex. Results from a sample of 99 female South African caregivers of adolescent (10-14 year old) youth supported our hypothesis, indicating that caregiver attitudes about providing youth with sex knowledge positively predict communication about sex only when caregivers have perceived control. This finding illustrates the importance of perceived control in predicting caregiver-youth communication, and therefore has implications for family-based interventions aimed at improving caregiver-youth communication about sex.

Sub-Saharan African university students' beliefs about condoms, condom-use intention, and subsequent condom use: a prospective study.

PubMed

Heeren, G Anita; Jemmott, John B; Mandeya, Andrew; Tyler, Joanne C

2009-04-01

Whether certain behavioral beliefs, normative beliefs, and control beliefs predict the intention to use condoms and subsequent condom use was examined among 320 undergraduates at a university in South Africa who completed confidential questionnaires on two occasions separated by 3 months. Participants' mean age was 23.4 years, 47.8% were women, 48.9% were South Africans, and 51.1% were from other sub-Saharan African countries. Multiple regression revealed that condom-use intention was predicted by hedonistic behavioral beliefs, normative beliefs regarding sexual partners and peers, and control beliefs regarding condom-use technical skill and impulse control. Logistic regression revealed that baseline condom-use intention predicted consistent condom use and condom use during most recent intercourse at 3-month follow-up. HIV/STI risk-reduction interventions for undergraduates in South Africa should target their condom-use hedonistic beliefs, normative beliefs regarding partners and peers, and control beliefs regarding technical skill and impulse control.

The role of self-control strength in the development of state anxiety in test situations.

PubMed

Englert, C; Bertrams, A

2013-06-01

Self-control strength may affect state anxiety because emotion regulation is impaired in individuals whose self-control strength has been temporarily depleted. Increases in state anxiety were expected to be larger for participants with depleted compared to nondepleted self-control strength, and trait test anxiety should predict increases in state anxiety more strongly if self-control strength is depleted. In a sample of 76 university students, trait test anxiety was assessed, self-control strength experimentally manipulated, and state anxiety measured before and after the announcement of a test. State anxiety increased after the announcement. Trait test anxiety predicted increases in state anxiety only in students with depleted self-control strength, suggesting that increased self-control strength may be useful for coping with anxiety.

Prediction of jump phenomena in rotationally-coupled maneuvers of aircraft, including nonlinear aerodynamic effects

NASA Technical Reports Server (NTRS)

Young, J. W.; Schy, A. A.; Johnson, K. G.

1977-01-01

An analytical method has been developed for predicting critical control inputs for which nonlinear rotational coupling may cause sudden jumps in aircraft response. The analysis includes the effect of aerodynamics which are nonlinear in angle of attack. The method involves the simultaneous solution of two polynomials in roll rate, whose coefficients are functions of angle of attack and the control inputs. Results obtained using this procedure are compared with calculated time histories to verify the validity of the method for predicting jump-like instabilities.

Control and prediction of the course of brewery fermentations by gravimetric analysis.

PubMed

Kosín, P; Savel, J; Broz, A; Sigler, K

2008-01-01

A simple, fast and cheap test suitable for predicting the course of brewery fermentations based on mass analysis is described and its efficiency is evaluated. Compared to commonly used yeast vitality tests, this analysis takes into account wort composition and other factors that influence fermentation performance. It can be used to predict the shape of the fermentation curve in brewery fermentations and in research and development projects concerning yeast vitality, fermentation conditions and wort composition. It can also be a useful tool for homebrewers to control their fermentations.

An Investigation of the Low Speed Stability and Control Characteristics of Swept-Forward and Swept-Back Wings in the Ames 40- by 80-Foot Wind Tunnel

DTIC Science & Technology

1947-06-01

effective dihedral, and the sharp reduction In lateral- control effectiveness. In general, simple theory enables good predictions to be made of the...ifoloh the simplified sweeo theory may fee used to predict the characteristics of swept Mings is eval- uated by it oompiFlsnn with the experimental...are shown together with the predictions baaed on theory for both concepts of aspect ratio*. For awept-bcok wings, basing the aspect ratio on the

Identification of the feedforward component in manual control with predictable target signals.

PubMed

Drop, Frank M; Pool, Daan M; Damveld, Herman J; van Paassen, Marinus M; Mulder, Max

2013-12-01

In the manual control of a dynamic system, the human controller (HC) often follows a visible and predictable reference path. Compared with a purely feedback control strategy, performance can be improved by making use of this knowledge of the reference. The operator could effectively introduce feedforward control in conjunction with a feedback path to compensate for errors, as hypothesized in literature. However, feedforward behavior has never been identified from experimental data, nor have the hypothesized models been validated. This paper investigates human control behavior in pursuit tracking of a predictable reference signal while being perturbed by a quasi-random multisine disturbance signal. An experiment was done in which the relative strength of the target and disturbance signals were systematically varied. The anticipated changes in control behavior were studied by means of an ARX model analysis and by fitting three parametric HC models: two different feedback models and a combined feedforward and feedback model. The ARX analysis shows that the experiment participants employed control action on both the error and the target signal. The control action on the target was similar to the inverse of the system dynamics. Model fits show that this behavior can be modeled best by the combined feedforward and feedback model.

Accounting for control mislabeling in case-control biomarker studies.

PubMed

Rantalainen, Mattias; Holmes, Chris C

2011-12-02

In biomarker discovery studies, uncertainty associated with case and control labels is often overlooked. By omitting to take into account label uncertainty, model parameters and the predictive risk can become biased, sometimes severely. The most common situation is when the control set contains an unknown number of undiagnosed, or future, cases. This has a marked impact in situations where the model needs to be well-calibrated, e.g., when the prediction performance of a biomarker panel is evaluated. Failing to account for class label uncertainty may lead to underestimation of classification performance and bias in parameter estimates. This can further impact on meta-analysis for combining evidence from multiple studies. Using a simulation study, we outline how conventional statistical models can be modified to address class label uncertainty leading to well-calibrated prediction performance estimates and reduced bias in meta-analysis. We focus on the problem of mislabeled control subjects in case-control studies, i.e., when some of the control subjects are undiagnosed cases, although the procedures we report are generic. The uncertainty in control status is a particular situation common in biomarker discovery studies in the context of genomic and molecular epidemiology, where control subjects are commonly sampled from the general population with an established expected disease incidence rate.

“No-o-o-o Peeking”: Preschoolers’ Executive Control, Social Competence, and Classroom Adjustment

PubMed Central

Denham, Susanne A.; Bassett, Hideko H.; Sirotkin, Yana S.; Brown, Chavaughn; Morris, Carol S.

2015-01-01

The goals of this study were to evaluate (1) how specific aspects of executive control, briefly assessed, predict social competence and classroom adjustment during preschool; and (2) differences between two aspects of executive control, according to child’s age, socioeconomic risk status, and gender. The facets of executive control were defined as cool executive control (CEC; affectively neutral, slow acting, and late developing) and hot executive control (HEC; more emotional, fast acting, and early developing). Two hundred eighty-seven 3- to 5-year-old children from private child care and Head Start centers were directly assessed during executive control tasks, and preschool teachers provided information on their school success. Aspects of executive control varied with age, socioeconomic risk, and gender. Specifically, older children performed better on CEC tasks across three age levels; for HEC tasks, change was seen only between 3-year-olds and 4-year-olds. Children of mothers with less formal education performed less well on CEC than those whose mothers had more education; girls performed better than boys on HEC tasks. Further, facets of executive control were differentially related to later social competence and classroom adjustment. HEC predicted social competence, whereas CEC uniquely predicted classroom adjustment. Implications for everyday practice and specific curricula formulation are discussed. PMID:26166925

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. Copyright © 2014 Elsevier Inc. All rights reserved.

The Role of Self-regulation and Affective Control in Predicting Interpersonal Reactivity of Drug Addicts

PubMed Central

Abolghasemi, Abbas; Rajabi, Saeed

2013-01-01

Background Due to its progressive nature in all aspects of life, addiction endangers the health of individuals, families and the society. Objectives The purpose of this study was to determine the role of self-regulation and affective control in predicting interpersonal reactivity of drug addicts. Materials and Methods This research is a correlation study. The statistical population of this study includes all drug addicts who were referred to addiction treatment centers of Ardabil in 2011 of whom 160 addicts were selected through convenience sampling. A self-regulation questionnaire, interpersonal reactivity questionnaire and affective control scale were used for data collection. Results Research results showed that self-regulation (r = -0.40) and affective control (r = -0.29) have a significant relationship with interpersonal reactivity of addicts (P < 0.001). The results of the multiple regression analysis indicated that 19 percent of interpersonal reactivity can be predicted by self-regulation and affective control. Conclusion These results suggest that self-regulation and affective control play an important role in exacerbating as well as reducing interpersonal reactivity of addicts. PMID:24971268

Model Predictive Control of the Current Profile and the Internal Energy of DIII-D Plasmas

NASA Astrophysics Data System (ADS)

Lauret, M.; Wehner, W.; Schuster, E.

2015-11-01

For efficient and stable operation of tokamak plasmas it is important that the current density profile and the internal energy are jointly controlled by using the available heating and current-drive (H&CD) sources. The proposed approach is a version of nonlinear model predictive control in which the input set is restricted in size by the possible combinations of the H&CD on/off states. The controller uses real-time predictions over a receding-time horizon of both the current density profile (nonlinear partial differential equation) and the internal energy (nonlinear ordinary differential equation) evolutions. At every time instant the effect of every possible combination of H&CD sources on the current profile and internal energy is evaluated over the chosen time horizon. The combination that leads to the best result, which is assessed by a user-defined cost function, is then applied up until the next time instant. Simulations results based on a control-oriented transport code illustrate the effectiveness of the proposed control method. Supported by the US DOE under DE-FC02-04ER54698 & DE-SC0010661.

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.

Data-Driven Nonlinear Subspace Modeling for Prediction and Control of Molten Iron Quality Indices in Blast Furnace Ironmaking

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhou, Ping; Song, Heda; Wang, Hong

Blast furnace (BF) in ironmaking is a nonlinear dynamic process with complicated physical-chemical reactions, where multi-phase and multi-field coupling and large time delay occur during its operation. In BF operation, the molten iron temperature (MIT) as well as Si, P and S contents of molten iron are the most essential molten iron quality (MIQ) indices, whose measurement, modeling and control have always been important issues in metallurgic engineering and automation field. This paper develops a novel data-driven nonlinear state space modeling for the prediction and control of multivariate MIQ indices by integrating hybrid modeling and control techniques. First, to improvemore » modeling efficiency, a data-driven hybrid method combining canonical correlation analysis and correlation analysis is proposed to identify the most influential controllable variables as the modeling inputs from multitudinous factors would affect the MIQ indices. Then, a Hammerstein model for the prediction of MIQ indices is established using the LS-SVM based nonlinear subspace identification method. Such a model is further simplified by using piecewise cubic Hermite interpolating polynomial method to fit the complex nonlinear kernel function. Compared to the original Hammerstein model, this simplified model can not only significantly reduce the computational complexity, but also has almost the same reliability and accuracy for a stable prediction of MIQ indices. Last, in order to verify the practicability of the developed model, it is applied in designing a genetic algorithm based nonlinear predictive controller for multivariate MIQ indices by directly taking the established model as a predictor. Industrial experiments show the advantages and effectiveness of the proposed approach.« less

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…

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…

The Role of Personality Factors in Predicting the Reported Physical Health Symptoms of Turkish College Students

ERIC Educational Resources Information Center

Ustundag-Budak, Meltem; Mocan-Aydin, Gul

2005-01-01

This study investigates the role of optimism, health control beliefs, perceived health competence, and medical help-seeking variables in predicting the frequency of reported physical symptoms. A total of 345 college students (207 male and 138 female) were presented with the Life Orientation Test, Multidimensional Health Locus of Control, Perceived…

Lexical Quality and Executive Control Predict Children's First and Second Language Reading Comprehension

ERIC Educational Resources Information Center

Raudszus, Henriette; Segers, Eliane; Verhoeven, Ludo

2018-01-01

This study compared how lexical quality (vocabulary and decoding) and executive control (working memory and inhibition) predict reading comprehension directly as well as indirectly, via syntactic integration, in monolingual and bilingual fourth grade children. The participants were 76 monolingual and 102 bilingual children (mean age 10 years,…

The Current Status of Unsteady CFD Approaches for Aerodynamic Flow Control

NASA Technical Reports Server (NTRS)

Carpenter, Mark H.; Singer, Bart A.; Yamaleev, Nail; Vatsa, Veer N.; Viken, Sally A.; Atkins, Harold L.

2002-01-01

An overview of the current status of time dependent algorithms is presented. Special attention is given to algorithms used to predict fluid actuator flows, as well as other active and passive flow control devices. Capabilities for the next decade are predicted, and principal impediments to the progress of time-dependent algorithms are identified.

Flight-determined aerodynamic derivatives of the AD-1 oblique-wing research airplane

NASA Technical Reports Server (NTRS)

Sim, A. G.; Curry, R. E.

1984-01-01

The AD-1 is a variable-sweep oblique-wing research airplane that exhibits unconventional stability and control characteristics. In this report, flight-determined and predicted stability and control derivatives for the AD-1 airplane are compared. The predictions are based on both wind tunnel and computational results. A final best estimate of derivatives is presented.

Evaluating the diagnostic utility of applying a machine learning algorithm to diffusion tensor MRI measures in individuals with major depressive disorder.

PubMed

Schnyer, David M; Clasen, Peter C; Gonzalez, Christopher; Beevers, Christopher G

2017-06-30

Using MRI to diagnose mental disorders has been a long-term goal. Despite this, the vast majority of prior neuroimaging work has been descriptive rather than predictive. The current study applies support vector machine (SVM) learning to MRI measures of brain white matter to classify adults with Major Depressive Disorder (MDD) and healthy controls. In a precisely matched group of individuals with MDD (n =25) and healthy controls (n =25), SVM learning accurately (74%) classified patients and controls across a brain map of white matter fractional anisotropy values (FA). The study revealed three main findings: 1) SVM applied to DTI derived FA maps can accurately classify MDD vs. healthy controls; 2) prediction is strongest when only right hemisphere white matter is examined; and 3) removing FA values from a region identified by univariate contrast as significantly different between MDD and healthy controls does not change the SVM accuracy. These results indicate that SVM learning applied to neuroimaging data can classify the presence versus absence of MDD and that predictive information is distributed across brain networks rather than being highly localized. Finally, MDD group differences revealed through typical univariate contrasts do not necessarily reveal patterns that provide accurate predictive information. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Individual differences in brainstem and basal ganglia structure predict postural control and balance loss in young and older adults.

PubMed

Boisgontier, Matthieu P; Cheval, Boris; Chalavi, Sima; van Ruitenbeek, Peter; Leunissen, Inge; Levin, Oron; Nieuwboer, Alice; Swinnen, Stephan P

2017-02-01

It remains unclear which specific brain regions are the most critical for human postural control and balance, and whether they mediate the effect of age. Here, associations between postural performance and corticosubcortical brain regions were examined in young and older adults using multiple structural imaging and linear mixed models. Results showed that of the regions involved in posture, the brainstem was the strongest predictor of postural control and balance: lower brainstem volume predicted larger center of pressure deviation and higher odds of balance loss. Analyses of white and gray matter in the brainstem showed that the pedunculopontine nucleus area appeared to be critical for postural control in both young and older adults. In addition, the brainstem mediated the effect of age on postural control, underscoring the brainstem's fundamental role in aging. Conversely, lower basal ganglia volume predicted better postural performance, suggesting an association between greater neural resources in the basal ganglia and greater movement vigor, resulting in exaggerated postural adjustments. Finally, results showed that practice, shorter height and heavier weight (i.e., higher body mass index), higher total physical activity, and larger ankle active (but not passive) range of motion were predictive of more stable posture, irrespective of age. Copyright © 2016 Elsevier Inc. All rights reserved.

Healthy work revisited: do changes in time strain predict well-being?

PubMed

Moen, Phyllis; Kelly, Erin L; Lam, Jack

2013-04-01

Building on Karasek and Theorell (R. Karasek & T. Theorell, 1990, Healthy work: Stress, productivity, and the reconstruction of working life, New York, NY: Basic Books), we theorized and tested the relationship between time strain (work-time demands and control) and seven self-reported health outcomes. We drew on survey data from 550 employees fielded before and 6 months after the implementation of an organizational intervention, the results only work environment (ROWE) in a white-collar organization. Cross-sectional (wave 1) models showed psychological time demands and time control measures were related to health outcomes in expected directions. The ROWE intervention did not predict changes in psychological time demands by wave 2, but did predict increased time control (a sense of time adequacy and schedule control). Statistical models revealed increases in psychological time demands and time adequacy predicted changes in positive (energy, mastery, psychological well-being, self-assessed health) and negative (emotional exhaustion, somatic symptoms, psychological distress) outcomes in expected directions, net of job and home demands and covariates. This study demonstrates the value of including time strain in investigations of the health effects of job conditions. Results encourage longitudinal models of change in psychological time demands as well as time control, along with the development and testing of interventions aimed at reducing time strain in different populations of workers.

Structured Kernel Subspace Learning for Autonomous Robot Navigation.

PubMed

Kim, Eunwoo; Choi, Sungjoon; Oh, Songhwai

2018-02-14

This paper considers two important problems for autonomous robot navigation in a dynamic environment, where the goal is to predict pedestrian motion and control a robot with the prediction for safe navigation. While there are several methods for predicting the motion of a pedestrian and controlling a robot to avoid incoming pedestrians, it is still difficult to safely navigate in a dynamic environment due to challenges, such as the varying quality and complexity of training data with unwanted noises. This paper addresses these challenges simultaneously by proposing a robust kernel subspace learning algorithm based on the recent advances in nuclear-norm and l 1 -norm minimization. We model the motion of a pedestrian and the robot controller using Gaussian processes. The proposed method efficiently approximates a kernel matrix used in Gaussian process regression by learning low-rank structured matrix (with symmetric positive semi-definiteness) to find an orthogonal basis, which eliminates the effects of erroneous and inconsistent data. Based on structured kernel subspace learning, we propose a robust motion model and motion controller for safe navigation in dynamic environments. We evaluate the proposed robust kernel learning in various tasks, including regression, motion prediction, and motion control problems, and demonstrate that the proposed learning-based systems are robust against outliers and outperform existing regression and navigation methods.

Likelihood of achieving air quality targets under model uncertainties.

PubMed

Digar, Antara; Cohan, Daniel S; Cox, Dennis D; Kim, Byeong-Uk; Boylan, James W

2011-01-01

Regulatory attainment demonstrations in the United States typically apply a bright-line test to predict whether a control strategy is sufficient to attain an air quality standard. Photochemical models are the best tools available to project future pollutant levels and are a critical part of regulatory attainment demonstrations. However, because photochemical models are uncertain and future meteorology is unknowable, future pollutant levels cannot be predicted perfectly and attainment cannot be guaranteed. This paper introduces a computationally efficient methodology for estimating the likelihood that an emission control strategy will achieve an air quality objective in light of uncertainties in photochemical model input parameters (e.g., uncertain emission and reaction rates, deposition velocities, and boundary conditions). The method incorporates Monte Carlo simulations of a reduced form model representing pollutant-precursor response under parametric uncertainty to probabilistically predict the improvement in air quality due to emission control. The method is applied to recent 8-h ozone attainment modeling for Atlanta, Georgia, to assess the likelihood that additional controls would achieve fixed (well-defined) or flexible (due to meteorological variability and uncertain emission trends) targets of air pollution reduction. The results show that in certain instances ranking of the predicted effectiveness of control strategies may differ between probabilistic and deterministic analyses.

Maintenance of equilibrium point control during an unexpectedly loaded rapid limb movement.

PubMed

Simmons, R W; Richardson, C

1984-06-08

Two experiments investigated whether the equilibrium point hypothesis or the mass-spring model of motor control subserves positioning accuracy during spring loaded, rapid, bi-articulated movement. For intact preparations, the equilibrium point hypothesis predicts response accuracy to be determined by a mixture of afferent and efferent information, whereas the mass-spring model predicts positioning to be under a direct control system. Subjects completed a series of load-resisted training trials to a spatial target. The magnitude of a sustained spring load was unexpectedly increased on selected trials. Results indicated positioning accuracy and applied force varied with increases in load, which suggests that the original efferent commands are modified by afferent information during the movement as predicted by the equilibrium point hypothesis.

Preliminary analysis of STS-2 entry flight data

NASA Technical Reports Server (NTRS)

1982-01-01

A preliminary analysis of the data obtained during the entry of the STS-2 flight was completed. The stability and control derivatives from STS-2 were examined. Questions still remain throughout the flight envelope and the area below Mach 3 needs more study. With three controls operating in a high gain feedback system, it is difficult to separate the individual effects of each of the controls. Analysis of the aerothermal data shows that wing structural-temperature measurements are generally repeatable and consistent with the trajectories. The measured wing upper surface temperatures are in reasonable agreement with Dryden predictions but wing lower surface temperatures are higher than Dryden predictions. Heating and heat transfer models will be adjusted to improve the temperature prediction capability for future trajectories.

A Multiple Agent Model of Human Performance in Automated Air Traffic Control and Flight Management Operations

NASA Technical Reports Server (NTRS)

Corker, Kevin; Pisanich, Gregory; Condon, Gregory W. (Technical Monitor)

1995-01-01

A predictive model of human operator performance (flight crew and air traffic control (ATC)) has been developed and applied in order to evaluate the impact of automation developments in flight management and air traffic control. The model is used to predict the performance of a two person flight crew and the ATC operators generating and responding to clearances aided by the Center TRACON Automation System (CTAS). The purpose of the modeling is to support evaluation and design of automated aids for flight management and airspace management and to predict required changes in procedure both air and ground in response to advancing automation in both domains. Additional information is contained in the original extended abstract.

Water hammer prediction and control: the Green's function method

NASA Astrophysics Data System (ADS)

Xuan, Li-Jun; Mao, Feng; Wu, Jie-Zhi

2012-04-01

By Green's function method we show that the water hammer (WH) can be analytically predicted for both laminar and turbulent flows (for the latter, with an eddy viscosity depending solely on the space coordinates), and thus its hazardous effect can be rationally controlled and minimized. To this end, we generalize a laminar water hammer equation of Wang et al. (J. Hydrodynamics, B2, 51, 1995) to include arbitrary initial condition and variable viscosity, and obtain its solution by Green's function method. The predicted characteristic WH behaviors by the solutions are in excellent agreement with both direct numerical simulation of the original governing equations and, by adjusting the eddy viscosity coefficient, experimentally measured turbulent flow data. Optimal WH control principle is thereby constructed and demonstrated.

Relationship of perceived stress with depression: complete mediation by perceived control and anxiety in Iran and the United States.

PubMed

Ghorbani, Nima; Krauss, Stephen W; Watson, P J; Lebreton, Daniel

2008-12-01

This study sought to clarify the importance and cross-cultural relevance of associations between generalized perceived stress and depression. Also tested was the hypothesis that perceived stress would correlate more strongly with anxiety than with depression, whereas control would be more predictive of depression than of anxiety. Relationships between perceived stress, anxiety, depression, and perceived control were examined in samples of Iranian (n = 191) and American (n = 197) undergraduates. Correlations among these variables were generally similar across the two societies. Perceived stress did predict anxiety better than depression, but perceptions of control predicted depression significantly better than anxiety only in the United States. Best fitting structural equation models revealed that anxiety and perceived control completely accounted for the linkage between perceived stress and depression in both societies. An equally acceptable and more parsimonious model described perceived stress as a consequence rather than as an antecedent of anxiety and perceived control. Structural equation models were essentially identical across the two cultures except that internal control displayed a significant negative relationship with anxiety only in Iran. This result seemed to disconfirm any possible suggestion that a supposedly individualistic process like internal control could have no noteworthy role within a presumably more collectivistic Muslim society like Iran. Overall, these data documented the importance of anxiety and perceived control in explaining the perceived stress-depression relationship cross-culturally and therefore questioned the usefulness of perceived stress in predicting depression. Whether this understanding of the stress-depression relationship deserves general acceptance will require additional studies that measure the frequency of stressful life events and that utilize a longitudinal design.

Rational metareasoning and the plasticity of cognitive control.

PubMed

Lieder, Falk; Shenhav, Amitai; Musslick, Sebastian; Griffiths, Thomas L

2018-04-01

The human brain has the impressive capacity to adapt how it processes information to high-level goals. While it is known that these cognitive control skills are malleable and can be improved through training, the underlying plasticity mechanisms are not well understood. Here, we develop and evaluate a model of how people learn when to exert cognitive control, which controlled process to use, and how much effort to exert. We derive this model from a general theory according to which the function of cognitive control is to select and configure neural pathways so as to make optimal use of finite time and limited computational resources. The central idea of our Learned Value of Control model is that people use reinforcement learning to predict the value of candidate control signals of different types and intensities based on stimulus features. This model correctly predicts the learning and transfer effects underlying the adaptive control-demanding behavior observed in an experiment on visual attention and four experiments on interference control in Stroop and Flanker paradigms. Moreover, our model explained these findings significantly better than an associative learning model and a Win-Stay Lose-Shift model. Our findings elucidate how learning and experience might shape people's ability and propensity to adaptively control their minds and behavior. We conclude by predicting under which circumstances these learning mechanisms might lead to self-control failure.

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.

Rational metareasoning and the plasticity of cognitive control

PubMed Central

Shenhav, Amitai; Musslick, Sebastian; Griffiths, Thomas L.

2018-01-01

The human brain has the impressive capacity to adapt how it processes information to high-level goals. While it is known that these cognitive control skills are malleable and can be improved through training, the underlying plasticity mechanisms are not well understood. Here, we develop and evaluate a model of how people learn when to exert cognitive control, which controlled process to use, and how much effort to exert. We derive this model from a general theory according to which the function of cognitive control is to select and configure neural pathways so as to make optimal use of finite time and limited computational resources. The central idea of our Learned Value of Control model is that people use reinforcement learning to predict the value of candidate control signals of different types and intensities based on stimulus features. This model correctly predicts the learning and transfer effects underlying the adaptive control-demanding behavior observed in an experiment on visual attention and four experiments on interference control in Stroop and Flanker paradigms. Moreover, our model explained these findings significantly better than an associative learning model and a Win-Stay Lose-Shift model. Our findings elucidate how learning and experience might shape people’s ability and propensity to adaptively control their minds and behavior. We conclude by predicting under which circumstances these learning mechanisms might lead to self-control failure. PMID:29694347

Anticipatory control through associative learning of subliminal relations: invisible may be better than visible.

PubMed

Farooqui, Ausaf A; Manly, Tom

2015-03-01

We showed that anticipatory cognitive control could be unconsciously instantiated through subliminal cues that predicted enhanced future control needs. In task-switching experiments, one of three subliminal cues preceded each trial. Participants had no conscious experience or knowledge of these cues, but their performance was significantly improved on switch trials after cues that predicted task switches (but not particular tasks). This utilization of subliminal information was flexible and adapted to a change in cues predicting task switches and occurred only when switch trials were difficult and effortful. When cues were consciously visible, participants were unable to discern their relevance and could not use them to enhance switch performance. Our results show that unconscious cognition can implicitly use subliminal information in a goal-directed manner for anticipatory control, and they also suggest that subliminal representations may be more conducive to certain forms of associative learning. © The Author(s) 2015.

Independence and Interdependence Predict Health and Wellbeing: Divergent Patterns in the United States and Japan

PubMed Central

Kitayama, Shinobu; Karasawa, Mayumi; Curhan, Katherine B.; Ryff, Carol D.; Markus, Hazel Rose

2010-01-01

A cross-cultural survey was used to examine two hypotheses designed to link culture to wellbeing and health. The first hypothesis states that people are motivated toward prevalent cultural mandates of either independence (personal control) in the United States or interdependence (relational harmony) in Japan. As predicted, Americans with compromised personal control and Japanese with strained relationships reported high perceived constraint. The second hypothesis holds that people achieve wellbeing and health through actualizing the respective cultural mandates in their modes of being. As predicted, the strongest predictor of wellbeing and health was personal control in the United States, but the absence of relational strain in Japan. All analyses controlled for age, gender, educational attainment, and personality traits. The overall pattern of findings underscores culturally distinct pathways (independent versus interdependent) in achieving the positive life outcomes. PMID:21833228

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.

Efficient operation scheduling for adsorption chillers using predictive optimization-based control methods

NASA Astrophysics Data System (ADS)

Bürger, Adrian; Sawant, Parantapa; Bohlayer, Markus; Altmann-Dieses, Angelika; Braun, Marco; Diehl, Moritz

2017-10-01

Within this work, the benefits of using predictive control methods for the operation of Adsorption Cooling Machines (ACMs) are shown on a simulation study. Since the internal control decisions of series-manufactured ACMs often cannot be influenced, the work focuses on optimized scheduling of an ACM considering its internal functioning as well as forecasts for load and driving energy occurrence. For illustration, an assumed solar thermal climate system is introduced and a system model suitable for use within gradient-based optimization methods is developed. The results of a system simulation using a conventional scheme for ACM scheduling are compared to the results of a predictive, optimization-based scheduling approach for the same exemplary scenario of load and driving energy occurrence. The benefits of the latter approach are shown and future actions for application of these methods for system control are addressed.

Unhealthy weight control behaviours in adolescent girls: a process model based on self-determination theory.

PubMed

Thøgersen-Ntoumani, Cecilie; Ntoumanis, Nikos; Nikitaras, Nikitas

2010-06-01

This study used self-determination theory (Deci, E.L., & Ryan, R.M. (2000). The 'what' and 'why' of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11, 227-268.) to examine predictors of body image concerns and unhealthy weight control behaviours in a sample of 350 Greek adolescent girls. A process model was tested which proposed that perceptions of parental autonomy support and two life goals (health and image) would predict adolescents' degree of satisfaction of their basic psychological needs. In turn, psychological need satisfaction was hypothesised to negatively predict body image concerns (i.e. drive for thinness and body dissatisfaction) and, indirectly, unhealthy weight control behaviours. The predictions of the model were largely supported indicating that parental autonomy support and adaptive life goals can indirectly impact upon the extent to which female adolescents engage in unhealthy weight control behaviours via facilitating the latter's psychological need satisfaction.

Automatic Train Operation Using Autonomic Prediction of Train Runs

NASA Astrophysics Data System (ADS)

Asuka, Masashi; Kataoka, Kenji; Komaya, Kiyotoshi; Nishida, Syogo

In this paper, we present an automatic train control method adaptable to disturbed train traffic conditions. The proposed method presumes transmission of detected time of a home track clearance to trains approaching to the station by employing equipment of Digital ATC (Automatic Train Control). Using the information, each train controls its acceleration by the method that consists of two approaches. First, by setting a designated restricted speed, the train controls its running time to arrive at the next station in accordance with predicted delay. Second, the train predicts the time at which it will reach the current braking pattern generated by Digital ATC, along with the time when the braking pattern transits ahead. By comparing them, the train correctly chooses the coasting drive mode in advance to avoid deceleration due to the current braking pattern. We evaluated the effectiveness of the proposed method regarding driving conditions, energy consumption and reduction of delays by simulation.

Predictive Management of Asian Carps in the Upper Mississippi River System

USGS Publications Warehouse

Vondracek, Bruce C.; Carlson, Andrew K.

2014-01-01

Prolific non-native organisms pose serious threats to ecosystems and economies worldwide. Nonnative bighead carp (Hypophthalmichthys nobilis) and silver carp (H. molitrix), collectively referred to as Asian carps, continue to colonize aquatic ecosystems throughout the central United States. These species are r-selected, exhibiting iteroparous spawning, rapid growth, broad environmental tolerance, high density, and long-distance movement. Hydrological, thermal, and physicochemical conditions are favorable for establishment beyond the current range, rendering containment and control imperative. Ecological approaches to confine Asian carp populations and prevent colonization characterize contemporary management in the United States. Foraging and reproduction of Asian carps govern habitat selection and movement, providing valuable insight for predictive control. Current management approaches are progressive and often anticipatory but deficient in human dimensions. We define predictive management of Asian carps as synthesis of ecology and human dimensions at regional and local scales to develop strategies for containment and control. We illustrate predictive management in the Upper Mississippi River System and suggest resource managers integrate predictive models, containment paradigms, and human dimensions to design effective, socially acceptable management strategies. Through continued research, university-agency collaboration, and public engagement, predictive management of Asian carps is an auspicious paradigm for preventing and alleviating consequences of colonization in the United States.

Temperature control in a solar collector field using Filtered Dynamic Matrix Control.

PubMed

Lima, Daniel Martins; Normey-Rico, Julio Elias; Santos, Tito Luís Maia

2016-05-01

This paper presents the output temperature control of a solar collector field of a desalinization plant using the Filtered Dynamic Matrix Control (FDMC). The FDMC is a modified controller based on the Dynamic Matrix Control (DMC), a predictive control strategy widely used in industry. In the FDMC, a filter is used in the prediction error, which allows the modification of the robustness and disturbance rejection characteristics of the original algorithm. The implementation and tuning of the FDMC are simple and maintain the advantages of DMC. Several simulation results using a validated model of the solar plant are presented considering different scenarios. The results are also compared to nonlinear control techniques, showing that FDMC, if properly tuned, can yield similar results to more complex control algorithms. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Predicting plantar fasciitis in runners.

PubMed

Warren, B L; Jones, C J

1987-02-01

Ninety-one runners were studied to determine whether specific variables were indicative of runners who had suffered with plantar fasciitis either presently or formerly vs runners who had never suffered with plantar fasciitis. Each runner was asked to complete a running history, was subjected to several anatomical measurements, and was asked to run on a treadmill in both a barefoot and shoe condition at a speed of 3.35 mps (8 min mile pace). Factor coefficients were used in a discriminant function analysis which revealed that, when group membership was predicted, 63% of the runners could be correctly assigned to their group. Considering that 76% of the control group was correctly predicted, it was concluded that the predictor variables were able to correctly predict membership of the control group, but not able to correctly predict the presently or formerly injured sufferers of plantar fasciitis.

Model predictive control of an air suspension system with damping multi-mode switching damper based on hybrid model

NASA Astrophysics Data System (ADS)

Sun, Xiaoqiang; Yuan, Chaochun; Cai, Yingfeng; Wang, Shaohua; Chen, Long

2017-09-01

This paper presents the hybrid modeling and the model predictive control of an air suspension system with damping multi-mode switching damper. Unlike traditional damper with continuously adjustable damping, in this study, a new damper with four discrete damping modes is applied to vehicle semi-active air suspension. The new damper can achieve different damping modes by just controlling the on-off statuses of two solenoid valves, which makes its damping adjustment more efficient and more reliable. However, since the damping mode switching induces different modes of operation, the air suspension system with the new damper poses challenging hybrid control problem. To model both the continuous/discrete dynamics and the switching between different damping modes, the framework of mixed logical dynamical (MLD) systems is used to establish the system hybrid model. Based on the resulting hybrid dynamical model, the system control problem is recast as a model predictive control (MPC) problem, which allows us to optimize the switching sequences of the damping modes by taking into account the suspension performance requirements. Numerical simulations results demonstrate the efficacy of the proposed control method finally.

Optimal Control of Distributed Energy Resources using Model Predictive Control

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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, minimizingmore » 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.« less

Reducing usage of the computational resources by event driven approach to model predictive control

NASA Astrophysics Data System (ADS)

Misik, Stefan; Bradac, Zdenek; Cela, Arben

2017-08-01

This paper deals with a real-time and optimal control of dynamic systems while also considers the constraints which these systems might be subject to. Main objective of this work is to propose a simple modification of the existing Model Predictive Control approach to better suit needs of computational resource-constrained real-time systems. An example using model of a mechanical system is presented and the performance of the proposed method is evaluated in a simulated environment.

Growth in perceived control across 25 years from the late teens to midlife: the role of personal and parents' education.

PubMed

Vargas Lascano, Dayuma I; Galambos, Nancy L; Krahn, Harvey J; Lachman, Margie E

2015-01-01

This study examined trajectories of perceived control and their association with parents' education and personal educational experience (educational attainment and years of full-time postsecondary education) in 971 Canadian high school seniors tracked 7 times across 25 years. Latent growth models showed that, on average, perceived control increased from age 18 to age 25 and decreased by age 32, with a further slower decrease by age 43. Parents' education contributed to a growing gap in perceived control, however, such that among individuals with at least 1 university-educated parent, perceived control increased across 25 years, reaching its highest level at age 43. Personal educational attainment (completion of a university degree or not) was not associated with growth in perceived control, but individuals who were higher on perceived control at age 18 were more likely to complete a university degree. Parallel process modeling found that perceived control at age 19 predicted gains through age 32 in years of postsecondary education. Postsecondary enrollment at age 19 did not predict gains in perceived control over time. Parents' education predicted both higher levels of perceived control and enrollment in full-time postsecondary education at age 19. Family socioeconomic status contributes to perceived control early in the transition to adulthood and may lead to diverging trajectories over the next 25 years, and perceived control contributes to subsequent postsecondary educational experience. Further longitudinal research should explore the development and determinants of perceived control across the full life span.

Intelligent monitoring and control of semiconductor manufacturing equipment

NASA Technical Reports Server (NTRS)

Murdock, Janet L.; Hayes-Roth, Barbara

1991-01-01

The use of AI methods to monitor and control semiconductor fabrication in a state-of-the-art manufacturing environment called the Rapid Thermal Multiprocessor is described. Semiconductor fabrication involves many complex processing steps with limited opportunities to measure process and product properties. By applying additional process and product knowledge to that limited data, AI methods augment classical control methods by detecting abnormalities and trends, predicting failures, diagnosing, planning corrective action sequences, explaining diagnoses or predictions, and reacting to anomalous conditions that classical control systems typically would not correct. Research methodology and issues are discussed, and two diagnosis scenarios are examined.

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.

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.

Neural network feedforward control of a closed-circuit wind tunnel

NASA Astrophysics Data System (ADS)

Sutcliffe, Peter

Accurate control of wind-tunnel test conditions can be dramatically enhanced using feedforward control architectures which allow operating conditions to be maintained at a desired setpoint through the use of mathematical models as the primary source of prediction. However, as the desired accuracy of the feedforward prediction increases, the model complexity also increases, so that an ever increasing computational load is incurred. This drawback can be avoided by employing a neural network that is trained offline using the output of a high fidelity wind-tunnel mathematical model, so that the neural network can rapidly reproduce the predictions of the model with a greatly reduced computational overhead. A novel neural network database generation method, developed through the use of fractional factorial arrays, was employed such that a neural network can accurately predict wind-tunnel parameters across a wide range of operating conditions whilst trained upon a highly efficient database. The subsequent network was incorporated into a Neural Network Model Predictive Control (NNMPC) framework to allow an optimised output schedule capable of providing accurate control of the wind-tunnel operating parameters. Facilitation of an optimised path through the solution space is achieved through the use of a chaos optimisation algorithm such that a more globally optimum solution is likely to be found with less computational expense than the gradient descent method. The parameters associated with the NNMPC such as the control horizon are determined through the use of a Taguchi methodology enabling the minimum number of experiments to be carried out to determine the optimal combination. The resultant NNMPC scheme was employed upon the Hessert Low Speed Wind Tunnel at the University of Notre Dame to control the test-section temperature such that it follows a pre-determined reference trajectory during changes in the test-section velocity. Experimental testing revealed that the derived NNMPC controller provided an excellent level of control over the test-section temperature in adherence to a reference trajectory even when faced with unforeseen disturbances such as rapid changes in the operating environment.

Which Neuropsychological Tests Predict Progression to Alzheimer’s Disease in Hispanics?

PubMed Central

Weissberger, Gali H.; Salmon, David P.; Bondi, Mark W.; Gollan, Tamar H.

2013-01-01

Objective To investigate which neuropsychological tests predict eventual progression to Alzheimer’s disease (AD) in both Hispanic and non-Hispanic individuals. Although our approach was exploratory, we predicted that tests that underestimate cognitive ability in healthy aging Hispanics might not be sensitive to future cognitive decline in this cultural group. Method We compared first-year data of 22 older adults (11 Hispanic) who were diagnosed as cognitively normal but eventually developed AD (decliners), to 60 age- and education-matched controls (27 Hispanic) who remained cognitively normal. To identify tests that may be culturally biased in our sample, we compared Hispanic with non-Hispanic controls on all tests and asked which tests were sensitive to future decline in each cultural group. Results Compared to age-, education-, and gender-matched non-Hispanic controls, Hispanic controls obtained lower scores on tests of language, executive function, and some measures of global cognition. Consistent with our predictions, some tests identified non-Hispanic, but not Hispanic, decliners (vocabulary, semantic fluency). Contrary to our predictions, a number of tests on which Hispanics obtained lower scores than non-Hispanics nevertheless predicted eventual progression to AD in both cultural groups (e.g., Boston Naming Test [BNT], Trails A and B). Conclusions Cross-cultural variation in test sensitivity to decline may reflect greater resistance of medium difficulty items to decline and bilingual advantages that initially protect Hispanics against some aspects of cognitive decline commonly observed in non-Hispanics with preclinical AD. These findings highlight a need for further consideration of cross-cultural differences in neuropsychological test performance and development of culturally unbiased measures. PMID:23688216

Ring-enhancement pattern on contrast-enhanced CT predicts adenosquamous carcinoma of the pancreas: a matched case-control study.

PubMed

Imaoka, Hiroshi; Shimizu, Yasuhiro; Mizuno, Nobumasa; Hara, Kazuo; Hijioka, Susumu; Tajika, Masahiro; Tanaka, Tsutomu; Ishihara, Makoto; Ogura, Takeshi; Obayashi, Tomohiko; Shinagawa, Akihide; Sakaguchi, Masafumi; Yamaura, Hidekazu; Kato, Mina; Niwa, Yasumasa; Yamao, Kenji

2014-01-01

Adenosquamous carcinoma of the pancreas (ASC) is a rare malignant neoplasm of the pancreas, exhibiting both glandular and squamous differentiation. However, little is known about its imaging features. This study examined the imaging features of pancreatic ASC. We evaluated images of contrast-enhanced computed tomography (CT) and endoscopic ultrasonography (EUS). As controls, solid pancreatic neoplasms matched in a 2:1 ratio to ASC cases for age, sex and tumor location were also evaluated. Twenty-three ASC cases were examined, and 46 solid pancreatic neoplasms (43 pancreatic ductal adenocarcinomas, two pancreatic neuroendocrine tumors and one acinar cell carcinoma) were matched as controls. Univariate analysis demonstrated significant differences in the outline and vascularity of tumors on contrast-enhanced CT in the ASC and control groups (P < 0.001 and P < 0.001, respectively). A smooth outline, cystic changes, and the ring-enhancement pattern on contrast-enhanced CT were seen to have significant predictive powers by stepwise forward logistic regression analysis (P = 0.044, P = 0.010, and P = 0.001, respectively). Of the three, the ring-enhancement pattern was the most useful, and its predictive diagnostic sensitivity, specificity, positive predictive value and negative predictive value for diagnosis of ASC were 65.2%, 89.6%, 75.0% and 84.3%, respectively. These results demonstrate that presence of the ring-enhancement pattern on contrast-enhanced CT is the most useful predictive factor for ASC. Copyright © 2014 IAP and EPC. Published by Elsevier B.V. All rights reserved.

Post-Stall Aerodynamic Modeling and Gain-Scheduled Control Design

NASA Technical Reports Server (NTRS)

Wu, Fen; Gopalarathnam, Ashok; Kim, Sungwan

2005-01-01

A multidisciplinary research e.ort that combines aerodynamic modeling and gain-scheduled control design for aircraft flight at post-stall conditions is described. The aerodynamic modeling uses a decambering approach for rapid prediction of post-stall aerodynamic characteristics of multiple-wing con.gurations using known section data. The approach is successful in bringing to light multiple solutions at post-stall angles of attack right during the iteration process. The predictions agree fairly well with experimental results from wind tunnel tests. The control research was focused on actuator saturation and .ight transition between low and high angles of attack regions for near- and post-stall aircraft using advanced LPV control techniques. The new control approaches maintain adequate control capability to handle high angle of attack aircraft control with stability and performance guarantee.

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.

Low trait self-control predicts self-handicapping.

PubMed

Uysal, Ahmet; Knee, C Raymond

2012-02-01

Past research has shown that self-handicapping stems from uncertainty about one's ability and self-presentational concerns. The present studies suggest that low dispositional self-control is also associated with self-handicapping. In 3 studies (N = 289), the association between self-control and self-handicapping was tested. Self-control was operationalized as trait self-control, whereas self-handicapping was operationalized as trait self-handicapping in Study 1 (N = 160), self-reported self-handicapping in Study 2 (N = 74), and behavioral self-handicapping in Study 3 (N = 55). In all 3 studies, hierarchical regression analyses revealed that low self-control predicts self-handicapping, independent of self-esteem, self-doubt, social desirability, and gender. © 2012 The Authors. Journal of Personality © 2012, Wiley Periodicals, Inc.

Gender differences in motor skill proficiency from childhood to adolescence: a longitudinal study.

PubMed

Barnett, Lisa M; van Beurden, Eric; Morgan, Philip J; Brooks, Lyndon O; Beard, John R

2010-06-01

Students' proficiency in three object control and three locomotor skills were assessed in 2000 (M age = 10.06 years, SD = 0.63) in New South Wales, Australia and in 2006-07 (M age = 16.44 years, SD = 0.64). In 2006-07, 266 students, 138 girls (51.9%) and 128 boys (48.1%), had at least one skill reassessed. Boys were more object control proficient than girls. Childhood object control proficiency significantly predicted (p = .001) adolescent object control proficiency (r2 = .39), and, while gender was significant (p = .001), it did not affect the relationship between these variables (p = .53). Because childhood object control proficiency is predictive of subsequent object control proficiency, developing skills in childhood is important.

Drinking and Parenting Practices as Predictors of Impaired Driving Behaviors Among U.S. Adolescents

PubMed Central

Li, Kaigang; Simons-Morton, Bruce G; Brooks-Russell, Ashley; Ehsani, Johnathon; Hingson, Ralph

2014-01-01

Objective: The purpose of this study was to identify the extent to which 10th-grade substance use and parenting practices predicted 11th-grade teenage driving while alcohol-/other drug–impaired (DWI) and riding with alcohol-/other drug–impaired drivers (RWI). Method: The data were from Waves 1 and 2 of the NEXT Generation study, with longitudinal assessment of a nationally representative sample of 10th graders starting in 2009–2010. Multivariate logistic regression analysis was used to examine the prospective associations between proposed predictors (heavy episodic drinking, illicit drug use, parental monitoring knowledge and control) in Wave 1 and DWI/RWI. Results: Heavy episodic drinking at Wave 1 predicted Wave 2 DWI (odds ratio [OR] = 3.73, p < .001) and RWI (OR = 3.92, p < .001) after controlling for parenting practices and selected covariates. Father’s monitoring knowledge predicted lower DWI prevalence at Wave 2 when controlling for covariates and teenage substance use (OR = 0.66, p < .001). In contrast, mother’s monitoring knowledge predicted lower RWI prevalence at Wave 2 when controlling for covariates only (OR = 0.67, p < .05), but the effect was reduced to nonsignificance when controlling for teen substance use. Conclusions: Heavy episodic drinking predicted DWI and RWI. In addition, parental monitoring knowledge, particularly by fathers, was protective against DWI, independent of the effect of substance use. This suggests that the enhancement of parenting practices could potentially discourage adolescent DWI. The findings suggest that the parenting practices of fathers and mothers may have differential effects on adolescent impaired-driving behaviors. PMID:24411792

Drinking and parenting practices as predictors of impaired driving behaviors among U.S. adolescents.

PubMed

Li, Kaigang; Simons-Morton, Bruce G; Brooks-Russell, Ashley; Ehsani, Johnathon; Hingson, Ralph

2014-01-01

The purpose of this study was to identify the extent to which 10th-grade substance use and parenting practices predicted 11th-grade teenage driving while alcohol-/other drug-impaired (DWI) and riding with alcohol-/other drug-impaired drivers (RWI). The data were from Waves 1 and 2 of the NEXT Generation study, with longitudinal assessment of a nationally representative sample of 10th graders starting in 2009-2010. Multivariate logistic regression analysis was used to examine the prospective associations between proposed predictors (heavy episodic drinking, illicit drug use, parental monitoring knowledge and control) in Wave 1 and DWI/RWI. Heavy episodic drinking at Wave 1 predicted Wave 2 DWI (odds ratio [OR] = 3.73, p < .001) and RWI (OR = 3.92, p < .001) after controlling for parenting practices and selected covariates. Father's monitoring knowledge predicted lower DWI prevalence at Wave 2 when controlling for covariates and teenage substance use (OR = 0.66, p < .001). In contrast, mother's monitoring knowledge predicted lower RWI prevalence at Wave 2 when controlling for covariates only (OR = 0.67, p < .05), but the effect was reduced to nonsignificance when controlling for teen substance use. Heavy episodic drinking predicted DWI and RWI. In addition, parental monitoring knowledge, particularly by fathers, was protective against DWI, independent of the effect of substance use. This suggests that the enhancement of parenting practices could potentially discourage adolescent DWI. The findings suggest that the parenting practices of fathers and mothers may have differential effects on adolescent impaired-driving behaviors.

Prediction of placebo responses: a systematic review of the literature

PubMed Central

Horing, Bjoern; Weimer, Katja; Muth, Eric R.; Enck, Paul

2014-01-01

Objective: Predicting who responds to placebo treatment—and under which circumstances—has been a question of interest and investigation for generations. However, the literature is disparate and inconclusive. This review aims to identify publications that provide high quality data on the topic of placebo response (PR) prediction. Methods: To identify studies concerned with PR prediction, independent searches were performed in an expert database (for all symptom modalities) and in PubMed (for pain only). Articles were selected when (a) they assessed putative predictors prior to placebo treatment and (b) an adequate control group was included when the associations of predictors and PRs were analyzed. Results: Twenty studies were identified, most with pain as dependent variable. Most predictors of PRs were psychological constructs related to actions, expected outcomes and the emotional valence attached to these events (goal-seeking, self-efficacy/-esteem, locus of control, optimism). Other predictors involved behavioral control (desire for control, eating restraint), personality variables (fun seeking, sensation seeking, neuroticism), or biological markers (sex, a single nucleotide polymorphism related to dopamine metabolism). Finally, suggestibility and beliefs in expectation biases, body consciousness, and baseline symptom severity were found to be predictive. Conclusions: While results are heterogeneous, some congruence of predictors can be identified. PRs mainly appear to be moderated by expectations of how the symptom might change after treatment, or expectations of how symptom repetition can be coped with. It is suggested to include the listed constructs in future research. Furthermore, a closer look at variables moderating symptom change in control groups seems warranted. PMID:25324797

Predictive value of hippocampal MR imaging-based high-dimensional mapping in mesial temporal epilepsy: preliminary findings.

PubMed

Hogan, R E; Wang, L; Bertrand, M E; Willmore, L J; Bucholz, R D; Nassif, A S; Csernansky, J G

2006-01-01

We objectively assessed surface structural changes of the hippocampus in mesial temporal sclerosis (MTS) and assessed the ability of large-deformation high-dimensional mapping (HDM-LD) to demonstrate hippocampal surface symmetry and predict group classification of MTS in right and left MTS groups compared with control subjects. Using eigenvector field analysis of HDM-LD segmentations of the hippocampus, we compared the symmetry of changes in the right and left MTS groups with a group of 15 matched controls. To assess the ability of HDM-LD to predict group classification, eigenvectors were selected by a logistic regression procedure when comparing the MTS group with control subjects. Multivariate analysis of variance on the coefficients from the first 9 eigenvectors accounted for 75% of the total variance between groups. The first 3 eigenvectors showed the largest differences between the control group and each of the MTS groups, but with eigenvector 2 showing the greatest difference in the MTS groups. Reconstruction of the hippocampal deformation vector fields due solely to eigenvector 2 shows symmetrical patterns in the right and left MTS groups. A "leave-one-out" (jackknife) procedure correctly predicted group classification in 14 of 15 (93.3%) left MTS subjects and all 15 right MTS subjects. Analysis of principal dimensions of hippocampal shape change suggests that MTS, after accounting for normal right-left asymmetries, affects the right and left hippocampal surface structure very symmetrically. Preliminary analysis using HDM-LD shows it can predict group classification of MTS and control hippocampi in this well-defined population of patients with MTS and mesial temporal lobe epilepsy (MTLE).

Reactive but not predictive locomotor adaptability is impaired in young Parkinson's disease patients.

PubMed

Moreno Catalá, María; Woitalla, Dirk; Arampatzis, Adamantios

2016-07-01

Gait and balance disorders are common in Parkinson's disease (PD) and major contributors to increased falling risk. Predictive and reactive adjustments can improve recovery performance after gait perturbations. However, these mechanisms have not been investigated in young-onset PD. We aimed to investigate the effect of gait perturbations on dynamic stability control as well as predictive and reactive adaptability to repeated gait perturbations in young PD patients. Fifteen healthy controls and twenty-five young patients (48±5yrs.) walked on a walkway. By means of a covered exchangeable element, the floor surface condition was altered to induce gait perturbations. The experimental protocol included a baseline on a hard surface, an unexpected trial on a soft surface and an adaptation phase with 5 soft trials to quantify the reactive adaptation. After the first and sixth soft trials, the surface was changed to hard, to examine after-effects and, thus, predictive motor control. Dynamic stability was assessed using the 'extrapolated center of mass' concept. Patients' unperturbed walking was less stable than controls' and this persisted in the perturbed trials. Both groups demonstrated after-effects directly after the first perturbation, showing similar predictive responses. However, PD patients did not improve their reactive behavior after repeated perturbations while controls showed clear locomotor adaptation. Our data suggest that more unstable gait patterns and a less effective reactive adaptation to perturbed walking may be a disease-related characteristic in young PD patients. These deficits were related to reduced ability to increase the base of support. Copyright © 2016 Elsevier B.V. All rights reserved.

The moderating effect of gender on the relationship between coping and suicide risk in a Portuguese community sample of adults.

PubMed

Campos, Rui C; Holden, Ronald R; Costa, Fátima; Oliveira, Ana Rita; Abreu, Marta; Fresca, Natália

2017-02-01

Background and aims(s): The study evaluated the contribution of coping strategies, based on the Toulousiane conceptualization of coping, to the prediction of suicide risk and tested the moderating effect of gender, controlling for depressive symptoms. A two-time data collection design was used. A community sample of 195 adults (91 men and 104 women) ranging in age from 19 to 65 years and living in several Portuguese regions, mostly in Alentejo, participated in this research. Gender, depressive symptoms, control, and withdrawal and conversion significantly predicted suicide risk and gender interacted with control, withdrawal and conversion, and social distraction in the prediction of suicide risk. Coping predicted suicide risk only for women. Results have important implications for assessment and intervention with suicide at-risk individuals. In particular,the evaluation and development of coping skills is indicated as a goal for therapists having suicide at-risk women as clients.

Evolution of Bacterial Suicide

NASA Astrophysics Data System (ADS)

Tchernookov, Martin; Nemenman, Ilya

2013-03-01

While active, controlled cellular suicide (autolysis) in bacteria is commonly observed, it has been hard to argue that autolysis can be beneficial to an individual who commits it. We propose a theoretical model that predicts that bacterial autolysis is evolutionarily advantageous to an individualand would fixate in physically structured environments for stationary phase colonies. We perform spatially resolved agent-based simulations of the model, which predict that lower mixing in the environment results in fixation of a higher autolysis rate from a single mutated cell, regardless of the colony's genetic diversity. We argue that quorum sensing will fixate as well, even if initially rare, if it is coupled to controlling the autolysis rate. The model does not predict a strong additional competitive advantage for cells where autolysis is controlled by quorum sensing systems that distinguish self from nonself. These predictions are broadly supported by recent experimental results in B. subtilisand S. pneumoniae. Research partially supported by the James S McDonnell Foundation grant No. 220020321 and by HFSP grant No. RGY0084/2011.

Electrophysiological evidence for a general auditory prediction deficit in adults who stutter

PubMed Central

Daliri, Ayoub; Max, Ludo

2015-01-01

We previously found that stuttering individuals do not show the typical auditory modulation observed during speech planning in nonstuttering individuals. In this follow-up study, we further elucidate this difference by investigating whether stuttering speakers’ atypical auditory modulation is observed only when sensory predictions are based on movement planning or also when predictable auditory input is not a consequence of one’s own actions. We recorded 10 stuttering and 10 nonstuttering adults’ auditory evoked potentials in response to random probe tones delivered while anticipating either speaking aloud or hearing one’s own speech played back and in a control condition without auditory input (besides probe tones). N1 amplitude of nonstuttering speakers was reduced prior to both speaking and hearing versus the control condition. Stuttering speakers, however, showed no N1 amplitude reduction in either the speaking or hearing condition as compared with control. Thus, findings suggest that stuttering speakers have general auditory prediction difficulties. PMID:26335995

Predictors of responses to stress among families coping with poverty-related stress.

PubMed

Santiago, Catherine DeCarlo; Etter, Erica Moran; Wadsworth, Martha E; Raviv, Tali

2012-05-01

This study tested how poverty-related stress (PRS), psychological distress, and responses to stress predicted future effortful coping and involuntary stress responses one year later. In addition, we explored age, sex, ethnicity, and parental influences on responses to stress over time. Hierarchical linear modeling analyses conducted with 98 low-income families (300 family members: 136 adults, 82 school-aged children, 82 adolescents) revealed that primary control coping, secondary control coping, disengagement, involuntary engagement, and involuntary disengagement each significantly predicted future use of that response. Primary and secondary control coping also predicted less maladaptive future responses to stress, while involuntary responses to stress undermined the development of adaptive responding. Age, sex, and interactions among PRS and prior coping were also found to predict certain responses to stress. In addition, child subgroup analyses demonstrate the importance of parental modeling of coping and involuntary stress responses, and warmth/nurturance and monitoring practices. Results are discussed with regard to the implications for preventive interventions with families in poverty.

Personality Assessment Screener, Childhood Abuse, and Adult Partner Violence in African American Women Using Primary Care.

PubMed

Porcerelli, John H; Hurrell, Kristen; Cogan, Rosemary; Jeffries, Keturah; Markova, Tsveti

2015-12-01

This study assessed the relationship between psychopathology with the Personality Assessment Screener (PAS) and childhood physical and sexual abuse and adult physical and sexual partner violence in a primary care sample of 98 urban-dwelling African American women. Patients completed the PAS, the Childhood Trauma Questionnaire, and the Conflict Tactics Scale. The PAS total score significantly correlated with all measures of childhood and adult abuse. Stepwise regression analyses revealed that PAS element scores of Suicidal Thinking and Hostile Control significantly predicted a history of childhood physical abuse; Suicidal Thinking, Hostile Control, and Acting Out significantly predicted a history of childhood sexual abuse; Suicidal Thinking, Negative Affect, and Alienation significantly predicted current adult partner physical violence; and Psychotic Features, Alcohol Problems, and Anger Control significantly predicted current adult sexual partner violence. The PAS appears to be a useful measure for fast-paced primary care settings for identifying patients who need a more thorough assessment for abuse. © The Author(s) 2015.

An Improved Model Predictive Current Controller of Switched Reluctance Machines Using Time-Multiplexed Current Sensor

PubMed Central

Li, Bingchu; Ling, Xiao; Huang, Yixiang; Gong, Liang; Liu, Chengliang

2017-01-01

This paper presents a fixed-switching-frequency model predictive current controller using multiplexed current sensor for switched reluctance machine (SRM) drives. The converter was modified to distinguish currents from simultaneously excited phases during the sampling period. The only current sensor installed in the converter was time division multiplexing for phase current sampling. During the commutation stage, the control steps of adjacent phases were shifted so that sampling time was staggered. The maximum and minimum duty ratio of pulse width modulation (PWM) was limited to keep enough sampling time for analog-to-digital (A/D) conversion. Current sensor multiplexing was realized without complex adjustment of either driver circuit nor control algorithms, while it helps to reduce the cost and errors introduced in current sampling due to inconsistency between sensors. The proposed controller is validated by both simulation and experimental results with a 1.5 kW three-phase 12/8 SRM. Satisfied current sampling is received with little difference compared with independent phase current sensors for each phase. The proposed controller tracks the reference current profile as accurately as the model predictive current controller with independent phase current sensors, while having minor tracking errors compared with a hysteresis current controller. PMID:28513554

Optimization control of LNG regasification plant using Model Predictive Control

NASA Astrophysics Data System (ADS)

Wahid, A.; Adicandra, F. F.

2018-03-01

Optimization of liquified natural gas (LNG) regasification plant is important to minimize costs, especially operational costs. Therefore, it is important to choose optimum LNG regasification plant design and maintaining the optimum operating conditions through the implementation of model predictive control (MPC). Optimal tuning parameter for MPC such as P (prediction horizon), M (control of the horizon) and T (sampling time) are achieved by using fine-tuning method. The optimal criterion for design is the minimum amount of energy used and for control is integral of square error (ISE). As a result, the optimum design is scheme 2 which is developed by Devold with an energy savings of 40%. To maintain the optimum conditions, required MPC with P, M and T as follows: tank storage pressure: 90, 2, 1; product pressure: 95, 2, 1; temperature vaporizer: 65, 2, 2; and temperature heater: 35, 6, 5, with ISE value at set point tracking respectively 0.99, 1792.78, 34.89 and 7.54, or improvement of control performance respectively 4.6%, 63.5%, 3.1% and 58.2% compared to PI controller performance. The energy savings that MPC controllers can make when there is a disturbance in temperature rise 1°C of sea water is 0.02 MW.

Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems

NASA Technical Reports Server (NTRS)

Groves, Curtis; Ilie, Marcel; Schallhorn, Paul

2014-01-01

Spacecraft components may be damaged due to airflow produced by Environmental Control Systems (ECS). There are uncertainties and errors associated with using Computational Fluid Dynamics (CFD) to predict the flow field around a spacecraft from the ECS System. This paper describes an approach to estimate the uncertainty in using CFD to predict the airflow speeds around an encapsulated spacecraft.

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…

Predicted and flight test results of the performance, stability and control of the space shuttle from reentry to landing

NASA Technical Reports Server (NTRS)

Kirsten, P. W.; Richardson, D. F.; Wilson, C. M.

1983-01-01

Aerodynaic performance, stability and control data obtained from the first five reentries of the Space Shuttle orbiter are given. Flight results are compared to pedicted data from Mach 26.4 to Mach 0.4. Differences between flight and predicted data as well as probable causes for the discrepancies are given.

Predicting the spread of sudden oak death in California (2010-2030): epidemic outcomes under no control

Treesearch

Ross K. Meentemeyer; Nik Cunniffe; Alex Cook; David M. Rizzo; Chris A. Gilligan

2010-01-01

Landscape- to regional-scale models of plant epidemics are direly needed to predict largescale impacts of disease and assess practicable options for control. While landscape heterogeneity is recognized as a major driver of disease dynamics, epidemiological models are rarely applied to realistic landscape conditions due to computational and data limitations. Here we...

Parent weight change predicts child weight change in family-based weight control program for pre-school children (Buffalo healthy tots)

USDA-ARS?s Scientific Manuscript database

Title: PARENT WEIGHT CHANGE PREDICTS CHILD WEIGHT CHANGE IN FAMILY-BASED WEIGHT CONTROL PROGRAM FOR PRE-SCHOOL CHILDREN (BUFFALO HEALTHY TOTS), Teresa Quattrin, MOl, James N Roemmich, PhDI, Rocco Paluch, MAl, Jihnhee Yu, PhD2, Leonard H Epstein, PhDI and Michelle A Ecker, RD, CDEI . lpediatrics, Uni...

Amazon forest carbon dynamics predicted by profiles of canopy leaf area and light environment

Treesearch

S. C. Stark; V. Leitold; J. L. Wu; M. O. Hunter; C. V. de Castilho; F. R. C. Costa; S. M. McMahon; G. G. Parker; M. Takako Shimabukuro; M. A. Lefsky; M. Keller; L. F. Alves; J. Schietti; Y. E. Shimabukuro; D. O. Brandao; T. K. Woodcock; N. Higuchi; P. B de Camargo; R. C. de Oliveira; S. R. Saleska

2012-01-01

Tropical forest structural variation across heterogeneous landscapes may control above-ground carbon dynamics. We tested the hypothesis that canopy structure (leaf area and light availability) – remotely estimated from LiDAR – control variation in above-ground coarse wood production (biomass growth). Using a statistical model, these factors predicted biomass growth...

Real-time control of combined surface water quantity and quality: polder flushing.

PubMed

Xu, M; van Overloop, P J; van de Giesen, N C; Stelling, G S

2010-01-01

In open water systems, keeping both water depths and water quality at specified values is critical for maintaining a 'healthy' water system. Many systems still require manual operation, at least for water quality management. When applying real-time control, both quantity and quality standards need to be met. In this paper, an artificial polder flushing case is studied. Model Predictive Control (MPC) is developed to control the system. In addition to MPC, a 'forward estimation' procedure is used to acquire water quality predictions for the simplified model used in MPC optimization. In order to illustrate the advantages of MPC, classical control [Proportional-Integral control (PI)] has been developed for comparison in the test case. The results show that both algorithms are able to control the polder flushing process, but MPC is more efficient in functionality and control flexibility.

The insertion of human dynamics models in the flight control loops of V/STOL research aircraft. Appendix 2: The optimal control model of a pilot in V/STOL aircraft control loops

NASA Technical Reports Server (NTRS)

Zipf, Mark E.

1989-01-01

An overview is presented of research work focussed on the design and insertion of classical models of human pilot dynamics within the flight control loops of V/STOL aircraft. The pilots were designed and configured for use in integrated control system research and design. The models of human behavior that were considered are: McRuer-Krendel (a single variable transfer function model); and Optimal Control Model (a multi-variable approach based on optimal control and stochastic estimation theory). These models attempt to predict human control response characteristics when confronted with compensatory tracking and state regulation tasks. An overview, mathematical description, and discussion of predictive limitations of the pilot models is presented. Design strategies and closed loop insertion configurations are introduced and considered for various flight control scenarios. Models of aircraft dynamics (both transfer function and state space based) are developed and discussed for their use in pilot design and application. Pilot design and insertion are illustrated for various flight control objectives. Results of pilot insertion within the control loops of two V/STOL research aricraft (Sikorski Black Hawk UH-60A, McDonnell Douglas Harrier II AV-8B) are presented and compared against actual pilot flight data. Conclusions are reached on the ability of the pilot models to adequately predict human behavior when confronted with similar control objectives.

The management submodel of the Wind Erosion Prediction System

USDA-ARS?s Scientific Manuscript database

The Wind Erosion Prediction System (WEPS) is a process-based, daily time-step, computer model that predicts soil erosion via simulation of the physical processes controlling wind erosion. WEPS is comprised of several individual modules (submodels) that reflect different sets of physical processes, ...

Early Predictors of Middle School Fraction Knowledge

ERIC Educational Resources Information Center

Bailey, Drew H.; Siegler, Robert S.; Geary, David C.

2014-01-01

Recent findings that earlier fraction knowledge predicts later mathematics achievement raise the question of what predicts later fraction knowledge. Analyses of longitudinal data indicated that whole number magnitude knowledge in first grade predicted knowledge of fraction magnitudes in middle school, controlling for whole number arithmetic…

Predicting outcomes of group cognitive behavior therapy for patients with affective and neurotic disorders.

PubMed

Hooke, Geoffrey R; Page, Andrew C

2002-10-01

An attempt was made to predict outcomes following group Cognitive Behavior Therapy (CBT) for patients with affective and neurotic disorders. A group of 348 patients at a private psychiatric clinic, treated in a group CBT program, completed the Depression, Anxiety, and Stress Scale (DASS) before and after treatment. Prior to treatment, data from the Locus of Control of Behavior (LCB), a Global Assessment of Function (GAF), the Health of the Nation Outcome Scales (HoNOS), and the Rosenberg Self Esteem Scale (RSE) were also collected. Results indicated that posttreatment stress scores of all patients were predicted by pretreatment stress and self-esteem. Among patients with neurotic disorders, posttreatment anxiety was predicted by initial anxiety and self-esteem whereas among patients with affective disorders, posttreatment anxiety scores were predicted by initial anxiety and GAF. For patients with neurotic disorders, self-esteem did not predict variance in posttreatment depression in addition to that explained by pretreatment depression. In contrast, for patients with affective disorders, pretreatment depression and Locus of Control predicted posttreatment depression.

The role of fear in predicting sexually transmitted infection screening.

PubMed

Shepherd, Lee; Smith, Michael A

2017-07-01

This study assessed the extent to which social-cognitive factors (attitude, subjective norm and perceived control) and the fear of a positive test result predict sexually transmitted infection (STI) screening intentions and subsequent behaviour. Study 1 (N = 85) used a longitudinal design to assess the factors that predict STI screening intention and future screening behaviour measured one month later at Time 2. Study 2 (N = 102) used an experimental design to determine whether the relationship between fear and screening varied depending on whether STI or HIV screening was being assessed both before and after controlling for social-cognitive factors. Across the studies the outcome measures were sexual health screening. In both studies, the fear of having an STI positively predicted STI screening intention. In Study 1, fear, but not the social-cognitive factors, also predicted subsequent STI screening behaviour. In Study 2, the fear of having HIV did not predict HIV screening intention, but attitude negatively and response efficacy positively predicted screening intention. This study highlights the importance of considering the nature of the health condition when assessing the role of fear on health promotion.

Does teacher evaluation based on student performance predict motivation, well-being, and ill-being?

PubMed

Cuevas, Ricardo; Ntoumanis, Nikos; Fernandez-Bustos, Juan G; Bartholomew, Kimberley

2018-06-01

This study tests an explanatory model based on self-determination theory, which posits that pressure experienced by teachers when they are evaluated based on their students' academic performance will differentially predict teacher adaptive and maladaptive motivation, well-being, and ill-being. A total of 360 Spanish physical education teachers completed a multi-scale inventory. We found support for a structural equation model that showed that perceived pressure predicted teacher autonomous motivation negatively, predicted amotivation positively, and was unrelated to controlled motivation. In addition, autonomous motivation predicted vitality positively and exhaustion negatively, whereas controlled motivation and amotivation predicted vitality negatively and exhaustion positively. Amotivation significantly mediated the relation between pressure and vitality and between pressure and exhaustion. The results underline the potential negative impact of pressure felt by teachers due to this type of evaluation on teacher motivation and psychological health. Copyright © 2018 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Interpreting Disruption Prediction Models to Improve Plasma Control

NASA Astrophysics Data System (ADS)

Parsons, Matthew

2017-10-01

In order for the tokamak to be a feasible design for a fusion reactor, it is necessary to minimize damage to the machine caused by plasma disruptions. Accurately predicting disruptions is a critical capability for triggering any mitigative actions, and a modest amount of attention has been given to efforts that employ machine learning techniques to make these predictions. By monitoring diagnostic signals during a discharge, such predictive models look for signs that the plasma is about to disrupt. Typically these predictive models are interpreted simply to give a `yes' or `no' response as to whether a disruption is approaching. However, it is possible to extract further information from these models to indicate which input signals are more strongly correlated with the plasma approaching a disruption. If highly accurate predictive models can be developed, this information could be used in plasma control schemes to make better decisions about disruption avoidance. This work was supported by a Grant from the 2016-2017 Fulbright U.S. Student Program, administered by the Franco-American Fulbright Commission in France.

Control of epileptic seizures in WAG/Rij rats by means of brain-computer interface

NASA Astrophysics Data System (ADS)

Makarov, Vladimir V.; Maksimenko, Vladimir A.; van Luijtelaar, Gilles; Lüttjohann, Annika; Hramov, Alexander E.

2018-02-01

The main issue of epileptology is the elimination of epileptic events. This can be achieved by a system that predicts the emergence of seizures in conjunction with a system that interferes with the process that leads to the onset of seizure. The prediction of seizures remains, for the present, unresolved in the absence epilepsy, due to the sudden onset of seizures. We developed an algorithm for predicting seizures in real time, evaluated it and implemented it into an online closed-loop brain stimulation system designed to prevent typical for the absence of epilepsy of spike waves (SWD) in the genetic rat model. The algorithm correctly predicts more than 85% of the seizures and the rest were successfully detected. Unlike the old beliefs that SWDs are unpredictable, current results show that they can be predicted and that the development of systems for predicting and preventing closed-loop capture is a feasible step on the way to intervention to achieve control and freedom from epileptic seizures.

Correlation study of theoretical and experimental results for spin tests of a 1/10 scale radio control model

NASA Technical Reports Server (NTRS)

Bihrle, W., Jr.

1976-01-01

A correlation study was conducted to determine the ability of current analytical spin prediction techniques to predict the flight motions of a current fighter airplane configuration during the spin entry, the developed spin, and the spin recovery motions. The airplane math model used aerodynamics measured on an exact replica of the flight test model using conventional static and forced-oscillation wind-tunnel test techniques and a recently developed rotation-balance test apparatus capable of measuring aerodynamics under steady spinning conditions. An attempt was made to predict the flight motions measured during stall/spin flight testing of an unpowered, radio-controlled model designed to be a 1/10 scale, dynamically-scaled model of a current fighter configuration. Comparison of the predicted and measured flight motions show that while the post-stall and spin entry motions were not well-predicted, the developed spinning motion (a steady flat spin) and the initial phases of the spin recovery motion are reasonably well predicted.

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.

Searching for the self: an identity control theory approach to triggers of occupational exploration.

PubMed

Anderson, Katherine L; Mounts, Nina S

2012-01-01

Identity control theory researchers have found evidence for two processes of identity development (identity defense and identity change) and have theorized a third process (identity exploration). College students (N = 123) self-rated as high or low in occupational identity certainty and importance received self-discrepant feedback to induce identity disturbance, and dependent measures of identity defense, identity change, and identity exploration were obtained. As predicted, high certainty about identity standards led to identity defense, while low certainty led to identity change. Although an interaction between certainty and importance was hypothesized to predict identity exploration, results showed that the two operated independently. Low certainty predicted exploration of additional occupational areas, whereas high importance predicted exploration of self, environment, and additional occupational areas.

Qualitative comparison of calculated turbulence responses with wind-tunnel measurements for a DC-10 derivative wing with an active control system

NASA Technical Reports Server (NTRS)

Perry, B., III

1981-01-01

Comparisons are presented analytically predicted and experimental turbulence responses of a wind tunnel model of a DC-10 derivative wing equipped with an active control system. The active control system was designed for the purpose of flutter suppression, but it had additional benefit of alleviating gust loads (wing bending moment) by about 25%. Comparisions of various wing responses are presented for variations in active control system parameters and tunnel speed. The analytical turbulence responses were obtained using DYLOFLEX, a computer program for dynamic loads analyses of flexible airplanes with active controls. In general, the analytical predictions agreed reasonably well with the experimental data.

Drug disposition and modelling before and after gastric bypass: immediate and controlled-release metoprolol formulations.

PubMed

Gesquiere, Ina; Darwich, Adam S; Van der Schueren, Bart; de Hoon, Jan; Lannoo, Matthias; Matthys, Christophe; Rostami, Amin; Foulon, Veerle; Augustijns, Patrick

2015-11-01

The aim of the present study was to evaluate the disposition of metoprolol after oral administration of an immediate and controlled-release formulation before and after Roux-en-Y gastric bypass (RYGB) surgery in the same individuals and to validate a physiologically based pharmacokinetic (PBPK) model for predicting oral bioavailability following RYGB. A single-dose pharmacokinetic study of metoprolol tartrate 200 mg immediate release and controlled release was performed in 14 volunteers before and 6-8 months after RYGB. The observed data were compared with predicted results from the PBPK modelling and simulation of metoprolol tartrate immediate and controlled-release formulation before and after RYGB. After administration of metoprolol immediate and controlled release, no statistically significant difference in the observed area under the curve (AUC(0-24 h)) was shown, although a tendency towards an increased oral exposure could be observed as the AUC(0-24 h) was 32.4% [95% confidence interval (CI) 1.36, 63.5] and 55.9% (95% CI 5.73, 106) higher following RYGB for the immediate and controlled-release formulation, respectively. This could be explained by surgery-related weight loss and a reduced presystemic biotransformation in the proximal gastrointestinal tract. The PBPK values predicted by modelling and simulation were similar to the observed data, confirming its validity. The disposition of metoprolol from an immediate-release and a controlled-release formulation was not significantly altered after RYGB; there was a tendency to an increase, which was also predicted by PBPK modelling and simulation. © 2015 The British Pharmacological Society.

Drug disposition and modelling before and after gastric bypass: immediate and controlled-release metoprolol formulations

PubMed Central

Gesquiere, Ina; Darwich, Adam S; Van der Schueren, Bart; de Hoon, Jan; Lannoo, Matthias; Matthys, Christophe; Rostami, Amin; Foulon, Veerle; Augustijns, Patrick

2015-01-01

Aims The aim of the present study was to evaluate the disposition of metoprolol after oral administration of an immediate and controlled-release formulation before and after Roux-en-Y gastric bypass (RYGB) surgery in the same individuals and to validate a physiologically based pharmacokinetic (PBPK) model for predicting oral bioavailability following RYGB. Methods A single-dose pharmacokinetic study of metoprolol tartrate 200 mg immediate release and controlled release was performed in 14 volunteers before and 6–8 months after RYGB. The observed data were compared with predicted results from the PBPK modelling and simulation of metoprolol tartrate immediate and controlled-release formulation before and after RYGB. Results After administration of metoprolol immediate and controlled release, no statistically significant difference in the observed area under the curve (AUC0–24 h) was shown, although a tendency towards an increased oral exposure could be observed as the AUC0–24 h was 32.4% [95% confidence interval (CI) 1.36, 63.5] and 55.9% (95% CI 5.73, 106) higher following RYGB for the immediate and controlled-release formulation, respectively. This could be explained by surgery-related weight loss and a reduced presystemic biotransformation in the proximal gastrointestinal tract. The PBPK values predicted by modelling and simulation were similar to the observed data, confirming its validity. Conclusions The disposition of metoprolol from an immediate-release and a controlled-release formulation was not significantly altered after RYGB; there was a tendency to an increase, which was also predicted by PBPK modelling and simulation. PMID:25917170

Control of African swine fever epidemics in industrialized swine populations.

PubMed

Halasa, Tariq; Bøtner, Anette; Mortensen, Sten; Christensen, Hanne; Toft, Nils; Boklund, Anette

2016-12-25

African swine fever (ASF) is a notifiable infectious disease with a high impact on swine health. The disease is endemic in certain regions in the Baltic countries and has spread to Poland constituting a risk of ASF spread toward Western Europe. Therefore, as part of contingency planning, it is important to explore strategies that can effectively control an epidemic of ASF. In this study, the epidemiological and economic effects of strategies to control the spread of ASF between domestic swine herds were examined using a published model (DTU-DADS-ASF). The control strategies were the basic EU and national strategy (Basic), the basic strategy plus pre-emptive depopulation of neighboring swine herds, and intensive surveillance of herds in the control zones, including testing live or dead animals. Virus spread via wild boar was not modelled. Under the basic control strategy, the median epidemic duration was predicted to be 21days (5th and 95th percentiles; 1-55days), the median number of infected herds was predicted to be 3 herds (1-8), and the total costs were predicted to be €326 million (€256-€442 million). Adding pre-emptive depopulation or intensive surveillance by testing live animals resulted in marginal improvements to the control of the epidemics. However, adding testing of dead animals in the protection and surveillance zones was predicted to be the optimal control scenario for an ASF epidemic in industrialized swine populations without contact to wild boar. This optimal scenario reduced the epidemic duration to 9days (1-38) and the total costs to €294 million (€257-€392 million). Export losses were the driving force of the total costs of the epidemics. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

A multivariate model exploring the predictive value of demographic, adolescent, and family factors on glycemic control in adolescents with type 1 diabetes.

PubMed

Agarwal, Shivani; Jawad, Abbas F; Miller, Victoria A

2016-11-01

The current study examined how a comprehensive set of variables from multiple domains, including at the adolescent and family level, were predictive of glycemic control in adolescents with type 1 diabetes (T1D). Participants included 100 adolescents with T1D ages 10-16 yrs and their parents. Participants were enrolled in a longitudinal study about youth decision-making involvement in chronic illness management of which the baseline data were available for analysis. Bivariate associations with glycemic control (HbA1C) were tested. Hierarchical linear regression was implemented to inform the predictive model. In bivariate analyses, race, family structure, household income, insulin regimen, adolescent-reported adherence to diabetes self-management, cognitive development, adolescent responsibility for T1D management, and parent behavior during the illness management discussion were associated with HbA1c. In the multivariate model, the only significant predictors of HbA1c were race and insulin regimen, accounting for 17% of the variance. Caucasians had better glycemic control than other racial groups. Participants using pre-mixed insulin therapy and basal-bolus insulin had worse glycemic control than those on insulin pumps. This study shows that despite associations of adolescent and family-level variables with glycemic control at the bivariate level, only race and insulin regimen are predictive of glycemic control in hierarchical multivariate analyses. This model offers an alternative way to examine the relationship of demographic and psychosocial factors on glycemic control in adolescents with T1D. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Dieting and unhealthy weight control behaviors during adolescence: Associations with 10-year changes in body mass index

PubMed Central

Neumark-Sztainer, Dianne; Wall, Melanie; Story, Mary; Standish, Amber R

2011-01-01

Background Dieting and unhealthy weight control behaviors are common among adolescents and questions exist regarding their long-term effect on weight status. Objective To examine 10-year longitudinal associations between dieting and unhealthy weight control behaviors and changes in body mass index (BMI) from adolescence to young adulthood. Methods and Procedures A diverse population-based sample of middle school and high school adolescents was followed for 10 years. Participants (N=1,902) completed surveys in 1998–99 (Project EAT-I), 2003–04 (Project EAT-II), and 2008–09 (Project EAT-III). Dieting and unhealthy weight control behaviors at Time 1 and Time 2 were used to predict 10-year changes in BMI at Time 3, adjusting for sociodemographic characteristics and Time 1 BMI. Results Dieting and unhealthy weight control behaviors at both Time 1 and Time 2 predicted greater BMI increases at Time 3 in males and females, as compared to no use of these behaviors. For example, females using unhealthy weight control behaviors at both Time 1 and Time 2 increased their BMI by 4.63 units as compared to 2.29 units in females not using these behaviors (p<.001). Associations were found in both overweight and non-overweight respondents. Specific weight control behaviors at Time 1 that predicted larger BMI increases at Time 3 included skipping meals and reporting eating very little (females and males), use of food substitutes (males), and diet pill use (females). Conclusions Findings clearly indicate that dieting and unhealthy weight control behaviors, as reported by adolescents, predict significant weight gain over time. PMID:22188838

Predictive modeling and reducing cyclic variability in autoignition engines

DOEpatents

Hellstrom, Erik; Stefanopoulou, Anna; Jiang, Li; Larimore, Jacob

2016-08-30

Methods and systems are provided for controlling a vehicle engine to reduce cycle-to-cycle combustion variation. A predictive model is applied to predict cycle-to-cycle combustion behavior of an engine based on observed engine performance variables. Conditions are identified, based on the predicted cycle-to-cycle combustion behavior, that indicate high cycle-to-cycle combustion variation. Corrective measures are then applied to prevent the predicted high cycle-to-cycle combustion variation.

Resilient Adolescent Adjustment among Girls: Buffers of Childhood Peer Rejection and Attention-Deficit/Hyperactivity Disorder

PubMed Central

Mikami, Amori Yee; Hinshaw, Stephen P.

2010-01-01

Examined a risk-resilience model of peer rejection and attention-deficit/hyperactivity disorder (ADHD) in a 5-year longitudinal study of 209 ethnically and socioeconomically diverse girls aged 6–13 at baseline and 11–18 at follow-up. Risk factors were childhood ADHD diagnosis and peer rejection; hypothesized protective factors were childhood measures of self-perceived scholastic competence, engagement in goal-directed play when alone, and popularity with adults. Adolescent criterion measures were multi-informant composites of externalizing and internalizing behavior plus indicators of academic achievement, eating pathology, and substance use. ADHD and peer rejection predicted risk for all criterion measures except for substance use, which was predicted by ADHD only. ADHD and peer rejection predicted lower adolescent academic achievement controlling for childhood achievement, but they did not predict adolescent externalizing and internalizing behavior after controlling for baseline levels of these constructs. Regarding buffers, self-perceived scholastic competence in childhood (with control of academic achievement) predicted resilient adolescent functioning. Contrary to hypothesis, goal-directed play in childhood was associated with poor adolescent outcomes. Buffers were not found to have differential effectiveness among girls with ADHD relative to comparison girls. PMID:17051436