Optimal reorientation of asymmetric underactuated spacecraft using differential flatness and receding horizon control

NASA Astrophysics Data System (ADS)

Cai, Wei-wei; Yang, Le-ping; Zhu, Yan-wei

2015-01-01

This paper presents a novel method integrating nominal trajectory optimization and tracking for the reorientation control of an underactuated spacecraft with only two available control torque inputs. By employing a pseudo input along the uncontrolled axis, the flatness property of a general underactuated spacecraft is extended explicitly, by which the reorientation trajectory optimization problem is formulated into the flat output space with all the differential constraints eliminated. Ultimately, the flat output optimization problem is transformed into a nonlinear programming problem via the Chebyshev pseudospectral method, which is improved by the conformal map and barycentric rational interpolation techniques to overcome the side effects of the differential matrix's ill-conditions on numerical accuracy. Treating the trajectory tracking control as a state regulation problem, we develop a robust closed-loop tracking control law using the receding-horizon control method, and compute the feedback control at each control cycle rapidly via the differential transformation method. Numerical simulation results show that the proposed control scheme is feasible and effective for the reorientation maneuver.

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.

Output Feedback Adaptive Control of Non-Minimum Phase Systems Using Optimal Control Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan

2018-01-01

This paper describes output feedback adaptive control approaches for non-minimum phase SISO systems with relative degree 1 and non-strictly positive real (SPR) MIMO systems with uniform relative degree 1 using the optimal control modification method. It is well-known that the standard model-reference adaptive control (MRAC) cannot be used to control non-SPR plants to track an ideal SPR reference model. Due to the ideal property of asymptotic tracking, MRAC attempts an unstable pole-zero cancellation which results in unbounded signals for non-minimum phase SISO systems. The optimal control modification can be used to prevent the unstable pole-zero cancellation which results in a stable adaptation of non-minimum phase SISO systems. However, the tracking performance using this approach could suffer if the unstable zero is located far away from the imaginary axis. The tracking performance can be recovered by using an observer-based output feedback adaptive control approach which uses a Luenberger observer design to estimate the state information of the plant. Instead of explicitly specifying an ideal SPR reference model, the reference model is established from the linear quadratic optimal control to account for the non-minimum phase behavior of the plant. With this non-minimum phase reference model, the observer-based output feedback adaptive control can maintain stability as well as tracking performance. However, in the presence of the mismatch between the SPR reference model and the non-minimum phase plant, the standard MRAC results in unbounded signals, whereas a stable adaptation can be achieved with the optimal control modification. An application of output feedback adaptive control for a flexible wing aircraft illustrates the approaches.

Dynamic optimization approach for integrated supplier selection and tracking control of single product inventory system with product discount

NASA Astrophysics Data System (ADS)

Sutrisno; Widowati; Heru Tjahjana, R.

2017-01-01

In this paper, we propose a mathematical model in the form of dynamic/multi-stage optimization to solve an integrated supplier selection problem and tracking control problem of single product inventory system with product discount. The product discount will be stated as a piece-wise linear function. We use dynamic programming to solve this proposed optimization to determine the optimal supplier and the optimal product volume that will be purchased from the optimal supplier for each time period so that the inventory level tracks a reference trajectory given by decision maker with minimal total cost. We give a numerical experiment to evaluate the proposed model. From the result, the optimal supplier was determined for each time period and the inventory level follows the given reference well.

Learning-Based Adaptive Optimal Tracking Control of Strict-Feedback Nonlinear Systems.

PubMed

Gao, Weinan; Jiang, Zhong-Ping; Weinan Gao; Zhong-Ping Jiang; Gao, Weinan; Jiang, Zhong-Ping

2018-06-01

This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods. This paper proposes a novel policy iteration technique for solving positive semidefinite HJB equations with rigorous convergence analysis. A two-phase data-driven learning method is developed and implemented online by ADP. The efficacy of the proposed adaptive optimal tracking control methodology is demonstrated via a Van der Pol oscillator with time-varying exogenous signals.

Optimal Output Trajectory Redesign for Invertible Systems

NASA Technical Reports Server (NTRS)

Devasia, S.

1996-01-01

Given a desired output trajectory, inversion-based techniques find input-state trajectories required to exactly track the output. These inversion-based techniques have been successfully applied to the endpoint tracking control of multijoint flexible manipulators and to aircraft control. The specified output trajectory uniquely determines the required input and state trajectories that are found through inversion. These input-state trajectories exactly track the desired output; however, they might not meet acceptable performance requirements. For example, during slewing maneuvers of flexible structures, the structural deformations, which depend on the required state trajectories, may be unacceptably large. Further, the required inputs might cause actuator saturation during an exact tracking maneuver, for example, in the flight control of conventional takeoff and landing aircraft. In such situations, a compromise is desired between the tracking requirement and other goals such as reduction of internal vibrations and prevention of actuator saturation; the desired output trajectory needs to redesigned. Here, we pose the trajectory redesign problem as an optimization of a general quadratic cost function and solve it in the context of linear systems. The solution is obtained as an off-line prefilter of the desired output trajectory. An advantage of our technique is that the prefilter is independent of the particular trajectory. The prefilter can therefore be precomputed, which is a major advantage over other optimization approaches. Previous works have addressed the issue of preshaping inputs to minimize residual and in-maneuver vibrations for flexible structures; Since the command preshaping is computed off-line. Further minimization of optimal quadratic cost functions has also been previously use to preshape command inputs for disturbance rejection. All of these approaches are applicable when the inputs to the system are known a priori. Typically, outputs (not inputs) are specified in tracking problems, and hence the input trajectories have to be computed. The inputs to the system are however, difficult to determine for non-minimum phase systems like flexible structures. One approach to solve this problem is to (1) choose a tracking controller (the desired output trajectory is now an input to the closed-loop system and (2) redesign this input to the closed-loop system. Thus we effectively perform output redesign. These redesigns are however, dependent on the choice of the tracking controllers. Thus the controller optimization and trajectory redesign problems become coupled; this coupled optimization is still an open problem. In contrast, we decouple the trajectory redesign problem from the choice of feedback-based tracking controller. It is noted that our approach remains valid when a particular tracking controller is chosen. In addition, the formulation of our problem not only allows for the minimization of residual vibration as in available techniques but also allows for the optimal reduction fo vibrations during the maneuver, e.g., the altitude control of flexible spacecraft. We begin by formulating the optimal output trajectory redesign problem and then solve it in the context of general linear systems. This theory is then applied to an example flexible structure, and simulation results are provided.

Optimal tracking control for a class of nonlinear discrete-time systems with time delays based on heuristic dynamic programming.

PubMed

Zhang, Huaguang; Song, Ruizhuo; Wei, Qinglai; Zhang, Tieyan

2011-12-01

In this paper, a novel heuristic dynamic programming (HDP) iteration algorithm is proposed to solve the optimal tracking control problem for a class of nonlinear discrete-time systems with time delays. The novel algorithm contains state updating, control policy iteration, and performance index iteration. To get the optimal states, the states are also updated. Furthermore, the "backward iteration" is applied to state updating. Two neural networks are used to approximate the performance index function and compute the optimal control policy for facilitating the implementation of HDP iteration algorithm. At last, we present two examples to demonstrate the effectiveness of the proposed HDP iteration algorithm.

An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan

2008-01-01

This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.

Intelligent system of coordination and control for manufacturing

NASA Astrophysics Data System (ADS)

Ciortea, E. M.

2016-08-01

This paper wants shaping an intelligent system monitoring and control, which leads to optimizing material and information flows of the company. The paper presents a model for tracking and control system using intelligent real. Production system proposed for simulation analysis provides the ability to track and control the process in real time. Using simulation models be understood: the influence of changes in system structure, commands influence on the general condition of the manufacturing process conditions influence the behavior of some system parameters. Practical character consists of tracking and real-time control of the technological process. It is based on modular systems analyzed using mathematical models, graphic-analytical sizing, configuration, optimization and simulation.

Optimal tracking and second order sliding power control of the DFIG wind turbine

NASA Astrophysics Data System (ADS)

Abdeddaim, S.; Betka, A.; Charrouf, O.

2017-02-01

In the present paper, an optimal operation of a grid-connected variable speed wind turbine equipped with a Doubly Fed Induction Generator (DFIG) is presented. The proposed cascaded nonlinear controller is designed to perform two main objectives. In the outer loop, a maximum power point tracking (MPPT) algorithm based on fuzzy logic theory is designed to permanently extract the optimal aerodynamic energy, whereas in the inner loop, a second order sliding mode control (2-SM) is applied to achieve smooth regulation of both stator active and reactive powers quantities. The obtained simulation results show a permanent track of the MPP point regardless of the turbine power-speed slope moreover the proposed sliding mode control strategy presents attractive features such as chattering-free, compared to the conventional first order sliding technique (1-SM).

Free terminal time optimal control problem of an HIV model based on a conjugate gradient method.

PubMed

Jang, Taesoo; Kwon, Hee-Dae; Lee, Jeehyun

2011-10-01

The minimum duration of treatment periods and the optimal multidrug therapy for human immunodeficiency virus (HIV) type 1 infection are considered. We formulate an optimal tracking problem, attempting to drive the states of the model to a "healthy" steady state in which the viral load is low and the immune response is strong. We study an optimal time frame as well as HIV therapeutic strategies by analyzing the free terminal time optimal tracking control problem. The minimum duration of treatment periods and the optimal multidrug therapy are found by solving the corresponding optimality systems with the additional transversality condition for the terminal time. We demonstrate by numerical simulations that the optimal dynamic multidrug therapy can lead to the long-term control of HIV by the strong immune response after discontinuation of therapy.

Trajectory planning and optimal tracking for an industrial mobile robot

NASA Astrophysics Data System (ADS)

Hu, Huosheng; Brady, J. Michael; Probert, Penelope J.

1994-02-01

This paper introduces a unified approach to trajectory planning and tracking for an industrial mobile robot subject to non-holonomic constraints. We show (1) how a smooth trajectory is generated that takes into account the constraints from the dynamic environment and the robot kinematics; and (2) how a general predictive controller works to provide optimal tracking capability for nonlinear systems. The tracking performance of the proposed guidance system is analyzed by simulation.

Optimal preview control for a linear continuous-time stochastic control system in finite-time horizon

NASA Astrophysics Data System (ADS)

Wu, Jiang; Liao, Fucheng; Tomizuka, Masayoshi

2017-01-01

This paper discusses the design of the optimal preview controller for a linear continuous-time stochastic control system in finite-time horizon, using the method of augmented error system. First, an assistant system is introduced for state shifting. Then, in order to overcome the difficulty of the state equation of the stochastic control system being unable to be differentiated because of Brownian motion, the integrator is introduced. Thus, the augmented error system which contains the integrator vector, control input, reference signal, error vector and state of the system is reconstructed. This leads to the tracking problem of the optimal preview control of the linear stochastic control system being transformed into the optimal output tracking problem of the augmented error system. With the method of dynamic programming in the theory of stochastic control, the optimal controller with previewable signals of the augmented error system being equal to the controller of the original system is obtained. Finally, numerical simulations show the effectiveness of the controller.

Optimal control of nonlinear continuous-time systems in strict-feedback form.

PubMed

Zargarzadeh, Hassan; Dierks, Travis; Jagannathan, Sarangapani

2015-10-01

This paper proposes a novel optimal tracking control scheme for nonlinear continuous-time systems in strict-feedback form with uncertain dynamics. The optimal tracking problem is transformed into an equivalent optimal regulation problem through a feedforward adaptive control input that is generated by modifying the standard backstepping technique. Subsequently, a neural network-based optimal control scheme is introduced to estimate the cost, or value function, over an infinite horizon for the resulting nonlinear continuous-time systems in affine form when the internal dynamics are unknown. The estimated cost function is then used to obtain the optimal feedback control input; therefore, the overall optimal control input for the nonlinear continuous-time system in strict-feedback form includes the feedforward plus the optimal feedback terms. It is shown that the estimated cost function minimizes the Hamilton-Jacobi-Bellman estimation error in a forward-in-time manner without using any value or policy iterations. Finally, optimal output feedback control is introduced through the design of a suitable observer. Lyapunov theory is utilized to show the overall stability of the proposed schemes without requiring an initial admissible controller. Simulation examples are provided to validate the theoretical results.

A stochastic optimal feedforward and feedback control methodology for superagility

NASA Technical Reports Server (NTRS)

Halyo, Nesim; Direskeneli, Haldun; Taylor, Deborah B.

1992-01-01

A new control design methodology is developed: Stochastic Optimal Feedforward and Feedback Technology (SOFFT). Traditional design techniques optimize a single cost function (which expresses the design objectives) to obtain both the feedforward and feedback control laws. This approach places conflicting demands on the control law such as fast tracking versus noise atttenuation/disturbance rejection. In the SOFFT approach, two cost functions are defined. The feedforward control law is designed to optimize one cost function, the feedback optimizes the other. By separating the design objectives and decoupling the feedforward and feedback design processes, both objectives can be achieved fully. A new measure of command tracking performance, Z-plots, is also developed. By analyzing these plots at off-nominal conditions, the sensitivity or robustness of the system in tracking commands can be predicted. Z-plots provide an important tool for designing robust control systems. The Variable-Gain SOFFT methodology was used to design a flight control system for the F/A-18 aircraft. It is shown that SOFFT can be used to expand the operating regime and provide greater performance (flying/handling qualities) throughout the extended flight regime. This work was performed under the NASA SBIR program. ICS plans to market the software developed as a new module in its commercial CACSD software package: ACET.

Control strategy of grid-connected photovoltaic generation system based on GMPPT method

NASA Astrophysics Data System (ADS)

Wang, Zhongfeng; Zhang, Xuyang; Hu, Bo; Liu, Jun; Li, Ligang; Gu, Yongqiang; Zhou, Bowen

2018-02-01

There are multiple local maximum power points when photovoltaic (PV) array runs under partial shading condition (PSC).However, the traditional maximum power point tracking (MPPT) algorithm might be easily trapped in local maximum power points (MPPs) and cannot find the global maximum power point (GMPP). To solve such problem, a global maximum power point tracking method (GMPPT) is improved, combined with traditional MPPT method and particle swarm optimization (PSO) algorithm. Under different operating conditions of PV cells, different tracking algorithms are used. When the environment changes, the improved PSO algorithm is adopted to realize the global optimal search, and the variable step incremental conductance (INC) method is adopted to achieve MPPT in optimal local location. Based on the simulation model of the PV grid system built in Matlab/Simulink, comparative analysis of the tracking effect of MPPT by the proposed control algorithm and the traditional MPPT method under the uniform solar condition and PSC, validate the correctness, feasibility and effectiveness of the proposed control strategy.

Nonlinear Multiobjective MPC-Based Optimal Operation of a High Consistency Refining System in Papermaking

DOE PAGES

Li, Mingjie; Zhou, Ping; Wang, Hong; ...

2017-09-19

As one of the most important unit in the papermaking industry, the high consistency (HC) refining system is confronted with challenges such as improving pulp quality, energy saving, and emissions reduction in its operation processes. Here in this correspondence, an optimal operation of HC refining system is presented using nonlinear multiobjective model predictive control strategies that aim at set-point tracking objective of pulp quality, economic objective, and specific energy (SE) consumption objective, respectively. First, a set of input and output data at different times are employed to construct the subprocess model of the state process model for the HC refiningmore » system, and then the Wiener-type model can be obtained through combining the mechanism model of Canadian Standard Freeness and the state process model that determines their structures based on Akaike information criterion. Second, the multiobjective optimization strategy that optimizes both the set-point tracking objective of pulp quality and SE consumption is proposed simultaneously, which uses NSGA-II approach to obtain the Pareto optimal set. Furthermore, targeting at the set-point tracking objective of pulp quality, economic objective, and SE consumption objective, the sequential quadratic programming method is utilized to produce the optimal predictive controllers. In conclusion, the simulation results demonstrate that the proposed methods can make the HC refining system provide a better performance of set-point tracking of pulp quality when these predictive controllers are employed. In addition, while the optimal predictive controllers orienting with comprehensive economic objective and SE consumption objective, it has been shown that they have significantly reduced the energy consumption.« less

Nonlinear Multiobjective MPC-Based Optimal Operation of a High Consistency Refining System in Papermaking

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

Li, Mingjie; Zhou, Ping; Wang, Hong

As one of the most important unit in the papermaking industry, the high consistency (HC) refining system is confronted with challenges such as improving pulp quality, energy saving, and emissions reduction in its operation processes. Here in this correspondence, an optimal operation of HC refining system is presented using nonlinear multiobjective model predictive control strategies that aim at set-point tracking objective of pulp quality, economic objective, and specific energy (SE) consumption objective, respectively. First, a set of input and output data at different times are employed to construct the subprocess model of the state process model for the HC refiningmore » system, and then the Wiener-type model can be obtained through combining the mechanism model of Canadian Standard Freeness and the state process model that determines their structures based on Akaike information criterion. Second, the multiobjective optimization strategy that optimizes both the set-point tracking objective of pulp quality and SE consumption is proposed simultaneously, which uses NSGA-II approach to obtain the Pareto optimal set. Furthermore, targeting at the set-point tracking objective of pulp quality, economic objective, and SE consumption objective, the sequential quadratic programming method is utilized to produce the optimal predictive controllers. In conclusion, the simulation results demonstrate that the proposed methods can make the HC refining system provide a better performance of set-point tracking of pulp quality when these predictive controllers are employed. In addition, while the optimal predictive controllers orienting with comprehensive economic objective and SE consumption objective, it has been shown that they have significantly reduced the energy consumption.« less

Perceptual control models of pursuit manual tracking demonstrate individual specificity and parameter consistency.

PubMed

Parker, Maximilian G; Tyson, Sarah F; Weightman, Andrew P; Abbott, Bruce; Emsley, Richard; Mansell, Warren

2017-11-01

Computational models that simulate individuals' movements in pursuit-tracking tasks have been used to elucidate mechanisms of human motor control. Whilst there is evidence that individuals demonstrate idiosyncratic control-tracking strategies, it remains unclear whether models can be sensitive to these idiosyncrasies. Perceptual control theory (PCT) provides a unique model architecture with an internally set reference value parameter, and can be optimized to fit an individual's tracking behavior. The current study investigated whether PCT models could show temporal stability and individual specificity over time. Twenty adults completed three blocks of 15 1-min, pursuit-tracking trials. Two blocks (training and post-training) were completed in one session and the third was completed after 1 week (follow-up). The target moved in a one-dimensional, pseudorandom pattern. PCT models were optimized to the training data using a least-mean-squares algorithm, and validated with data from post-training and follow-up. We found significant inter-individual variability (partial η 2 : .464-.697) and intra-individual consistency (Cronbach's α: .880-.976) in parameter estimates. Polynomial regression revealed that all model parameters, including the reference value parameter, contribute to simulation accuracy. Participants' tracking performances were significantly more accurately simulated by models developed from their own tracking data than by models developed from other participants' data. We conclude that PCT models can be optimized to simulate the performance of an individual and that the test-retest reliability of individual models is a necessary criterion for evaluating computational models of human performance.

Optimality based repetitive controller design for track-following servo system of optical disk drives.

PubMed

Chen, Wentao; Zhang, Weidong

2009-10-01

In an optical disk drive servo system, to attenuate the external periodic disturbances induced by inevitable disk eccentricity, repetitive control has been used successfully. The performance of a repetitive controller greatly depends on the bandwidth of the low-pass filter included in the repetitive controller. However, owing to the plant uncertainty and system stability, it is difficult to maximize the bandwidth of the low-pass filter. In this paper, we propose an optimality based repetitive controller design method for the track-following servo system with norm-bounded uncertainties. By embedding a lead compensator in the repetitive controller, both the system gain at periodic signal's harmonics and the bandwidth of the low-pass filter are greatly increased. The optimal values of the repetitive controller's parameters are obtained by solving two optimization problems. Simulation and experimental results are provided to illustrate the effectiveness of the proposed method.

Distributed cooperative H∞ optimal tracking control of MIMO nonlinear multi-agent systems in strict-feedback form via adaptive dynamic programming

NASA Astrophysics Data System (ADS)

Luy, N. T.

2018-04-01

The design of distributed cooperative H∞ optimal controllers for multi-agent systems is a major challenge when the agents' models are uncertain multi-input and multi-output nonlinear systems in strict-feedback form in the presence of external disturbances. In this paper, first, the distributed cooperative H∞ optimal tracking problem is transformed into controlling the cooperative tracking error dynamics in affine form. Second, control schemes and online algorithms are proposed via adaptive dynamic programming (ADP) and the theory of zero-sum differential graphical games. The schemes use only one neural network (NN) for each agent instead of three from ADP to reduce computational complexity as well as avoid choosing initial NN weights for stabilising controllers. It is shown that despite not using knowledge of cooperative internal dynamics, the proposed algorithms not only approximate values to Nash equilibrium but also guarantee all signals, such as the NN weight approximation errors and the cooperative tracking errors in the closed-loop system, to be uniformly ultimately bounded. Finally, the effectiveness of the proposed method is shown by simulation results of an application to wheeled mobile multi-robot systems.

Neural-Network-Based Robust Optimal Tracking Control for MIMO Discrete-Time Systems With Unknown Uncertainty Using Adaptive Critic Design.

PubMed

Liu, Lei; Wang, Zhanshan; Zhang, Huaguang

2018-04-01

This paper is concerned with the robust optimal tracking control strategy for a class of nonlinear multi-input multi-output discrete-time systems with unknown uncertainty via adaptive critic design (ACD) scheme. The main purpose is to establish an adaptive actor-critic control method, so that the cost function in the procedure of dealing with uncertainty is minimum and the closed-loop system is stable. Based on the neural network approximator, an action network is applied to generate the optimal control signal and a critic network is used to approximate the cost function, respectively. In contrast to the previous methods, the main features of this paper are: 1) the ACD scheme is integrated into the controllers to cope with the uncertainty and 2) a novel cost function, which is not in quadric form, is proposed so that the total cost in the design procedure is reduced. It is proved that the optimal control signals and the tracking errors are uniformly ultimately bounded even when the uncertainty exists. Finally, a numerical simulation is developed to show the effectiveness of the present approach.

Orbital and angular motion construction for low thrust interplanetary flight

NASA Astrophysics Data System (ADS)

Yelnikov, R. V.; Mashtakov, Y. V.; Ovchinnikov, M. Yu.; Tkachev, S. S.

2016-11-01

Low thrust interplanetary flight is considered. Firstly, the fuel-optimal control is found. Then the angular motion is synthesized. This motion provides the thruster tracking of the required by optimal control direction. And, finally, reaction wheel control law for tracking this angular motion is proposed and implemented. The numerical example is given and total operation time for thrusters is found. Disturbances from solar pressure, thrust eccentricity, inaccuracy of reaction wheels installation and errors of inertia tensor are taken into account.

Safe-trajectory optimization and tracking control in ultra-close proximity to a failed satellite

NASA Astrophysics Data System (ADS)

Zhang, Jingrui; Chu, Xiaoyu; Zhang, Yao; Hu, Quan; Zhai, Guang; Li, Yanyan

2018-03-01

This paper presents a trajectory-optimization method for a chaser spacecraft operating in ultra-close proximity to a failed satellite. Based on the combination of active and passive trajectory protection, the constraints in the optimization framework are formulated for collision avoidance and successful docking in the presence of any thruster failure. The constraints are then handled by an adaptive Gauss pseudospectral method, in which the dynamic residuals are used as the metric to determine the distribution of collocation points. A finite-time feedback control is further employed in tracking the optimized trajectory. In particular, the stability and convergence of the controller are proved. Numerical results are given to demonstrate the effectiveness of the proposed methods.

An optimal model-based trajectory following architecture synthesising the lateral adaptive preview strategy and longitudinal velocity planning for highly automated vehicle

NASA Astrophysics Data System (ADS)

Cao, Haotian; Song, Xiaolin; Zhao, Song; Bao, Shan; Huang, Zhi

2017-08-01

Automated driving has received a broad of attentions from the academia and industry, since it is effective to greatly reduce the severity of potential traffic accidents and achieve the ultimate automobile safety and comfort. This paper presents an optimal model-based trajectory following architecture for highly automated vehicle in its driving tasks such as automated guidance or lane keeping, which includes a velocity-planning module, a steering controller and a velocity-tracking controller. The velocity-planning module considering the optimal time-consuming and passenger comforts simultaneously could generate a smooth velocity profile. The robust sliding mode control (SMC) steering controller with adaptive preview time strategy could not only track the target path well, but also avoid a big lateral acceleration occurred in its path-tracking progress due to a fuzzy-adaptive preview time mechanism introduced. In addition, an SMC controller with input-output linearisation method for velocity tracking is built and validated. Simulation results show this trajectory following architecture are effective and feasible for high automated driving vehicle, comparing with the Driver-in-the-Loop simulations performed by an experienced driver and novice driver, respectively. The simulation results demonstrate that the present trajectory following architecture could plan a satisfying longitudinal speed profile, track the target path well and safely when dealing with different road geometry structure, it ensures a good time efficiency and driving comfort simultaneously.

Performance Optimizing Multi-Objective Adaptive Control with Time-Varying Model Reference Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan

2017-01-01

This paper presents a new adaptive control approach that involves a performance optimization objective. The problem is cast as a multi-objective optimal control. The control synthesis involves the design of a performance optimizing controller from a subset of control inputs. The effect of the performance optimizing controller is to introduce an uncertainty into the system that can degrade tracking of the reference model. An adaptive controller from the remaining control inputs is designed to reduce the effect of the uncertainty while maintaining a notion of performance optimization in the adaptive control system.

Evaluation of optimal control type models for the human gunner in an Anti-Aircraft Artillery (AAA) system

NASA Technical Reports Server (NTRS)

Phatak, A. V.; Kessler, K. M.

1975-01-01

The selection of the structure of optimal control type models for the human gunner in an anti aircraft artillery system is considered. Several structures within the LQG framework may be formulated. Two basic types are considered: (1) kth derivative controllers; and (2) proportional integral derivative (P-I-D) controllers. It is shown that a suitable criterion for model structure determination can be based on the ensemble statistics of the tracking error. In the case when the ensemble tracking steady state error is zero, it is suggested that a P-I-D controller formulation be used in preference to the kth derivative controller.

Toward Optimization of Gaze-Controlled Human-Computer Interaction: Application to Hindi Virtual Keyboard for Stroke Patients.

PubMed

Meena, Yogesh Kumar; Cecotti, Hubert; Wong-Lin, Kongfatt; Dutta, Ashish; Prasad, Girijesh

2018-04-01

Virtual keyboard applications and alternative communication devices provide new means of communication to assist disabled people. To date, virtual keyboard optimization schemes based on script-specific information, along with multimodal input access facility, are limited. In this paper, we propose a novel method for optimizing the position of the displayed items for gaze-controlled tree-based menu selection systems by considering a combination of letter frequency and command selection time. The optimized graphical user interface layout has been designed for a Hindi language virtual keyboard based on a menu wherein 10 commands provide access to type 88 different characters, along with additional text editing commands. The system can be controlled in two different modes: eye-tracking alone and eye-tracking with an access soft-switch. Five different keyboard layouts have been presented and evaluated with ten healthy participants. Furthermore, the two best performing keyboard layouts have been evaluated with eye-tracking alone on ten stroke patients. The overall performance analysis demonstrated significantly superior typing performance, high usability (87% SUS score), and low workload (NASA TLX with 17 scores) for the letter frequency and time-based organization with script specific arrangement design. This paper represents the first optimized gaze-controlled Hindi virtual keyboard, which can be extended to other languages.

Optimal control of motorsport differentials

NASA Astrophysics Data System (ADS)

Tremlett, A. J.; Massaro, M.; Purdy, D. J.; Velenis, E.; Assadian, F.; Moore, A. P.; Halley, M.

2015-12-01

Modern motorsport limited slip differentials (LSD) have evolved to become highly adjustable, allowing the torque bias that they generate to be tuned in the corner entry, apex and corner exit phases of typical on-track manoeuvres. The task of finding the optimal torque bias profile under such varied vehicle conditions is complex. This paper presents a nonlinear optimal control method which is used to find the minimum time optimal torque bias profile through a lane change manoeuvre. The results are compared to traditional open and fully locked differential strategies, in addition to considering related vehicle stability and agility metrics. An investigation into how the optimal torque bias profile changes with reduced track-tyre friction is also included in the analysis. The optimal LSD profile was shown to give a performance gain over its locked differential counterpart in key areas of the manoeuvre where a quick direction change is required. The methodology proposed can be used to find both optimal passive LSD characteristics and as the basis of a semi-active LSD control algorithm.

Analytical solutions to optimal underactuated spacecraft formation reconfiguration

NASA Astrophysics Data System (ADS)

Huang, Xu; Yan, Ye; Zhou, Yang

2015-11-01

Underactuated systems can generally be defined as systems with fewer number of control inputs than that of the degrees of freedom to be controlled. In this paper, analytical solutions to optimal underactuated spacecraft formation reconfiguration without either the radial or the in-track control are derived. By using a linear dynamical model of underactuated spacecraft formation in circular orbits, controllability analysis is conducted for either underactuated case. Indirect optimization methods based on the minimum principle are then introduced to generate analytical solutions to optimal open-loop underactuated reconfiguration problems. Both fixed and free final conditions constraints are considered for either underactuated case and comparisons between these two final conditions indicate that the optimal control strategies with free final conditions require less control efforts than those with the fixed ones. Meanwhile, closed-loop adaptive sliding mode controllers for both underactuated cases are designed to guarantee optimal trajectory tracking in the presence of unmatched external perturbations, linearization errors, and system uncertainties. The adaptation laws are designed via a Lyapunov-based method to ensure the overall stability of the closed-loop system. The explicit expressions of the terminal convergent regions of each system states have also been obtained. Numerical simulations demonstrate the validity and feasibility of the proposed open-loop and closed-loop control schemes for optimal underactuated spacecraft formation reconfiguration in circular orbits.

Neural network robust tracking control with adaptive critic framework for uncertain nonlinear systems.

PubMed

Wang, Ding; Liu, Derong; Zhang, Yun; Li, Hongyi

2018-01-01

In this paper, we aim to tackle the neural robust tracking control problem for a class of nonlinear systems using the adaptive critic technique. The main contribution is that a neural-network-based robust tracking control scheme is established for nonlinear systems involving matched uncertainties. The augmented system considering the tracking error and the reference trajectory is formulated and then addressed under adaptive critic optimal control formulation, where the initial stabilizing controller is not needed. The approximate control law is derived via solving the Hamilton-Jacobi-Bellman equation related to the nominal augmented system, followed by closed-loop stability analysis. The robust tracking control performance is guaranteed theoretically via Lyapunov approach and also verified through simulation illustration. Copyright © 2017 Elsevier Ltd. All rights reserved.

Design Method of Digital Optimal Control Scheme and Multiple Paralleled Bridge Type Current Amplifier for Generating Gradient Magnetic Fields in MRI Systems

NASA Astrophysics Data System (ADS)

Watanabe, Shuji; Takano, Hiroshi; Fukuda, Hiroya; Hiraki, Eiji; Nakaoka, Mutsuo

This paper deals with a digital control scheme of multiple paralleled high frequency switching current amplifier with four-quadrant chopper for generating gradient magnetic fields in MRI (Magnetic Resonance Imaging) systems. In order to track high precise current pattern in Gradient Coils (GC), the proposal current amplifier cancels the switching current ripples in GC with each other and designed optimum switching gate pulse patterns without influences of the large filter current ripple amplitude. The optimal control implementation and the linear control theory in GC current amplifiers have affinity to each other with excellent characteristics. The digital control system can be realized easily through the digital control implementation, DSPs or microprocessors. Multiple-parallel operational microprocessors realize two or higher paralleled GC current pattern tracking amplifier with optimal control design and excellent results are given for improving the image quality of MRI systems.

Optimal Variable-Structure Control Tracking of Spacecraft Maneuvers

NASA Technical Reports Server (NTRS)

Crassidis, John L.; Vadali, Srinivas R.; Markley, F. Landis

1999-01-01

An optimal control approach using variable-structure (sliding-mode) tracking for large angle spacecraft maneuvers is presented. The approach expands upon a previously derived regulation result using a quaternion parameterization for the kinematic equations of motion. This parameterization is used since it is free of singularities. The main contribution of this paper is the utilization of a simple term in the control law that produces a maneuver to the reference attitude trajectory in the shortest distance. Also, a multiplicative error quaternion between the desired and actual attitude is used to derive the control law. Sliding-mode switching surfaces are derived using an optimal-control analysis. Control laws are given using either external torque commands or reaction wheel commands. Global asymptotic stability is shown for both cases using a Lyapunov analysis. Simulation results are shown which use the new control strategy to stabilize the motion of the Microwave Anisotropy Probe spacecraft.

Investigation, development and application of optimal output feedback theory. Volume 2: Development of an optimal, limited state feedback outer-loop digital flight control system for 3-D terminal area operation

NASA Technical Reports Server (NTRS)

Broussard, J. R.; Halyo, N.

1984-01-01

This report contains the development of a digital outer-loop three dimensional radio navigation (3-D RNAV) flight control system for a small commercial jet transport. The outer-loop control system is designed using optimal stochastic limited state feedback techniques. Options investigated using the optimal limited state feedback approach include integrated versus hierarchical control loop designs, 20 samples per second versus 5 samples per second outer-loop operation and alternative Type 1 integration command errors. Command generator tracking techniques used in the digital control design enable the jet transport to automatically track arbitrary curved flight paths generated by waypoints. The performance of the design is demonstrated using detailed nonlinear aircraft simulations in the terminal area, frequency domain multi-input sigma plots, frequency domain single-input Bode plots and closed-loop poles. The response of the system to a severe wind shear during a landing approach is also presented.

Investigations into the design principles in the chemotactic behavior of Escherichia coli.

PubMed

Kim, Tae-Hwan; Jung, Sung Hoon; Cho, Kwang-Hyun

2008-01-01

Inspired by the recent studies on the analysis of biased random walk behavior of Escherichia coli[Passino, K.M., 2002. Biomimicry of bacterial foraging for distributed optimization and control. IEEE Control Syst. Mag. 22 (3), 52-67; Passino, K.M., 2005. Biomimicry for Optimization, Control and Automation. Springer-Verlag, pp. 768-798; Liu, Y., Passino, K.M., 2002. Biomimicry of social foraging bacteria for distributed optimization: models, principles, and emergent behaviors. J. Optim. Theory Appl. 115 (3), 603-628], we have developed a model describing the motile behavior of E. coli by specifying some simple rules on the chemotaxis. Based on this model, we have analyzed the role of some key parameters involved in the chemotactic behavior to unravel the underlying design principles. By investigating the target tracking capability of E. coli in a maze through computer simulations, we found that E. coli clusters can be controlled as target trackers in a complex micro-scale-environment. In addition, we have explored the dynamical characteristics of this target tracking mechanism through perturbation of parameters under noisy environments. It turns out that the E. coli chemotaxis mechanism might be designed such that it is sensitive enough to efficiently track the target and also robust enough to overcome environmental noises.

On the internal target model in a tracking task

NASA Technical Reports Server (NTRS)

Caglayan, A. K.; Baron, S.

1981-01-01

An optimal control model for predicting operator's dynamic responses and errors in target tracking ability is summarized. The model, which predicts asymmetry in the tracking data, is dependent on target maneuvers and trajectories. Gunners perception, decision making, control, and estimate of target positions and velocity related to crossover intervals are discussed. The model provides estimates for means, standard deviations, and variances for variables investigated and for operator estimates of future target positions and velocities.

Graph-based geometric-iconic guide-wire tracking.

PubMed

Honnorat, Nicolas; Vaillant, Régis; Paragios, Nikos

2011-01-01

In this paper we introduce a novel hybrid graph-based approach for Guide-wire tracking. The image support is captured by steerable filters and improved through tensor voting. Then, a graphical model is considered that represents guide-wire extraction/tracking through a B-spline control-point model. Points with strong geometric interest (landmarks) are automatically determined and anchored to such a representation. Tracking is then performed through discrete MRFs that optimize the spatio-temporal positions of the control points while establishing landmark temporal correspondences. Promising results demonstrate the potentials of our method.

Optimal disturbance rejecting control of hyperbolic systems

NASA Technical Reports Server (NTRS)

Biswas, Saroj K.; Ahmed, N. U.

1994-01-01

Optimal regulation of hyperbolic systems in the presence of unknown disturbances is considered. Necessary conditions for determining the optimal control that tracks a desired trajectory in the presence of the worst possible perturbations are developed. The results also characterize the worst possible disturbance that the system will be able to tolerate before any degradation of the system performance. Numerical results on the control of a vibrating beam are presented.

Master-slave control with trajectory planning and Bouc-Wen model for tracking control of piezo-driven stage

NASA Astrophysics Data System (ADS)

Lu, Xiaojun; Liu, Changli; Chen, Lei

2018-04-01

In this paper, a redundant Piezo-driven stage having 3RRR compliant mechanism is introduced, we propose the master-slave control with trajectory planning (MSCTP) strategy and Bouc-Wen model to improve its micro-motion tracking performance. The advantage of the proposed controller lies in that its implementation only requires a simple control strategy without the complexity of modeling to avoid the master PEA's tracking error. The dynamic model of slave PEA system with Bouc-Wen hysteresis is established and identified via particle swarm optimization (PSO) approach. The Piezo-driven stage with operating period T=1s and 2s is implemented to track a prescribed circle. The simulation results show that MSCTP with Bouc-Wen model reduces the trajectory tracking errors to the range of the accuracy of our available measurement.

Dynamic optimization of ISR sensors using a risk-based reward function applied to ground and space surveillance scenarios

NASA Astrophysics Data System (ADS)

DeSena, J. T.; Martin, S. R.; Clarke, J. C.; Dutrow, D. A.; Newman, A. J.

2012-06-01

As the number and diversity of sensing assets available for intelligence, surveillance and reconnaissance (ISR) operations continues to expand, the limited ability of human operators to effectively manage, control and exploit the ISR ensemble is exceeded, leading to reduced operational effectiveness. Automated support both in the processing of voluminous sensor data and sensor asset control can relieve the burden of human operators to support operation of larger ISR ensembles. In dynamic environments it is essential to react quickly to current information to avoid stale, sub-optimal plans. Our approach is to apply the principles of feedback control to ISR operations, "closing the loop" from the sensor collections through automated processing to ISR asset control. Previous work by the authors demonstrated non-myopic multiple platform trajectory control using a receding horizon controller in a closed feedback loop with a multiple hypothesis tracker applied to multi-target search and track simulation scenarios in the ground and space domains. This paper presents extensions in both size and scope of the previous work, demonstrating closed-loop control, involving both platform routing and sensor pointing, of a multisensor, multi-platform ISR ensemble tasked with providing situational awareness and performing search, track and classification of multiple moving ground targets in irregular warfare scenarios. The closed-loop ISR system is fullyrealized using distributed, asynchronous components that communicate over a network. The closed-loop ISR system has been exercised via a networked simulation test bed against a scenario in the Afghanistan theater implemented using high-fidelity terrain and imagery data. In addition, the system has been applied to space surveillance scenarios requiring tracking of space objects where current deliberative, manually intensive processes for managing sensor assets are insufficiently responsive. Simulation experiment results are presented. The algorithm to jointly optimize sensor schedules against search, track, and classify is based on recent work by Papageorgiou and Raykin on risk-based sensor management. It uses a risk-based objective function and attempts to minimize and balance the risks of misclassifying and losing track on an object. It supports the requirement to generate tasking for metric and feature data concurrently and synergistically, and account for both tracking accuracy and object characterization, jointly, in computing reward and cost for optimizing tasking decisions.

Minimum energy control for a two-compartment neuron to extracellular electric fields

NASA Astrophysics Data System (ADS)

Yi, Guo-Sheng; Wang, Jiang; Li, Hui-Yan; Wei, Xi-Le; Deng, Bin

2016-11-01

The energy optimization of extracellular electric field (EF) stimulus for a neuron is considered in this paper. We employ the optimal control theory to design a low energy EF input for a reduced two-compartment model. It works by driving the neuron to closely track a prescriptive spike train. A cost function is introduced to balance the contradictory objectives, i.e., tracking errors and EF stimulus energy. By using the calculus of variations, we transform the minimization of cost function to a six-dimensional two-point boundary value problem (BVP). Through solving the obtained BVP in the cases of three fundamental bifurcations, it is shown that the control method is able to provide an optimal EF stimulus of reduced energy for the neuron to effectively track a prescriptive spike train. Further, the feasibility of the adopted method is interpreted from the point of view of the biophysical basis of spike initiation. These investigations are conducive to designing stimulating dose for extracellular neural stimulation, which are also helpful to interpret the effects of extracellular field on neural activity.

Improved design of constrained model predictive tracking control for batch processes against unknown uncertainties.

PubMed

Wu, Sheng; Jin, Qibing; Zhang, Ridong; Zhang, Junfeng; Gao, Furong

2017-07-01

In this paper, an improved constrained tracking control design is proposed for batch processes under uncertainties. A new process model that facilitates process state and tracking error augmentation with further additional tuning is first proposed. Then a subsequent controller design is formulated using robust stable constrained MPC optimization. Unlike conventional robust model predictive control (MPC), the proposed method enables the controller design to bear more degrees of tuning so that improved tracking control can be acquired, which is very important since uncertainties exist inevitably in practice and cause model/plant mismatches. An injection molding process is introduced to illustrate the effectiveness of the proposed MPC approach in comparison with conventional robust MPC. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Modeling human tracking error in several different anti-tank systems

NASA Technical Reports Server (NTRS)

Kleinman, D. L.

1981-01-01

An optimal control model for generating time histories of human tracking errors in antitank systems is outlined. Monte Carlo simulations of human operator responses for three Army antitank systems are compared. System/manipulator dependent data comparisons reflecting human operator limitations in perceiving displayed quantities and executing intended control motions are presented. Motor noise parameters are also discussed.

The Passive Series Stiffness That Optimizes Torque Tracking for a Lower-Limb Exoskeleton in Human Walking

PubMed Central

Zhang, Juanjuan; Collins, Steven H.

2017-01-01

This study uses theory and experiments to investigate the relationship between the passive stiffness of series elastic actuators and torque tracking performance in lower-limb exoskeletons during human walking. Through theoretical analysis with our simplified system model, we found that the optimal passive stiffness matches the slope of the desired torque-angle relationship. We also conjectured that a bandwidth limit resulted in a maximum rate of change in torque error that can be commanded through control input, which is fixed across desired and passive stiffness conditions. This led to hypotheses about the interactions among optimal control gains, passive stiffness and desired quasi-stiffness. Walking experiments were conducted with multiple angle-based desired torque curves. The observed lowest torque tracking errors identified for each combination of desired and passive stiffnesses were shown to be linearly proportional to the magnitude of the difference between the two stiffnesses. The proportional gains corresponding to the lowest observed errors were seen inversely proportional to passive stiffness values and to desired stiffness. These findings supported our hypotheses, and provide guidance to application-specific hardware customization as well as controller design for torque-controlled robotic legged locomotion. PMID:29326580

Optimal control to modelling motorcycle rider steering: local versus global coordinate systems in rider preview

NASA Astrophysics Data System (ADS)

Rowell, S.; Popov, A. A.; Meijaard, J. P.

2010-04-01

The response of a motorcycle is heavily dependent on the rider's control actions, and consequently a means of replicating the rider's behaviour provides an important extension to motorcycle dynamics. The primary objective here is to develop effective path-following simulations and to understand how riders control motorcycles. Optimal control theory is applied to the tracking of roadway by a motorcycle, using a non-linear motorcycle model operating in free control by steering torque input. A path-following controller with road preview is designed by minimising tracking errors and control effort. Tight controls with high weightings on performance and loose controls with high weightings on control power are defined. Special attention is paid to the modelling of multipoint preview in local and global coordinate systems. The controller model is simulated over a standard single lane-change manoeuvre. It is argued that the local coordinates point of view is more representative of the way that a human rider operates and interprets information. The simulations suggest that for accurate path following, using optimal control, the problem must be solved by the local coordinates approach in order to achieve accurate results with short preview horizons. Furthermore, some weaknesses of the optimal control approach are highlighted here.

Real Time Optima Tracking Using Harvesting Models of the Genetic Algorithm

NASA Technical Reports Server (NTRS)

Baskaran, Subbiah; Noever, D.

1999-01-01

Tracking optima in real time propulsion control, particularly for non-stationary optimization problems is a challenging task. Several approaches have been put forward for such a study including the numerical method called the genetic algorithm. In brief, this approach is built upon Darwinian-style competition between numerical alternatives displayed in the form of binary strings, or by analogy to 'pseudogenes'. Breeding of improved solution is an often cited parallel to natural selection in.evolutionary or soft computing. In this report we present our results of applying a novel model of a genetic algorithm for tracking optima in propulsion engineering and in real time control. We specialize the algorithm to mission profiling and planning optimizations, both to select reduced propulsion needs through trajectory planning and to explore time or fuel conservation strategies.

Radar coordination and resource management in a distributed sensor network using emergent control

NASA Astrophysics Data System (ADS)

Weir, B. S.; Sokol, T. M.

2009-05-01

As the list of anti-air warfare and ballistic missile defense missions grows, there is an increasing need to coordinate and optimize usage of radar resources across the netted force. Early attempts at this optimization involved top-down control mechanisms whereby sensors accept resource tasking orders from networked tracking elements. These approaches rely heavily on uncertain knowledge of sensor constraints and capabilities. Furthermore, advanced sensor systems may support self-defense missions of the host platform and are therefore unable to relinquish control to an external function. To surmount these issues, the use of bottom-up emergent control techniques is proposed. The information necessary to make quality, network-wide resource allocations is readily available to sensor nodes with access to a netted track picture. By assessing resource priorities relative to the network (versus local) track picture, sensors can understand the contribution of their resources to the netted force. This allows the sensors to apply resources where most needed and remove waste. Furthermore, simple local rules for resource usage, when properly constructed, allow sensors to obtain a globally optimal resource allocation without direct coordination (emergence). These results are robust to partial implementation (i.e., not all nodes upgraded at once) and failures on individual nodes (whether from casualty or reallocation to other sensor missions), and they leave resource control decisions in the hands of the sensor systems instead of an external function. This paper presents independent research and development work on emergent control of sensor resources and the impact to resource allocation and tracking performance.

Performance comparison of optimal fractional order hybrid fuzzy PID controllers for handling oscillatory fractional order processes with dead time.

PubMed

Das, Saptarshi; Pan, Indranil; Das, Shantanu

2013-07-01

Fuzzy logic based PID controllers have been studied in this paper, considering several combinations of hybrid controllers by grouping the proportional, integral and derivative actions with fuzzy inferencing in different forms. Fractional order (FO) rate of error signal and FO integral of control signal have been used in the design of a family of decomposed hybrid FO fuzzy PID controllers. The input and output scaling factors (SF) along with the integro-differential operators are tuned with real coded genetic algorithm (GA) to produce optimum closed loop performance by simultaneous consideration of the control loop error index and the control signal. Three different classes of fractional order oscillatory processes with various levels of relative dominance between time constant and time delay have been used to test the comparative merits of the proposed family of hybrid fractional order fuzzy PID controllers. Performance comparison of the different FO fuzzy PID controller structures has been done in terms of optimal set-point tracking, load disturbance rejection and minimal variation of manipulated variable or smaller actuator requirement etc. In addition, multi-objective Non-dominated Sorting Genetic Algorithm (NSGA-II) has been used to study the Pareto optimal trade-offs between the set point tracking and control signal, and the set point tracking and load disturbance performance for each of the controller structure to handle the three different types of processes. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Tracking with a Cooperatively Controlled Swarm of GMTI Equipped UAVS

DTIC Science & Technology

2008-12-02

with Ground Optimal Placement of GMTI UAVs for ground target tracking Abhijit Sinha°, Thia. Kirubarajana and Yaakov Bar-Shalom6 " Electrical and...Storrs, CT 06269, USA Abstract—With the recent advent of moderate-cost unmanned (or uninhabited) aerial vehicles (UAV) and their success in...the sensor platforms are mobile one has to decide the optimal placement of sensors. With the recent advent of af- fordable unmanned aerial vehicles

Norm-Optimal ILC Applied to a High-Speed Rack Feeder

NASA Astrophysics Data System (ADS)

Schindele, Dominik; Aschemann, Harald; Ritzke, Jöran

2010-09-01

Rack feeders as automated conveying systems for high bay rackings are of high practical importance. To shorten the transport times by using trajectories with increased kinematic values accompanying control measures for a reduction of the excited structural vibrations are necessary. In this contribution, the model-based design of a norm-optimal iterative learning control structure is presented. The rack feeder is modelled as an elastic multibody system. For the mathematical description of the bending deflections a Ritz ansatz is introduced. The tracking control design is performed separately for both axes using decentralised state space representations. Both the achievable performance and the resulting tracking accuracy of the proposed control concept are shown by measurement results from the experimental set-up.

Development of a new integrated local trajectory planning and tracking control framework for autonomous ground vehicles

NASA Astrophysics Data System (ADS)

Li, Xiaohui; Sun, Zhenping; Cao, Dongpu; Liu, Daxue; He, Hangen

2017-03-01

This study proposes a novel integrated local trajectory planning and tracking control (ILTPTC) framework for autonomous vehicles driving along a reference path with obstacles avoidance. For this ILTPTC framework, an efficient state-space sampling-based trajectory planning scheme is employed to smoothly follow the reference path. A model-based predictive path generation algorithm is applied to produce a set of smooth and kinematically-feasible paths connecting the initial state with the sampling terminal states. A velocity control law is then designed to assign a speed value at each of the points along the generated paths. An objective function considering both safety and comfort performance is carefully formulated for assessing the generated trajectories and selecting the optimal one. For accurately tracking the optimal trajectory while overcoming external disturbances and model uncertainties, a combined feedforward and feedback controller is developed. Both simulation analyses and vehicle testing are performed to verify the effectiveness of the proposed ILTPTC framework, and future research is also briefly discussed.

Loop shaping design for tracking performance in machine axes.

PubMed

Schinstock, Dale E; Wei, Zhouhong; Yang, Tao

2006-01-01

A modern interpretation of classical loop shaping control design methods is presented in the context of tracking control for linear motor stages. Target applications include noncontacting machines such as laser cutters and markers, water jet cutters, and adhesive applicators. The methods are directly applicable to the common PID controller and are pertinent to many electromechanical servo actuators other than linear motors. In addition to explicit design techniques a PID tuning algorithm stressing the importance of tracking is described. While the theory behind these techniques is not new, the analysis of their application to modern systems is unique in the research literature. The techniques and results should be important to control practitioners optimizing PID controller designs for tracking and in comparing results from classical designs to modern techniques. The methods stress high-gain controller design and interpret what this means for PID. Nothing in the methods presented precludes the addition of feedforward control methods for added improvements in tracking. Laboratory results from a linear motor stage demonstrate that with large open-loop gain very good tracking performance can be achieved. The resultant tracking errors compare very favorably to results from similar motions on similar systems that utilize much more complicated controllers.

The 14th Annual Conference on Manual Control. [digital simulation of human operator dynamics

NASA Technical Reports Server (NTRS)

1978-01-01

Human operator dynamics during actual manual control or while monitoring the automatic control systems involved in air-to-air tracking, automobile driving, the operator of undersea vehicles, and remote handling are examined. Optimal control models and the use of mathematical theory in representing man behavior in complex man machine system tasks are discussed with emphasis on eye/head tracking and scanning; perception and attention allocation; decision making; and motion simulation and effects.

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.

Eye gaze tracking for endoscopic camera positioning: an application of a hardware/software interface developed to automate Aesop.

PubMed

Ali, S M; Reisner, L A; King, B; Cao, A; Auner, G; Klein, M; Pandya, A K

2008-01-01

A redesigned motion control system for the medical robot Aesop allows automating and programming its movements. An IR eye tracking system has been integrated with this control interface to implement an intelligent, autonomous eye gaze-based laparoscopic positioning system. A laparoscopic camera held by Aesop can be moved based on the data from the eye tracking interface to keep the user's gaze point region at the center of a video feedback monitor. This system setup provides autonomous camera control that works around the surgeon, providing an optimal robotic camera platform.

Optimal critic learning for robot control in time-varying environments.

PubMed

Wang, Chen; Li, Yanan; Ge, Shuzhi Sam; Lee, Tong Heng

2015-10-01

In this paper, optimal critic learning is developed for robot control in a time-varying environment. The unknown environment is described as a linear system with time-varying parameters, and impedance control is employed for the interaction control. Desired impedance parameters are obtained in the sense of an optimal realization of the composite of trajectory tracking and force regulation. Q -function-based critic learning is developed to determine the optimal impedance parameters without the knowledge of the system dynamics. The simulation results are presented and compared with existing methods, and the efficacy of the proposed method is verified.

Robust Sliding Mode Control Based on GA Optimization and CMAC Compensation for Lower Limb Exoskeleton

PubMed Central

Long, Yi; Du, Zhi-jiang; Wang, Wei-dong; Dong, Wei

2016-01-01

A lower limb assistive exoskeleton is designed to help operators walk or carry payloads. The exoskeleton is required to shadow human motion intent accurately and compliantly to prevent incoordination. If the user's intention is estimated accurately, a precise position control strategy will improve collaboration between the user and the exoskeleton. In this paper, a hybrid position control scheme, combining sliding mode control (SMC) with a cerebellar model articulation controller (CMAC) neural network, is proposed to control the exoskeleton to react appropriately to human motion intent. A genetic algorithm (GA) is utilized to determine the optimal sliding surface and the sliding control law to improve performance of SMC. The proposed control strategy (SMC_GA_CMAC) is compared with three other types of approaches, that is, conventional SMC without optimization, optimal SMC with GA (SMC_GA), and SMC with CMAC compensation (SMC_CMAC), all of which are employed to track the desired joint angular position which is deduced from Clinical Gait Analysis (CGA) data. Position tracking performance is investigated with cosimulation using ADAMS and MATLAB/SIMULINK in two cases, of which the first case is without disturbances while the second case is with a bounded disturbance. The cosimulation results show the effectiveness of the proposed control strategy which can be employed in similar exoskeleton systems. PMID:27069353

Robust Sliding Mode Control Based on GA Optimization and CMAC Compensation for Lower Limb Exoskeleton.

PubMed

Long, Yi; Du, Zhi-Jiang; Wang, Wei-Dong; Dong, Wei

2016-01-01

A lower limb assistive exoskeleton is designed to help operators walk or carry payloads. The exoskeleton is required to shadow human motion intent accurately and compliantly to prevent incoordination. If the user's intention is estimated accurately, a precise position control strategy will improve collaboration between the user and the exoskeleton. In this paper, a hybrid position control scheme, combining sliding mode control (SMC) with a cerebellar model articulation controller (CMAC) neural network, is proposed to control the exoskeleton to react appropriately to human motion intent. A genetic algorithm (GA) is utilized to determine the optimal sliding surface and the sliding control law to improve performance of SMC. The proposed control strategy (SMC_GA_CMAC) is compared with three other types of approaches, that is, conventional SMC without optimization, optimal SMC with GA (SMC_GA), and SMC with CMAC compensation (SMC_CMAC), all of which are employed to track the desired joint angular position which is deduced from Clinical Gait Analysis (CGA) data. Position tracking performance is investigated with cosimulation using ADAMS and MATLAB/SIMULINK in two cases, of which the first case is without disturbances while the second case is with a bounded disturbance. The cosimulation results show the effectiveness of the proposed control strategy which can be employed in similar exoskeleton systems.

Modal-space reference-model-tracking fuzzy control of earthquake excited structures

NASA Astrophysics Data System (ADS)

Park, Kwan-Soon; Ok, Seung-Yong

2015-01-01

This paper describes an adaptive modal-space reference-model-tracking fuzzy control technique for the vibration control of earthquake-excited structures. In the proposed approach, the fuzzy logic is introduced to update optimal control force so that the controlled structural response can track the desired response of a reference model. For easy and practical implementation, the reference model is constructed by assigning the target damping ratios to the first few dominant modes in modal space. The numerical simulation results demonstrate that the proposed approach successfully achieves not only the adaptive fault-tolerant control system against partial actuator failures but also the robust performance against the variations of the uncertain system properties by redistributing the feedback control forces to the available actuators.

Optimal Design of MPPT Controllers for Grid Connected Photovoltaic Array System

NASA Astrophysics Data System (ADS)

Ebrahim, M. A.; AbdelHadi, H. A.; Mahmoud, H. M.; Saied, E. M.; Salama, M. M.

2016-10-01

Integrating photovoltaic (PV) plants into electric power system exhibits challenges to power system dynamic performance. These challenges stem primarily from the natural characteristics of PV plants, which differ in some respects from the conventional plants. The most significant challenge is how to extract and regulate the maximum power from the sun. This paper presents the optimal design for the most commonly used Maximum Power Point Tracking (MPPT) techniques based on Proportional Integral tuned by Particle Swarm Optimization (PI-PSO). These suggested techniques are, (1) the incremental conductance, (2) perturb and observe, (3) fractional short circuit current and (4) fractional open circuit voltage techniques. This research work provides a comprehensive comparative study with the energy availability ratio from photovoltaic panels. The simulation results proved that the proposed controllers have an impressive tracking response. The system dynamic performance improved greatly using the proposed controllers.

Lane changing trajectory planning and tracking control for intelligent vehicle on curved road.

PubMed

Wang, Lukun; Zhao, Xiaoying; Su, Hao; Tang, Gongyou

2016-01-01

This paper explores lane changing trajectory planning and tracking control for intelligent vehicle on curved road. A novel arcs trajectory is planned for the desired lane changing trajectory. A kinematic controller and a dynamics controller are designed to implement the trajectory tracking control. Firstly, the kinematic model and dynamics model of intelligent vehicle with non-holonomic constraint are established. Secondly, two constraints of lane changing on curved road in practice (LCCP) are proposed. Thirdly, two arcs with same curvature are constructed for the desired lane changing trajectory. According to the geometrical characteristics of arcs trajectory, equations of desired state can be calculated. Finally, the backstepping method is employed to design a kinematic trajectory tracking controller. Then the sliding-mode dynamics controller is designed to ensure that the motion of the intelligent vehicle can follow the desired velocity generated by kinematic controller. The stability of control system is proved by Lyapunov theory. Computer simulation demonstrates that the desired arcs trajectory and state curves with B-spline optimization can meet the requirements of LCCP constraints and the proposed control schemes can make tracking errors to converge uniformly.

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.

Adaptive Optimal Control Using Frequency Selective Information of the System Uncertainty With Application to Unmanned Aircraft.

PubMed

Maity, Arnab; Hocht, Leonhard; Heise, Christian; Holzapfel, Florian

2018-01-01

A new efficient adaptive optimal control approach is presented in this paper based on the indirect model reference adaptive control (MRAC) architecture for improvement of adaptation and tracking performance of the uncertain system. The system accounts here for both matched and unmatched unknown uncertainties that can act as plant as well as input effectiveness failures or damages. For adaptation of the unknown parameters of these uncertainties, the frequency selective learning approach is used. Its idea is to compute a filtered expression of the system uncertainty using multiple filters based on online instantaneous information, which is used for augmentation of the update law. It is capable of adjusting a sudden change in system dynamics without depending on high adaptation gains and can satisfy exponential parameter error convergence under certain conditions in the presence of structured matched and unmatched uncertainties as well. Additionally, the controller of the MRAC system is designed using a new optimal control method. This method is a new linear quadratic regulator-based optimal control formulation for both output regulation and command tracking problems. It provides a closed-form control solution. The proposed overall approach is applied in a control of lateral dynamics of an unmanned aircraft problem to show its effectiveness.

End-point controller design for an experimental two-link flexible manipulator using convex optimization

NASA Technical Reports Server (NTRS)

Oakley, Celia M.; Barratt, Craig H.

1990-01-01

Recent results in linear controller design are used to design an end-point controller for an experimental two-link flexible manipulator. A nominal 14-state linear-quadratic-Gaussian (LQG) controller was augmented with a 528-tap finite-impulse-response (FIR) filter designed using convex optimization techniques. The resulting 278-state controller produced improved end-point trajectory tracking and disturbance rejection in simulation and experimentally in real time.

Proportional plus integral MIMO controller for regulation and tracking with anti-wind-up features

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

Puleston, P.F.; Mantz, R.J.

1993-11-01

A proportional plus integral matrix control structure for MIMO systems is proposed. Based on a standard optimal control structure with integral action, it permits a greater degree of independence of the design and tuning of the regulating and tracking features, without considerably increasing the controller complexity. Fast recovery from load disturbances is achieved, while large overshoots associated with set-point changes and reset wind-up problems can be reduced. A simple effective procedure for practical tuning is introduced.

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

Cheung, Michael L M; Chan, Anthony T C; The Chinese University of Hong Kong

Purpose: To develop a formulation for 4D treatment planning for a tumour tracking volumetric modulated arc therapy treatment (VMAT) plan for lung cancer. Methods: A VMAT plan was optimized based on a reference phase of the 4DCT of a lung cancer patient. The PTV was generated from the GTV of the reference phase. The collimator angle was set to 90 degrees such that the MLC travels along superior-inferior direction which is the main component of movement of a lung tumour. Then, each control point of the VMAT plan was assigned to a particular phase of the 4DCT in chronological order.more » The MLC positions of each control point were shifted according to the position of the tumour centroid of its assigned phase to form a tumour tracking VMAT plan. The control points of the same phase were grouped to form a pseudo VMAT plan for that particular phase. Dose calculation was performed for each pseudo VMAT plan on the corresponding phase of the 4DCT. The CTs of all phases were registered to the reference phase CT according to the displacement of the tumour centroid. The individual dose distributions of the pseudo VMAT plans were summed up and displayed on the reference phase of the 4DCT. A control VMAT plan was optimized based on a PTV generated from the ITV of all phases and compared with the tumour tracking VMAT plan. Results: Both plans achieved >95% volume coverage at the prescription dose level (96% for the tumour tracking plan and 97% for the control plan). But the normal lung volume irradiated at the prescription dose level was 39% less for the tumour tracking plan than the control plan. Conclusion: A formulation of 4D treatment planning for tumour tracking VMAT plans for lung cancer was developed.« less

Design and control of the precise tracking bed based on complex electromechanical design theory

NASA Astrophysics Data System (ADS)

Ren, Changzhi; Liu, Zhao; Wu, Liao; Chen, Ken

2010-05-01

The precise tracking technology is wide used in astronomical instruments, satellite tracking and aeronautic test bed. However, the precise ultra low speed tracking drive system is one high integrated electromechanical system, which one complexly electromechanical design method is adopted to improve the efficiency, reliability and quality of the system during the design and manufacture circle. The precise Tracking Bed is one ultra-exact, ultra-low speed, high precision and huge inertial instrument, which some kind of mechanism and environment of the ultra low speed is different from general technology. This paper explores the design process based on complex electromechanical optimizing design theory, one non-PID with a CMAC forward feedback control method is used in the servo system of the precise tracking bed and some simulation results are discussed.

An evolutionary computation based algorithm for calculating solar differential rotation by automatic tracking of coronal bright points

NASA Astrophysics Data System (ADS)

Shahamatnia, Ehsan; Dorotovič, Ivan; Fonseca, Jose M.; Ribeiro, Rita A.

2016-03-01

Developing specialized software tools is essential to support studies of solar activity evolution. With new space missions such as Solar Dynamics Observatory (SDO), solar images are being produced in unprecedented volumes. To capitalize on that huge data availability, the scientific community needs a new generation of software tools for automatic and efficient data processing. In this paper a prototype of a modular framework for solar feature detection, characterization, and tracking is presented. To develop an efficient system capable of automatic solar feature tracking and measuring, a hybrid approach combining specialized image processing, evolutionary optimization, and soft computing algorithms is being followed. The specialized hybrid algorithm for tracking solar features allows automatic feature tracking while gathering characterization details about the tracked features. The hybrid algorithm takes advantages of the snake model, a specialized image processing algorithm widely used in applications such as boundary delineation, image segmentation, and object tracking. Further, it exploits the flexibility and efficiency of Particle Swarm Optimization (PSO), a stochastic population based optimization algorithm. PSO has been used successfully in a wide range of applications including combinatorial optimization, control, clustering, robotics, scheduling, and image processing and video analysis applications. The proposed tool, denoted PSO-Snake model, was already successfully tested in other works for tracking sunspots and coronal bright points. In this work, we discuss the application of the PSO-Snake algorithm for calculating the sidereal rotational angular velocity of the solar corona. To validate the results we compare them with published manual results performed by an expert.

Permanent magnet synchronous motor servo system control based on μC/OS

NASA Astrophysics Data System (ADS)

Shi, Chongyang; Chen, Kele; Chen, Xinglong

2015-10-01

When Opto-Electronic Tracking system operates in complex environments, every subsystem must operate efficiently and stably. As a important part of Opto-Electronic Tracking system, the performance of PMSM(Permanent Magnet Synchronous Motor) servo system affects the Opto-Electronic Tracking system's accuracy and speed greatly[1][2]. This paper applied embedded real-time operating system μC/OS to the control of PMSM servo system, implemented SVPWM(Space Vector Pulse Width Modulation) algorithm in PMSM servo system, optimized the stability of PMSM servo system. Pointing on the characteristics of the Opto-Electronic Tracking system, this paper expanded μC/OS with software redundancy processes, remote debugging and upgrading. As a result, the Opto- Electronic Tracking system performs efficiently and stably.

Optimization design about gimbal structure of high-precision autonomous celestial navigation tracking mirror system

NASA Astrophysics Data System (ADS)

Huang, Wei; Yang, Xiao-xu; Han, Jun-feng; Wei, Yu; Zhang, Jing; Xie, Mei-lin; Yue, Peng

2016-01-01

High precision tracking platform of celestial navigation with control mirror servo structure form, to solve the disadvantages of big volume and rotational inertia, slow response speed, and so on. It improved the stability and tracking accuracy of platform. Due to optical sensor and mirror are installed on the middle-gimbal, stiffness and resonant frequency requirement for high. Based on the application of finite element modality analysis theory, doing Research on dynamic characteristics of the middle-gimbal, and ANSYS was used for the finite element dynamic emulator analysis. According to the result of the computer to find out the weak links of the structure, and Put forward improvement suggestions and reanalysis. The lowest resonant frequency of optimization middle-gimbal avoid the bandwidth of the platform servo mechanism, and much higher than the disturbance frequency of carrier aircraft, and reduces mechanical resonance of the framework. Reaching provides a theoretical basis for the whole machine structure optimization design of high-precision of autonomous Celestial navigation tracking mirror system.

Optimal and Autonomous Control Using Reinforcement Learning: A Survey.

PubMed

Kiumarsi, Bahare; Vamvoudakis, Kyriakos G; Modares, Hamidreza; Lewis, Frank L

2018-06-01

This paper reviews the current state of the art on reinforcement learning (RL)-based feedback control solutions to optimal regulation and tracking of single and multiagent systems. Existing RL solutions to both optimal and control problems, as well as graphical games, will be reviewed. RL methods learn the solution to optimal control and game problems online and using measured data along the system trajectories. We discuss Q-learning and the integral RL algorithm as core algorithms for discrete-time (DT) and continuous-time (CT) systems, respectively. Moreover, we discuss a new direction of off-policy RL for both CT and DT systems. Finally, we review several applications.

Structural dynamic interaction with solar tracking control for evolutionary Space Station concepts

NASA Technical Reports Server (NTRS)

Lim, Tae W.; Cooper, Paul A.; Ayers, J. Kirk

1992-01-01

The sun tracking control system design of the Solar Alpha Rotary Joint (SARJ) and the interaction of the control system with the flexible structure of Space Station Freedom (SSF) evolutionary concepts are addressed. The significant components of the space station pertaining to the SARJ control are described and the tracking control system design is presented. Finite element models representing two evolutionary concepts, enhanced operations capability (EOC) and extended operations capability (XOC), are employed to evaluate the influence of low frequency flexible structure on the control system design and performance. The design variables of the control system are synthesized using a constrained optimization technique to meet design requirements, to provide a given level of control system stability margin, and to achieve the most responsive tracking performance. The resulting SARJ control system design and performance of the EOC and XOC configurations are presented and compared to those of the SSF configuration. Performance limitations caused by the low frequency of the dominant flexible mode are discussed.

Distributed cooperative regulation for multiagent systems and its applications to power systems: a survey.

PubMed

Hu, Jianqiang; Li, Yaping; Yong, Taiyou; Cao, Jinde; Yu, Jie; Mao, Wenbo

2014-01-01

Cooperative regulation of multiagent systems has become an active research area in the past decade. This paper reviews some recent progress in distributed coordination control for leader-following multiagent systems and its applications in power system and mainly focuses on the cooperative tracking control in terms of consensus tracking control and containment tracking control. Next, methods on how to rank the network nodes are summarized for undirected/directed network, based on which one can determine which follower should be connected to leaders such that partial followers can perceive leaders' information. Furthermore, we present a survey of the most relevant scientific studies investigating the regulation and optimization problems in power systems based on distributed strategies. Finally, some potential applications in the frequency tracking regulation of smart grids are discussed at the end of the paper.

Distributed Cooperative Regulation for Multiagent Systems and Its Applications to Power Systems: A Survey

PubMed Central

Li, Yaping; Yong, Taiyou; Yu, Jie; Mao, Wenbo

2014-01-01

Cooperative regulation of multiagent systems has become an active research area in the past decade. This paper reviews some recent progress in distributed coordination control for leader-following multiagent systems and its applications in power system and mainly focuses on the cooperative tracking control in terms of consensus tracking control and containment tracking control. Next, methods on how to rank the network nodes are summarized for undirected/directed network, based on which one can determine which follower should be connected to leaders such that partial followers can perceive leaders' information. Furthermore, we present a survey of the most relevant scientific studies investigating the regulation and optimization problems in power systems based on distributed strategies. Finally, some potential applications in the frequency tracking regulation of smart grids are discussed at the end of the paper. PMID:25243199

Sensitivity of Space Station alpha joint robust controller to structural modal parameter variations

NASA Technical Reports Server (NTRS)

Kumar, Renjith R.; Cooper, Paul A.; Lim, Tae W.

1991-01-01

The photovoltaic array sun tracking control system of Space Station Freedom is described. A synthesis procedure for determining optimized values of the design variables of the control system is developed using a constrained optimization technique. The synthesis is performed to provide a given level of stability margin, to achieve the most responsive tracking performance, and to meet other design requirements. Performance of the baseline design, which is synthesized using predicted structural characteristics, is discussed and the sensitivity of the stability margin is examined for variations of the frequencies, mode shapes and damping ratios of dominant structural modes. The design provides enough robustness to tolerate a sizeable error in the predicted modal parameters. A study was made of the sensitivity of performance indicators as the modal parameters of the dominant modes vary. The design variables are resynthesized for varying modal parameters in order to achieve the most responsive tracking performance while satisfying the design requirements. This procedure of reoptimization design parameters would be useful in improving the control system performance if accurate model data are provided.

Rats track odour trails accurately using a multi-layered strategy with near-optimal sampling.

PubMed

Khan, Adil Ghani; Sarangi, Manaswini; Bhalla, Upinder Singh

2012-02-28

Tracking odour trails is a crucial behaviour for many animals, often leading to food, mates or away from danger. It is an excellent example of active sampling, where the animal itself controls how to sense the environment. Here we show that rats can track odour trails accurately with near-optimal sampling. We trained rats to follow odour trails drawn on paper spooled through a treadmill. By recording local field potentials (LFPs) from the olfactory bulb, and sniffing rates, we find that sniffing but not LFPs differ between tracking and non-tracking conditions. Rats can track odours within ~1 cm, and this accuracy is degraded when one nostril is closed. Moreover, they show path prediction on encountering a fork, wide 'casting' sweeps on encountering a gap and detection of reappearance of the trail in 1-2 sniffs. We suggest that rats use a multi-layered strategy, and achieve efficient sampling and high accuracy in this complex task.

Analysis of a spatial tracking subsystem for optical communications

NASA Technical Reports Server (NTRS)

Win, Moe Z.; Chen, CHIEN-C.

1992-01-01

Spatial tracking plays a very critical role in designing optical communication systems because of the small angular beamwidth associated with the optical signal. One possible solution for spatial tracking is to use a nutating mirror which dithers the incoming beam at a rate much higher than the mechanical disturbances. A power detector then senses the change in detected power as the signal is reflected off the nutating mirror. This signal is then correlated with the nutator driver signals to obtain estimates of the azimuth and elevation tracking signals to control the fast scanning mirrors. A theoretical analysis is performed for a spatial tracking system using a nutator disturbed by shot noise and mechanical vibrations. Contributions of shot noise and mechanical vibrations to the total tracking error variance are derived. Given the vibration spectrum and the expected signal power, there exists an optimal amplitude for the nutation which optimizes the receiver performance. The expected performance of a nutator based system is estimated based on the choice of nutation amplitude.

Cartesian control of redundant robots

NASA Technical Reports Server (NTRS)

Colbaugh, R.; Glass, K.

1989-01-01

A Cartesian-space position/force controller is presented for redundant robots. The proposed control structure partitions the control problem into a nonredundant position/force trajectory tracking problem and a redundant mapping problem between Cartesian control input F is a set member of the set R(sup m) and robot actuator torque T is a set member of the set R(sup n) (for redundant robots, m is less than n). The underdetermined nature of the F yields T map is exploited so that the robot redundancy is utilized to improve the dynamic response of the robot. This dynamically optimal F yields T map is implemented locally (in time) so that it is computationally efficient for on-line control; however, it is shown that the map possesses globally optimal characteristics. Additionally, it is demonstrated that the dynamically optimal F yields T map can be modified so that the robot redundancy is used to simultaneously improve the dynamic response and realize any specified kinematic performance objective (e.g., manipulability maximization or obstacle avoidance). Computer simulation results are given for a four degree of freedom planar redundant robot under Cartesian control, and demonstrate that position/force trajectory tracking and effective redundancy utilization can be achieved simultaneously with the proposed controller.

Adaptive GSA-based optimal tuning of PI controlled servo systems with reduced process parametric sensitivity, robust stability and controller robustness.

PubMed

Precup, Radu-Emil; David, Radu-Codrut; Petriu, Emil M; Radac, Mircea-Bogdan; Preitl, Stefan

2014-11-01

This paper suggests a new generation of optimal PI controllers for a class of servo systems characterized by saturation and dead zone static nonlinearities and second-order models with an integral component. The objective functions are expressed as the integral of time multiplied by absolute error plus the weighted sum of the integrals of output sensitivity functions of the state sensitivity models with respect to two process parametric variations. The PI controller tuning conditions applied to a simplified linear process model involve a single design parameter specific to the extended symmetrical optimum (ESO) method which offers the desired tradeoff to several control system performance indices. An original back-calculation and tracking anti-windup scheme is proposed in order to prevent the integrator wind-up and to compensate for the dead zone nonlinearity of the process. The minimization of the objective functions is carried out in the framework of optimization problems with inequality constraints which guarantee the robust stability with respect to the process parametric variations and the controller robustness. An adaptive gravitational search algorithm (GSA) solves the optimization problems focused on the optimal tuning of the design parameter specific to the ESO method and of the anti-windup tracking gain. A tuning method for PI controllers is proposed as an efficient approach to the design of resilient control systems. The tuning method and the PI controllers are experimentally validated by the adaptive GSA-based tuning of PI controllers for the angular position control of a laboratory servo system.

Neural-network-based navigation and control of unmanned aerial vehicles for detecting unintended emissions

NASA Astrophysics Data System (ADS)

Zargarzadeh, H.; Nodland, David; Thotla, V.; Jagannathan, S.; Agarwal, S.

2012-06-01

Unmanned Aerial Vehicles (UAVs) are versatile aircraft with many applications, including the potential for use to detect unintended electromagnetic emissions from electronic devices. A particular area of recent interest has been helicopter unmanned aerial vehicles. Because of the nature of these helicopters' dynamics, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via output feedback control for trajectory tracking of a helicopter UAV using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic, virtual, and dynamic controllers and an observer. Optimal tracking is accomplished with a single NN utilized for cost function approximation. The controller positions the helicopter, which is equipped with an antenna, such that the antenna can detect unintended emissions. The overall closed-loop system stability with the proposed controller is demonstrated by using Lyapunov analysis. Finally, results are provided to demonstrate the effectiveness of the proposed control design for positioning the helicopter for unintended emissions detection.

Linear quadratic tracking problems in Hilbert space - Application to optimal active noise suppression

NASA Technical Reports Server (NTRS)

Banks, H. T.; Silcox, R. J.; Keeling, S. L.; Wang, C.

1989-01-01

A unified treatment of the linear quadratic tracking (LQT) problem, in which a control system's dynamics are modeled by a linear evolution equation with a nonhomogeneous component that is linearly dependent on the control function u, is presented; the treatment proceeds from the theoretical formulation to a numerical approximation framework. Attention is given to two categories of LQT problems in an infinite time interval: the finite energy and the finite average energy. The behavior of the optimal solution for finite time-interval problems as the length of the interval tends to infinity is discussed. Also presented are the formulations and properties of LQT problems in a finite time interval.

A minimum attention control law for ball catching.

PubMed

Jang, Cheongjae; Lee, Jee-eun; Lee, Sohee; Park, F C

2015-10-06

Digital implementations of control laws typically involve discretization with respect to both time and space, and a control law that can achieve a task at coarser levels of discretization can be said to require less control attention, and also reduced implementation costs. One means of quantitatively capturing the attention of a control law is to measure the rate of change of the control with respect to changes in state and time. In this paper we present an attention-minimizing control law for ball catching and other target tracking tasks based on Brockett's attention criterion. We first highlight the connections between this attention criterion and some well-known principles from human motor control. Under the assumption that the optimal control law is the sum of a linear time-varying feedback term and a time-varying feedforward term, we derive an LQR-based minimum attention tracking control law that is stable, and obtained efficiently via a finite-dimensional optimization over the symmetric positive-definite matrices. Taking ball catching as our primary task, we perform numerical experiments comparing the performance of the various control strategies examined in the paper. Consistent with prevailing theories about human ball catching, our results exhibit several familiar features, e.g., the transition from open-loop to closed-loop control during the catching movement, and improved robustness to spatiotemporal discretization. The presented control laws are applicable to more general tracking problems that are subject to limited communication resources.

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.

Empty tracks optimization based on Z-Map model

NASA Astrophysics Data System (ADS)

Liu, Le; Yan, Guangrong; Wang, Zaijun; Zang, Genao

2017-12-01

For parts with many features, there are more empty tracks during machining. If these tracks are not optimized, the machining efficiency will be seriously affected. In this paper, the characteristics of the empty tracks are studied in detail. Combining with the existing optimization algorithm, a new tracks optimization method based on Z-Map model is proposed. In this method, the tool tracks are divided into the unit processing section, and then the Z-Map model simulation technique is used to analyze the order constraint between the unit segments. The empty stroke optimization problem is transformed into the TSP with sequential constraints, and then through the genetic algorithm solves the established TSP problem. This kind of optimization method can not only optimize the simple structural parts, but also optimize the complex structural parts, so as to effectively plan the empty tracks and greatly improve the processing efficiency.

Power Control for Direct-Driven Permanent Magnet Wind Generator System with Battery Storage

PubMed Central

Guang, Chu Xiao; Ying, Kong

2014-01-01

The objective of this paper is to construct a wind generator system (WGS) loss model that addresses the loss of the wind turbine and the generator. It aims to optimize the maximum effective output power and turbine speed. Given that the wind generator system has inertia and is nonlinear, the dynamic model of the wind generator system takes the advantage of the duty of the Buck converter and employs feedback linearization to design the optimized turbine speed tracking controller and the load power controller. According to that, this paper proposes a dual-mode dynamic coordination strategy based on the auxiliary load to reduce the influence of mode conversion on the lifetime of the battery. Optimized speed and power rapid tracking as well as the reduction of redundant power during mode conversion have gone through the test based on a 5 kW wind generator system test platform. The generator output power as the capture target has also been proved to be efficient. PMID:25050405

Power control for direct-driven permanent magnet wind generator system with battery storage.

PubMed

Guang, Chu Xiao; Ying, Kong

2014-01-01

The objective of this paper is to construct a wind generator system (WGS) loss model that addresses the loss of the wind turbine and the generator. It aims to optimize the maximum effective output power and turbine speed. Given that the wind generator system has inertia and is nonlinear, the dynamic model of the wind generator system takes the advantage of the duty of the Buck converter and employs feedback linearization to design the optimized turbine speed tracking controller and the load power controller. According to that, this paper proposes a dual-mode dynamic coordination strategy based on the auxiliary load to reduce the influence of mode conversion on the lifetime of the battery. Optimized speed and power rapid tracking as well as the reduction of redundant power during mode conversion have gone through the test based on a 5 kW wind generator system test platform. The generator output power as the capture target has also been proved to be efficient.

Modeling the effects of high-G stress on pilots in a tracking task

NASA Technical Reports Server (NTRS)

Korn, J.; Kleinman, D. L.

1978-01-01

Air-to-air tracking experiments were conducted at the Aerospace Medical Research Laboratories using both fixed and moving base dynamic environment simulators. The obtained data, which includes longitudinal error of a simulated air-to-air tracking task as well as other auxiliary variables, was analyzed using an ensemble averaging method. In conjunction with these experiments, the optimal control model is applied to model a human operator under high-G stress.

Continuous Firefly Algorithm for Optimal Tuning of Pid Controller in Avr System

NASA Astrophysics Data System (ADS)

Bendjeghaba, Omar

2014-01-01

This paper presents a tuning approach based on Continuous firefly algorithm (CFA) to obtain the proportional-integral- derivative (PID) controller parameters in Automatic Voltage Regulator system (AVR). In the tuning processes the CFA is iterated to reach the optimal or the near optimal of PID controller parameters when the main goal is to improve the AVR step response characteristics. Conducted simulations show the effectiveness and the efficiency of the proposed approach. Furthermore the proposed approach can improve the dynamic of the AVR system. Compared with particle swarm optimization (PSO), the new CFA tuning method has better control system performance in terms of time domain specifications and set-point tracking.

INDIRECT INTELLIGENT SLIDING MODE CONTROL OF A SHAPE MEMORY ALLOY ACTUATED FLEXIBLE BEAM USING HYSTERETIC RECURRENT NEURAL NETWORKS.

PubMed

Hannen, Jennifer C; Crews, John H; Buckner, Gregory D

2012-08-01

This paper introduces an indirect intelligent sliding mode controller (IISMC) for shape memory alloy (SMA) actuators, specifically a flexible beam deflected by a single offset SMA tendon. The controller manipulates applied voltage, which alters SMA tendon temperature to track reference bending angles. A hysteretic recurrent neural network (HRNN) captures the nonlinear, hysteretic relationship between SMA temperature and bending angle. The variable structure control strategy provides robustness to model uncertainties and parameter variations, while effectively compensating for system nonlinearities, achieving superior tracking compared to an optimized PI controller.

Non linear predictive control of a LEGO mobile robot

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

Real-Time Control of an Ensemble of Heterogeneous Resources

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

Bernstein, Andrey; Bouman, Niek J.; Le Boudec, Jean-Yves

This paper focuses on the problem of controlling an ensemble of heterogeneous resources connected to an electrical grid at the same point of common coupling (PCC). The controller receives an aggregate power setpoint for the ensemble in real time and tracks this setpoint by issuing individual optimal setpoints to the resources. The resources can have continuous or discrete nature (e.g., heating systems consisting of a finite number of heaters that each can be either switched on or off) and/or can be highly uncertain (e.g., photovoltaic (PV) systems or residential loads). A naive approach would lead to a stochastic mixed-integer optimizationmore » problem to be solved at the controller at each time step, which might be infeasible in real time. Instead, we allow the controller to solve a continuous convex optimization problem and compensate for the errors at the resource level by using a variant of the well-known error diffusion algorithm. We give conditions guaranteeing that our algorithm tracks the power setpoint at the PCC on average while issuing optimal setpoints to individual resources. We illustrate the approach numerically by controlling a collection of batteries, PV systems, and discrete loads.« less

Robust optimization based energy dispatch in smart grids considering demand uncertainty

NASA Astrophysics Data System (ADS)

Nassourou, M.; Puig, V.; Blesa, J.

2017-01-01

In this study we discuss the application of robust optimization to the problem of economic energy dispatch in smart grids. Robust optimization based MPC strategies for tackling uncertain load demands are developed. Unexpected additive disturbances are modelled by defining an affine dependence between the control inputs and the uncertain load demands. The developed strategies were applied to a hybrid power system connected to an electrical power grid. Furthermore, to demonstrate the superiority of the standard Economic MPC over the MPC tracking, a comparison (e.g average daily cost) between the standard MPC tracking, the standard Economic MPC, and the integration of both in one-layer and two-layer approaches was carried out. The goal of this research is to design a controller based on Economic MPC strategies, that tackles uncertainties, in order to minimise economic costs and guarantee service reliability of the system.

Kinematically Optimal Robust Control of Redundant Manipulators

NASA Astrophysics Data System (ADS)

Galicki, M.

2017-12-01

This work deals with the problem of the robust optimal task space trajectory tracking subject to finite-time convergence. Kinematic and dynamic equations of a redundant manipulator are assumed to be uncertain. Moreover, globally unbounded disturbances are allowed to act on the manipulator when tracking the trajectory by the endeffector. Furthermore, the movement is to be accomplished in such a way as to minimize both the manipulator torques and their oscillations thus eliminating the potential robot vibrations. Based on suitably defined task space non-singular terminal sliding vector variable and the Lyapunov stability theory, we derive a class of chattering-free robust kinematically optimal controllers, based on the estimation of transpose Jacobian, which seem to be effective in counteracting both uncertain kinematics and dynamics, unbounded disturbances and (possible) kinematic and/or algorithmic singularities met on the robot trajectory. The numerical simulations carried out for a redundant manipulator of a SCARA type consisting of the three revolute kinematic pairs and operating in a two-dimensional task space, illustrate performance of the proposed controllers as well as comparisons with other well known control schemes.

Generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB.

PubMed

Lee, Leng-Feng; Umberger, Brian R

2016-01-01

Computer modeling, simulation and optimization are powerful tools that have seen increased use in biomechanics research. Dynamic optimizations can be categorized as either data-tracking or predictive problems. The data-tracking approach has been used extensively to address human movement problems of clinical relevance. The predictive approach also holds great promise, but has seen limited use in clinical applications. Enhanced software tools would facilitate the application of predictive musculoskeletal simulations to clinically-relevant research. The open-source software OpenSim provides tools for generating tracking simulations but not predictive simulations. However, OpenSim includes an extensive application programming interface that permits extending its capabilities with scripting languages such as MATLAB. In the work presented here, we combine the computational tools provided by MATLAB with the musculoskeletal modeling capabilities of OpenSim to create a framework for generating predictive simulations of musculoskeletal movement based on direct collocation optimal control techniques. In many cases, the direct collocation approach can be used to solve optimal control problems considerably faster than traditional shooting methods. Cyclical and discrete movement problems were solved using a simple 1 degree of freedom musculoskeletal model and a model of the human lower limb, respectively. The problems could be solved in reasonable amounts of time (several seconds to 1-2 hours) using the open-source IPOPT solver. The problems could also be solved using the fmincon solver that is included with MATLAB, but the computation times were excessively long for all but the smallest of problems. The performance advantage for IPOPT was derived primarily by exploiting sparsity in the constraints Jacobian. The framework presented here provides a powerful and flexible approach for generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB. This should allow researchers to more readily use predictive simulation as a tool to address clinical conditions that limit human mobility.

Generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB

PubMed Central

Lee, Leng-Feng

2016-01-01

Computer modeling, simulation and optimization are powerful tools that have seen increased use in biomechanics research. Dynamic optimizations can be categorized as either data-tracking or predictive problems. The data-tracking approach has been used extensively to address human movement problems of clinical relevance. The predictive approach also holds great promise, but has seen limited use in clinical applications. Enhanced software tools would facilitate the application of predictive musculoskeletal simulations to clinically-relevant research. The open-source software OpenSim provides tools for generating tracking simulations but not predictive simulations. However, OpenSim includes an extensive application programming interface that permits extending its capabilities with scripting languages such as MATLAB. In the work presented here, we combine the computational tools provided by MATLAB with the musculoskeletal modeling capabilities of OpenSim to create a framework for generating predictive simulations of musculoskeletal movement based on direct collocation optimal control techniques. In many cases, the direct collocation approach can be used to solve optimal control problems considerably faster than traditional shooting methods. Cyclical and discrete movement problems were solved using a simple 1 degree of freedom musculoskeletal model and a model of the human lower limb, respectively. The problems could be solved in reasonable amounts of time (several seconds to 1–2 hours) using the open-source IPOPT solver. The problems could also be solved using the fmincon solver that is included with MATLAB, but the computation times were excessively long for all but the smallest of problems. The performance advantage for IPOPT was derived primarily by exploiting sparsity in the constraints Jacobian. The framework presented here provides a powerful and flexible approach for generating optimal control simulations of musculoskeletal movement using OpenSim and MATLAB. This should allow researchers to more readily use predictive simulation as a tool to address clinical conditions that limit human mobility. PMID:26835184

Study of the fractional order proportional integral controller for the permanent magnet synchronous motor based on the differential evolution algorithm.

PubMed

Zheng, Weijia; Pi, Youguo

2016-07-01

A tuning method of the fractional order proportional integral speed controller for a permanent magnet synchronous motor is proposed in this paper. Taking the combination of the integral of time and absolute error and the phase margin as the optimization index, the robustness specification as the constraint condition, the differential evolution algorithm is applied to search the optimal controller parameters. The dynamic response performance and robustness of the obtained optimal controller are verified by motor speed-tracking experiments on the motor speed control platform. Experimental results show that the proposed tuning method can enable the obtained control system to achieve both the optimal dynamic response performance and the robustness to gain variations. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Development of an optimal automatic control law and filter algorithm for steep glideslope capture and glideslope tracking

NASA Technical Reports Server (NTRS)

Halyo, N.

1976-01-01

A digital automatic control law to capture a steep glideslope and track the glideslope to a specified altitude is developed for the longitudinal/vertical dynamics of a CTOL aircraft using modern estimation and control techniques. The control law uses a constant gain Kalman filter to process guidance information from the microwave landing system, and acceleration from body mounted accelerometer data. The filter outputs navigation data and wind velocity estimates which are used in controlling the aircraft. Results from a digital simulation of the aircraft dynamics and the control law are presented for various wind conditions.

Robust guaranteed cost tracking control of quadrotor UAV with uncertainties.

PubMed

Xu, Zhiwei; Nian, Xiaohong; Wang, Haibo; Chen, Yinsheng

2017-07-01

In this paper, a robust guaranteed cost controller (RGCC) is proposed for quadrotor UAV system with uncertainties to address set-point tracking problem. A sufficient condition of the existence for RGCC is derived by Lyapunov stability theorem. The designed RGCC not only guarantees the whole closed-loop system asymptotically stable but also makes the quadratic performance level built for the closed-loop system have an upper bound irrespective to all admissible parameter uncertainties. Then, an optimal robust guaranteed cost controller is developed to minimize the upper bound of performance level. Simulation results verify the presented control algorithms possess small overshoot and short setting time, with which the quadrotor has ability to perform set-point tracking task well. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Pareto Design of State Feedback Tracking Control of a Biped Robot via Multiobjective PSO in Comparison with Sigma Method and Genetic Algorithms: Modified NSGAII and MATLAB's Toolbox

PubMed Central

Mahmoodabadi, M. J.; Taherkhorsandi, M.; Bagheri, A.

2014-01-01

An optimal robust state feedback tracking controller is introduced to control a biped robot. In the literature, the parameters of the controller are usually determined by a tedious trial and error process. To eliminate this process and design the parameters of the proposed controller, the multiobjective evolutionary algorithms, that is, the proposed method, modified NSGAII, Sigma method, and MATLAB's Toolbox MOGA, are employed in this study. Among the used evolutionary optimization algorithms to design the controller for biped robots, the proposed method operates better in the aspect of designing the controller since it provides ample opportunities for designers to choose the most appropriate point based upon the design criteria. Three points are chosen from the nondominated solutions of the obtained Pareto front based on two conflicting objective functions, that is, the normalized summation of angle errors and normalized summation of control effort. Obtained results elucidate the efficiency of the proposed controller in order to control a biped robot. PMID:24616619

A combined stochastic feedforward and feedback control design methodology with application to autoland design

NASA Technical Reports Server (NTRS)

Halyo, Nesim

1987-01-01

A combined stochastic feedforward and feedback control design methodology was developed. The objective of the feedforward control law is to track the commanded trajectory, whereas the feedback control law tries to maintain the plant state near the desired trajectory in the presence of disturbances and uncertainties about the plant. The feedforward control law design is formulated as a stochastic optimization problem and is embedded into the stochastic output feedback problem where the plant contains unstable and uncontrollable modes. An algorithm to compute the optimal feedforward is developed. In this approach, the use of error integral feedback, dynamic compensation, control rate command structures are an integral part of the methodology. An incremental implementation is recommended. Results on the eigenvalues of the implemented versus designed control laws are presented. The stochastic feedforward/feedback control methodology is used to design a digital automatic landing system for the ATOPS Research Vehicle, a Boeing 737-100 aircraft. The system control modes include localizer and glideslope capture and track, and flare to touchdown. Results of a detailed nonlinear simulation of the digital control laws, actuator systems, and aircraft aerodynamics are presented.

Optimal Control Modification for Robust Adaptation of Singularly Perturbed Systems with Slow Actuators

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Ishihara, Abraham; Stepanyan, Vahram; Boskovic, Jovan

2009-01-01

Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. The model matching conditions in the transformed time coordinate results in increase in the feedback gain and modification of the adaptive law.

Optimal Control Modification Adaptive Law for Time-Scale Separated Systems

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2010-01-01

Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.

Optimal Control Modification for Time-Scale Separated Systems

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2012-01-01

Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.

The integrated manual and automatic control of complex flight systems

NASA Technical Reports Server (NTRS)

Schmidt, David K.

1991-01-01

Research dealt with the general area of optimal flight control synthesis for manned flight vehicles. The work was generic; no specific vehicle was the focus of study. However, the class of vehicles generally considered were those for which high authority, multivariable control systems might be considered, for the purpose of stabilization and the achievement of optimal handling characteristics. Within this scope, the topics of study included several optimal control synthesis techniques, control-theoretic modeling of the human operator in flight control tasks, and the development of possible handling qualities metrics and/or measures of merit. Basic contributions were made in all these topics, including human operator (pilot) models for multi-loop tasks, optimal output feedback flight control synthesis techniques; experimental validations of the methods developed, and fundamental modeling studies of the air-to-air tracking and flared landing tasks.

Optimal second order sliding mode control for linear uncertain systems.

PubMed

Das, Madhulika; Mahanta, Chitralekha

2014-11-01

In this paper an optimal second order sliding mode controller (OSOSMC) is proposed to track a linear uncertain system. The optimal controller based on the linear quadratic regulator method is designed for the nominal system. An integral sliding mode controller is combined with the optimal controller to ensure robustness of the linear system which is affected by parametric uncertainties and external disturbances. To achieve finite time convergence of the sliding mode, a nonsingular terminal sliding surface is added with the integral sliding surface giving rise to a second order sliding mode controller. The main advantage of the proposed OSOSMC is that the control input is substantially reduced and it becomes chattering free. Simulation results confirm superiority of the proposed OSOSMC over some existing. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal Predictive Control for Path Following of a Full Drive-by-Wire Vehicle at Varying Speeds

NASA Astrophysics Data System (ADS)

SONG, Pan; GAO, Bolin; XIE, Shugang; FANG, Rui

2017-05-01

The current research of the global chassis control problem for the full drive-by-wire vehicle focuses on the control allocation (CA) of the four-wheel-distributed traction/braking/steering systems. However, the path following performance and the handling stability of the vehicle can be enhanced a step further by automatically adjusting the vehicle speed to the optimal value. The optimal solution for the combined longitudinal and lateral motion control (MC) problem is given. First, a new variable step-size spatial transformation method is proposed and utilized in the prediction model to derive the dynamics of the vehicle with respect to the road, such that the tracking errors can be explicitly obtained over the prediction horizon at varying speeds. Second, a nonlinear model predictive control (NMPC) algorithm is introduced to handle the nonlinear coupling between any two directions of the vehicular planar motion and computes the sequence of the optimal motion states for following the desired path. Third, a hierarchical control structure is proposed to separate the motion controller into a NMPC based path planner and a terminal sliding mode control (TSMC) based path follower. As revealed through off-line simulations, the hierarchical methodology brings nearly 1700% improvement in computational efficiency without loss of control performance. Finally, the control algorithm is verified through a hardware in-the-loop simulation system. Double-lane-change (DLC) test results show that by using the optimal predictive controller, the root-mean-square (RMS) values of the lateral deviations and the orientation errors can be reduced by 41% and 30%, respectively, comparing to those by the optimal preview acceleration (OPA) driver model with the non-preview speed-tracking method. Additionally, the average vehicle speed is increased by 0.26 km/h with the peak sideslip angle suppressed to 1.9°. This research proposes a novel motion controller, which provides the full drive-by-wire vehicle with better lane-keeping and collision-avoidance capabilities during autonomous driving.

4D Optimization of Scanned Ion Beam Tracking Therapy for Moving Tumors

PubMed Central

Eley, John Gordon; Newhauser, Wayne David; Lüchtenborg, Robert; Graeff, Christian; Bert, Christoph

2014-01-01

Motion mitigation strategies are needed to fully realize the theoretical advantages of scanned ion beam therapy for patients with moving tumors. The purpose of this study was to determine whether a new four-dimensional (4D) optimization approach for scanned-ion-beam tracking could reduce dose to avoidance volumes near a moving target while maintaining target dose coverage, compared to an existing 3D-optimized beam tracking approach. We tested these approaches computationally using a simple 4D geometrical phantom and a complex anatomic phantom, that is, a 4D computed tomogram of the thorax of a lung cancer patient. We also validated our findings using measurements of carbon-ion beams with a motorized film phantom. Relative to 3D-optimized beam tracking, 4D-optimized beam tracking reduced the maximum predicted dose to avoidance volumes by 53% in the simple phantom and by 13% in the thorax phantom. 4D-optimized beam tracking provided similar target dose homogeneity in the simple phantom (standard deviation of target dose was 0.4% versus 0.3%) and dramatically superior homogeneity in the thorax phantom (D5-D95 was 1.9% versus 38.7%). Measurements demonstrated that delivery of 4D-optimized beam tracking was technically feasible and confirmed a 42% decrease in maximum film exposure in the avoidance region compared with 3D-optimized beam tracking. In conclusion, we found that 4D-optimized beam tracking can reduce the maximum dose to avoidance volumes near a moving target while maintaining target dose coverage, compared with 3D-optimized beam tracking. PMID:24889215

4D optimization of scanned ion beam tracking therapy for moving tumors

NASA Astrophysics Data System (ADS)

Eley, John Gordon; Newhauser, Wayne David; Lüchtenborg, Robert; Graeff, Christian; Bert, Christoph

2014-07-01

Motion mitigation strategies are needed to fully realize the theoretical advantages of scanned ion beam therapy for patients with moving tumors. The purpose of this study was to determine whether a new four-dimensional (4D) optimization approach for scanned-ion-beam tracking could reduce dose to avoidance volumes near a moving target while maintaining target dose coverage, compared to an existing 3D-optimized beam tracking approach. We tested these approaches computationally using a simple 4D geometrical phantom and a complex anatomic phantom, that is, a 4D computed tomogram of the thorax of a lung cancer patient. We also validated our findings using measurements of carbon-ion beams with a motorized film phantom. Relative to 3D-optimized beam tracking, 4D-optimized beam tracking reduced the maximum predicted dose to avoidance volumes by 53% in the simple phantom and by 13% in the thorax phantom. 4D-optimized beam tracking provided similar target dose homogeneity in the simple phantom (standard deviation of target dose was 0.4% versus 0.3%) and dramatically superior homogeneity in the thorax phantom (D5-D95 was 1.9% versus 38.7%). Measurements demonstrated that delivery of 4D-optimized beam tracking was technically feasible and confirmed a 42% decrease in maximum film exposure in the avoidance region compared with 3D-optimized beam tracking. In conclusion, we found that 4D-optimized beam tracking can reduce the maximum dose to avoidance volumes near a moving target while maintaining target dose coverage, compared with 3D-optimized beam tracking.

Dynamic optimization and adaptive controller design

NASA Astrophysics Data System (ADS)

Inamdar, S. R.

2010-10-01

In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

Experimental and Theoretical Results in Output Trajectory Redesign for Flexible Structures

NASA Technical Reports Server (NTRS)

Dewey, J. S.; Leang, K.; Devasia, S.

1998-01-01

In this paper we study the optimal redesign of output trajectories for linear invertible systems. This is particularly important for tracking control of flexible structures because the input-state trajectores, that achieve tracking of the required output may cause excessive vibrations in the structure. We pose and solve this problem, in the context of linear systems, as the minimization of a quadratic cost function. The theory is developed and applied to the output tracking of a flexible structure and experimental results are presented.

A novel open-loop tracking strategy for photovoltaic systems.

PubMed

Alexandru, Cătălin

2013-01-01

This paper approaches a dual-axis equatorial tracking system that is used to increase the photovoltaic efficiency by maximizing the degree of use of the solar radiation. The innovative aspect in the solar tracker design consists in considering the tracking mechanism as a perturbation for the DC motors. The goal is to control the DC motors, which are perturbed with the motor torques whose computation is based on the dynamic model of the mechanical structure on which external forces act. The daily and elevation angles of the PV module represent the input parameters in the mechanical device, while the outputs transmitted to the controller are the motor torques. The controller tuning is approached by a parametric optimization process, using design of experiments and response surface methodology techniques, in a multiple regression. The simulation and experimental results demonstrate the operational performance of the tracking system.

A Novel Open-Loop Tracking Strategy for Photovoltaic Systems

PubMed Central

Alexandru, Cătălin

2013-01-01

This paper approaches a dual-axis equatorial tracking system that is used to increase the photovoltaic efficiency by maximizing the degree of use of the solar radiation. The innovative aspect in the solar tracker design consists in considering the tracking mechanism as a perturbation for the DC motors. The goal is to control the DC motors, which are perturbed with the motor torques whose computation is based on the dynamic model of the mechanical structure on which external forces act. The daily and elevation angles of the PV module represent the input parameters in the mechanical device, while the outputs transmitted to the controller are the motor torques. The controller tuning is approached by a parametric optimization process, using design of experiments and response surface methodology techniques, in a multiple regression. The simulation and experimental results demonstrate the operational performance of the tracking system. PMID:24327803

Wind turbine power tracking using an improved multimodel quadratic approach.

PubMed

Khezami, Nadhira; Benhadj Braiek, Naceur; Guillaud, Xavier

2010-07-01

In this paper, an improved multimodel optimal quadratic control structure for variable speed, pitch regulated wind turbines (operating at high wind speeds) is proposed in order to integrate high levels of wind power to actively provide a primary reserve for frequency control. On the basis of the nonlinear model of the studied plant, and taking into account the wind speed fluctuations, and the electrical power variation, a multimodel linear description is derived for the wind turbine, and is used for the synthesis of an optimal control law involving a state feedback, an integral action and an output reference model. This new control structure allows a rapid transition of the wind turbine generated power between different desired set values. This electrical power tracking is ensured with a high-performance behavior for all other state variables: turbine and generator rotational speeds and mechanical shaft torque; and smooth and adequate evolution of the control variables. 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Tracking control of concentration profiles in a fed-batch bioreactor using a linear algebra methodology.

PubMed

Rómoli, Santiago; Serrano, Mario Emanuel; Ortiz, Oscar Alberto; Vega, Jorge Rubén; Eduardo Scaglia, Gustavo Juan

2015-07-01

Based on a linear algebra approach, this paper aims at developing a novel control law able to track reference profiles that were previously-determined in the literature. A main advantage of the proposed strategy is that the control actions are obtained by solving a system of linear equations. The optimal controller parameters are selected through Monte Carlo Randomized Algorithm in order to minimize a proposed cost index. The controller performance is evaluated through several tests, and compared with other controller reported in the literature. Finally, a Monte Carlo Randomized Algorithm is conducted to assess the performance of the proposed controller. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Real-time tracking control of electro-hydraulic force servo systems using offline feedback control and adaptive control.

PubMed

Shen, Gang; Zhu, Zhencai; Zhao, Jinsong; Zhu, Weidong; Tang, Yu; Li, Xiang

2017-03-01

This paper focuses on an application of an electro-hydraulic force tracking controller combined with an offline designed feedback controller (ODFC) and an online adaptive compensator in order to improve force tracking performance of an electro-hydraulic force servo system (EHFS). A proportional-integral controller has been employed and a parameter-based force closed-loop transfer function of the EHFS is identified by a continuous system identification algorithm. By taking the identified system model as a nominal plant model, an H ∞ offline design method is employed to establish an optimized feedback controller with consideration of the performance, control efforts, and robustness of the EHFS. In order to overcome the disadvantage of the offline designed controller and cope with the varying dynamics of the EHFS, an online adaptive compensator with a normalized least-mean-square algorithm is cascaded to the force closed-loop system of the EHFS compensated by the ODFC. Some comparative experiments are carried out on a real-time EHFS using an xPC rapid prototype technology, and the proposed controller yields a better force tracking performance improvement. Copyright © 2016. Published by Elsevier Ltd.

Human-tracking strategies for a six-legged rescue robot based on distance and view

NASA Astrophysics Data System (ADS)

Pan, Yang; Gao, Feng; Qi, Chenkun; Chai, Xun

2016-03-01

Human tracking is an important issue for intelligent robotic control and can be used in many scenarios, such as robotic services and human-robot cooperation. Most of current human-tracking methods are targeted for mobile/tracked robots, but few of them can be used for legged robots. Two novel human-tracking strategies, view priority strategy and distance priority strategy, are proposed specially for legged robots, which enable them to track humans in various complex terrains. View priority strategy focuses on keeping humans in its view angle arrange with priority, while its counterpart, distance priority strategy, focuses on keeping human at a reasonable distance with priority. To evaluate these strategies, two indexes(average and minimum tracking capability) are defined. With the help of these indexes, the view priority strategy shows advantages compared with distance priority strategy. The optimization is done in terms of these indexes, which let the robot has maximum tracking capability. The simulation results show that the robot can track humans with different curves like square, circular, sine and screw paths. Two novel control strategies are proposed which specially concerning legged robot characteristics to solve human tracking problems more efficiently in rescue circumstances.

Boundary control of bidomain equations with state-dependent switching source functions in the ionic model

NASA Astrophysics Data System (ADS)

Chamakuri, Nagaiah; Engwer, Christian; Kunisch, Karl

2014-09-01

Optimal control for cardiac electrophysiology based on the bidomain equations in conjunction with the Fenton-Karma ionic model is considered. This generic ventricular model approximates well the restitution properties and spiral wave behavior of more complex ionic models of cardiac action potentials. However, it is challenging due to the appearance of state-dependent discontinuities in the source terms. A computational framework for the numerical realization of optimal control problems is presented. Essential ingredients are a shape calculus based treatment of the sensitivities of the discontinuous source terms and a marching cubes algorithm to track iso-surface of excitation wavefronts. Numerical results exhibit successful defibrillation by applying an optimally controlled extracellular stimulus.

An optimal control model approach to the design of compensators for simulator delay

NASA Technical Reports Server (NTRS)

Baron, S.; Lancraft, R.; Caglayan, A.

1982-01-01

The effects of display delay on pilot performance and workload and of the design of the filters to ameliorate these effects were investigated. The optimal control model for pilot/vehicle analysis was used both to determine the potential delay effects and to design the compensators. The model was applied to a simple roll tracking task and to a complex hover task. The results confirm that even small delays can degrade performance and impose a workload penalty. A time-domain compensator designed by using the optimal control model directly appears capable of providing extensive compensation for these effects even in multi-input, multi-output problems.

An adaptive optimal control for smart structures based on the subspace tracking identification technique

NASA Astrophysics Data System (ADS)

Ripamonti, Francesco; Resta, Ferruccio; Borroni, Massimo; Cazzulani, Gabriele

2014-04-01

A new method for the real-time identification of mechanical system modal parameters is used in order to design different adaptive control logics aiming to reduce the vibrations in a carbon fiber plate smart structure. It is instrumented with three piezoelectric actuators, three accelerometers and three strain gauges. The real-time identification is based on a recursive subspace tracking algorithm whose outputs are elaborated by an ARMA model. A statistical approach is finally applied to choose the modal parameter correct values. These are given in input to model-based control logics such as a gain scheduling and an adaptive LQR control.

Design and evaluation of a Stochastic Optimal Feed-forward and Feedback Technology (SOFFT) flight control architecture

NASA Technical Reports Server (NTRS)

Ostroff, Aaron J.; Proffitt, Melissa S.

1994-01-01

This paper describes the design and evaluation of a stochastic optimal feed-forward and feedback technology (SOFFT) control architecture with emphasis on the feed-forward controller design. The SOFFT approach allows the designer to independently design the feed-forward and feedback controllers to meet separate objectives and then integrate the two controllers. The feed-forward controller has been integrated with an existing high-angle-of-attack (high-alpha) feedback controller. The feed-forward controller includes a variable command model with parameters selected to satisfy level 1 flying qualities with a high-alpha adjustment to achieve desired agility guidelines, a nonlinear interpolation approach that scales entire matrices for approximation of the plant model, and equations for calculating feed-forward gains developed for perfect plant-model tracking. The SOFFT design was applied to a nonlinear batch simulation model of an F/A-18 aircraft modified for thrust vectoring. Simulation results show that agility guidelines are met and that the SOFFT controller filters undesired pilot-induced frequencies more effectively during a tracking task than a flight controller that has the same feedback control law but does not have the SOFFT feed-forward control.

Optimal Power Flow Pursuit

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

Dall'Anese, Emiliano; Simonetto, Andrea

This paper considers distribution networks featuring inverter-interfaced distributed energy resources, and develops distributed feedback controllers that continuously drive the inverter output powers to solutions of AC optimal power flow (OPF) problems. Particularly, the controllers update the power setpoints based on voltage measurements as well as given (time-varying) OPF targets, and entail elementary operations implementable onto low-cost microcontrollers that accompany power-electronics interfaces of gateways and inverters. The design of the control framework is based on suitable linear approximations of the AC power-flow equations as well as Lagrangian regularization methods. Convergence and OPF-target tracking capabilities of the controllers are analytically established. Overall,more » the proposed method allows to bypass traditional hierarchical setups where feedback control and optimization operate at distinct time scales, and to enable real-time optimization of distribution systems.« less

High Accuracy Passive Magnetic Field-Based Localization for Feedback Control Using Principal Component Analysis.

PubMed

Foong, Shaohui; Sun, Zhenglong

2016-08-12

In this paper, a novel magnetic field-based sensing system employing statistically optimized concurrent multiple sensor outputs for precise field-position association and localization is presented. This method capitalizes on the independence between simultaneous spatial field measurements at multiple locations to induce unique correspondences between field and position. This single-source-multi-sensor configuration is able to achieve accurate and precise localization and tracking of translational motion without contact over large travel distances for feedback control. Principal component analysis (PCA) is used as a pseudo-linear filter to optimally reduce the dimensions of the multi-sensor output space for computationally efficient field-position mapping with artificial neural networks (ANNs). Numerical simulations are employed to investigate the effects of geometric parameters and Gaussian noise corruption on PCA assisted ANN mapping performance. Using a 9-sensor network, the sensing accuracy and closed-loop tracking performance of the proposed optimal field-based sensing system is experimentally evaluated on a linear actuator with a significantly more expensive optical encoder as a comparison.

Lateral control system design for VTOL landing on a DD963 in high sea states. M.S. Thesis

NASA Technical Reports Server (NTRS)

Bodson, M.

1982-01-01

The problem of designing lateral control systems for the safe landing of VTOL aircraft on small ships is addressed. A ship model is derived. The issues of estimation and prediction of ship motions are discussed, using optimal linear linear estimation techniques. The roll motion is the most important of the lateral motions, and it is found that it can be predicted for up to 10 seconds in perfect conditions. The automatic landing of the VTOL aircraft is considered, and a lateral controller, defined as a ship motion tracker, is designed, using optimal control techniqes. The tradeoffs between the tracking errors and the control authority are obtained. The important couplings between the lateral motions and controls are demonstrated, and it is shown that the adverse couplings between the sway and the roll motion at the landing pad are significant constraints in the tracking of the lateral ship motions. The robustness of the control system, including the optimal estimator, is studied, using the singular values analysis. Through a robustification procedure, a robust control system is obtained, and the usefulness of the singular values to define stability margins that take into account general types of unstructured modelling errors is demonstrated. The minimal destabilizing perturbations indicated by the singular values analysis are interpreted and related to the multivariable Nyquist diagrams.

Optimal design and control of an electromechanical transfemoral prosthesis with energy regeneration.

PubMed

Rohani, Farbod; Richter, Hanz; van den Bogert, Antonie J

2017-01-01

In this paper, we present the design of an electromechanical above-knee active prosthesis with energy storage and regeneration. The system consists of geared knee and ankle motors, parallel springs for each motor, an ultracapacitor, and controllable four-quadrant power converters. The goal is to maximize the performance of the system by finding optimal controls and design parameters. A model of the system dynamics was developed, and used to solve a combined trajectory and design optimization problem. The objectives of the optimization were to minimize tracking error relative to human joint motions, as well as energy use. The optimization problem was solved by the method of direct collocation, based on joint torque and joint angle data from ten subjects walking at three speeds. After optimization of controls and design parameters, the simulated system could operate at zero energy cost while still closely emulating able-bodied gait. This was achieved by controlled energy transfer between knee and ankle, and by controlled storage and release of energy throughout the gait cycle. Optimal gear ratios and spring parameters were similar across subjects and walking speeds.

Real-time motion compensation for EM bronchoscope tracking with smooth output - ex-vivo validation

NASA Astrophysics Data System (ADS)

Reichl, Tobias; Gergel, Ingmar; Menzel, Manuela; Hautmann, Hubert; Wegner, Ingmar; Meinzer, Hans-Peter; Navab, Nassir

2012-02-01

Navigated bronchoscopy provides benefits for endoscopists and patients, but accurate tracking information is needed. We present a novel real-time approach for bronchoscope tracking combining electromagnetic (EM) tracking, airway segmentation, and a continuous model of output. We augment a previously published approach by including segmentation information in the tracking optimization instead of image similarity. Thus, the new approach is feasible in real-time. Since the true bronchoscope trajectory is continuous, the output is modeled using splines and the control points are optimized with respect to displacement from EM tracking measurements and spatial relation to segmented airways. Accuracy of the proposed method and its components is evaluated on a ventilated porcine ex-vivo lung with respect to ground truth data acquired from a human expert. We demonstrate the robustness of the output of the proposed method against added artificial noise in the input data. Smoothness in terms of inter-frame distance is shown to remain below 2 mm, even when up to 5 mm of Gaussian noise are added to the input. The approach is shown to be easily extensible to include other measures like image similarity.

A parameter optimization approach to controller partitioning for integrated flight/propulsion control application

NASA Technical Reports Server (NTRS)

Schmidt, Phillip; Garg, Sanjay; Holowecky, Brian

1992-01-01

A parameter optimization framework is presented to solve the problem of partitioning a centralized controller into a decentralized hierarchical structure suitable for integrated flight/propulsion control implementation. The controller partitioning problem is briefly discussed and a cost function to be minimized is formulated, such that the resulting 'optimal' partitioned subsystem controllers will closely match the performance (including robustness) properties of the closed-loop system with the centralized controller while maintaining the desired controller partitioning structure. The cost function is written in terms of parameters in a state-space representation of the partitioned sub-controllers. Analytical expressions are obtained for the gradient of this cost function with respect to parameters, and an optimization algorithm is developed using modern computer-aided control design and analysis software. The capabilities of the algorithm are demonstrated by application to partitioned integrated flight/propulsion control design for a modern fighter aircraft in the short approach to landing task. The partitioning optimization is shown to lead to reduced-order subcontrollers that match the closed-loop command tracking and decoupling performance achieved by a high-order centralized controller.

A parameter optimization approach to controller partitioning for integrated flight/propulsion control application

NASA Technical Reports Server (NTRS)

Schmidt, Phillip H.; Garg, Sanjay; Holowecky, Brian R.

1993-01-01

A parameter optimization framework is presented to solve the problem of partitioning a centralized controller into a decentralized hierarchical structure suitable for integrated flight/propulsion control implementation. The controller partitioning problem is briefly discussed and a cost function to be minimized is formulated, such that the resulting 'optimal' partitioned subsystem controllers will closely match the performance (including robustness) properties of the closed-loop system with the centralized controller while maintaining the desired controller partitioning structure. The cost function is written in terms of parameters in a state-space representation of the partitioned sub-controllers. Analytical expressions are obtained for the gradient of this cost function with respect to parameters, and an optimization algorithm is developed using modern computer-aided control design and analysis software. The capabilities of the algorithm are demonstrated by application to partitioned integrated flight/propulsion control design for a modern fighter aircraft in the short approach to landing task. The partitioning optimization is shown to lead to reduced-order subcontrollers that match the closed-loop command tracking and decoupling performance achieved by a high-order centralized controller.

Portfolio optimization for index tracking modelling in Malaysia stock market

NASA Astrophysics Data System (ADS)

Siew, Lam Weng; Jaaman, Saiful Hafizah; Ismail, Hamizun

2016-06-01

Index tracking is an investment strategy in portfolio management which aims to construct an optimal portfolio to generate similar mean return with the stock market index mean return without purchasing all of the stocks that make up the index. The objective of this paper is to construct an optimal portfolio using the optimization model which adopts regression approach in tracking the benchmark stock market index return. In this study, the data consists of weekly price of stocks in Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index from January 2010 until December 2013. The results of this study show that the optimal portfolio is able to track FBMKLCI Index at minimum tracking error of 1.0027% with 0.0290% excess mean return over the mean return of FBMKLCI Index. The significance of this study is to construct the optimal portfolio using optimization model which adopts regression approach in tracking the stock market index without purchasing all index components.

Multi-objective LQR with optimum weight selection to design FOPID controllers for delayed fractional order processes.

PubMed

Das, Saptarshi; Pan, Indranil; Das, Shantanu

2015-09-01

An optimal trade-off design for fractional order (FO)-PID controller is proposed with a Linear Quadratic Regulator (LQR) based technique using two conflicting time domain objectives. A class of delayed FO systems with single non-integer order element, exhibiting both sluggish and oscillatory open loop responses, have been controlled here. The FO time delay processes are handled within a multi-objective optimization (MOO) formalism of LQR based FOPID design. A comparison is made between two contemporary approaches of stabilizing time-delay systems withinLQR. The MOO control design methodology yields the Pareto optimal trade-off solutions between the tracking performance and total variation (TV) of the control signal. Tuning rules are formed for the optimal LQR-FOPID controller parameters, using median of the non-dominated Pareto solutions to handle delayed FO processes. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Autorotation flight control system

NASA Technical Reports Server (NTRS)

Bachelder, Edward N. (Inventor); Aponso, Bimal L. (Inventor); Lee, Dong-Chan (Inventor)

2011-01-01

The present invention provides computer implemented methodology that permits the safe landing and recovery of rotorcraft following engine failure. With this invention successful autorotations may be performed from well within the unsafe operating area of the height-velocity profile of a helicopter by employing the fast and robust real-time trajectory optimization algorithm that commands control motion through an intuitive pilot display, or directly in the case of autonomous rotorcraft. The algorithm generates optimal trajectories and control commands via the direct-collocation optimization method, solved using a nonlinear programming problem solver. The control inputs computed are collective pitch and aircraft pitch, which are easily tracked and manipulated by the pilot or converted to control actuator commands for automated operation during autorotation in the case of an autonomous rotorcraft. The formulation of the optimal control problem has been carefully tailored so the solutions resemble those of an expert pilot, accounting for the performance limitations of the rotorcraft and safety concerns.

Preliminary Assessment of Optimal Longitudinal-Mode Control for Drag Reduction through Distributed Aeroelastic Shaping

NASA Technical Reports Server (NTRS)

Ippolito, Corey; Nguyen, Nhan; Lohn, Jason; Dolan, John

2014-01-01

The emergence of advanced lightweight materials is resulting in a new generation of lighter, flexible, more-efficient airframes that are enabling concepts for active aeroelastic wing-shape control to achieve greater flight efficiency and increased safety margins. These elastically shaped aircraft concepts require non-traditional methods for large-scale multi-objective flight control that simultaneously seek to gain aerodynamic efficiency in terms of drag reduction while performing traditional command-tracking tasks as part of a complete guidance and navigation solution. This paper presents results from a preliminary study of a notional multi-objective control law for an aeroelastic flexible-wing aircraft controlled through distributed continuous leading and trailing edge control surface actuators. This preliminary study develops and analyzes a multi-objective control law derived from optimal linear quadratic methods on a longitudinal vehicle dynamics model with coupled aeroelastic dynamics. The controller tracks commanded attack-angle while minimizing drag and controlling wing twist and bend. This paper presents an overview of the elastic aircraft concept, outlines the coupled vehicle model, presents the preliminary control law formulation and implementation, presents results from simulation, provides analysis, and concludes by identifying possible future areas for research

Reinforcement learning design-based adaptive tracking control with less learning parameters for nonlinear discrete-time MIMO systems.

PubMed

Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan

2015-01-01

Based on the neural network (NN) approximator, an online reinforcement learning algorithm is proposed for a class of affine multiple input and multiple output (MIMO) nonlinear discrete-time systems with unknown functions and disturbances. In the design procedure, two networks are provided where one is an action network to generate an optimal control signal and the other is a critic network to approximate the cost function. An optimal control signal and adaptation laws can be generated based on two NNs. In the previous approaches, the weights of critic and action networks are updated based on the gradient descent rule and the estimations of optimal weight vectors are directly adjusted in the design. Consequently, compared with the existing results, the main contributions of this paper are: 1) only two parameters are needed to be adjusted, and thus the number of the adaptation laws is smaller than the previous results and 2) the updating parameters do not depend on the number of the subsystems for MIMO systems and the tuning rules are replaced by adjusting the norms on optimal weight vectors in both action and critic networks. It is proven that the tracking errors, the adaptation laws, and the control inputs are uniformly bounded using Lyapunov analysis method. The simulation examples are employed to illustrate the effectiveness of the proposed algorithm.

Aerospace plane guidance using geometric control theory

NASA Technical Reports Server (NTRS)

Van Buren, Mark A.; Mease, Kenneth D.

1990-01-01

A reduced-order method employing decomposition, based on time-scale separation, of the 4-D state space in a 2-D slow manifold and a family of 2-D fast manifolds is shown to provide an excellent approximation to the full-order minimum-fuel ascent trajectory. Near-optimal guidance is obtained by tracking the reduced-order trajectory. The tracking problem is solved as regulation problems on the family of fast manifolds, using the exact linearization methodology from nonlinear geometric control theory. The validity of the overall guidance approach is indicated by simulation.

Experimental and Theoretical Results in Output-Trajectory Redesign for Flexible Structures

NASA Technical Reports Server (NTRS)

Dewey, J. S.; Devasia, Santosh

1996-01-01

In this paper we study the optimal redesign of output trajectory for linear invertible systems. This is particularly important for tracking control of flexible structures because the input-state trajectories that achieve the required output may cause excessive vibrations in the structure. A trade-off is then required between tracking and vibrations reduction. We pose and solve this problem as the minimization of a quadratic cost function. The theory is developed and applied to the output tracking of a flexible structure and experimental results are presented.

Analysis multi-agent with precense of the leader

NASA Astrophysics Data System (ADS)

Achmadi, Sentot; Marjono, Miswanto

2017-12-01

The phenomenon of swarm is a natural phenomenon that is often done by a collection of living things in the form of motion from one place to another. By clustering, a group of animals can increase their effectiveness in food search and avoid predators. A group of geese also performs a swarm phenomenon when flying and forms an inverted V-formation with one of the geese acting as a leader. Each flying track of members of the geese group always follows the leader's path at a certain distance. This article discusses the mathematical modeling of the swarm phenomenon, which is the optimal tracking control for multi-agent model with the influence of the leader in the 2-dimensional space. The leader in this model is intended to track the specified path. Firstly, the leader's motion control is to follow the predetermined path using the Tracking Error Dynamic method. Then, the path from the leader is used to design the motion control of each agent to track the leader's path at a certain distance. The result of numerical simulation shows that the leader trajectory can track the specified path. Similarly, the motion of each agent can trace and follow the leader's path.

Power optimal single-axis articulating strategies

NASA Technical Reports Server (NTRS)

Kumar, Renjith R.; Heck, Michael L.

1991-01-01

Power optimal single axis articulating PV array motion for Space Station Freedom is investigated. The motivation is to eliminate one of the articular joints to reduce Station costs. Optimal (maximum power) Beta tracking is addressed for local vertical local horizontal (LVLH) and non-LVLH attitudes. Effects of intra-array shadowing are also presented. Maximum power availability while Beta tracking is compared to full sun tracking and optimal alpha tracking. The results are quantified in orbital and yearly minimum, maximum, and average values of power availability.

Scheduled power tracking control of the wind-storage hybrid system based on the reinforcement learning theory

NASA Astrophysics Data System (ADS)

Li, Ze

2017-09-01

In allusion to the intermittency and uncertainty of the wind electricity, energy storage and wind generator are combined into a hybrid system to improve the controllability of the output power. A scheduled power tracking control method is proposed based on the reinforcement learning theory and Q-learning algorithm. In this method, the state space of the environment is formed with two key factors, i.e. the state of charge of the energy storage and the difference value between the actual wind power and scheduled power, the feasible action is the output power of the energy storage, and the corresponding immediate rewarding function is designed to reflect the rationality of the control action. By interacting with the environment and learning from the immediate reward, the optimal control strategy is gradually formed. After that, it could be applied to the scheduled power tracking control of the hybrid system. Finally, the rationality and validity of the method are verified through simulation examples.

Run-to-Run Optimization Control Within Exact Inverse Framework for Scan Tracking.

PubMed

Yeoh, Ivan L; Reinhall, Per G; Berg, Martin C; Chizeck, Howard J; Seibel, Eric J

2017-09-01

A run-to-run optimization controller uses a reduced set of measurement parameters, in comparison to more general feedback controllers, to converge to the best control point for a repetitive process. A new run-to-run optimization controller is presented for the scanning fiber device used for image acquisition and display. This controller utilizes very sparse measurements to estimate a system energy measure and updates the input parameterizations iteratively within a feedforward with exact-inversion framework. Analysis, simulation, and experimental investigations on the scanning fiber device demonstrate improved scan accuracy over previous methods and automatic controller adaptation to changing operating temperature. A specific application example and quantitative error analyses are provided of a scanning fiber endoscope that maintains high image quality continuously across a 20 °C temperature rise without interruption of the 56 Hz video.

Two Reconfigurable Flight-Control Design Methods: Robust Servomechanism and Control Allocation

NASA Technical Reports Server (NTRS)

Burken, John J.; Lu, Ping; Wu, Zheng-Lu; Bahm, Cathy

2001-01-01

Two methods for control system reconfiguration have been investigated. The first method is a robust servomechanism control approach (optimal tracking problem) that is a generalization of the classical proportional-plus-integral control to multiple input-multiple output systems. The second method is a control-allocation approach based on a quadratic programming formulation. A globally convergent fixed-point iteration algorithm has been developed to make onboard implementation of this method feasible. These methods have been applied to reconfigurable entry flight control design for the X-33 vehicle. Examples presented demonstrate simultaneous tracking of angle-of-attack and roll angle commands during failures of the fight body flap actuator. Although simulations demonstrate success of the first method in most cases, the control-allocation method appears to provide uniformly better performance in all cases.

Verifiable Adaptive Control with Analytical Stability Margins by Optimal Control Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.

2010-01-01

This paper presents a verifiable model-reference adaptive control method based on an optimal control formulation for linear uncertain systems. A predictor model is formulated to enable a parameter estimation of the system parametric uncertainty. The adaptation is based on both the tracking error and predictor error. Using a singular perturbation argument, it can be shown that the closed-loop system tends to a linear time invariant model asymptotically under an assumption of fast adaptation. A stability margin analysis is given to estimate a lower bound of the time delay margin using a matrix measure method. Using this analytical method, the free design parameter n of the optimal control modification adaptive law can be determined to meet a specification of stability margin for verification purposes.

A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI

PubMed Central

Stawicki, Piotr; Gembler, Felix; Rezeika, Aya; Volosyak, Ivan

2017-01-01

Steady state visual evoked potentials (SSVEPs)-based Brain-Computer interfaces (BCIs), as well as eyetracking devices, provide a pathway for re-establishing communication for people with severe disabilities. We fused these control techniques into a novel eyetracking/SSVEP hybrid system, which utilizes eye tracking for initial rough selection and the SSVEP technology for fine target activation. Based on our previous studies, only four stimuli were used for the SSVEP aspect, granting sufficient control for most BCI users. As Eye tracking data is not used for activation of letters, false positives due to inappropriate dwell times are avoided. This novel approach combines the high speed of eye tracking systems and the high classification accuracies of low target SSVEP-based BCIs, leading to an optimal combination of both methods. We evaluated accuracy and speed of the proposed hybrid system with a 30-target spelling application implementing all three control approaches (pure eye tracking, SSVEP and the hybrid system) with 32 participants. Although the highest information transfer rates (ITRs) were achieved with pure eye tracking, a considerable amount of subjects was not able to gain sufficient control over the stand-alone eye-tracking device or the pure SSVEP system (78.13% and 75% of the participants reached reliable control, respectively). In this respect, the proposed hybrid was most universal (over 90% of users achieved reliable control), and outperformed the pure SSVEP system in terms of speed and user friendliness. The presented hybrid system might offer communication to a wider range of users in comparison to the standard techniques. PMID:28379187

Study of a Simulation Tool to Determine Achievable Control Dynamics and Control Power Requirements with Perfect Tracking

NASA Technical Reports Server (NTRS)

Ostroff, Aaron J.

1998-01-01

This paper contains a study of two methods for use in a generic nonlinear simulation tool that could be used to determine achievable control dynamics and control power requirements while performing perfect tracking maneuvers over the entire flight envelope. The two methods are NDI (nonlinear dynamic inversion) and the SOFFT(Stochastic Optimal Feedforward and Feedback Technology) feedforward control structure. Equivalent discrete and continuous SOFFT feedforward controllers have been developed. These equivalent forms clearly show that the closed-loop plant model loop is a plant inversion and is the same as the NDI formulation. The main difference is that the NDI formulation has a closed-loop controller structure whereas SOFFT uses an open-loop command model. Continuous, discrete, and hybrid controller structures have been developed and integrated into the formulation. Linear simulation results show that seven different configurations all give essentially the same response, with the NDI hybrid being slightly different. The SOFFT controller gave better tracking performance compared to the NDI controller when a nonlinear saturation element was added. Future plans include evaluation using a nonlinear simulation.

Optimal Strategy for Integrated Dynamic Inventory Control and Supplier Selection in Unknown Environment via Stochastic Dynamic Programming

NASA Astrophysics Data System (ADS)

Sutrisno; Widowati; Solikhin

2016-06-01

In this paper, we propose a mathematical model in stochastic dynamic optimization form to determine the optimal strategy for an integrated single product inventory control problem and supplier selection problem where the demand and purchasing cost parameters are random. For each time period, by using the proposed model, we decide the optimal supplier and calculate the optimal product volume purchased from the optimal supplier so that the inventory level will be located at some point as close as possible to the reference point with minimal cost. We use stochastic dynamic programming to solve this problem and give several numerical experiments to evaluate the model. From the results, for each time period, the proposed model was generated the optimal supplier and the inventory level was tracked the reference point well.

Modified optimal control pilot model for computer-aided design and analysis

NASA Technical Reports Server (NTRS)

Davidson, John B.; Schmidt, David K.

1992-01-01

This paper presents the theoretical development of a modified optimal control pilot model based upon the optimal control model (OCM) of the human operator developed by Kleinman, Baron, and Levison. This model is input compatible with the OCM and retains other key aspects of the OCM, such as a linear quadratic solution for the pilot gains with inclusion of control rate in the cost function, a Kalman estimator, and the ability to account for attention allocation and perception threshold effects. An algorithm designed for each implementation in current dynamic systems analysis and design software is presented. Example results based upon the analysis of a tracking task using three basic dynamic systems are compared with measured results and with similar analyses performed with the OCM and two previously proposed simplified optimal pilot models. The pilot frequency responses and error statistics obtained with this modified optimal control model are shown to compare more favorably to the measured experimental results than the other previously proposed simplified models evaluated.

A new enhanced index tracking model in portfolio optimization with sum weighted approach

NASA Astrophysics Data System (ADS)

Siew, Lam Weng; Jaaman, Saiful Hafizah; Hoe, Lam Weng

2017-04-01

Index tracking is a portfolio management which aims to construct the optimal portfolio to achieve similar return with the benchmark index return at minimum tracking error without purchasing all the stocks that make up the index. Enhanced index tracking is an improved portfolio management which aims to generate higher portfolio return than the benchmark index return besides minimizing the tracking error. The objective of this paper is to propose a new enhanced index tracking model with sum weighted approach to improve the existing index tracking model for tracking the benchmark Technology Index in Malaysia. The optimal portfolio composition and performance of both models are determined and compared in terms of portfolio mean return, tracking error and information ratio. The results of this study show that the optimal portfolio of the proposed model is able to generate higher mean return than the benchmark index at minimum tracking error. Besides that, the proposed model is able to outperform the existing model in tracking the benchmark index. The significance of this study is to propose a new enhanced index tracking model with sum weighted apporach which contributes 67% improvement on the portfolio mean return as compared to the existing model.

Closed-form recursive formula for an optimal tracker with terminal constraints

NASA Technical Reports Server (NTRS)

Juang, J.-N.; Turner, J. D.; Chun, H. M.

1984-01-01

Feedback control laws are derived for a class of optimal finite time tracking problems with terminal constraints. Analytical solutions are obtained for the feedback gain and the closed-loop response trajectory. Such formulations are expressed in recursive forms so that a real-time computer implementation becomes feasible. Two examples are given to illustrate the validity and usefulness of the formulations.

Disturbance observer based model predictive control for accurate atmospheric entry of spacecraft

NASA Astrophysics Data System (ADS)

Wu, Chao; Yang, Jun; Li, Shihua; Li, Qi; Guo, Lei

2018-05-01

Facing the complex aerodynamic environment of Mars atmosphere, a composite atmospheric entry trajectory tracking strategy is investigated in this paper. External disturbances, initial states uncertainties and aerodynamic parameters uncertainties are the main problems. The composite strategy is designed to solve these problems and improve the accuracy of Mars atmospheric entry. This strategy includes a model predictive control for optimized trajectory tracking performance, as well as a disturbance observer based feedforward compensation for external disturbances and uncertainties attenuation. 500-run Monte Carlo simulations show that the proposed composite control scheme achieves more precise Mars atmospheric entry (3.8 km parachute deployment point distribution error) than the baseline control scheme (8.4 km) and integral control scheme (5.8 km).

Servo-hydraulic actuator in controllable canonical form: Identification and experimental validation

NASA Astrophysics Data System (ADS)

Maghareh, Amin; Silva, Christian E.; Dyke, Shirley J.

2018-02-01

Hydraulic actuators have been widely used to experimentally examine structural behavior at multiple scales. Real-time hybrid simulation (RTHS) is one innovative testing method that largely relies on such servo-hydraulic actuators. In RTHS, interface conditions must be enforced in real time, and controllers are often used to achieve tracking of the desired displacements. Thus, neglecting the dynamics of hydraulic transfer system may result either in system instability or sub-optimal performance. Herein, we propose a nonlinear dynamical model for a servo-hydraulic actuator (a.k.a. hydraulic transfer system) coupled with a nonlinear physical specimen. The nonlinear dynamical model is transformed into controllable canonical form for further tracking control design purposes. Through a number of experiments, the controllable canonical model is validated.

Reconfigurable Flight Control Designs With Application to the X-33 Vehicle

NASA Technical Reports Server (NTRS)

Burken, John J.; Lu, Ping; Wu, Zhenglu

1999-01-01

Two methods for control system reconfiguration have been investigated. The first method is a robust servomechanism control approach (optimal tracking problem) that is a generalization of the classical proportional-plus-integral control to multiple input-multiple output systems. The second method is a control-allocation approach based on a quadratic programming formulation. A globally convergent fixed-point iteration algorithm has been developed to make onboard implementation of this method feasible. These methods have been applied to reconfigurable entry flight control design for the X-33 vehicle. Examples presented demonstrate simultaneous tracking of angle-of-attack and roll angle commands during failures of the right body flap actuator. Although simulations demonstrate success of the first method in most cases, the control-allocation method appears to provide uniformly better performance in all cases.

Optimization Control of the Color-Coating Production Process for Model Uncertainty

PubMed Central

He, Dakuo; Wang, Zhengsong; Yang, Le; Mao, Zhizhong

2016-01-01

Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results. PMID:27247563

Optimization Control of the Color-Coating Production Process for Model Uncertainty.

PubMed

He, Dakuo; Wang, Zhengsong; Yang, Le; Mao, Zhizhong

2016-01-01

Optimized control of the color-coating production process (CCPP) aims at reducing production costs and improving economic efficiency while meeting quality requirements. However, because optimization control of the CCPP is hampered by model uncertainty, a strategy that considers model uncertainty is proposed. Previous work has introduced a mechanistic model of CCPP based on process analysis to simulate the actual production process and generate process data. The partial least squares method is then applied to develop predictive models of film thickness and economic efficiency. To manage the model uncertainty, the robust optimization approach is introduced to improve the feasibility of the optimized solution. Iterative learning control is then utilized to further refine the model uncertainty. The constrained film thickness is transformed into one of the tracked targets to overcome the drawback that traditional iterative learning control cannot address constraints. The goal setting of economic efficiency is updated continuously according to the film thickness setting until this reaches its desired value. Finally, fuzzy parameter adjustment is adopted to ensure that the economic efficiency and film thickness converge rapidly to their optimized values under the constraint conditions. The effectiveness of the proposed optimization control strategy is validated by simulation results.

Intelligent complementary sliding-mode control for LUSMS-based X-Y-theta motion control stage.

PubMed

Lin, Faa-Jeng; Chen, Syuan-Yi; Shyu, Kuo-Kai; Liu, Yen-Hung

2010-07-01

An intelligent complementary sliding-mode control (ICSMC) system using a recurrent wavelet-based Elman neural network (RWENN) estimator is proposed in this study to control the mover position of a linear ultrasonic motors (LUSMs)-based X-Y-theta motion control stage for the tracking of various contours. By the addition of a complementary generalized error transformation, the complementary sliding-mode control (CSMC) can efficiently reduce the guaranteed ultimate bound of the tracking error by half compared with the slidingmode control (SMC) while using the saturation function. To estimate a lumped uncertainty on-line and replace the hitting control of the CSMC directly, the RWENN estimator is adopted in the proposed ICSMC system. In the RWENN, each hidden neuron employs a different wavelet function as an activation function to improve both the convergent precision and the convergent time compared with the conventional Elman neural network (ENN). The estimation laws of the RWENN are derived using the Lyapunov stability theorem to train the network parameters on-line. A robust compensator is also proposed to confront the uncertainties including approximation error, optimal parameter vectors, and higher-order terms in Taylor series. Finally, some experimental results of various contours tracking show that the tracking performance of the ICSMC system is significantly improved compared with the SMC and CSMC systems.

Dynamic modelling and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances

NASA Astrophysics Data System (ADS)

Yang, Xinxin; Ge, Shuzhi Sam; He, Wei

2018-04-01

In this paper, both the closed-form dynamics and adaptive robust tracking control of a space robot with two-link flexible manipulators under unknown disturbances are developed. The dynamic model of the system is described with assumed modes approach and Lagrangian method. The flexible manipulators are represented as Euler-Bernoulli beams. Based on singular perturbation technique, the displacements/joint angles and flexible modes are modelled as slow and fast variables, respectively. A sliding mode control is designed for trajectories tracking of the slow subsystem under unknown but bounded disturbances, and an adaptive sliding mode control is derived for slow subsystem under unknown slowly time-varying disturbances. An optimal linear quadratic regulator method is proposed for the fast subsystem to damp out the vibrations of the flexible manipulators. Theoretical analysis validates the stability of the proposed composite controller. Numerical simulation results demonstrate the performance of the closed-loop flexible space robot system.

Fuzzy Controller Design Using Evolutionary Techniques for Twin Rotor MIMO System: A Comparative Study.

PubMed

Hashim, H A; Abido, M A

2015-01-01

This paper presents a comparative study of fuzzy controller design for the twin rotor multi-input multioutput (MIMO) system (TRMS) considering most promising evolutionary techniques. These are gravitational search algorithm (GSA), particle swarm optimization (PSO), artificial bee colony (ABC), and differential evolution (DE). In this study, the gains of four fuzzy proportional derivative (PD) controllers for TRMS have been optimized using the considered techniques. The optimization techniques are developed to identify the optimal control parameters for system stability enhancement, to cancel high nonlinearities in the model, to reduce the coupling effect, and to drive TRMS pitch and yaw angles into the desired tracking trajectory efficiently and accurately. The most effective technique in terms of system response due to different disturbances has been investigated. In this work, it is observed that GSA is the most effective technique in terms of solution quality and convergence speed.

Fuzzy Controller Design Using Evolutionary Techniques for Twin Rotor MIMO System: A Comparative Study

PubMed Central

Hashim, H. A.; Abido, M. A.

2015-01-01

This paper presents a comparative study of fuzzy controller design for the twin rotor multi-input multioutput (MIMO) system (TRMS) considering most promising evolutionary techniques. These are gravitational search algorithm (GSA), particle swarm optimization (PSO), artificial bee colony (ABC), and differential evolution (DE). In this study, the gains of four fuzzy proportional derivative (PD) controllers for TRMS have been optimized using the considered techniques. The optimization techniques are developed to identify the optimal control parameters for system stability enhancement, to cancel high nonlinearities in the model, to reduce the coupling effect, and to drive TRMS pitch and yaw angles into the desired tracking trajectory efficiently and accurately. The most effective technique in terms of system response due to different disturbances has been investigated. In this work, it is observed that GSA is the most effective technique in terms of solution quality and convergence speed. PMID:25960738

Improving piezo actuators for nanopositioning tasks

NASA Astrophysics Data System (ADS)

Seeliger, Martin; Gramov, Vassil; Götz, Bernt

2018-02-01

In recent years, numerous applications emerged on the market with seemingly contradicting demands. On one side, the structure size decreased while on the other side, the overall sample size and speed of operation increased. Although the principle usage of piezoelectric positioning solutions has become a standard in the field of micro- and nanopositioning, surface inspection and manipulation, piezosystem jena now enhanced the performance beyond simple control loop tuning and actuator design. In automated manufacturing machines, a given signal has to be tracked fast and precise. However, control systems naturally decrease the ability to follow this signal in real time. piezosystem jena developed a new signal feed forward system bypassing the PID control. This way, we could reduce signal tracking errors by a factor of three compared to a conventionally optimized PID control. Of course, PID-values still have to be adjusted to specific conditions, e.g. changing additional mass, to optimize the performance. This can now be done with a new automatic tuning tool designed to analyze the current setup, find the best fitting configuration, and also gather and display theoretical as well as experimental performance data. Thus, the control quality of a mechanical setup can be improved within a few minutes without the need of external calibration equipment. Furthermore, new mechanical optimization techniques that focus not only on the positioning device, but also take the whole setup into account, prevent parasitic motion down to a few nanometers.

Optimal tyre usage for a Formula One car

NASA Astrophysics Data System (ADS)

Tremlett, A. J.; Limebeer, D. J. N.

2016-10-01

Variations in track temperature, surface conditions and layout have led tyre manufacturers to produce a range of rubber compounds for race events. Each compound has unique friction and durability characteristics. Efficient tyre management over a full race distance is a crucial component of a competitive race strategy. A minimum lap time optimal control calculation and a thermodynamic tyre wear model are used to establish optimal tyre warming and tyre usage strategies. Lap time sensitivities demonstrate that relatively small changes in control strategy can lead to significant reductions in the associated wear metrics. The illustrated methodology shows how vehicle setup parameters can be optimised for minimum tyre usage.

An Optimal Parameter Discretization Strategy for Multiple Model Adaptive Estimation and Control

DTIC Science & Technology

1989-12-01

Zicker . MMAE-Based Control with Space- Time Point Process Observations. IEEE Transactions on Aerospace and Elec- tronic Systems, AES-21 (3):292-300, 1985...Transactions of the Conference of Army Math- ematicians, Bethesda MD, 1982. (AD-POO1 033). 65. William L. Zicker . Pointing and Tracking of Particle

Error rate information in attention allocation pilot models

NASA Technical Reports Server (NTRS)

Faulkner, W. H.; Onstott, E. D.

1977-01-01

The Northrop urgency decision pilot model was used in a command tracking task to compare the optimized performance of multiaxis attention allocation pilot models whose urgency functions were (1) based on tracking error alone, and (2) based on both tracking error and error rate. A matrix of system dynamics and command inputs was employed, to create both symmetric and asymmetric two axis compensatory tracking tasks. All tasks were single loop on each axis. Analysis showed that a model that allocates control attention through nonlinear urgency functions using only error information could not achieve performance of the full model whose attention shifting algorithm included both error and error rate terms. Subsequent to this analysis, tracking performance predictions for the full model were verified by piloted flight simulation. Complete model and simulation data are presented.

Optimal Appearance Model for Visual Tracking

PubMed Central

Wang, Yuru; Jiang, Longkui; Liu, Qiaoyuan; Yin, Minghao

2016-01-01

Many studies argue that integrating multiple cues in an adaptive way increases tracking performance. However, what is the definition of adaptiveness and how to realize it remains an open issue. On the premise that the model with optimal discriminative ability is also optimal for tracking the target, this work realizes adaptiveness and robustness through the optimization of multi-cue integration models. Specifically, based on prior knowledge and current observation, a set of discrete samples are generated to approximate the foreground and background distribution. With the goal of optimizing the classification margin, an objective function is defined, and the appearance model is optimized by introducing optimization algorithms. The proposed optimized appearance model framework is embedded into a particle filter for a field test, and it is demonstrated to be robust against various kinds of complex tracking conditions. This model is general and can be easily extended to other parameterized multi-cue models. PMID:26789639

State-dependent differential Riccati equation to track control of time-varying systems with state and control nonlinearities.

PubMed

Korayem, M H; Nekoo, S R

2015-07-01

This work studies an optimal control problem using the state-dependent Riccati equation (SDRE) in differential form to track for time-varying systems with state and control nonlinearities. The trajectory tracking structure provides two nonlinear differential equations: the state-dependent differential Riccati equation (SDDRE) and the feed-forward differential equation. The independence of the governing equations and stability of the controller are proven along the trajectory using the Lyapunov approach. Backward integration (BI) is capable of solving the equations as a numerical solution; however, the forward solution methods require the closed-form solution to fulfill the task. A closed-form solution is introduced for SDDRE, but the feed-forward differential equation has not yet been obtained. Different ways of solving the problem are expressed and analyzed. These include BI, closed-form solution with corrective assumption, approximate solution, and forward integration. Application of the tracking problem is investigated to control robotic manipulators possessing rigid or flexible joints. The intention is to release a general program for automatic implementation of an SDDRE controller for any manipulator that obeys the Denavit-Hartenberg (D-H) principle when only D-H parameters are received as input data. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Sensor management in RADAR/IRST track fusion

NASA Astrophysics Data System (ADS)

Hu, Shi-qiang; Jing, Zhong-liang

2004-07-01

In this paper, a novel radar management strategy technique suitable for RADAR/IRST track fusion, which is based on Fisher Information Matrix (FIM) and fuzzy stochastic decision approach, is put forward. Firstly, optimal radar measurements' scheduling is obtained by the method of maximizing determinant of the Fisher information matrix of radar and IRST measurements, which is managed by the expert system. Then, suggested a "pseudo sensor" to predict the possible target position using the polynomial method based on the radar and IRST measurements, using "pseudo sensor" model to estimate the target position even if the radar is turned off. At last, based on the tracking performance and the state of target maneuver, fuzzy stochastic decision is used to adjust the optimal radar scheduling and retrieve the module parameter of "pseudo sensor". The experiment result indicates that the algorithm can not only limit Radar activity effectively but also keep the tracking accuracy of active/passive system well. And this algorithm eliminates the drawback of traditional Radar management methods that the Radar activity is fixed and not easy to control and protect.

Charged particle tracking without magnetic field: Optimal measurement of track momentum by a Bayesian analysis of the multiple measurements of deflections due to multiple scattering

NASA Astrophysics Data System (ADS)

Frosini, Mikael; Bernard, Denis

2017-09-01

We revisit the precision of the measurement of track parameters (position, angle) with optimal methods in the presence of detector resolution, multiple scattering and zero magnetic field. We then obtain an optimal estimator of the track momentum by a Bayesian analysis of the filtering innovations of a series of Kalman filters applied to the track. This work could pave the way to the development of autonomous high-performance gas time-projection chambers (TPC) or silicon wafer γ-ray space telescopes and be a powerful guide in the optimization of the design of the multi-kilo-ton liquid argon TPCs that are under development for neutrino studies.

Sliding Mode Thermal Control System for Space Station Furnace Facility

NASA Technical Reports Server (NTRS)

Jackson Mark E.; Shtessel, Yuri B.

1998-01-01

The decoupled control of the nonlinear, multiinput-multioutput, and highly coupled space station furnace facility (SSFF) thermal control system is addressed. Sliding mode control theory, a subset of variable-structure control theory, is employed to increase the performance, robustness, and reliability of the SSFF's currently designed control system. This paper presents the nonlinear thermal control system description and develops the sliding mode controllers that cause the interconnected subsystems to operate in their local sliding modes, resulting in control system invariance to plant uncertainties and external and interaction disturbances. The desired decoupled flow-rate tracking is achieved by optimization of the local linear sliding mode equations. The controllers are implemented digitally and extensive simulation results are presented to show the flow-rate tracking robustness and invariance to plant uncertainties, nonlinearities, external disturbances, and variations of the system pressure supplied to the controlled subsystems.

Grey Wolf based control for speed ripple reduction at low speed operation of PMSM drives.

PubMed

Djerioui, Ali; Houari, Azeddine; Ait-Ahmed, Mourad; Benkhoris, Mohamed-Fouad; Chouder, Aissa; Machmoum, Mohamed

2018-03-01

Speed ripple at low speed-high torque operation of Permanent Magnet Synchronous Machine (PMSM) drives is considered as one of the major issues to be treated. The presented work proposes an efficient PMSM speed controller based on Grey Wolf (GW) algorithm to ensure a high-performance control for speed ripple reduction at low speed operation. The main idea of the proposed control algorithm is to propose a specific objective function in order to incorporate the advantage of fast optimization process of the GW optimizer. The role of GW optimizer is to find the optimal input controls that satisfy the speed tracking requirements. The synthesis methodology of the proposed control algorithm is detailed and the feasibility and performances of the proposed speed controller is confirmed by simulation and experimental results. The GW algorithm is a model-free controller and the parameters of its objective function are easy to be tuned. The GW controller is compared to PI one on real test bench. Then, the superiority of the first algorithm is highlighted. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

PSO Algorithm Particle Filters for Improving the Performance of Lane Detection and Tracking Systems in Difficult Roads

PubMed Central

Cheng, Wen-Chang

2012-01-01

In this paper we propose a robust lane detection and tracking method by combining particle filters with the particle swarm optimization method. This method mainly uses the particle filters to detect and track the local optimum of the lane model in the input image and then seeks the global optimal solution of the lane model by a particle swarm optimization method. The particle filter can effectively complete lane detection and tracking in complicated or variable lane environments. However, the result obtained is usually a local optimal system status rather than the global optimal system status. Thus, the particle swarm optimization method is used to further refine the global optimal system status in all system statuses. Since the particle swarm optimization method is a global optimization algorithm based on iterative computing, it can find the global optimal lane model by simulating the food finding way of fish school or insects under the mutual cooperation of all particles. In verification testing, the test environments included highways and ordinary roads as well as straight and curved lanes, uphill and downhill lanes, lane changes, etc. Our proposed method can complete the lane detection and tracking more accurately and effectively then existing options. PMID:23235453

Integrated multiple-model adaptive fault identification and reconfigurable fault-tolerant control for Lead-Wing close formation systems

NASA Astrophysics Data System (ADS)

Liu, Chun; Jiang, Bin; Zhang, Ke

2018-03-01

This paper investigates the attitude and position tracking control problem for Lead-Wing close formation systems in the presence of loss of effectiveness and lock-in-place or hardover failure. In close formation flight, Wing unmanned aerial vehicle movements are influenced by vortex effects of the neighbouring Lead unmanned aerial vehicle. This situation allows modelling of aerodynamic coupling vortex-effects and linearisation based on optimal close formation geometry. Linearised Lead-Wing close formation model is transformed into nominal robust H-infinity models with respect to Mach hold, Heading hold, and Altitude hold autopilots; static feedback H-infinity controller is designed to guarantee effective tracking of attitude and position while manoeuvring Lead unmanned aerial vehicle. Based on H-infinity control design, an integrated multiple-model adaptive fault identification and reconfigurable fault-tolerant control scheme is developed to guarantee asymptotic stability of close-loop systems, error signal boundedness, and attitude and position tracking properties. Simulation results for Lead-Wing close formation systems validate the efficiency of the proposed integrated multiple-model adaptive control algorithm.

Reusable Launch Vehicle Control In Multiple Time Scale Sliding Modes

NASA Technical Reports Server (NTRS)

Shtessel, Yuri; Hall, Charles; Jackson, Mark

2000-01-01

A reusable launch vehicle control problem during ascent is addressed via multiple-time scaled continuous sliding mode control. The proposed sliding mode controller utilizes a two-loop structure and provides robust, de-coupled tracking of both orientation angle command profiles and angular rate command profiles in the presence of bounded external disturbances and plant uncertainties. Sliding mode control causes the angular rate and orientation angle tracking error dynamics to be constrained to linear, de-coupled, homogeneous, and vector valued differential equations with desired eigenvalues placement. Overall stability of a two-loop control system is addressed. An optimal control allocation algorithm is designed that allocates torque commands into end-effector deflection commands, which are executed by the actuators. The dual-time scale sliding mode controller was designed for the X-33 technology demonstration sub-orbital launch vehicle in the launch mode. Simulation results show that the designed controller provides robust, accurate, de-coupled tracking of the orientation angle command profiles in presence of external disturbances and vehicle inertia uncertainties. This is a significant advancement in performance over that achieved with linear, gain scheduled control systems currently being used for launch vehicles.

Time-domain prefilter design for enhanced tracking and vibration suppression in machine motion control

NASA Astrophysics Data System (ADS)

Cole, Matthew O. T.; Shinonawanik, Praween; Wongratanaphisan, Theeraphong

2018-05-01

Structural flexibility can impact negatively on machine motion control systems by causing unmeasured positioning errors and vibration at locations where accurate motion is important for task execution. To compensate for these effects, command signal prefiltering may be applied. In this paper, a new FIR prefilter design method is described that combines finite-time vibration cancellation with dynamic compensation properties. The time-domain formulation exploits the relation between tracking error and the moment values of the prefilter impulse response function. Optimal design solutions for filters having minimum H2 norm are derived and evaluated. The control approach does not require additional actuation or sensing and can be effective even without complete and accurate models of the machine dynamics. Results from implementation and testing on an experimental high-speed manipulator having a Delta robot architecture with directionally compliant end-effector are presented. The results show the importance of prefilter moment values for tracking performance and confirm that the proposed method can achieve significant reductions in both peak and RMS tracking error, as well as settling time, for complex motion patterns.

The performance of matched-field track-before-detect methods using shallow-water Pacific data.

PubMed

Tantum, Stacy L; Nolte, Loren W; Krolik, Jeffrey L; Harmanci, Kerem

2002-07-01

Matched-field track-before-detect processing, which extends the concept of matched-field processing to include modeling of the source dynamics, has recently emerged as a promising approach for maintaining the track of a moving source. In this paper, optimal Bayesian and minimum variance beamforming track-before-detect algorithms which incorporate a priori knowledge of the source dynamics in addition to the underlying uncertainties in the ocean environment are presented. A Markov model is utilized for the source motion as a means of capturing the stochastic nature of the source dynamics without assuming uniform motion. In addition, the relationship between optimal Bayesian track-before-detect processing and minimum variance track-before-detect beamforming is examined, revealing how an optimal tracking philosophy may be used to guide the modification of existing beamforming techniques to incorporate track-before-detect capabilities. Further, the benefits of implementing an optimal approach over conventional methods are illustrated through application of these methods to shallow-water Pacific data collected as part of the SWellEX-1 experiment. The results show that incorporating Markovian dynamics for the source motion provides marked improvement in the ability to maintain target track without the use of a uniform velocity hypothesis.

Closed-form recursive formula for an optimal tracker with terminal constraints

NASA Technical Reports Server (NTRS)

Juang, J. N.; Turner, J. D.; Chun, H. M.

1986-01-01

Feedback control laws are derived for a class of optimal finite time tracking problems with terminal constraints. Analytical solutions are obtained for the feedback gain and the closed-loop response trajectory. Such formulations are expressed in recursive forms so that a real-time computer implementation becomes feasible. An example involving the feedback slewing of a flexible spacecraft is given to illustrate the validity and usefulness of the formulations.

Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects.

PubMed

Kang, Ziho; Mandal, Saptarshi; Crutchfield, Jerry; Millan, Angel; McClung, Sarah N

2016-01-01

Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1) participants interrogate dynamic multielement objects that can overlap on the display and (2) visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were addressed by (1) developing dynamic areas of interests (AOIs) in the form of either convex or rectangular shapes to represent the moving and shape-changing multielement objects, (2) introducing the concept of AOI gap tolerance (AGT) that controls the size of the AOIs to address the overlapping and visual angle error issues, and (3) finding a near optimal AGT value. The approach was tested in the context of air traffic control (ATC) operations where air traffic controller specialists (ATCSs) interrogated multiple moving aircraft on a radar display to detect and control the aircraft for the purpose of maintaining safe and expeditious air transportation. In addition, we show how eye tracking analysis results can differ based on how we define dynamic AOIs to determine eye fixations on moving objects. The results serve as a framework to more accurately analyze eye tracking data and to better support the analysis of human performance.

Designs and Algorithms to Map Eye Tracking Data with Dynamic Multielement Moving Objects

PubMed Central

Mandal, Saptarshi

2016-01-01

Design concepts and algorithms were developed to address the eye tracking analysis issues that arise when (1) participants interrogate dynamic multielement objects that can overlap on the display and (2) visual angle error of the eye trackers is incapable of providing exact eye fixation coordinates. These issues were addressed by (1) developing dynamic areas of interests (AOIs) in the form of either convex or rectangular shapes to represent the moving and shape-changing multielement objects, (2) introducing the concept of AOI gap tolerance (AGT) that controls the size of the AOIs to address the overlapping and visual angle error issues, and (3) finding a near optimal AGT value. The approach was tested in the context of air traffic control (ATC) operations where air traffic controller specialists (ATCSs) interrogated multiple moving aircraft on a radar display to detect and control the aircraft for the purpose of maintaining safe and expeditious air transportation. In addition, we show how eye tracking analysis results can differ based on how we define dynamic AOIs to determine eye fixations on moving objects. The results serve as a framework to more accurately analyze eye tracking data and to better support the analysis of human performance. PMID:27725830

Genetic algorithm with maximum-minimum crossover (GA-MMC) applied in optimization of radiation pattern control of phased-array radars for rocket tracking systems.

PubMed

Silva, Leonardo W T; Barros, Vitor F; Silva, Sandro G

2014-08-18

In launching operations, Rocket Tracking Systems (RTS) process the trajectory data obtained by radar sensors. In order to improve functionality and maintenance, radars can be upgraded by replacing antennas with parabolic reflectors (PRs) with phased arrays (PAs). These arrays enable the electronic control of the radiation pattern by adjusting the signal supplied to each radiating element. However, in projects of phased array radars (PARs), the modeling of the problem is subject to various combinations of excitation signals producing a complex optimization problem. In this case, it is possible to calculate the problem solutions with optimization methods such as genetic algorithms (GAs). For this, the Genetic Algorithm with Maximum-Minimum Crossover (GA-MMC) method was developed to control the radiation pattern of PAs. The GA-MMC uses a reconfigurable algorithm with multiple objectives, differentiated coding and a new crossover genetic operator. This operator has a different approach from the conventional one, because it performs the crossover of the fittest individuals with the least fit individuals in order to enhance the genetic diversity. Thus, GA-MMC was successful in more than 90% of the tests for each application, increased the fitness of the final population by more than 20% and reduced the premature convergence.

Genetic Algorithm with Maximum-Minimum Crossover (GA-MMC) Applied in Optimization of Radiation Pattern Control of Phased-Array Radars for Rocket Tracking Systems

PubMed Central

Silva, Leonardo W. T.; Barros, Vitor F.; Silva, Sandro G.

2014-01-01

In launching operations, Rocket Tracking Systems (RTS) process the trajectory data obtained by radar sensors. In order to improve functionality and maintenance, radars can be upgraded by replacing antennas with parabolic reflectors (PRs) with phased arrays (PAs). These arrays enable the electronic control of the radiation pattern by adjusting the signal supplied to each radiating element. However, in projects of phased array radars (PARs), the modeling of the problem is subject to various combinations of excitation signals producing a complex optimization problem. In this case, it is possible to calculate the problem solutions with optimization methods such as genetic algorithms (GAs). For this, the Genetic Algorithm with Maximum-Minimum Crossover (GA-MMC) method was developed to control the radiation pattern of PAs. The GA-MMC uses a reconfigurable algorithm with multiple objectives, differentiated coding and a new crossover genetic operator. This operator has a different approach from the conventional one, because it performs the crossover of the fittest individuals with the least fit individuals in order to enhance the genetic diversity. Thus, GA-MMC was successful in more than 90% of the tests for each application, increased the fitness of the final population by more than 20% and reduced the premature convergence. PMID:25196013

Optimization of control gain by operator adjustment

NASA Technical Reports Server (NTRS)

Kruse, W.; Rothbauer, G.

1973-01-01

An optimal gain was established by measuring errors at 5 discrete control gain settings in an experimental set-up consisting of a 2-dimensional, first-order pursuit tracking task performed by subjects (S's). No significant experience effect on optimum gain setting was found in the first experiment. During the second experiment, in which control gain was continuously adjustable, high experienced S's tended to reach the previously determined optimum gain quite accurately and quickly. Less experienced S's tended to select a marginally optimum gain either below or above the experimentally determined optimum depending on initial control gain setting, although mean settings of both groups were equal. This quick and simple method is recommended for selecting control gains for different control systems and forcing functions.

Comparison between goal programming and cointegration approaches in enhanced index tracking

NASA Astrophysics Data System (ADS)

Lam, Weng Siew; Jamaan, Saiful Hafizah Hj.

2013-04-01

Index tracking is a popular form of passive fund management in stock market. Passive management is a buy-and-hold strategy that aims to achieve rate of return similar to the market return. Index tracking problem is a problem of reproducing the performance of a stock market index, without purchasing all of the stocks that make up the index. This can be done by establishing an optimal portfolio that minimizes risk or tracking error. An improved index tracking (enhanced index tracking) is a dual-objective optimization problem, a trade-off between maximizing the mean return and minimizing the tracking error. Enhanced index tracking aims to generate excess return over the return achieved by the index. The objective of this study is to compare the portfolio compositions and performances by using two different approaches in enhanced index tracking problem, which are goal programming and cointegration. The result of this study shows that the optimal portfolios for both approaches are able to outperform the Malaysia market index which is Kuala Lumpur Composite Index. Both approaches give different optimal portfolio compositions. Besides, the cointegration approach outperforms the goal programming approach because the cointegration approach gives higher mean return and lower risk or tracking error. Therefore, the cointegration approach is more appropriate for the investors in Malaysia.

Improving maximum power point tracking of partially shaded photovoltaic system by using IPSO-BELBIC

NASA Astrophysics Data System (ADS)

Al-Alim El-Garhy, M. Abd; Mubarak, R. I.; El-Bably, M.

2017-08-01

Solar photovoltaic (PV) arrays in remote applications are often related to the rapid changes in the partial shading pattern. Rapid changes of the partial shading pattern make the tracking of maximum power point (MPP) of the global peak through the local ones too difficult. An essential need to make a fast and efficient algorithm to detect the peaks values which always vary as the sun irradiance changes. This paper presents two algorithms based on the improved particle swarm optimization technique one of them with PID controller (IPSO-PID), and the other one with Brain Emotional Learning Based Intelligent Controller (IPSO-BELBIC). These techniques improve the maximum power point (MPP) tracking capabilities for photovoltaic (PV) system under partial shading circumstances. The main aim of these improved algorithms is to accelerate the velocity of IPSO to reach to (MPP) and increase its efficiency. These algorithms also improve the tracking time under complex irradiance conditions. Based on these conditions, the tracking time of these presented techniques improves to 2 msec, with an efficiency of 100%.

Nonlinear optimal control for the synchronization of chaotic and hyperchaotic finance systems

NASA Astrophysics Data System (ADS)

Rigatos, G.; Siano, P.; Loia, V.; Ademi, S.; Ghosh, T.

2017-11-01

It is possible to make specific finance systems get synchronized to other finance systems exhibiting chaotic and hyperchaotic dynamics, by applying nonlinear optimal (H-infinity) control. This signifies that chaotic behavior can be generated in finance systems by exerting a suitable control input. Actually, a lead financial system is considered which exhibits inherently chaotic dynamics. Moreover, a follower finance system is introduced having parameters in its model that inherently prohibit the appearance of chaotic dynamics. Through the application of a suitable nonlinear optimal (H-infinity) control input it is proven that the follower finance system can replicate the chaotic dynamics of the lead finance system. By applying Lyapunov analysis it is proven that asymptotically the follower finance system gets synchronized with the lead system and that the tracking error between the state variables of the two systems vanishes.

Optimum Sensors Integration for Multi-Sensor Multi-Target Environment for Ballistic Missile Defense Applications

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

Imam, Neena; Barhen, Jacob; Glover, Charles Wayne

2012-01-01

Multi-sensor networks may face resource limitations in a dynamically evolving multiple target tracking scenario. It is necessary to task the sensors efficiently so that the overall system performance is maximized within the system constraints. The central sensor resource manager may control the sensors to meet objective functions that are formulated to meet system goals such as minimization of track loss, maximization of probability of target detection, and minimization of track error. This paper discusses the variety of techniques that may be utilized to optimize sensor performance for either near term gain or future reward over a longer time horizon.

Markerless human motion tracking using hierarchical multi-swarm cooperative particle swarm optimization.

PubMed

Saini, Sanjay; Zakaria, Nordin; Rambli, Dayang Rohaya Awang; Sulaiman, Suziah

2015-01-01

The high-dimensional search space involved in markerless full-body articulated human motion tracking from multiple-views video sequences has led to a number of solutions based on metaheuristics, the most recent form of which is Particle Swarm Optimization (PSO). However, the classical PSO suffers from premature convergence and it is trapped easily into local optima, significantly affecting the tracking accuracy. To overcome these drawbacks, we have developed a method for the problem based on Hierarchical Multi-Swarm Cooperative Particle Swarm Optimization (H-MCPSO). The tracking problem is formulated as a non-linear 34-dimensional function optimization problem where the fitness function quantifies the difference between the observed image and a projection of the model configuration. Both the silhouette and edge likelihoods are used in the fitness function. Experiments using Brown and HumanEva-II dataset demonstrated that H-MCPSO performance is better than two leading alternative approaches-Annealed Particle Filter (APF) and Hierarchical Particle Swarm Optimization (HPSO). Further, the proposed tracking method is capable of automatic initialization and self-recovery from temporary tracking failures. Comprehensive experimental results are presented to support the claims.

Neural network based optimal control of HVAC&R systems

NASA Astrophysics Data System (ADS)

Ning, Min

Heating, Ventilation, Air-Conditioning and Refrigeration (HVAC&R) systems have wide applications in providing a desired indoor environment for different types of buildings. It is well acknowledged that 30%-40% of the total energy generated is consumed by buildings and HVAC&R systems alone account for more than 50% of the building energy consumption. Low operational efficiency especially under partial load conditions and poor control are part of reasons for such high energy consumption. To improve energy efficiency, HVAC&R systems should be properly operated to maintain a comfortable and healthy indoor environment under dynamic ambient and indoor conditions with the least energy consumption. This research focuses on the optimal operation of HVAC&R systems. The optimization problem is formulated and solved to find the optimal set points for the chilled water supply temperature, discharge air temperature and AHU (air handling unit) fan static pressure such that the indoor environment is maintained with the least chiller and fan energy consumption. To achieve this objective, a dynamic system model is developed first to simulate the system behavior under different control schemes and operating conditions. The system model is modular in structure, which includes a water-cooled vapor compression chiller model and a two-zone VAV system model. A fuzzy-set based extended transformation approach is then applied to investigate the uncertainties of this model caused by uncertain parameters and the sensitivities of the control inputs with respect to the interested model outputs. A multi-layer feed forward neural network is constructed and trained in unsupervised mode to minimize the cost function which is comprised of overall energy cost and penalty cost when one or more constraints are violated. After training, the network is implemented as a supervisory controller to compute the optimal settings for the system. In order to implement the optimal set points predicted by the supervisory controller, a set of five adaptive PI (proportional-integral) controllers are designed for each of the five local control loops of the HVAC&R system. The five controllers are used to track optimal set points and zone air temperature set points. Parameters of these PI controllers are tuned online to reduce tracking errors. The updating rules are derived from Lyapunov stability analysis. Simulation results show that compared to the conventional night reset operation scheme, the optimal operation scheme saves around 10% energy under full load condition and 19% energy under partial load conditions.

Optimal Decentralized Protocol for Electric Vehicle Charging

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

Gan, LW; Topcu, U; Low, SH

We propose a decentralized algorithm to optimally schedule electric vehicle (EV) charging. The algorithm exploits the elasticity of electric vehicle loads to fill the valleys in electric load profiles. We first formulate the EV charging scheduling problem as an optimal control problem, whose objective is to impose a generalized notion of valley-filling, and study properties of optimal charging profiles. We then give a decentralized algorithm to iteratively solve the optimal control problem. In each iteration, EVs update their charging profiles according to the control signal broadcast by the utility company, and the utility company alters the control signal to guidemore » their updates. The algorithm converges to optimal charging profiles (that are as "flat" as they can possibly be) irrespective of the specifications (e.g., maximum charging rate and deadline) of EVs, even if EVs do not necessarily update their charging profiles in every iteration, and use potentially outdated control signal when they update. Moreover, the algorithm only requires each EV solving its local problem, hence its implementation requires low computation capability. We also extend the algorithm to track a given load profile and to real-time implementation.« less

Multiple Target Laser Designator (MTLD)

DTIC Science & Technology

2007-03-01

Optimized Liquid Crystal Scanning Element Optimize the Nonimaging Predictive Algorithm for Target Ranging, Tracking, and Position Estimation...commercial potential. 3.0 PROGRESS THIS QUARTER 3.1 Optimization of Nonimaging Holographic Antenna for Target Tracking and Position Estimation (Task 6) In

Study on robot motion control for intelligent welding processes based on the laser tracking sensor

NASA Astrophysics Data System (ADS)

Zhang, Bin; Wang, Qian; Tang, Chen; Wang, Ju

2017-06-01

A robot motion control method is presented for intelligent welding processes of complex spatial free-form curve seams based on the laser tracking sensor. First, calculate the tip position of the welding torch according to the velocity of the torch and the seam trajectory detected by the sensor. Then, search the optimal pose of the torch under constraints using genetic algorithms. As a result, the intersection point of the weld seam and the laser plane of the sensor is within the detectable range of the sensor. Meanwhile, the angle between the axis of the welding torch and the tangent of the weld seam meets the requirements. The feasibility of the control method is proved by simulation.

Moving-window dynamic optimization: design of stimulation profiles for walking.

PubMed

Dosen, Strahinja; Popović, Dejan B

2009-05-01

The overall goal of the research is to improve control for electrical stimulation-based assistance of walking in hemiplegic individuals. We present the simulation for generating offline input (sensors)-output (intensity of muscle stimulation) representation of walking that serves in synthesizing a rule-base for control of electrical stimulation for restoration of walking. The simulation uses new algorithm termed moving-window dynamic optimization (MWDO). The optimization criterion was to minimize the sum of the squares of tracking errors from desired trajectories with the penalty function on the total muscle efforts. The MWDO was developed in the MATLAB environment and tested using target trajectories characteristic for slow-to-normal walking recorded in healthy individual and a model with the parameters characterizing the potential hemiplegic user. The outputs of the simulation are piecewise constant intensities of electrical stimulation and trajectories generated when the calculated stimulation is applied to the model. We demonstrated the importance of this simulation by showing the outputs for healthy and hemiplegic individuals, using the same target trajectories. Results of the simulation show that the MWDO is an efficient tool for analyzing achievable trajectories and for determining the stimulation profiles that need to be delivered for good tracking.

3D laser traking of a particle in 3DFM

NASA Astrophysics Data System (ADS)

Desai, Kalpit; Welch, Gregory; Bishop, Gary; Taylor, Russell; Superfine, Richard

2003-11-01

The principal goal of 3D tracking in our home-built 3D Magnetic Force Microscope is to monitor movement of the particle with respect to laser beam waist and keep the particle at the center of laser beam. The sensory element is a Quadrant Photo Diode (QPD) which captures scattering of light caused by particle motion with bandwidth up to 40 KHz. XYZ translation stage is the driver element which moves particle back in the center of the laser with accuracy of couple of nanometers and with bandwidth up to 300 Hz. Since our particles vary in size, composition and shape, instead of using a priori model we use standard system identification techniques to have optimal approximation to the relationship between particle motion and QPD response. We have developed position feedback control system software that is capable of 3-dimensional tracking of beads that are attached to cilia on living cells which are beating at up to 15Hz. We have also modeled the control system of instrument to simulate performance of 3D particle tracking for different experimental conditions. Given operational level of nanometers, noise poses a great challenge for the tracking system. We propose to use stochastic control theory approaches to increase robustness of tracking.

ORACLS: A system for linear-quadratic-Gaussian control law design

NASA Technical Reports Server (NTRS)

Armstrong, E. S.

1978-01-01

A modern control theory design package (ORACLS) for constructing controllers and optimal filters for systems modeled by linear time-invariant differential or difference equations is described. Numerical linear-algebra procedures are used to implement the linear-quadratic-Gaussian (LQG) methodology of modern control theory. Algorithms are included for computing eigensystems of real matrices, the relative stability of a matrix, factored forms for nonnegative definite matrices, the solutions and least squares approximations to the solutions of certain linear matrix algebraic equations, the controllability properties of a linear time-invariant system, and the steady state covariance matrix of an open-loop stable system forced by white noise. Subroutines are provided for solving both the continuous and discrete optimal linear regulator problems with noise free measurements and the sampled-data optimal linear regulator problem. For measurement noise, duality theory and the optimal regulator algorithms are used to solve the continuous and discrete Kalman-Bucy filter problems. Subroutines are also included which give control laws causing the output of a system to track the output of a prescribed model.

A Novel Technique for Maximum Power Point Tracking of a Photovoltaic Based on Sensing of Array Current Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

NASA Astrophysics Data System (ADS)

El-Zoghby, Helmy M.; Bendary, Ahmed F.

2016-10-01

Maximum Power Point Tracking (MPPT) is now widely used method in increasing the photovoltaic (PV) efficiency. The conventional MPPT methods have many problems concerning the accuracy, flexibility and efficiency. The MPP depends on the PV temperature and solar irradiation that randomly varied. In this paper an artificial intelligence based controller is presented through implementing of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to obtain maximum power from PV. The ANFIS inputs are the temperature and cell current, and the output is optimal voltage at maximum power. During operation the trained ANFIS senses the PV current using suitable sensor and also senses the temperature to determine the optimal operating voltage that corresponds to the current at MPP. This voltage is used to control the boost converter duty cycle. The MATLAB simulation results shows the effectiveness of the ANFIS with sensing the PV current in obtaining the MPPT from the PV.

Control strategies for wind farm power optimization: LES study

NASA Astrophysics Data System (ADS)

Ciri, Umberto; Rotea, Mario; Leonardi, Stefano

2017-11-01

Turbines in wind farms operate in off-design conditions as wake interactions occur for particular wind directions. Advanced wind farm control strategies aim at coordinating and adjusting turbine operations to mitigate power losses in such conditions. Coordination is achieved by controlling on upstream turbines either the wake intensity, through the blade pitch angle or the generator torque, or the wake direction, through yaw misalignment. Downstream turbines can be adapted to work in waked conditions and limit power losses, using the blade pitch angle or the generator torque. As wind conditions in wind farm operations may change significantly, it is difficult to determine and parameterize the variations of the coordinated optimal settings. An alternative is model-free control and optimization of wind farms, which does not require any parameterization and can track the optimal settings as conditions vary. In this work, we employ a model-free optimization algorithm, extremum-seeking control, to find the optimal set-points of generator torque, blade pitch and yaw angle for a three-turbine configuration. Large-Eddy Simulations are used to provide a virtual environment to evaluate the performance of the control strategies under realistic, unsteady incoming wind. This work was supported by the National Science Foundation, Grants No. 1243482 (the WINDINSPIRE project) and IIP 1362033 (I/UCRC WindSTAR). TACC is acknowledged for providing computational time.

UCAV path planning in the presence of radar-guided surface-to-air missile threats

NASA Astrophysics Data System (ADS)

Zeitz, Frederick H., III

This dissertation addresses the problem of path planning for unmanned combat aerial vehicles (UCAVs) in the presence of radar-guided surface-to-air missiles (SAMs). The radars, collocated with SAM launch sites, operate within the structure of an Integrated Air Defense System (IADS) that permits communication and cooperation between individual radars. The problem is formulated in the framework of the interaction between three sub-systems: the aircraft, the IADS, and the missile. The main features of this integrated model are: The aircraft radar cross section (RCS) depends explicitly on both the aspect and bank angles; hence, the RCS and aircraft dynamics are coupled. The probabilistic nature of IADS tracking is accounted for; namely, the probability that the aircraft has been continuously tracked by the IADS depends on the aircraft RCS and range from the perspective of each radar within the IADS. Finally, the requirement to maintain tracking prior to missile launch and during missile flyout are also modeled. Based on this model, the problem of UCAV path planning is formulated as a minimax optimal control problem, with the aircraft bank angle serving as control. Necessary conditions of optimality for this minimax problem are derived. Based on these necessary conditions, properties of the optimal paths are derived. These properties are used to discretize the dynamic optimization problem into a finite-dimensional, nonlinear programming problem that can be solved numerically. Properties of the optimal paths are also used to initialize the numerical procedure. A homotopy method is proposed to solve the finite-dimensional, nonlinear programming problem, and a heuristic method is proposed to improve the discretization during the homotopy process. Based upon the properties of numerical solutions, a method is proposed for parameterizing and storing information for later recall in flight to permit rapid replanning in response to changing threats. Illustrative examples are presented that confirm the standard flying tactics of "denying range, aspect, and aim," by yielding flight paths that "weave" to avoid long exposures of aspects with large RCS.

A Globally Optimal Particle Tracking Technique for Stereo Imaging Velocimetry Experiments

NASA Technical Reports Server (NTRS)

McDowell, Mark

2008-01-01

An important phase of any Stereo Imaging Velocimetry experiment is particle tracking. Particle tracking seeks to identify and characterize the motion of individual particles entrained in a fluid or air experiment. We analyze a cylindrical chamber filled with water and seeded with density-matched particles. In every four-frame sequence, we identify a particle track by assigning a unique track label for each camera image. The conventional approach to particle tracking is to use an exhaustive tree-search method utilizing greedy algorithms to reduce search times. However, these types of algorithms are not optimal due to a cascade effect of incorrect decisions upon adjacent tracks. We examine the use of a guided evolutionary neural net with simulated annealing to arrive at a globally optimal assignment of tracks. The net is guided both by the minimization of the search space through the use of prior limiting assumptions about valid tracks and by a strategy which seeks to avoid high-energy intermediate states which can trap the net in a local minimum. A stochastic search algorithm is used in place of back-propagation of error to further reduce the chance of being trapped in an energy well. Global optimization is achieved by minimizing an objective function, which includes both track smoothness and particle-image utilization parameters. In this paper we describe our model and present our experimental results. We compare our results with a nonoptimizing, predictive tracker and obtain an average increase in valid track yield of 27 percent

Image-based tracking and sensor resource management for UAVs in an urban environment

NASA Astrophysics Data System (ADS)

Samant, Ashwin; Chang, K. C.

2010-04-01

Coordination and deployment of multiple unmanned air vehicles (UAVs) requires a lot of human resources in order to carry out a successful mission. The complexity of such a surveillance mission is significantly increased in the case of an urban environment where targets can easily escape from the UAV's field of view (FOV) due to intervening building and line-of-sight obstruction. In the proposed methodology, we focus on the control and coordination of multiple UAVs having gimbaled video sensor onboard for tracking multiple targets in an urban environment. We developed optimal path planning algorithms with emphasis on dynamic target prioritizations and persistent target updates. The command center is responsible for target prioritization and autonomous control of multiple UAVs, enabling a single operator to monitor and control a team of UAVs from a remote location. The results are obtained using extensive 3D simulations in Google Earth using Tangent plus Lyapunov vector field guidance for target tracking.

Direct energy balance based active disturbance rejection control for coal-fired power plant.

PubMed

Sun, Li; Hua, Qingsong; Li, Donghai; Pan, Lei; Xue, Yali; Lee, Kwang Y

2017-09-01

The conventional direct energy balance (DEB) based PI control can fulfill the fundamental tracking requirements of the coal-fired power plant. However, it is challenging to deal with the cases when the coal quality variation is present. To this end, this paper introduces the active disturbance rejection control (ADRC) to the DEB structure, where the coal quality variation is deemed as a kind of unknown disturbance that can be estimated and mitigated promptly. Firstly, the nonlinearity of a recent power plant model is analyzed based on the gap metric, which provides guidance on how to set the pressure set-point in line with the power demand. Secondly, the approximate decoupling effect of the DEB structure is analyzed based on the relative gain analysis in frequency domain. Finally, the synthesis of the DEB based ADRC control system is carried out based on multi-objective optimization. The optimized ADRC results show that the integrated absolute error (IAE) indices of the tracking performances in both loops can be simultaneously improved, in comparison with the DEB based PI control and H ∞ control system. The regulation performance in the presence of the coal quality variation is significantly improved under the ADRC control scheme. Moreover, the robustness of the proposed strategy is shown comparable with the H ∞ control. Copyright © 2017. Published by Elsevier Ltd.

The dosimetric impact of inversely optimized arc radiotherapy plan modulation for real-time dynamic MLC tracking delivery.

PubMed

Falk, Marianne; Larsson, Tobias; Keall, Paul; Chul Cho, Byung; Aznar, Marianne; Korreman, Stine; Poulsen, Per; Munck Af Rosenschold, Per

2012-03-01

Real-time dynamic multileaf collimator (MLC) tracking for management of intrafraction tumor motion can be challenging for highly modulated beams, as the leaves need to travel far to adjust for target motion perpendicular to the leaf travel direction. The plan modulation can be reduced by using a leaf position constraint (LPC) that reduces the difference in the position of adjacent MLC leaves in the plan. The purpose of this study was to investigate the impact of the LPC on the quality of inversely optimized arc radiotherapy plans and the effect of the MLC motion pattern on the dosimetric accuracy of MLC tracking delivery. Specifically, the possibility of predicting the accuracy of MLC tracking delivery based on the plan modulation was investigated. Inversely optimized arc radiotherapy plans were created on CT-data of three lung cancer patients. For each case, five plans with a single 358° arc were generated with LPC priorities of 0 (no LPC), 0.25, 0.5, 0.75, and 1 (highest possible LPC), respectively. All the plans had a prescribed dose of 2 Gy × 30, used 6 MV, a maximum dose rate of 600 MU/min and a collimator angle of 45° or 315°. To quantify the plan modulation, an average adjacent leaf distance (ALD) was calculated by averaging the mean adjacent leaf distance for each control point. The linear relationship between the plan quality [i.e., the calculated dose distributions and the number of monitor units (MU)] and the LPC was investigated, and the linear regression coefficient as well as a two tailed confidence level of 95% was used in the evaluation. The effect of the plan modulation on the performance of MLC tracking was tested by delivering the plans to a cylindrical diode array phantom moving with sinusoidal motion in the superior-inferior direction with a peak-to-peak displacement of 2 cm and a cycle time of 6 s. The delivery was adjusted to the target motion using MLC tracking, guided in real-time by an infrared optical system. The dosimetric results were evaluated using gamma index evaluation with static target measurements as reference. The plan quality parameters did not depend significantly on the LPC (p ≥ 0.066), whereas the ALD depended significantly on the LPC (p < 0.001). The gamma index failure rate depended significantly on the ALD, weighted to the percentage of the beam delivered in each control point of the plan (ALD(w)) when MLC tracking was used (p < 0.001), but not for delivery without MLC tracking (p ≥ 0.342). The gamma index failure rate with the criteria of 2% and 2 mm was decreased from > 33.9% without MLC tracking to <31.4% (LPC 0) and <2.2% (LPC 1) with MLC tracking. The results indicate that the dosimetric robustness of MLC tracking delivery of an inversely optimized arc radiotherapy plan can be improved by incorporating leaf position constraints in the objective function without otherwise affecting the plan quality. The dosimetric robustness may be estimated prior to delivery by evaluating the ALD(w) of the plan.

A generalised optimal linear quadratic tracker with universal applications. Part 2: discrete-time systems

NASA Astrophysics Data System (ADS)

Ebrahimzadeh, Faezeh; Tsai, Jason Sheng-Hong; Chung, Min-Ching; Liao, Ying Ting; Guo, Shu-Mei; Shieh, Leang-San; Wang, Li

2017-01-01

Contrastive to Part 1, Part 2 presents a generalised optimal linear quadratic digital tracker (LQDT) with universal applications for the discrete-time (DT) systems. This includes (1) a generalised optimal LQDT design for the system with the pre-specified trajectories of the output and the control input and additionally with both the input-to-output direct-feedthrough term and known/estimated system disturbances or extra input/output signals; (2) a new optimal filter-shaped proportional plus integral state-feedback LQDT design for non-square non-minimum phase DT systems to achieve a minimum-phase-like tracking performance; (3) a new approach for computing the control zeros of the given non-square DT systems; and (4) a one-learning-epoch input-constrained iterative learning LQDT design for the repetitive DT systems.

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.

Teleoperation System with Hybrid Pneumatic-Piezoelectric Actuation for MRI-Guided Needle Insertion with Haptic Feedback

PubMed Central

Shang, Weijian; Su, Hao; Li, Gang; Fischer, Gregory S.

2014-01-01

This paper presents a surgical master-slave tele-operation system for percutaneous interventional procedures under continuous magnetic resonance imaging (MRI) guidance. This system consists of a piezoelectrically actuated slave robot for needle placement with integrated fiber optic force sensor utilizing Fabry-Perot interferometry (FPI) sensing principle. The sensor flexure is optimized and embedded to the slave robot for measuring needle insertion force. A novel, compact opto-mechanical FPI sensor interface is integrated into an MRI robot control system. By leveraging the complementary features of pneumatic and piezoelectric actuation, a pneumatically actuated haptic master robot is also developed to render force associated with needle placement interventions to the clinician. An aluminum load cell is implemented and calibrated to close the impedance control loop of the master robot. A force-position control algorithm is developed to control the hybrid actuated system. Teleoperated needle insertion is demonstrated under live MR imaging, where the slave robot resides in the scanner bore and the user manipulates the master beside the patient outside the bore. Force and position tracking results of the master-slave robot are demonstrated to validate the tracking performance of the integrated system. It has a position tracking error of 0.318mm and sine wave force tracking error of 2.227N. PMID:25126446

Teleoperation System with Hybrid Pneumatic-Piezoelectric Actuation for MRI-Guided Needle Insertion with Haptic Feedback.

PubMed

Shang, Weijian; Su, Hao; Li, Gang; Fischer, Gregory S

2013-01-01

This paper presents a surgical master-slave tele-operation system for percutaneous interventional procedures under continuous magnetic resonance imaging (MRI) guidance. This system consists of a piezoelectrically actuated slave robot for needle placement with integrated fiber optic force sensor utilizing Fabry-Perot interferometry (FPI) sensing principle. The sensor flexure is optimized and embedded to the slave robot for measuring needle insertion force. A novel, compact opto-mechanical FPI sensor interface is integrated into an MRI robot control system. By leveraging the complementary features of pneumatic and piezoelectric actuation, a pneumatically actuated haptic master robot is also developed to render force associated with needle placement interventions to the clinician. An aluminum load cell is implemented and calibrated to close the impedance control loop of the master robot. A force-position control algorithm is developed to control the hybrid actuated system. Teleoperated needle insertion is demonstrated under live MR imaging, where the slave robot resides in the scanner bore and the user manipulates the master beside the patient outside the bore. Force and position tracking results of the master-slave robot are demonstrated to validate the tracking performance of the integrated system. It has a position tracking error of 0.318mm and sine wave force tracking error of 2.227N.

Enhanced index tracking modelling in portfolio optimization

NASA Astrophysics Data System (ADS)

Lam, W. S.; Hj. Jaaman, Saiful Hafizah; Ismail, Hamizun bin

2013-09-01

Enhanced index tracking is a popular form of passive fund management in stock market. It is a dual-objective optimization problem, a trade-off between maximizing the mean return and minimizing the risk. Enhanced index tracking aims to generate excess return over the return achieved by the index without purchasing all of the stocks that make up the index by establishing an optimal portfolio. The objective of this study is to determine the optimal portfolio composition and performance by using weighted model in enhanced index tracking. Weighted model focuses on the trade-off between the excess return and the risk. The results of this study show that the optimal portfolio for the weighted model is able to outperform the Malaysia market index which is Kuala Lumpur Composite Index because of higher mean return and lower risk without purchasing all the stocks in the market index.

Retinal optical coherence tomography at 1 μm with dynamic focus control and axial motion tracking

NASA Astrophysics Data System (ADS)

Cua, Michelle; Lee, Sujin; Miao, Dongkai; Ju, Myeong Jin; Mackenzie, Paul J.; Jian, Yifan; Sarunic, Marinko V.

2016-02-01

High-resolution optical coherence tomography (OCT) retinal imaging is important to noninvasively visualize the various retinal structures to aid in better understanding of the pathogenesis of vision-robbing diseases. However, conventional OCT systems have a trade-off between lateral resolution and depth-of-focus. In this report, we present the development of a focus-stacking OCT system with automatic focus optimization for high-resolution, extended-focal-range clinical retinal imaging by incorporating a variable-focus liquid lens into the sample arm optics. Retinal layer tracking and selection was performed using a graphics processing unit accelerated processing platform for focus optimization, providing real-time layer-specific en face visualization. After optimization, multiple volumes focused at different depths were acquired, registered, and stitched together to yield a single, high-resolution focus-stacked dataset. Using this system, we show high-resolution images of the retina and optic nerve head, from which we extracted clinically relevant parameters such as the nerve fiber layer thickness and lamina cribrosa microarchitecture.

Prediction-Correction Algorithms for Time-Varying Constrained Optimization

DOE PAGES

Simonetto, Andrea; Dall'Anese, Emiliano

2017-07-26

This article develops online algorithms to track solutions of time-varying constrained optimization problems. Particularly, resembling workhorse Kalman filtering-based approaches for dynamical systems, the proposed methods involve prediction-correction steps to provably track the trajectory of the optimal solutions of time-varying convex problems. The merits of existing prediction-correction methods have been shown for unconstrained problems and for setups where computing the inverse of the Hessian of the cost function is computationally affordable. This paper addresses the limitations of existing methods by tackling constrained problems and by designing first-order prediction steps that rely on the Hessian of the cost function (and do notmore » require the computation of its inverse). In addition, the proposed methods are shown to improve the convergence speed of existing prediction-correction methods when applied to unconstrained problems. Numerical simulations corroborate the analytical results and showcase performance and benefits of the proposed algorithms. A realistic application of the proposed method to real-time control of energy resources is presented.« less

Retinal optical coherence tomography at 1 μm with dynamic focus control and axial motion tracking.

PubMed

Cua, Michelle; Lee, Sujin; Miao, Dongkai; Ju, Myeong Jin; Mackenzie, Paul J; Jian, Yifan; Sarunic, Marinko V

2016-02-01

High-resolution optical coherence tomography (OCT) retinal imaging is important to noninvasively visualize the various retinal structures to aid in better understanding of the pathogenesis of vision-robbing diseases. However, conventional OCT systems have a trade-off between lateral resolution and depth-of-focus. In this report, we present the development of a focus-stacking OCT system with automatic focus optimization for high-resolution, extended-focal-range clinical retinal imaging by incorporating a variable-focus liquid lens into the sample arm optics. Retinal layer tracking and selection was performed using a graphics processing unit accelerated processing platform for focus optimization, providing real-time layer-specific en face visualization. After optimization, multiple volumes focused at different depths were acquired, registered, and stitched together to yield a single, high-resolution focus-stacked dataset. Using this system, we show high-resolution images of the retina and optic nerve head, from which we extracted clinically relevant parameters such as the nerve fiber layer thickness and lamina cribrosa microarchitecture.

Energy optimization for upstream data transfer in 802.15.4 beacon-enabled star formulation

NASA Astrophysics Data System (ADS)

Liu, Hua; Krishnamachari, Bhaskar

2008-08-01

Energy saving is one of the major concerns for low rate personal area networks. This paper models energy consumption for beacon-enabled time-slotted media accessing control cooperated with sleeping scheduling in a star network formulation for IEEE 802.15.4 standard. We investigate two different upstream (data transfer from devices to a network coordinator) strategies: a) tracking strategy: the devices wake up and check status (track the beacon) in each time slot; b) non-tracking strategy: nodes only wake-up upon data arriving and stay awake till data transmitted to the coordinator. We consider the tradeoff between energy cost and average data transmission delay for both strategies. Both scenarios are formulated as optimization problems and the optimal solutions are discussed. Our results show that different data arrival rate and system parameters (such as contention access period interval, upstream speed etc.) result in different strategies in terms of energy optimization with maximum delay constraints. Hence, according to different applications and system settings, different strategies might be chosen by each node to achieve energy optimization for both self-interested view and system view. We give the relation among the tunable parameters by formulas and plots to illustrate which strategy is better under corresponding parameters. There are two main points emphasized in our results with delay constraints: on one hand, when the system setting is fixed by coordinator, nodes in the network can intelligently change their strategies according to corresponding application data arrival rate; on the other hand, when the nodes' applications are known by the coordinator, the coordinator can tune the system parameters to achieve optimal system energy consumption.

Extended cooperative control synthesis

NASA Technical Reports Server (NTRS)

Davidson, John B.; Schmidt, David K.

1994-01-01

This paper reports on research for extending the Cooperative Control Synthesis methodology to include a more accurate modeling of the pilot's controller dynamics. Cooperative Control Synthesis (CCS) is a methodology that addresses the problem of how to design control laws for piloted, high-order, multivariate systems and/or non-conventional dynamic configurations in the absence of flying qualities specifications. This is accomplished by emphasizing the parallel structure inherent in any pilot-controlled, augmented vehicle. The original CCS methodology is extended to include the Modified Optimal Control Model (MOCM), which is based upon the optimal control model of the human operator developed by Kleinman, Baron, and Levison in 1970. This model provides a modeling of the pilot's compensation dynamics that is more accurate than the simplified pilot dynamic representation currently in the CCS methodology. Inclusion of the MOCM into the CCS also enables the modeling of pilot-observation perception thresholds and pilot-observation attention allocation affects. This Extended Cooperative Control Synthesis (ECCS) allows for the direct calculation of pilot and system open- and closed-loop transfer functions in pole/zero form and is readily implemented in current software capable of analysis and design for dynamic systems. Example results based upon synthesizing an augmentation control law for an acceleration command system in a compensatory tracking task using the ECCS are compared with a similar synthesis performed by using the original CCS methodology. The ECCS is shown to provide augmentation control laws that yield more favorable, predicted closed-loop flying qualities and tracking performance than those synthesized using the original CCS methodology.

Numerical simulation of active track tensioning system for autonomous hybrid vehicle

NASA Astrophysics Data System (ADS)

Mȩżyk, Arkadiusz; Czapla, Tomasz; Klein, Wojciech; Mura, Gabriel

2017-05-01

One of the most important components of a high speed tracked vehicle is an efficient suspension system. The vehicle should be able to operate both in rough terrain for performance of engineering tasks as well as on the road with high speed. This is especially important for an autonomous platform that operates either with or without human supervision, so that the vibration level can rise compared to a manned vehicle. In this case critical electronic and electric parts must be protected to ensure the reliability of the vehicle. The paper presents a dynamic parameters determination methodology of suspension system for an autonomous high speed tracked platform with total weight of about 5 tonnes and hybrid propulsion system. Common among tracked vehicles suspension solutions and cost-efficient, the torsion-bar system was chosen. One of the most important issues was determining optimal track tensioning - in this case an active hydraulic system was applied. The selection of system parameters was performed with using numerical model based on multi-body dynamic approach. The results of numerical analysis were used to define parameters of active tensioning control system setup. LMS Virtual.Lab Motion was used for multi-body dynamics numerical calculation and Matlab/SIMULINK for control system simulation.

A university teaching simulation facility

NASA Technical Reports Server (NTRS)

Stark, Lawrence; Kim, Won-Soo; Tendick, Frank; Tyler, Mitchell; Hannaford, Blake; Barakat, Wissam; Bergengruen, Olaf; Braddi, Louis; Eisenberg, Joseph; Ellis, Stephen

1987-01-01

An experimental telerobotics (TR) simulation is described suitable for studying human operator (HO) performance. Simple manipulator pick-and-place and tracking tasks allowed quantitative comparison of a number of calligraphic display viewing conditions. A number of control modes could be compared in this TR simulation, including displacement, rate, and acceleratory control using position and force joysticks. A homeomorphic controller turned out to be no better than joysticks; the adaptive properties of the HO can apparently permit quite good control over a variety of controller configurations and control modes. Training by optimal control example seemed helpful in preliminary experiments.

Dynamics and Control of Three-Dimensional Perching Maneuver under Dynamic Stall Influence

NASA Astrophysics Data System (ADS)

Feroskhan, Mir Alikhan Bin Mohammad

Perching is a type of aggressive maneuver performed by the class 'Aves' species to attain precision point landing with a generally short landing distance. Perching capability is desirable on unmanned aerial vehicles (UAVs) due to its efficient deceleration process that potentially expands the functionality and flight envelope of the aircraft. This dissertation extends the previous works on perching, which is mostly limited to two-dimensional (2D) cases, to its state-of-the-art threedimensional (3D) variety. This dissertation presents the aerodynamic modeling and optimization framework adopted to generate unprecedented variants of the 3D perching maneuver that include the sideslip perching trajectory, which ameliorates the existing 2D perching concept by eliminating the undesirable undershoot and reliance on gravity. The sideslip perching technique methodically utilizes the lateral and longitudinal drag mechanisms through consecutive phases of yawing and pitching-up motion. Since perching maneuver involves high rates of change in the angles of attack and large turn rates, introduction of three internal variables thus becomes necessary for addressing the influence of dynamic stall delay on the UAV's transient post-stall behavior. These variables are then integrated into a static nonlinear aerodynamic model, developed using empirical and analytical methods, and into an optimization framework that generates a trajectory of sideslip perching maneuver, acquiring over 70% velocity reduction. An impact study of the dynamic stall influence on the optimal perching trajectories suggests that consideration of dynamic stall delay is essential due to the significant discrepancies in the corresponding control inputs required. A comparative study between 2D and 3D perching is also conducted to examine the different drag mechanisms employed by 2D and 3D perching respectively. 3D perching is presented as a more efficient deceleration technique with respect to spatial costs and initial altitude range. Contraction analysis is shown to be a useful technique in identifying the state variables that are required to be tracked for attaining stability of optimal perching trajectories. Based on the selected tracking variables, two sliding control strategies are proposed and comparatively examined to close the control loop and provide the required robustness and convergence to the optimal perching trajectory in the presence of perturbations and dynamic stall model inaccuracies. This dissertation concludes that the sliding controller with the adaptive gain feature is more effective and essential in providing better tracking performance through illustrations of the corresponding convergence area and at higher intensity of perturbations.

Empirical Study on Designing of Gaze Tracking Camera Based on the Information of User's Head Movement.

PubMed

Pan, Weiyuan; Jung, Dongwook; Yoon, Hyo Sik; Lee, Dong Eun; Naqvi, Rizwan Ali; Lee, Kwan Woo; Park, Kang Ryoung

2016-08-31

Gaze tracking is the technology that identifies a region in space that a user is looking at. Most previous non-wearable gaze tracking systems use a near-infrared (NIR) light camera with an NIR illuminator. Based on the kind of camera lens used, the viewing angle and depth-of-field (DOF) of a gaze tracking camera can be different, which affects the performance of the gaze tracking system. Nevertheless, to our best knowledge, most previous researches implemented gaze tracking cameras without ground truth information for determining the optimal viewing angle and DOF of the camera lens. Eye-tracker manufacturers might also use ground truth information, but they do not provide this in public. Therefore, researchers and developers of gaze tracking systems cannot refer to such information for implementing gaze tracking system. We address this problem providing an empirical study in which we design an optimal gaze tracking camera based on experimental measurements of the amount and velocity of user's head movements. Based on our results and analyses, researchers and developers might be able to more easily implement an optimal gaze tracking system. Experimental results show that our gaze tracking system shows high performance in terms of accuracy, user convenience and interest.

Empirical Study on Designing of Gaze Tracking Camera Based on the Information of User’s Head Movement

PubMed Central

Pan, Weiyuan; Jung, Dongwook; Yoon, Hyo Sik; Lee, Dong Eun; Naqvi, Rizwan Ali; Lee, Kwan Woo; Park, Kang Ryoung

2016-01-01

Gaze tracking is the technology that identifies a region in space that a user is looking at. Most previous non-wearable gaze tracking systems use a near-infrared (NIR) light camera with an NIR illuminator. Based on the kind of camera lens used, the viewing angle and depth-of-field (DOF) of a gaze tracking camera can be different, which affects the performance of the gaze tracking system. Nevertheless, to our best knowledge, most previous researches implemented gaze tracking cameras without ground truth information for determining the optimal viewing angle and DOF of the camera lens. Eye-tracker manufacturers might also use ground truth information, but they do not provide this in public. Therefore, researchers and developers of gaze tracking systems cannot refer to such information for implementing gaze tracking system. We address this problem providing an empirical study in which we design an optimal gaze tracking camera based on experimental measurements of the amount and velocity of user’s head movements. Based on our results and analyses, researchers and developers might be able to more easily implement an optimal gaze tracking system. Experimental results show that our gaze tracking system shows high performance in terms of accuracy, user convenience and interest. PMID:27589768

Tracking scanning laser ophthalmoscope (TSLO)

NASA Astrophysics Data System (ADS)

Hammer, Daniel X.; Ferguson, R. Daniel; Magill, John C.; White, Michael A.; Elsner, Ann E.; Webb, Robert H.

2003-07-01

The effectiveness of image stabilization with a retinal tracker in a multi-function, compact scanning laser ophthalmoscope (TSLO) was demonstrated in initial human subject tests. The retinal tracking system uses a confocal reflectometer with a closed loop optical servo system to lock onto features in the fundus. The system is modular to allow configuration for many research and clinical applications, including hyperspectral imaging, multifocal electroretinography (MFERG), perimetry, quantification of macular and photo-pigmentation, imaging of neovascularization and other subretinal structures (drusen, hyper-, and hypo-pigmentation), and endogenous fluorescence imaging. Optical hardware features include dual wavelength imaging and detection, integrated monochromator, higher-order motion control, and a stimulus source. The system software consists of a real-time feedback control algorithm and a user interface. Software enhancements include automatic bias correction, asymmetric feature tracking, image averaging, automatic track re-lock, and acquisition and logging of uncompressed images and video files. Normal adult subjects were tested without mydriasis to optimize the tracking instrumentation and to characterize imaging performance. The retinal tracking system achieves a bandwidth of greater than 1 kHz, which permits tracking at rates that greatly exceed the maximum rate of motion of the human eye. The TSLO stabilized images in all test subjects during ordinary saccades up to 500 deg/sec with an inter-frame accuracy better than 0.05 deg. Feature lock was maintained for minutes despite subject eye blinking. Successful frame averaging allowed image acquisition with decreased noise in low-light applications. The retinal tracking system significantly enhances the imaging capabilities of the scanning laser ophthalmoscope.

ArF scanner performance improvement by using track integrated CD optimization

NASA Astrophysics Data System (ADS)

Huang, Jacky; Yu, Shinn-Sheng; Ke, Chih-Ming; Wu, Timothy; Wang, Yu-Hsi; Gau, Tsai-Sheng; Wang, Dennis; Li, Allen; Yang, Wenge; Kaoru, Araki

2006-03-01

In advanced semiconductor processing, shrinking CD is one of the main objectives when moving to the next generation technology. Improving CD uniformity (CDU) with shrinking CD is one of the biggest challenges. From ArF lithography CD error budget analysis, PEB (post exposure bake) contributes more than 40% CD variations. It turns out that hot plate performance such as CD matching and within-plate temperature control play key roles in litho cell wafer per hour (WPH). Traditionally wired or wireless thermal sensor wafers were used to match and optimize hot plates. However, sensor-to-sensor matching and sensor data quality vs. sensor lifetime or sensor thermal history are still unknown. These concerns make sensor wafers more suitable for coarse mean-temperature adjustment. For precise temperature adjustment, especially within-hot-plate temperature uniformity, using CD instead of sensor wafer temperature is a better and more straightforward metrology to calibrate hot plates. In this study, we evaluated TEL clean track integrated optical CD metrology (IM) combined with TEL CD Optimizer (CDO) software to improve 193-nm resist within-wafer and wafer-to-wafer CD uniformity. Within-wafer CD uniformity is mainly affected by the temperature non-uniformity on the PEB hot plate. Based on CD and PEB sensitivity of photo resists, a physical model has been established to control the CD uniformity through fine-tuning PEB temperature settings. CD data collected by track integrated CD metrology was fed into this model, and the adjustment of PEB setting was calculated and executed through track internal APC system. This auto measurement, auto feed forward, auto calibration and auto adjustment system can reduce the engineer key-in error and improve the hot plate calibration cycle time. And this PEB auto calibration system can easily bring hot-plate-to-hot-plate CD matching to within 0.5nm and within-wafer CDU (3σ) to less than 1.5nm.

Reflector control technology in space laser communication

NASA Astrophysics Data System (ADS)

Xie, Meilin; Ma, Caiwen; Yao, Cheng; Huang, Wei; Lian, Xuezheng; Feng, Xubin; Jing, Feng

2017-11-01

The optical frequencies band is used as information carrier to realize laser communication between two low-orbit micro-satellites in space which equipped with inter-satellite laser communication terminals, optical switches, space routers and other payload. The laser communication terminal adopts a two-dimensional turntable with a single mirror structure. In this paper, the perturbation model of satellite platform is established in this paper. The relationship between the coupling and coordinate transformation of satellite disturbance is analyzed and the laser pointing vector is deduced. Using the tracking differentiator to speed up the circular grating angle information constitute speed loop feedback, which avoids the problem of error amplification caused by the high frequency of the conventional difference algorithm. Finally, the suppression ability of the satellite platform disturbance and the tracking accuracy of the tracking system are simulated and analyzed. The results show that the tracking accuracy of the whole system is 10μrad in the case of satellite vibration, which provides the basis for the optimization of the performance of the space-borne laser communication control system.

Portfolio optimization in enhanced index tracking with goal programming approach

NASA Astrophysics Data System (ADS)

Siew, Lam Weng; Jaaman, Saiful Hafizah Hj.; Ismail, Hamizun bin

2014-09-01

Enhanced index tracking is a popular form of passive fund management in stock market. Enhanced index tracking aims to generate excess return over the return achieved by the market index without purchasing all of the stocks that make up the index. This can be done by establishing an optimal portfolio to maximize the mean return and minimize the risk. The objective of this paper is to determine the portfolio composition and performance using goal programming approach in enhanced index tracking and comparing it to the market index. Goal programming is a branch of multi-objective optimization which can handle decision problems that involve two different goals in enhanced index tracking, a trade-off between maximizing the mean return and minimizing the risk. The results of this study show that the optimal portfolio with goal programming approach is able to outperform the Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index because of higher mean return and lower risk without purchasing all the stocks in the market index.

Optimal control of the gear shifting process for shift smoothness in dual-clutch transmissions

NASA Astrophysics Data System (ADS)

Li, Guoqiang; Görges, Daniel

2018-03-01

The control of the transmission system in vehicles is significant for the driving comfort. In order to design a controller for smooth shifting and comfortable driving, a dynamic model of a dual-clutch transmission is presented in this paper. A finite-time linear quadratic regulator is proposed for the optimal control of the two friction clutches in the torque phase for the upshift process. An integral linear quadratic regulator is introduced to regulate the relative speed difference between the engine and the slipping clutch under the optimization of the input torque during the inertia phase. The control objective focuses on smoothing the upshift process so as to improve the driving comfort. Considering the available sensors in vehicles for feedback control, an observer design is presented to track the immeasurable variables. Simulation results show that the jerk can be reduced both in the torque phase and inertia phase, indicating good shift performance. Furthermore, compared with conventional controllers for the upshift process, the proposed control method can reduce shift jerk and improve shift quality.

Intelligent and robust optimization frameworks for smart grids

NASA Astrophysics Data System (ADS)

Dhansri, Naren Reddy

A smart grid implies a cyberspace real-time distributed power control system to optimally deliver electricity based on varying consumer characteristics. Although smart grids solve many of the contemporary problems, they give rise to new control and optimization problems with the growing role of renewable energy sources such as wind or solar energy. Under highly dynamic nature of distributed power generation and the varying consumer demand and cost requirements, the total power output of the grid should be controlled such that the load demand is met by giving a higher priority to renewable energy sources. Hence, the power generated from renewable energy sources should be optimized while minimizing the generation from non renewable energy sources. This research develops a demand-based automatic generation control and optimization framework for real-time smart grid operations by integrating conventional and renewable energy sources under varying consumer demand and cost requirements. Focusing on the renewable energy sources, the intelligent and robust control frameworks optimize the power generation by tracking the consumer demand in a closed-loop control framework, yielding superior economic and ecological benefits and circumvent nonlinear model complexities and handles uncertainties for superior real-time operations. The proposed intelligent system framework optimizes the smart grid power generation for maximum economical and ecological benefits under an uncertain renewable wind energy source. The numerical results demonstrate that the proposed framework is a viable approach to integrate various energy sources for real-time smart grid implementations. The robust optimization framework results demonstrate the effectiveness of the robust controllers under bounded power plant model uncertainties and exogenous wind input excitation while maximizing economical and ecological performance objectives. Therefore, the proposed framework offers a new worst-case deterministic optimization algorithm for smart grid automatic generation control.

Fuzzy logic control of stand-alone photovoltaic system with battery storage

NASA Astrophysics Data System (ADS)

Lalouni, S.; Rekioua, D.; Rekioua, T.; Matagne, E.

Photovoltaic energy has nowadays an increased importance in electrical power applications, since it is considered as an essentially inexhaustible and broadly available energy resource. However, the output power provided via the photovoltaic conversion process depends on solar irradiation and temperature. Therefore, to maximize the efficiency of the photovoltaic energy system, it is necessary to track the maximum power point of the PV array. The present paper proposes a maximum power point tracker (MPPT) method, based on fuzzy logic controller (FLC), applied to a stand-alone photovoltaic system. It uses a sampling measure of the PV array power and voltage then determines an optimal increment required to have the optimal operating voltage which permits maximum power tracking. This method carries high accuracy around the optimum point when compared to the conventional one. The stand-alone photovoltaic system used in this paper includes two bi-directional DC/DC converters and a lead-acid battery bank to overcome the scare periods. One converter works as an MPP tracker, while the other regulates the batteries state of charge and compensates the power deficit to provide a continuous delivery of energy to the load. The Obtained simulation results show the effectiveness of the proposed fuzzy logic controller.

Improved power control using optimal adjustable coefficients for three-phase photovoltaic inverter under unbalanced grid voltage.

PubMed

Wang, Qianggang; Zhou, Niancheng; Lou, Xiaoxuan; Chen, Xu

2014-01-01

Unbalanced grid faults will lead to several drawbacks in the output power quality of photovoltaic generation (PV) converters, such as power fluctuation, current amplitude swell, and a large quantity of harmonics. The aim of this paper is to propose a flexible AC current generation method by selecting coefficients to overcome these problems in an optimal way. Three coefficients are brought in to tune the output current reference within the required limits of the power quality (the current harmonic distortion, the AC current peak, the power fluctuation, and the DC voltage fluctuation). Through the optimization algorithm, the coefficients can be determined aiming to generate the minimum integrated amplitudes of the active and reactive power references with the constraints of the inverter current and DC voltage fluctuation. Dead-beat controller is utilized to track the optimal current reference in a short period. The method has been verified in PSCAD/EMTDC software.

Improved Power Control Using Optimal Adjustable Coefficients for Three-Phase Photovoltaic Inverter under Unbalanced Grid Voltage

PubMed Central

Wang, Qianggang; Zhou, Niancheng; Lou, Xiaoxuan; Chen, Xu

2014-01-01

Unbalanced grid faults will lead to several drawbacks in the output power quality of photovoltaic generation (PV) converters, such as power fluctuation, current amplitude swell, and a large quantity of harmonics. The aim of this paper is to propose a flexible AC current generation method by selecting coefficients to overcome these problems in an optimal way. Three coefficients are brought in to tune the output current reference within the required limits of the power quality (the current harmonic distortion, the AC current peak, the power fluctuation, and the DC voltage fluctuation). Through the optimization algorithm, the coefficients can be determined aiming to generate the minimum integrated amplitudes of the active and reactive power references with the constraints of the inverter current and DC voltage fluctuation. Dead-beat controller is utilized to track the optimal current reference in a short period. The method has been verified in PSCAD/EMTDC software. PMID:25243215

Optimal Regulation of Virtual Power Plants

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

Dall Anese, Emiliano; Guggilam, Swaroop S.; Simonetto, Andrea

This paper develops a real-time algorithmic framework for aggregations of distributed energy resources (DERs) in distribution networks to provide regulation services in response to transmission-level requests. Leveraging online primal-dual-type methods for time-varying optimization problems and suitable linearizations of the nonlinear AC power-flow equations, we believe this work establishes the system-theoretic foundation to realize the vision of distribution-level virtual power plants. The optimization framework controls the output powers of dispatchable DERs such that, in aggregate, they respond to automatic-generation-control and/or regulation-services commands. This is achieved while concurrently regulating voltages within the feeder and maximizing customers' and utility's performance objectives. Convergence andmore » tracking capabilities are analytically established under suitable modeling assumptions. Simulations are provided to validate the proposed approach.« less

Optimal shifting control strategy in inertia phase of an automatic transmission for automotive applications

NASA Astrophysics Data System (ADS)

Meng, Fei; Tao, Gang; Zhang, Tao; Hu, Yihuai; Geng, Peng

2015-08-01

Shifting quality is a crucial factor in all parts of the automobile industry. To ensure an optimal gear shifting strategy with best fuel economy for a stepped automatic transmission, the controller should be designed to meet the challenge of lacking of a feedback sensor to measure the relevant variables. This paper focuses on a new kind of automatic transmission using proportional solenoid valve to control the clutch pressure, a speed difference of the clutch based control strategy is designed for the shift control during the inertia phase. First, the mechanical system is shown and the system dynamic model is built. Second, the control strategy is designed based on the characterization analysis of models which are derived from dynamics of the drive line and electro-hydraulic actuator. Then, the controller uses conventional Proportional-Integral-Derivative control theory, and a robust two-degree-of-freedom controller is also carried out to determine the optimal control parameters to further improve the system performance. Finally, the designed control strategy with different controller is implemented on a simulation model. The compared results show that the speed difference of clutch can track the desired trajectory well and improve the shift quality effectively.

Towards 3D ultrasound image based soft tissue tracking: a transrectal ultrasound prostate image alignment system.

PubMed

Baumann, Michael; Mozer, Pierre; Daanen, Vincent; Troccaz, Jocelyne

2007-01-01

The emergence of real-time 3D ultrasound (US) makes it possible to consider image-based tracking of subcutaneous soft tissue targets for computer guided diagnosis and therapy. We propose a 3D transrectal US based tracking system for precise prostate biopsy sample localisation. The aim is to improve sample distribution, to enable targeting of unsampled regions for repeated biopsies, and to make post-interventional quality controls possible. Since the patient is not immobilized, since the prostate is mobile and due to the fact that probe movements are only constrained by the rectum during biopsy acquisition, the tracking system must be able to estimate rigid transformations that are beyond the capture range of common image similarity measures. We propose a fast and robust multi-resolution attribute-vector registration approach that combines global and local optimization methods to solve this problem. Global optimization is performed on a probe movement model that reduces the dimensionality of the search space and thus renders optimization efficient. The method was tested on 237 prostate volumes acquired from 14 different patients for 3D to 3D and 3D to orthogonal 2D slices registration. The 3D-3D version of the algorithm converged correctly in 96.7% of all cases in 6.5s with an accuracy of 1.41mm (r.m.s.) and 3.84mm (max). The 3D to slices method yielded a success rate of 88.9% in 2.3s with an accuracy of 1.37mm (r.m.s.) and 4.3mm (max).

Stillwater Hybrid Geo-Solar Power Plant Optimization Analyses

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

Wendt, Daniel S.; Mines, Gregory L.; Turchi, Craig S.

2015-09-02

The Stillwater Power Plant is the first hybrid plant in the world able to bring together a medium-enthalpy geothermal unit with solar thermal and solar photovoltaic systems. Solar field and power plant models have been developed to predict the performance of the Stillwater geothermal / solar-thermal hybrid power plant. The models have been validated using operational data from the Stillwater plant. A preliminary effort to optimize performance of the Stillwater hybrid plant using optical characterization of the solar field has been completed. The Stillwater solar field optical characterization involved measurement of mirror reflectance, mirror slope error, and receiver position error.more » The measurements indicate that the solar field may generate 9% less energy than the design value if an appropriate tracking offset is not employed. A perfect tracking offset algorithm may be able to boost the solar field performance by about 15%. The validated Stillwater hybrid plant models were used to evaluate hybrid plant operating strategies including turbine IGV position optimization, ACC fan speed and turbine IGV position optimization, turbine inlet entropy control using optimization of multiple process variables, and mixed working fluid substitution. The hybrid plant models predict that each of these operating strategies could increase net power generation relative to the baseline Stillwater hybrid plant operations.« less

Handling qualities of large flexible control-configured aircraft

NASA Technical Reports Server (NTRS)

Swaim, R. L.

1980-01-01

The effects on handling qualities of low frequency symmetric elastic mode interaction with the rigid body dynamics of a large flexible aircraft was analyzed by use of a mathematical pilot modeling computer simulation. An extension of the optimal control model for a human pilot was made so that the mode interaction effects on the pilot's control task could be assessed. Pilot ratings were determined for a longitudinal tracking task with parametric variations in the undamped natural frequencies of the two lowest frequency symmetric elastic modes made to induce varying amounts of mode interaction. Relating numerical performance index values associated with the frequency variations used in several dynamic cases, to a numerical Cooper-Harper pilot rating has proved successful in discriminating when the mathematical pilot can or cannot separate rigid from elastic response in the tracking task.

An adaptive critic-based scheme for consensus control of nonlinear multi-agent systems

NASA Astrophysics Data System (ADS)

Heydari, Ali; Balakrishnan, S. N.

2014-12-01

The problem of decentralised consensus control of a network of heterogeneous nonlinear systems is formulated as an optimal tracking problem and a solution is proposed using an approximate dynamic programming based neurocontroller. The neurocontroller training comprises an initial offline training phase and an online re-optimisation phase to account for the fact that the reference signal subject to tracking is not fully known and available ahead of time, i.e., during the offline training phase. As long as the dynamics of the agents are controllable, and the communication graph has a directed spanning tree, this scheme guarantees the synchronisation/consensus even under switching communication topology and directed communication graph. Finally, an aerospace application is selected for the evaluation of the performance of the method. Simulation results demonstrate the potential of the scheme.

Multi-objective control of nonlinear boiler-turbine dynamics with actuator magnitude and rate constraints.

PubMed

Chen, Pang-Chia

2013-01-01

This paper investigates multi-objective controller design approaches for nonlinear boiler-turbine dynamics subject to actuator magnitude and rate constraints. System nonlinearity is handled by a suitable linear parameter varying system representation with drum pressure as the system varying parameter. Variation of the drum pressure is represented by suitable norm-bounded uncertainty and affine dependence on system matrices. Based on linear matrix inequality algorithms, the magnitude and rate constraints on the actuator and the deviations of fluid density and water level are formulated while the tracking abilities on the drum pressure and power output are optimized. Variation ranges of drum pressure and magnitude tracking commands are used as controller design parameters, determined according to the boiler-turbine's operation range. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

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.

Slushy weightings for the optimal pilot model. [considering visual tracking task

NASA Technical Reports Server (NTRS)

Dillow, J. D.; Picha, D. G.; Anderson, R. O.

1975-01-01

A pilot model is described which accounts for the effect of motion cues in a well defined visual tracking task. The effect of visual and motion cues are accounted for in the model in two ways. First, the observation matrix in the pilot model is structured to account for the visual and motion inputs presented to the pilot. Secondly, the weightings in the quadratic cost function associated with the pilot model are modified to account for the pilot's perception of the variables he considers important in the task. Analytic results obtained using the pilot model are compared to experimental results and in general good agreement is demonstrated. The analytic model yields small improvements in tracking performance with the addition of motion cues for easily controlled task dynamics and large improvements in tracking performance with the addition of motion cues for difficult task dynamics.

From Fault-Diagnosis and Performance Recovery of a Controlled System to Chaotic Secure Communication

NASA Astrophysics Data System (ADS)

Hsu, Wen-Teng; Tsai, Jason Sheng-Hong; Guo, Fang-Cheng; Guo, Shu-Mei; Shieh, Leang-San

Chaotic systems are often applied to encryption on secure communication, but they may not provide high-degree security. In order to improve the security of communication, chaotic systems may need to add other secure signals, but this may cause the system to diverge. In this paper, we redesign a communication scheme that could create secure communication with additional secure signals, and the proposed scheme could keep system convergence. First, we introduce the universal state-space adaptive observer-based fault diagnosis/estimator and the high-performance tracker for the sampled-data linear time-varying system with unanticipated decay factors in actuators/system states. Besides, robustness, convergence in the mean, and tracking ability are given in this paper. A residual generation scheme and a mechanism for auto-tuning switched gain is also presented, so that the introduced methodology is applicable for the fault detection and diagnosis (FDD) for actuator and state faults to yield a high tracking performance recovery. The evolutionary programming-based adaptive observer is then applied to the problem of secure communication. Whenever the tracker induces a large control input which might not conform to the input constraint of some physical systems, the proposed modified linear quadratic optimal tracker (LQT) can effectively restrict the control input within the specified constraint interval, under the acceptable tracking performance. The effectiveness of the proposed design methodology is illustrated through tracking control simulation examples.

Modeling human target acquisition in ground-to-air weapon systems

NASA Technical Reports Server (NTRS)

Phatak, A. V.; Mohr, R. L.; Vikmanis, M.; Wei, K. C.

1982-01-01

The problems associated with formulating and validating mathematical models for describing and predicting human target acquisition response are considered. In particular, the extension of the human observer model to include the acquisition phase as well as the tracking segment is presented. Relationship of the Observer model structure to the more complex Standard Optimal Control model formulation and to the simpler Transfer Function/Noise representation is discussed. Problems pertinent to structural identifiability and the form of the parameterization are elucidated. A systematic approach toward the identification of the observer acquisition model parameters from ensemble tracking error data is presented.

Multisource passive acoustic tracking: an application of random finite set data fusion

NASA Astrophysics Data System (ADS)

Ali, Andreas M.; Hudson, Ralph E.; Lorenzelli, Flavio; Yao, Kung

2010-04-01

Multisource passive acoustic tracking is useful in animal bio-behavioral study by replacing or enhancing human involvement during and after field data collection. Multiple simultaneous vocalizations are a common occurrence in a forest or a jungle, where many species are encountered. Given a set of nodes that are capable of producing multiple direction-of-arrivals (DOAs), such data needs to be combined into meaningful estimates. Random Finite Set provides the mathematical probabilistic model, which is suitable for analysis and optimal estimation algorithm synthesis. Then the proposed algorithm has been verified using a simulation and a controlled test experiment.

The research on the mean shift algorithm for target tracking

NASA Astrophysics Data System (ADS)

CAO, Honghong

2017-06-01

The traditional mean shift algorithm for target tracking is effective and high real-time, but there still are some shortcomings. The traditional mean shift algorithm is easy to fall into local optimum in the tracking process, the effectiveness of the method is weak when the object is moving fast. And the size of the tracking window never changes, the method will fail when the size of the moving object changes, as a result, we come up with a new method. We use particle swarm optimization algorithm to optimize the mean shift algorithm for target tracking, Meanwhile, SIFT (scale-invariant feature transform) and affine transformation make the size of tracking window adaptive. At last, we evaluate the method by comparing experiments. Experimental result indicates that the proposed method can effectively track the object and the size of the tracking window changes.

Torque-based optimal acceleration control for electric vehicle

NASA Astrophysics Data System (ADS)

Lu, Dongbin; Ouyang, Minggao

2014-03-01

The existing research of the acceleration control mainly focuses on an optimization of the velocity trajectory with respect to a criterion formulation that weights acceleration time and fuel consumption. The minimum-fuel acceleration problem in conventional vehicle has been solved by Pontryagin's maximum principle and dynamic programming algorithm, respectively. The acceleration control with minimum energy consumption for battery electric vehicle(EV) has not been reported. In this paper, the permanent magnet synchronous motor(PMSM) is controlled by the field oriented control(FOC) method and the electric drive system for the EV(including the PMSM, the inverter and the battery) is modeled to favor over a detailed consumption map. The analytical algorithm is proposed to analyze the optimal acceleration control and the optimal torque versus speed curve in the acceleration process is obtained. Considering the acceleration time, a penalty function is introduced to realize a fast vehicle speed tracking. The optimal acceleration control is also addressed with dynamic programming(DP). This method can solve the optimal acceleration problem with precise time constraint, but it consumes a large amount of computation time. The EV used in simulation and experiment is a four-wheel hub motor drive electric vehicle. The simulation and experimental results show that the required battery energy has little difference between the acceleration control solved by analytical algorithm and that solved by DP, and is greatly reduced comparing with the constant pedal opening acceleration. The proposed analytical and DP algorithms can minimize the energy consumption in EV's acceleration process and the analytical algorithm is easy to be implemented in real-time control.

Thermal optimum design for tracking primary mirror of Space Telescope

NASA Astrophysics Data System (ADS)

Pan, Hai-jun; Ruan, Ping; Li, Fu; Wang, Hong-Wei

2011-08-01

In the conventional method, the structural parameters of primary mirror are usually optimized just by the requirement of mechanical performance. Because the influences of structural parameters on thermal stability are not taken fully into account in this simple method, the lightweight optimum design of primary mirror usually brings the bad thermal stability, especially in the complex environment. In order to obtain better thermal stability, a new method about structure-thermal optimum design of tracking primary mirror is discussed. During the optimum process, both the lightweight ratio and thermal stability will be taken into account. The structure-thermal optimum is introduced into the analysis process and commenced after lightweight design as the secondary optimum. Using the engineering analysis of software ANSYS, a parameter finite element analysis (FEA) model of mirror is built. On the premise of appropriate lightweight ratio, the RMS of structure-thermal deformation of mirror surface and lightweight ratio are assigned to be state variables, and the maximal RMS of temperature gradient load to be object variable. The results show that certain structural parameters of tracking primary mirror have different influences on mechanical performance and thermal stability, even they are opposite. By structure-thermal optimizing, the optimized mirror model discussed in this paper has better thermal stability than the old one under the same thermal loads, which can drastically reduce difficulty in thermal control.

Reachability Analysis Applied to Space Situational Awareness

NASA Astrophysics Data System (ADS)

Holzinger, M.; Scheeres, D.

Several existing and emerging applications of Space Situational Awareness (SSA) relate directly to spacecraft Rendezvous, Proximity Operations, and Docking (RPOD) and Formation / Cluster Flight (FCF). When multiple Resident Space Ob jects (RSOs) are in vicinity of one another with appreciable periods between observations, correlating new RSO tracks to previously known objects becomes a non-trivial problem. A particularly difficult sub-problem is seen when long breaks in observations are coupled with continuous, low- thrust maneuvers. Reachability theory, directly related to optimal control theory, can compute contiguous reachability sets for known or estimated control authority and can support such RSO search and correlation efforts in both ground and on-board settings. Reachability analysis can also directly estimate the minimum control authority of a given RSO. For RPOD and FCF applications, emerging mission concepts such as fractionation drastically increase system complexity of on-board autonomous fault management systems. Reachability theory, as applied to SSA in RPOD and FCF applications, can involve correlation of nearby RSO observations, control authority estimation, and sensor track re-acquisition. Additional uses of reachability analysis are formation reconfiguration, worst-case passive safety, and propulsion failure modes such as a "stuck" thruster. Existing reachability theory is applied to RPOD and FCF regimes. An optimal control policy is developed to maximize the reachability set and optimal control law discontinuities (switching) are examined. The Clohessy-Wiltshire linearized equations of motion are normalized to accentuate relative control authority for spacecraft propulsion systems at both Low Earth Orbit (LEO) and Geostationary Earth Orbit (GEO). Several examples with traditional and low thrust propulsion systems in LEO and GEO are explored to illustrate the effects of relative control authority on the time-varying reachability set surface. Both monopropellant spacecraft at LEO and Hall thruster spacecraft at GEO are shown to be strongly actuated while Hall thruster spacecraft at LEO are found to be weakly actuated. Weaknesses with the current implementation are discussed and future numerical improvements and analytical efforts are discussed.

Technical Note: A novel leaf sequencing optimization algorithm which considers previous underdose and overdose events for MLC tracking radiotherapy

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

Wisotzky, Eric, E-mail: eric.wisotzky@charite.de, E-mail: eric.wisotzky@ipk.fraunhofer.de; O’Brien, Ricky; Keall, Paul J., E-mail: paul.keall@sydney.edu.au

2016-01-15

Purpose: Multileaf collimator (MLC) tracking radiotherapy is complex as the beam pattern needs to be modified due to the planned intensity modulation as well as the real-time target motion. The target motion cannot be planned; therefore, the modified beam pattern differs from the original plan and the MLC sequence needs to be recomputed online. Current MLC tracking algorithms use a greedy heuristic in that they optimize for a given time, but ignore past errors. To overcome this problem, the authors have developed and improved an algorithm that minimizes large underdose and overdose regions. Additionally, previous underdose and overdose events aremore » taken into account to avoid regions with high quantity of dose events. Methods: The authors improved the existing MLC motion control algorithm by introducing a cumulative underdose/overdose map. This map represents the actual projection of the planned tumor shape and logs occurring dose events at each specific regions. These events have an impact on the dose cost calculation and reduce recurrence of dose events at each region. The authors studied the improvement of the new temporal optimization algorithm in terms of the L1-norm minimization of the sum of overdose and underdose compared to not accounting for previous dose events. For evaluation, the authors simulated the delivery of 5 conformal and 14 intensity-modulated radiotherapy (IMRT)-plans with 7 3D patient measured tumor motion traces. Results: Simulations with conformal shapes showed an improvement of L1-norm up to 8.5% after 100 MLC modification steps. Experiments showed comparable improvements with the same type of treatment plans. Conclusions: A novel leaf sequencing optimization algorithm which considers previous dose events for MLC tracking radiotherapy has been developed and investigated. Reductions in underdose/overdose are observed for conformal and IMRT delivery.« less

Evolutionary Design of Controlled Structures

NASA Technical Reports Server (NTRS)

Masters, Brett P.; Crawley, Edward F.

1997-01-01

Basic physical concepts of structural delay and transmissibility are provided for simple rod and beam structures. Investigations show the sensitivity of these concepts to differing controlled-structures variables, and to rational system modeling effects. An evolutionary controls/structures design method is developed. The basis of the method is an accurate model formulation for dynamic compensator optimization and Genetic Algorithm based updating of sensor/actuator placement and structural attributes. One and three dimensional examples from the literature are used to validate the method. Frequency domain interpretation of these controlled structure systems provide physical insight as to how the objective is optimized and consequently what is important in the objective. Several disturbance rejection type controls-structures systems are optimized for a stellar interferometer spacecraft application. The interferometric designs include closed loop tracking optics. Designs are generated for differing structural aspect ratios, differing disturbance attributes, and differing sensor selections. Physical limitations in achieving performance are given in terms of average system transfer function gains and system phase loss. A spacecraft-like optical interferometry system is investigated experimentally over several different optimized controlled structures configurations. Configurations represent common and not-so-common approaches to mitigating pathlength errors induced by disturbances of two different spectra. Results show that an optimized controlled structure for low frequency broadband disturbances achieves modest performance gains over a mass equivalent regular structure, while an optimized structure for high frequency narrow band disturbances is four times better in terms of root-mean-square pathlength. These results are predictable given the nature of the physical system and the optimization design variables. Fundamental limits on controlled performance are discussed based on the measured and fit average system transfer function gains and system phase loss.

The Application of Auto-Disturbance Rejection Control Optimized by Least Squares Support Vector Machines Method and Time-Frequency Representation in Voltage Source Converter-High Voltage Direct Current System.

PubMed

Liu, Ying-Pei; Liang, Hai-Ping; Gao, Zhong-Ke

2015-01-01

In order to improve the performance of voltage source converter-high voltage direct current (VSC-HVDC) system, we propose an improved auto-disturbance rejection control (ADRC) method based on least squares support vector machines (LSSVM) in the rectifier side. Firstly, we deduce the high frequency transient mathematical model of VSC-HVDC system. Then we investigate the ADRC and LSSVM principles. We ignore the tracking differentiator in the ADRC controller aiming to improve the system dynamic response speed. On this basis, we derive the mathematical model of ADRC controller optimized by LSSVM for direct current voltage loop. Finally we carry out simulations to verify the feasibility and effectiveness of our proposed control method. In addition, we employ the time-frequency representation methods, i.e., Wigner-Ville distribution (WVD) and adaptive optimal kernel (AOK) time-frequency representation, to demonstrate our proposed method performs better than the traditional method from the perspective of energy distribution in time and frequency plane.

The Application of Auto-Disturbance Rejection Control Optimized by Least Squares Support Vector Machines Method and Time-Frequency Representation in Voltage Source Converter-High Voltage Direct Current System

PubMed Central

Gao, Zhong-Ke

2015-01-01

In order to improve the performance of voltage source converter-high voltage direct current (VSC-HVDC) system, we propose an improved auto-disturbance rejection control (ADRC) method based on least squares support vector machines (LSSVM) in the rectifier side. Firstly, we deduce the high frequency transient mathematical model of VSC-HVDC system. Then we investigate the ADRC and LSSVM principles. We ignore the tracking differentiator in the ADRC controller aiming to improve the system dynamic response speed. On this basis, we derive the mathematical model of ADRC controller optimized by LSSVM for direct current voltage loop. Finally we carry out simulations to verify the feasibility and effectiveness of our proposed control method. In addition, we employ the time-frequency representation methods, i.e., Wigner-Ville distribution (WVD) and adaptive optimal kernel (AOK) time-frequency representation, to demonstrate our proposed method performs better than the traditional method from the perspective of energy distribution in time and frequency plane. PMID:26098556

Utilization of Historic Information in an Optimisation Task

NASA Technical Reports Server (NTRS)

Boesser, T.

1984-01-01

One of the basic components of a discrete model of motor behavior and decision making, which describes tracking and supervisory control in unitary terms, is assumed to be a filtering mechanism which is tied to the representational principles of human memory for time-series information. In a series of experiments subjects used the time-series information with certain significant limitations: there is a range-effect; asymmetric distributions seem to be recognized, but it does not seem to be possible to optimize performance based on skewed distributions. Thus there is a transformation of the displayed data between the perceptual system and representation in memory involving a loss of information. This rules out a number of representational principles for time-series information in memory and fits very well into the framework of a comprehensive discrete model for control of complex systems, modelling continuous control (tracking), discrete responses, supervisory behavior and learning.

Optimized tracking of RF carriers with phase noise, including Pioneer 10 results

NASA Technical Reports Server (NTRS)

Vilnrotter, V. A.; Hurd, W. J.; Brown, D. H.

1987-01-01

The ability to track very weak signals from distant spacecraft is limited by the phase instabilities of the received signal and of the local oscillator employed by the receiver. These instabilities ultimately limit the minimum loop bandwidth that can be used in a phase-coherent receiver, and hence limit the ratio of received carrier power to noise spectral density which can be tracked phase coherently. A method is presented for near real time estimation of the received carrier phase and additive noise spectrum, and optimization of the phase locked loop bandwidth. The method was used with the breadboard Deep Space Network (DSN) Advanced Receiver to optimize tracking of very weak signals from the Pioneer 10 spacecraft, which is now more distant that the edge of the solar system. Tracking with bandwidths of 0.1 Hz to 1.0 Hz reduces tracking signal threshold and increases carrier loop signal to noise ratio (SNR) by 5 dB to 15 dB compared to the 3 Hz bandwidth of the receivers now used operationally in the DSN. This will enable the DSN to track Pioneer 10 until its power sources fails near the end of the century.

Experimental research of flow servo-valve

NASA Astrophysics Data System (ADS)

Takosoglu, Jakub

Positional control of pneumatic drives is particularly important in pneumatic systems. Some methods of positioning pneumatic cylinders for changeover and tracking control are known. Choking method is the most development-oriented and has the greatest potential. An optimal and effective method, particularly when applied to pneumatic drives, has been searched for a long time. Sophisticated control systems with algorithms utilizing artificial intelligence methods are designed therefor. In order to design the control algorithm, knowledge about real parameters of servo-valves used in control systems of electro-pneumatic servo-drives is required. The paper presents the experimental research of flow servo-valve.

Model-based observer and feedback control design for a rigid Joukowski foil in a Kármán vortex street.

PubMed

Free, Brian A; Paley, Derek A

2018-03-14

Obstacles and swimming fish in flow create a wake with an alternating left/right vortex pattern known as a Kármán vortex street and reverse Kármán vortex street, respectively. An energy-efficient fish behavior resembling slaloming through the vortex street is called Kármán gaiting. This paper describes the use of a bioinspired array of pressure sensors on a Joukowski foil to estimate and control flow-relative position in a Kármán vortex street using potential flow theory, recursive Bayesian filtering, and trajectory-tracking feedback control. The Joukowski foil is fixed in downstream position in a flowing water channel and free to move on air bearings in the cross-stream direction by controlling its angle of attack to generate lift. Inspired by the lateral-line neuromasts found in fish, the sensing and control scheme is validated using off-the-shelf pressure sensors in an experimental testbed that includes a flapping device to create vortices. We derive a potential flow model that describes the flow over a Joukowski foil in a Kármán vortex street and identify an optimal path through a Kármán vortex street using empirical observability. The optimally observable trajectory is one that passes through each vortex in the street. The estimated vorticity and location of the Kármán vortex street are used in a closed-loop control to track either the optimally observable path or the energetically efficient gait exhibited by fish. Results from the closed-loop control experiments in the flow tank show that the artificial lateral line in conjunction with a potential flow model and Bayesian estimator allow the robot to perform fish-like slaloming behavior in a Kármán vortex street. This work is a precursor to an autonomous robotic fish sensing the wake of another fish and/or performing pursuit and schooling behavior.

Efficient global fiber tracking on multi-dimensional diffusion direction maps

NASA Astrophysics Data System (ADS)

Klein, Jan; Köhler, Benjamin; Hahn, Horst K.

2012-02-01

Global fiber tracking algorithms have recently been proposed which were able to compute results of unprecedented quality. They account for avoiding accumulation errors by a global optimization process at the cost of a high computation time of several hours or even days. In this paper, we introduce a novel global fiber tracking algorithm which, for the first time, globally optimizes the underlying diffusion direction map obtained from DTI or HARDI data, instead of single fiber segments. As a consequence, the number of iterations in the optimization process can drastically be reduced by about three orders of magnitude. Furthermore, in contrast to all previous algorithms, the density of the tracked fibers can be adjusted after the optimization within a few seconds. We evaluated our method for diffusion-weighted images obtained from software phantoms, healthy volunteers, and tumor patients. We show that difficult fiber bundles, e.g., the visual pathways or tracts for different motor functions can be determined and separated in an excellent quality. Furthermore, crossing and kissing bundles are correctly resolved. On current standard hardware, a dense fiber tracking result of a whole brain can be determined in less than half an hour which is a strong improvement compared to previous work.

Extracting motor synergies from random movements for low-dimensional task-space control of musculoskeletal robots.

PubMed

Fu, Kin Chung Denny; Dalla Libera, Fabio; Ishiguro, Hiroshi

2015-10-08

In the field of human motor control, the motor synergy hypothesis explains how humans simplify body control dimensionality by coordinating groups of muscles, called motor synergies, instead of controlling muscles independently. In most applications of motor synergies to low-dimensional control in robotics, motor synergies are extracted from given optimal control signals. In this paper, we address the problems of how to extract motor synergies without optimal data given, and how to apply motor synergies to achieve low-dimensional task-space tracking control of a human-like robotic arm actuated by redundant muscles, without prior knowledge of the robot. We propose to extract motor synergies from a subset of randomly generated reaching-like movement data. The essence is to first approximate the corresponding optimal control signals, using estimations of the robot's forward dynamics, and to extract the motor synergies subsequently. In order to avoid modeling difficulties, a learning-based control approach is adopted such that control is accomplished via estimations of the robot's inverse dynamics. We present a kernel-based regression formulation to estimate the forward and the inverse dynamics, and a sliding controller in order to cope with estimation error. Numerical evaluations show that the proposed method enables extraction of motor synergies for low-dimensional task-space control.

Density control in ITER: an iterative learning control and robust control approach

NASA Astrophysics Data System (ADS)

Ravensbergen, T.; de Vries, P. C.; Felici, F.; Blanken, T. C.; Nouailletas, R.; Zabeo, L.

2018-01-01

Plasma density control for next generation tokamaks, such as ITER, is challenging because of multiple reasons. The response of the usual gas valve actuators in future, larger fusion devices, might be too slow for feedback control. Both pellet fuelling and the use of feedforward-based control may help to solve this problem. Also, tight density limits arise during ramp-up, due to operational limits related to divertor detachment and radiative collapses. As the number of shots available for controller tuning will be limited in ITER, in this paper, iterative learning control (ILC) is proposed to determine optimal feedforward actuator inputs based on tracking errors, obtained in previous shots. This control method can take the actuator and density limits into account and can deal with large actuator delays. However, a purely feedforward-based density control may not be sufficient due to the presence of disturbances and shot-to-shot differences. Therefore, robust control synthesis is used to construct a robustly stabilizing feedback controller. In simulations, it is shown that this combined controller strategy is able to achieve good tracking performance in the presence of shot-to-shot differences, tight constraints, and model mismatches.

Optimal intravenous infusion to decrease the haematocrit level in patient of DHF infection

NASA Astrophysics Data System (ADS)

Handayani, D.; Nuraini, N.; Saragih, R.; Wijaya, K. P.; Naiborhu, J.

2014-02-01

The optimal control of infusion model for Dengue Hemorrhagic Fever (DHF) infection is formulated here. The infusion model will be presented in form of haematocrit level. The input control aim to normalize the haematocrit level and is expressed as infusion volume on mL/day. The stability near the equilibrium points will be analyzed. Numerical simulation shows the dynamic of each infection compartments which gives a description of within-host dynamic of dengue virus. These results show particularly that infected compartments tend to be vanished in ±15days after the onset of the virus. In fact, without any control added, the haematocrit level will decrease but not up to the normal level. Therefore the effective haematocrit normalization should be done with the treatment control. Control treatment for a fixed time using a control input can bring haematocrit level to normal range 42-47%. The optimal control in this paper is divided into three cases, i.e. fixed end point, constrained input, and tracking haematocrit state. Each case shows different infection condition in human body. However, all cases require that the haematocrit level to be in normal range in fixed final time.

Dynamic inverse models in human-cyber-physical systems

NASA Astrophysics Data System (ADS)

Robinson, Ryan M.; Scobee, Dexter R. R.; Burden, Samuel A.; Sastry, S. Shankar

2016-05-01

Human interaction with the physical world is increasingly mediated by automation. This interaction is characterized by dynamic coupling between robotic (i.e. cyber) and neuromechanical (i.e. human) decision-making agents. Guaranteeing performance of such human-cyber-physical systems will require predictive mathematical models of this dynamic coupling. Toward this end, we propose a rapprochement between robotics and neuromechanics premised on the existence of internal forward and inverse models in the human agent. We hypothesize that, in tele-robotic applications of interest, a human operator learns to invert automation dynamics, directly translating from desired task to required control input. By formulating the model inversion problem in the context of a tracking task for a nonlinear control system in control-a_ne form, we derive criteria for exponential tracking and show that the resulting dynamic inverse model generally renders a portion of the physical system state (i.e., the internal dynamics) unobservable from the human operator's perspective. Under stability conditions, we show that the human can achieve exponential tracking without formulating an estimate of the system's state so long as they possess an accurate model of the system's dynamics. These theoretical results are illustrated using a planar quadrotor example. We then demonstrate that the automation can intervene to improve performance of the tracking task by solving an optimal control problem. Performance is guaranteed to improve under the assumption that the human learns and inverts the dynamic model of the altered system. We conclude with a discussion of practical limitations that may hinder exact dynamic model inversion.

Distributed cluster management techniques for unattended ground sensor networks

NASA Astrophysics Data System (ADS)

Essawy, Magdi A.; Stelzig, Chad A.; Bevington, James E.; Minor, Sharon

2005-05-01

Smart Sensor Networks are becoming important target detection and tracking tools. The challenging problems in such networks include the sensor fusion, data management and communication schemes. This work discusses techniques used to distribute sensor management and multi-target tracking responsibilities across an ad hoc, self-healing cluster of sensor nodes. Although miniaturized computing resources possess the ability to host complex tracking and data fusion algorithms, there still exist inherent bandwidth constraints on the RF channel. Therefore, special attention is placed on the reduction of node-to-node communications within the cluster by minimizing unsolicited messaging, and distributing the sensor fusion and tracking tasks onto local portions of the network. Several challenging problems are addressed in this work including track initialization and conflict resolution, track ownership handling, and communication control optimization. Emphasis is also placed on increasing the overall robustness of the sensor cluster through independent decision capabilities on all sensor nodes. Track initiation is performed using collaborative sensing within a neighborhood of sensor nodes, allowing each node to independently determine if initial track ownership should be assumed. This autonomous track initiation prevents the formation of duplicate tracks while eliminating the need for a central "management" node to assign tracking responsibilities. Track update is performed as an ownership node requests sensor reports from neighboring nodes based on track error covariance and the neighboring nodes geo-positional location. Track ownership is periodically recomputed using propagated track states to determine which sensing node provides the desired coverage characteristics. High fidelity multi-target simulation results are presented, indicating the distribution of sensor management and tracking capabilities to not only reduce communication bandwidth consumption, but to also simplify multi-target tracking within the cluster.

A real-time guidance algorithm for aerospace plane optimal ascent to low earth orbit

NASA Technical Reports Server (NTRS)

Calise, A. J.; Flandro, G. A.; Corban, J. E.

1989-01-01

Problems of onboard trajectory optimization and synthesis of suitable guidance laws for ascent to low Earth orbit of an air-breathing, single-stage-to-orbit vehicle are addressed. A multimode propulsion system is assumed which incorporates turbojet, ramjet, Scramjet, and rocket engines. An algorithm for generating fuel-optimal climb profiles is presented. This algorithm results from the application of the minimum principle to a low-order dynamic model that includes angle-of-attack effects and the normal component of thrust. Maximum dynamic pressure and maximum aerodynamic heating rate constraints are considered. Switching conditions are derived which, under appropriate assumptions, govern optimal transition from one propulsion mode to another. A nonlinear transformation technique is employed to derived a feedback controller for tracking the computed trajectory. Numerical results illustrate the nature of the resulting fuel-optimal climb paths.

A tyre slip-based integrated chassis control of front/rear traction distribution and four-wheel independent brake from moderate driving to limit handling

NASA Astrophysics Data System (ADS)

Joa, Eunhyek; Park, Kwanwoo; Koh, Youngil; Yi, Kyongsu; Kim, Kilsoo

2018-04-01

This paper presents a tyre slip-based integrated chassis control of front/rear traction distribution and four-wheel braking for enhanced performance from moderate driving to limit handling. The proposed algorithm adopted hierarchical structure: supervisor - desired motion tracking controller - optimisation-based control allocation. In the supervisor, by considering transient cornering characteristics, desired vehicle motion is calculated. In the desired motion tracking controller, in order to track desired vehicle motion, virtual control input is determined in the manner of sliding mode control. In the control allocation, virtual control input is allocated to minimise cost function. The cost function consists of two major parts. First part is a slip-based tyre friction utilisation quantification, which does not need a tyre force estimation. Second part is an allocation guideline, which guides optimally allocated inputs to predefined solution. The proposed algorithm has been investigated via simulation from moderate driving to limit handling scenario. Compared to Base and direct yaw moment control system, the proposed algorithm can effectively reduce tyre dissipation energy in the moderate driving situation. Moreover, the proposed algorithm enhances limit handling performance compared to Base and direct yaw moment control system. In addition to comparison with Base and direct yaw moment control, comparison the proposed algorithm with the control algorithm based on the known tyre force information has been conducted. The results show that the performance of the proposed algorithm is similar with that of the control algorithm with the known tyre force information.

A robust hybrid fuzzy-simulated annealing-intelligent water drops approach for tuning a distribution static compensator nonlinear controller in a distribution system

NASA Astrophysics Data System (ADS)

Bagheri Tolabi, Hajar; Hosseini, Rahil; Shakarami, Mahmoud Reza

2016-06-01

This article presents a novel hybrid optimization approach for a nonlinear controller of a distribution static compensator (DSTATCOM). The DSTATCOM is connected to a distribution system with the distributed generation units. The nonlinear control is based on partial feedback linearization. Two proportional-integral-derivative (PID) controllers regulate the voltage and track the output in this control system. In the conventional scheme, the trial-and-error method is used to determine the PID controller coefficients. This article uses a combination of a fuzzy system, simulated annealing (SA) and intelligent water drops (IWD) algorithms to optimize the parameters of the controllers. The obtained results reveal that the response of the optimized controlled system is effectively improved by finding a high-quality solution. The results confirm that using the tuning method based on the fuzzy-SA-IWD can significantly decrease the settling and rising times, the maximum overshoot and the steady-state error of the voltage step response of the DSTATCOM. The proposed hybrid tuning method for the partial feedback linearizing (PFL) controller achieved better regulation of the direct current voltage for the capacitor within the DSTATCOM. Furthermore, in the event of a fault the proposed controller tuned by the fuzzy-SA-IWD method showed better performance than the conventional controller or the PFL controller without optimization by the fuzzy-SA-IWD method with regard to both fault duration and clearing times.

Tracking and data relay satellite system configuration and tradeoff study. Volume 1: Study summary

NASA Technical Reports Server (NTRS)

Hill, T. E.

1973-01-01

A study was conducted to determine the configuration and tradeoffs of a tracking and data relay satellite. The study emphasized the design of a three axis stabilized satellite and a telecommunications system optimized for support of low and medium data rate user spacecraft. Telecommunications support to low and high, or low medium, and high data rate users, considering launches with the Delta 2914, the Atlas/Centaur, and the space shuttle was also considered. The following subjects are presented: (1) launch and deployment profile, (2) spacecraft mechanical and structural design, (3) attitude stabilization and control subsystem, and (4) reliability analysis.

Neural-network-based state feedback control of a nonlinear discrete-time system in nonstrict feedback form.

PubMed

Jagannathan, Sarangapani; He, Pingan

2008-12-01

In this paper, a suite of adaptive neural network (NN) controllers is designed to deliver a desired tracking performance for the control of an unknown, second-order, nonlinear discrete-time system expressed in nonstrict feedback form. In the first approach, two feedforward NNs are employed in the controller with tracking error as the feedback variable whereas in the adaptive critic NN architecture, three feedforward NNs are used. In the adaptive critic architecture, two action NNs produce virtual and actual control inputs, respectively, whereas the third critic NN approximates certain strategic utility function and its output is employed for tuning action NN weights in order to attain the near-optimal control action. Both the NN control methods present a well-defined controller design and the noncausal problem in discrete-time backstepping design is avoided via NN approximation. A comparison between the controller methodologies is highlighted. The stability analysis of the closed-loop control schemes is demonstrated. The NN controller schemes do not require an offline learning phase and the NN weights can be initialized at zero or random. Results show that the performance of the proposed controller schemes is highly satisfactory while meeting the closed-loop stability.

Distributed adaptive neural network control for a class of heterogeneous nonlinear multi-agent systems subject to actuation failures

NASA Astrophysics Data System (ADS)

Cui, Bing; Zhao, Chunhui; Ma, Tiedong; Feng, Chi

2017-02-01

In this paper, the cooperative adaptive consensus tracking problem for heterogeneous nonlinear multi-agent systems on directed graph is addressed. Each follower is modelled as a general nonlinear system with the unknown and nonidentical nonlinear dynamics, disturbances and actuator failures. Cooperative fault tolerant neural network tracking controllers with online adaptive learning features are proposed to guarantee that all agents synchronise to the trajectory of one leader with bounded adjustable synchronisation errors. With the help of linear quadratic regulator-based optimal design, a graph-dependent Lyapunov proof provides error bounds that depend on the graph topology, one virtual matrix and some design parameters. Of particular interest is that if the control gain is selected appropriately, the proposed control scheme can be implemented in a unified framework no matter whether there are faults or not. Furthermore, the fault detection and isolation are not needed to implement. Finally, a simulation is given to verify the effectiveness of the proposed method.

Intelligent Optimization of Modulation Indexes in Unified Tracking and Communication System

NASA Astrophysics Data System (ADS)

Yang, Wei-wei; Cong, Bo; Huang, Qiong; Zhu, Li-wei

2016-02-01

In the unified tracking and communication system, the ranging signal and the telemetry, communication signals are used in the same channel. In the link budget, it is necessary to allocate the power reasonably, so as to ensure the performance of system and reduce the cost. In this paper, the nonlinear optimization problem is studied using intelligent optimization method. Simulation analysis results show that the proposed method is effective.

Two-craft Coulomb formation study about circular orbits and libration points

NASA Astrophysics Data System (ADS)

Inampudi, Ravi Kishore

This dissertation investigates the dynamics and control of a two-craft Coulomb formation in circular orbits and at libration points; it addresses relative equilibria, stability and optimal reconfigurations of such formations. The relative equilibria of a two-craft tether formation connected by line-of-sight elastic forces moving in circular orbits and at libration points are investigated. In circular Earth orbits and Earth-Moon libration points, the radial, along-track, and orbit normal great circle equilibria conditions are found. An example of modeling the tether force using Coulomb force is discussed. Furthermore, the non-great-circle equilibria conditions for a two-spacecraft tether structure in circular Earth orbit and at collinear libration points are developed. Then the linearized dynamics and stability analysis of a 2-craft Coulomb formation at Earth-Moon libration points are studied. For orbit-radial equilibrium, Coulomb forces control the relative distance between the two satellites. The gravity gradient torques on the formation due to the two planets help stabilize the formation. Similar analysis is performed for along-track and orbit-normal relative equilibrium configurations. Where necessary, the craft use a hybrid thrusting-electrostatic actuation system. The two-craft dynamics at the libration points provide a general framework with circular Earth orbit dynamics forming a special case. In the presence of differential solar drag perturbations, a Lyapunov feedback controller is designed to stabilize a radial equilibrium, two-craft Coulomb formation at collinear libration points. The second part of the thesis investigates optimal reconfigurations of two-craft Coulomb formations in circular Earth orbits by applying nonlinear optimal control techniques. The objective of these reconfigurations is to maneuver the two-craft formation between two charged equilibria configurations. The reconfiguration of spacecraft is posed as an optimization problem using the calculus of variations approach. The optimality criteria are minimum time, minimum acceleration of the separation distance, minimum Coulomb and electric propulsion fuel usage, and minimum electrical power consumption. The continuous time problem is discretized using a pseudospectral method, and the resulting finite dimensional problem is solved using a sequential quadratic programming algorithm. The software package, DIDO, implements this approach. This second part illustrates how pseudospectral methods significantly simplify the solution-finding process.

Statistical-Mechanics-Inspired Optimization of Sensor Field Configuration for Detection of Mobile Targets (PREPRINT)

DTIC Science & Technology

2010-11-01

pected target motion. Along this line, Wettergren [5] analyzed the performance of the track - before - detect schemes for the sensor networks. Furthermore...dressed by Baumgartner and Ferrari [11] for the reorganization of the sensor field to achieve the maximum coverage. The track - before - detect -based optimal...confirming a target. In accordance with the track - before - detect paradigm [4], a moving target is detected if the kd (typically kd = 3 or 4) sensors detect

How to track protists in three dimensions

NASA Astrophysics Data System (ADS)

Drescher, Knut; Leptos, Kyriacos C.; Goldstein, Raymond E.

2009-01-01

We present an apparatus optimized for tracking swimming micro-organisms in the size range of 10-1000 μm, in three dimensions (3Ds), far from surfaces, and with negligible background convective fluid motion. Charge coupled device cameras attached to two long working distance microscopes synchronously image the sample from two perpendicular directions, with narrow band dark-field or bright-field illumination chosen to avoid triggering a phototactic response. The images from the two cameras can be combined to yield 3D tracks of the organism. Using additional, highly directional broad-spectrum illumination with millisecond timing control the phototactic trajectories in 3D of organisms ranging from Chlamydomonas to Volvox can be studied in detail. Surface-mediated hydrodynamic interactions can also be investigated without convective interference. Minimal modifications to the apparatus allow for studies of chemotaxis and other taxes.

Advanced Structural Optimization Under Consideration of Cost Tracking

NASA Astrophysics Data System (ADS)

Zell, D.; Link, T.; Bickelmaier, S.; Albinger, J.; Weikert, S.; Cremaschi, F.; Wiegand, A.

2014-06-01

In order to improve the design process of launcher configurations in the early development phase, the software Multidisciplinary Optimization (MDO) was developed. The tool combines different efficient software tools such as Optimal Design Investigations (ODIN) for structural optimizations, Aerospace Trajectory Optimization Software (ASTOS) for trajectory and vehicle design optimization for a defined payload and mission.The present paper focuses to the integration and validation of ODIN. ODIN enables the user to optimize typical axis-symmetric structures by means of sizing the stiffening designs concerning strength and stability while minimizing the structural mass. In addition a fully automatic finite element model (FEM) generator module creates ready-to-run FEM models of a complete stage or launcher assembly.Cost tracking respectively future improvements concerning cost optimization are indicated.

Adaptive control for solar energy based DC microgrid system development

NASA Astrophysics Data System (ADS)

Zhang, Qinhao

During the upgrading of current electric power grid, it is expected to develop smarter, more robust and more reliable power systems integrated with distributed generations. To realize these objectives, traditional control techniques are no longer effective in either stabilizing systems or delivering optimal and robust performances. Therefore, development of advanced control methods has received increasing attention in power engineering. This work addresses two specific problems in the control of solar panel based microgrid systems. First, a new control scheme is proposed for the microgrid systems to achieve optimal energy conversion ratio in the solar panels. The control system can optimize the efficiency of the maximum power point tracking (MPPT) algorithm by implementing two layers of adaptive control. Such a hierarchical control architecture has greatly improved the system performance, which is validated through both mathematical analysis and computer simulation. Second, in the development of the microgrid transmission system, the issues related to the tele-communication delay and constant power load (CPL)'s negative incremental impedance are investigated. A reference model based method is proposed for pole and zero placements that address the challenges of the time delay and CPL in closed-loop control. The effectiveness of the proposed modeling and control design methods are demonstrated in a simulation testbed. Practical aspects of the proposed methods for general microgrid systems are also discussed.

Engine Yaw Augmentation for Hybrid-Wing-Body Aircraft via Optimal Control Allocation Techniques

NASA Technical Reports Server (NTRS)

Taylor, Brian R.; Yoo, Seung Yeun

2011-01-01

Asymmetric engine thrust was implemented in a hybrid-wing-body non-linear simulation to reduce the amount of aerodynamic surface deflection required for yaw stability and control. Hybrid-wing-body aircraft are especially susceptible to yaw surface deflection due to their decreased bare airframe yaw stability resulting from the lack of a large vertical tail aft of the center of gravity. Reduced surface deflection, especially for trim during cruise flight, could reduce the fuel consumption of future aircraft. Designed as an add-on, optimal control allocation techniques were used to create a control law that tracks total thrust and yaw moment commands with an emphasis on not degrading the baseline system. Implementation of engine yaw augmentation is shown and feasibility is demonstrated in simulation with a potential drag reduction of 2 to 4 percent. Future flight tests are planned to demonstrate feasibility in a flight environment.

GA-optimized feedforward-PID tracking control for a rugged electrohydraulic system design.

PubMed

Sarkar, B K; Mandal, P; Saha, R; Mookherjee, S; Sanyal, D

2013-11-01

Rugged electrohydraulic systems are preferred for remote and harsh applications. Despite the low bandwidth, large deadband and flow nonlinearities in proportional valves valve and highly nonlinear friction in industry-grade cylinders that comprise rugged systems, their maintenance are much easier than very sophisticated and delicate servocontrol and servocylinder systems. With the target of making the easily maintainable system to perform comparably to a servosystem, a feedforward control has been designed here for compensating the nonlinearities. A PID feedback of the piston displacement has been employed in tandem for absorbing the unmodeled effects. All the controller parameters have been optimized by a real-coded genetic algorithm. The agreement between the achieved real-time responses for step and sinusoidal demands with those achieved by modern servosystems clearly establishes the acceptability of the controller design. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

A variable-speed, constant-frequency wind power generation scheme using a slip-ring induction generator

NASA Astrophysics Data System (ADS)

Velayudhan, C.; Bundell, J. H.

This paper investigates a variable-speed, constant-frequency double output induction generator which is capable of absorbing the mechanical energy from a fixed pitch wind turbine and converting it into electrical energy at constant grid voltage and frequency. Rotor power at varying voltage and frequency is either fed to electronically controlled resistances and used as heat energy or is rectified, inverted by a controllable line-commutated inverter and returned to the grid. Optimal power tracking is by means of an adaptive controller which controls the developed torque of the generator by monitoring the shaft speed.

Poster - Thur Eve - 76: A quality control to achieve planning consistency in arc radiotherapy of the prostate.

PubMed

Zeng, G; Murphy, J; Annis, S-L; Wu, X; Wang, Y; McGowan, T; Macpherson, M

2012-07-01

To report a quality control program in prostate radiation therapy at our center that includes semi-automated planning process to generate high quality plans and in-house software to track plan quality in the subsequent clinical application. Arc planning in Eclipse v10.0 was preformed for both intact prostate and post-prostatectomy treatments. The planning focuses on DVH requirements and dose distributions being able to tolerate daily setup variations. A modified structure set is used to standardize the optimization, including short rectum and bladder in the fields to effectively tighten dose to target and a rectum expansion with 1cm cropped from PTV to block dose and shape posterior isodose lines. Structure, plan and optimization templates are used to streamline plan generation. DVH files are exported from Eclipse to a quality tracking software with GUI written in Matlab that can report the dose-volume data either for an individual patient or over a patient population. For 100 intact prostate patients treated with 78Gy, rectal D50, D25, D15 and D5 are 30.1±6.2Gy, 50.6±7.9Gy, 65.9±6.0Gy and 76.6±1.4Gy respectively, well below the limits 50Gy, 65Gy, 75Gy and 78Gy respectively. For prostate bed with prescription of 66Gy, rectal D50 is 35.9±6.9Gy. In both sites, PTV is covered by 95% prescription and the hotspots are less than 5%. The semi-automated planning method can efficiently create high quality plans while the tracking software can monitor the feedback from clinical application. It is a comprehensive and robust quality control program in radiation therapy. © 2012 American Association of Physicists in Medicine.

Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

NASA Astrophysics Data System (ADS)

Liu, Qiaoyuan; Wang, Yuru; Yin, Minghao; Ren, Jinchang; Li, Ruizhi

2017-11-01

Although various visual tracking algorithms have been proposed in the last 2-3 decades, it remains a challenging problem for effective tracking with fast motion, deformation, occlusion, etc. Under complex tracking conditions, most tracking models are not discriminative and adaptive enough. When the combined feature vectors are inputted to the visual models, this may lead to redundancy causing low efficiency and ambiguity causing poor performance. An effective tracking algorithm is proposed to decontaminate features for each video sequence adaptively, where the visual modeling is treated as an optimization problem from the perspective of evolution. Every feature vector is compared to a biological individual and then decontaminated via classical evolutionary algorithms. With the optimized subsets of features, the "curse of dimensionality" has been avoided while the accuracy of the visual model has been improved. The proposed algorithm has been tested on several publicly available datasets with various tracking challenges and benchmarked with a number of state-of-the-art approaches. The comprehensive experiments have demonstrated the efficacy of the proposed methodology.

X33 Reusable Launch Vehicle Control on Sliding Modes: Concepts for a Control System Development

NASA Technical Reports Server (NTRS)

Shtessel, Yuri B.

1998-01-01

Control of the X33 reusable launch vehicle is considered. The launch control problem consists of automatic tracking of the launch trajectory which is assumed to be optimally precalculated. It requires development of a reliable, robust control algorithm that can automatically adjust to some changes in mission specifications (mass of payload, target orbit) and the operating environment (atmospheric perturbations, interconnection perturbations from the other subsystems of the vehicle, thrust deficiencies, failure scenarios). One of the effective control strategies successfully applied in nonlinear systems is the Sliding Mode Control. The main advantage of the Sliding Mode Control is that the system's state response in the sliding surface remains insensitive to certain parameter variations, nonlinearities and disturbances. Employing the time scaling concept, a new two (three)-loop structure of the control system for the X33 launch vehicle was developed. Smoothed sliding mode controllers were designed to robustly enforce the given closed-loop dynamics. Simulations of the 3-DOF model of the X33 launch vehicle with the table-look-up models for Euler angle reference profiles and disturbance torque profiles showed a very accurate, robust tracking performance.

Terminal area automatic navigation, guidance, and control research using the Microwave Landing System (MLS). Part 2: RNAV/MLS transition problems for aircraft

NASA Technical Reports Server (NTRS)

Pines, S.

1982-01-01

The problems in navigation and guidance encountered by aircraft in the initial transition period in changing from distance measuring equipment, VORTAC, and barometric instruments to the more precise microwave landing system data type navaids in the terminal area are investigated. The effects of the resulting discontinuities on the estimates of position and velocity for both optimal (Kalman type navigation schemes) and fixed gain (complementary type) navigation filters, and the effects of the errors in cross track, track angle, and altitude on the guidance equation and control commands during the critical landing phase are discussed. A method is presented to remove the discontinuities from the navigation loop and to reconstruct an RNAV path designed to land the aircraft with minimal turns and altitude changes.

Collaborative real-time scheduling of multiple PTZ cameras for multiple object tracking in video surveillance

NASA Astrophysics Data System (ADS)

Liu, Yu-Che; Huang, Chung-Lin

2013-03-01

This paper proposes a multi-PTZ-camera control mechanism to acquire close-up imagery of human objects in a surveillance system. The control algorithm is based on the output of multi-camera, multi-target tracking. Three main concerns of the algorithm are (1) the imagery of human object's face for biometric purposes, (2) the optimal video quality of the human objects, and (3) minimum hand-off time. Here, we define an objective function based on the expected capture conditions such as the camera-subject distance, pan tile angles of capture, face visibility and others. Such objective function serves to effectively balance the number of captures per subject and quality of captures. In the experiments, we demonstrate the performance of the system which operates in real-time under real world conditions on three PTZ cameras.

Detumbling control for kinematically redundant space manipulator post-grasping a rotational satellite

NASA Astrophysics Data System (ADS)

Wang, Mingming; Luo, Jianjun; Yuan, Jianping; Walter, Ulrich

2017-12-01

The objective of this paper is to establish a detumbling strategy and a coordination control scheme for a kinematically redundant space manipulator post-grasping a rotational satellite. First, the dynamics of the kinematically redundant space robot after grasping the target is presented, which lays the foundation for the coordination controller design. Subsequently, optimal detumbling and motion planning strategy for the post-capture phase is proposed based on the quartic Bézier curves and adaptive differential evolution (DE) algorithm subject to the specific constraints. Both detumbling time and control torques are taken into account for the generation of the optimal detumbling strategy. Furthermore, a coordination control scheme is presented to track the designed reference path while regulating the attitude of the chaser to a desired value, which successfully dumps the initial angular velocity of the rotational satellite and controls the base attitude synchronously. Simulation results are presented for detumbling a target with rotational motion using a 7 degree-of-freedom (DOF) redundant space manipulator, which demonstrates the effectiveness of the proposed method.

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

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.

Analysis and simulation tools for solar array power systems

NASA Astrophysics Data System (ADS)

Pongratananukul, Nattorn

This dissertation presents simulation tools developed specifically for the design of solar array power systems. Contributions are made in several aspects of the system design phases, including solar source modeling, system simulation, and controller verification. A tool to automate the study of solar array configurations using general purpose circuit simulators has been developed based on the modeling of individual solar cells. Hierarchical structure of solar cell elements, including semiconductor properties, allows simulation of electrical properties as well as the evaluation of the impact of environmental conditions. A second developed tool provides a co-simulation platform with the capability to verify the performance of an actual digital controller implemented in programmable hardware such as a DSP processor, while the entire solar array including the DC-DC power converter is modeled in software algorithms running on a computer. This "virtual plant" allows developing and debugging code for the digital controller, and also to improve the control algorithm. One important task in solar arrays is to track the maximum power point on the array in order to maximize the power that can be delivered. Digital controllers implemented with programmable processors are particularly attractive for this task because sophisticated tracking algorithms can be implemented and revised when needed to optimize their performance. The proposed co-simulation tools are thus very valuable in developing and optimizing the control algorithm, before the system is built. Examples that demonstrate the effectiveness of the proposed methodologies are presented. The proposed simulation tools are also valuable in the design of multi-channel arrays. In the specific system that we have designed and tested, the control algorithm is implemented on a single digital signal processor. In each of the channels the maximum power point is tracked individually. In the prototype we built, off-the-shelf commercial DC-DC converters were utilized. At the end, the overall performance of the entire system was evaluated using solar array simulators capable of simulating various I-V characteristics, and also by using an electronic load. Experimental results are presented.

Quantification of larval zebrafish motor function in multi-well plates using open-source MATLAB® applications

PubMed Central

Zhou, Yangzhong; Cattley, Richard T.; Cario, Clinton L.; Bai, Qing; Burton, Edward A.

2014-01-01

This article describes a method to quantify the movements of larval zebrafish in multi-well plates, using the open-source MATLAB® applications LSRtrack and LSRanalyze. The protocol comprises four stages: generation of high-quality, flatly-illuminated video recordings with exposure settings that facilitate object recognition; analysis of the resulting recordings using tools provided in LSRtrack to optimize tracking accuracy and motion detection; analysis of tracking data using LSRanalyze or custom MATLAB® scripts; implementation of validation controls. The method is reliable, automated and flexible, requires less than one hour of hands-on work for completion once optimized, and shows excellent signal:noise characteristics. The resulting data can be analyzed to determine: positional preference; displacement, velocity and acceleration; duration and frequency of movement events and rest periods. This approach is widely applicable to analyze spontaneous or stimulus-evoked zebrafish larval neurobehavioral phenotypes resulting from a broad array of genetic and environmental manipulations, in a multi-well plate format suitable for high-throughput applications. PMID:24901738

Quantification of larval zebrafish motor function in multiwell plates using open-source MATLAB applications.

PubMed

Zhou, Yangzhong; Cattley, Richard T; Cario, Clinton L; Bai, Qing; Burton, Edward A

2014-07-01

This article describes a method to quantify the movements of larval zebrafish in multiwell plates, using the open-source MATLAB applications LSRtrack and LSRanalyze. The protocol comprises four stages: generation of high-quality, flatly illuminated video recordings with exposure settings that facilitate object recognition; analysis of the resulting recordings using tools provided in LSRtrack to optimize tracking accuracy and motion detection; analysis of tracking data using LSRanalyze or custom MATLAB scripts; and implementation of validation controls. The method is reliable, automated and flexible, requires <1 h of hands-on work for completion once optimized and shows excellent signal:noise characteristics. The resulting data can be analyzed to determine the following: positional preference; displacement, velocity and acceleration; and duration and frequency of movement events and rest periods. This approach is widely applicable to the analysis of spontaneous or stimulus-evoked zebrafish larval neurobehavioral phenotypes resulting from a broad array of genetic and environmental manipulations, in a multiwell plate format suitable for high-throughput applications.

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

Simonetto, Andrea; Dall'Anese, Emiliano

This article develops online algorithms to track solutions of time-varying constrained optimization problems. Particularly, resembling workhorse Kalman filtering-based approaches for dynamical systems, the proposed methods involve prediction-correction steps to provably track the trajectory of the optimal solutions of time-varying convex problems. The merits of existing prediction-correction methods have been shown for unconstrained problems and for setups where computing the inverse of the Hessian of the cost function is computationally affordable. This paper addresses the limitations of existing methods by tackling constrained problems and by designing first-order prediction steps that rely on the Hessian of the cost function (and do notmore » require the computation of its inverse). In addition, the proposed methods are shown to improve the convergence speed of existing prediction-correction methods when applied to unconstrained problems. Numerical simulations corroborate the analytical results and showcase performance and benefits of the proposed algorithms. A realistic application of the proposed method to real-time control of energy resources is presented.« less

A general-purpose framework to simulate musculoskeletal system of human body: using a motion tracking approach.

PubMed

Ehsani, Hossein; Rostami, Mostafa; Gudarzi, Mohammad

2016-02-01

Computation of muscle force patterns that produce specified movements of muscle-actuated dynamic models is an important and challenging problem. This problem is an undetermined one, and then a proper optimization is required to calculate muscle forces. The purpose of this paper is to develop a general model for calculating all muscle activation and force patterns in an arbitrary human body movement. For this aim, the equations of a multibody system forward dynamics, which is considered for skeletal system of the human body model, is derived using Lagrange-Euler formulation. Next, muscle contraction dynamics is added to this model and forward dynamics of an arbitrary musculoskeletal system is obtained. For optimization purpose, the obtained model is used in computed muscle control algorithm, and a closed-loop system for tracking desired motions is derived. Finally, a popular sport exercise, biceps curl, is simulated by using this algorithm and the validity of the obtained results is evaluated via EMG signals.

Optimizing and controlling earthmoving operations using spatial technologies

NASA Astrophysics Data System (ADS)

Alshibani, Adel

This thesis presents a model designed for optimizing, tracking, and controlling earthmoving operations. The proposed model utilizes, Genetic Algorithm (GA), Linear Programming (LP), and spatial technologies including Global Positioning Systems (GPS) and Geographic Information Systems (GIS) to support the management functions of the developed model. The model assists engineers and contractors in selecting near optimum crew formations in planning phase and during construction, using GA and LP supported by the Pathfinder Algorithm developed in a GIS environment. GA is used in conjunction with a set of rules developed to accelerate the optimization process and to avoid generating and evaluating hypothetical and unrealistic crew formations. LP is used to determine quantities of earth to be moved from different borrow pits and to be placed at different landfill sites to meet project constraints and to minimize the cost of these earthmoving operations. On the one hand, GPS is used for onsite data collection and for tracking construction equipment in near real-time. On the other hand, GIS is employed to automate data acquisition and to analyze the collected spatial data. The model is also capable of reconfiguring crew formations dynamically during the construction phase while site operations are in progress. The optimization of the crew formation considers: (1) construction time, (2) construction direct cost, or (3) construction total cost. The model is also capable of generating crew formations to meet, as close as possible, specified time and/or cost constraints. In addition, the model supports tracking and reporting of project progress utilizing the earned-value concept and the project ratio method with modifications that allow for more accurate forecasting of project time and cost at set future dates and at completion. The model is capable of generating graphical and tabular reports. The developed model has been implemented in prototype software, using Object-Oriented Programming, Microsoft Foundation Classes (MFC), and has been coded using visual C++ V.6. Microsoft Access is employed as database management system. The developed software operates in Microsoft windows' environment. Three example applications were analyzed to validate the development made and to illustrate the essential features of the developed model.

Combined use of algorithms for peak picking, peak tracking and retention modelling to optimize the chromatographic conditions for liquid chromatography-mass spectrometry analysis of fluocinolone acetonide and its degradation products.

PubMed

Fredriksson, Mattias J; Petersson, Patrik; Axelsson, Bengt-Olof; Bylund, Dan

2011-10-17

A strategy for rapid optimization of liquid chromatography column temperature and gradient shape is presented. The optimization as such is based on the well established retention and peak width models implemented in software like e.g. DryLab and LC simulator. The novel part of the strategy is a highly automated processing algorithm for detection and tracking of chromatographic peaks in noisy liquid chromatography-mass spectrometry (LC-MS) data. The strategy is presented and visualized by the optimization of the separation of two degradants present in ultraviolet (UV) exposed fluocinolone acetonide. It should be stressed, however, that it can be utilized for LC-MS analysis of any sample and application where several runs are conducted on the same sample. In the application presented, 30 components that were difficult or impossible to detect in the UV data could be automatically detected and tracked in the MS data by using the proposed strategy. The number of correctly tracked components was above 95%. Using the parameters from the reconstructed data sets to the model gave good agreement between predicted and observed retention times at optimal conditions. The area of the smallest tracked component was estimated to 0.08% compared to the main component, a level relevant for the characterization of impurities in the pharmaceutical industry. Copyright © 2011 Elsevier B.V. All rights reserved.

SU-E-T-562: Motion Tracking Optimization for Conformal Arc Radiotherapy Plans: A QUASAR Phantom Based Study

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

Xu, Z; Wang, I; Yao, R

Purpose: This study is to use plan parameters optimization (Dose rate, collimator angle, couch angle, initial starting phase) to improve the performance of conformal arc radiotherapy plans with motion tracking by increasing the plan performance score (PPS). Methods: Two types of 3D conformal arc plans were created based on QUASAR respiratory motion phantom with spherical and cylindrical targets. Sinusoidal model was applied to the MLC leaves to generate motion tracking plans. A MATLAB program was developed to calculate PPS of each plan (ranges from 0–1) and optimize plan parameters. We first selected the dose rate for motion tracking plans andmore » then used simulated annealing algorithm to search for the combination of the other parameters that resulted in the plan of the maximal PPS. The optimized motion tracking plan was delivered by Varian Truebeam Linac. In-room cameras and stopwatch were used for starting phase selection and synchronization between phantom motion and plan delivery. Gaf-EBT2 dosimetry films were used to measure the dose delivered to the target in QUASAR phantom. Dose profiles and Truebeam trajectory log files were used for plan delivery performance evaluation. Results: For spherical target, the maximal PPS (PPSsph) of the optimized plan was 0.79: (Dose rate: 500MU/min, Collimator: 90°, Couch: +10°, starting phase: 0.83π). For cylindrical target, the maximal PPScyl was 0.75 (Dose rate: 300MU/min, Collimator: 87°, starting phase: 0.97π) with couch at 0°. Differences of dose profiles between motion tracking plans (with the maximal and the minimal PPS) and 3D conformal plans were as follows: PPSsph=0.79: %ΔFWHM: 8.9%, %Dmax: 3.1%; PPSsph=0.52: %ΔFWHM: 10.4%, %Dmax: 6.1%. PPScyl=0.75: %ΔFWHM: 4.7%, %Dmax: 3.6%; PPScyl=0.42: %ΔFWHM: 12.5%, %Dmax: 9.6%. Conclusion: By achieving high plan performance score through parameters optimization, we can improve target dose conformity of motion tracking plan by decreasing total MLC leaf travel distance and leaf speed.« less

Studies of pointing, acquisition, and tracking of agile optical wireless transceivers for free-space optical communication networks

NASA Astrophysics Data System (ADS)

Ho, Tzung-Hsien; Trisno, Sugianto; Smolyaninov, Igor I.; Milner, Stuart D.; Davis, Christopher C.

2004-02-01

Free space, dynamic, optical wireless communications will require topology control for optimization of network performance. Such networks may need to be configured for bi- or multiple-connectedness, reliability and quality-of-service. Topology control involves the introduction of new links and/or nodes into the network to achieve such performance objectives through autonomous reconfiguration as well as precise pointing, acquisition, tracking, and steering of laser beams. Reconfiguration may be required because of link degradation resulting from obscuration or node loss. As a result, the optical transceivers may need to be re-directed to new or existing nodes within the network and tracked on moving nodes. The redirection of transceivers may require operation over a whole sphere, so that small-angle beam steering techniques cannot be applied. In this context, we are studying the performance of optical wireless links using lightweight, bi-static transceivers mounted on high-performance stepping motor driven stages. These motors provide an angular resolution of 0.00072 degree at up to 80,000 steps per second. This paper focuses on the performance characteristics of these agile transceivers for pointing, acquisition, and tracking (PAT), including the influence of acceleration/deceleration time, motor angular speed, and angular re-adjustment, on latency and packet loss in small free space optical (FSO) wireless test networks.

3D Visual Tracking of an Articulated Robot in Precision Automated Tasks

PubMed Central

Alzarok, Hamza; Fletcher, Simon; Longstaff, Andrew P.

2017-01-01

The most compelling requirements for visual tracking systems are a high detection accuracy and an adequate processing speed. However, the combination between the two requirements in real world applications is very challenging due to the fact that more accurate tracking tasks often require longer processing times, while quicker responses for the tracking system are more prone to errors, therefore a trade-off between accuracy and speed, and vice versa is required. This paper aims to achieve the two requirements together by implementing an accurate and time efficient tracking system. In this paper, an eye-to-hand visual system that has the ability to automatically track a moving target is introduced. An enhanced Circular Hough Transform (CHT) is employed for estimating the trajectory of a spherical target in three dimensions, the colour feature of the target was carefully selected by using a new colour selection process, the process relies on the use of a colour segmentation method (Delta E) with the CHT algorithm for finding the proper colour of the tracked target, the target was attached to the six degree of freedom (DOF) robot end-effector that performs a pick-and-place task. A cooperation of two Eye-to Hand cameras with their image Averaging filters are used for obtaining clear and steady images. This paper also examines a new technique for generating and controlling the observation search window in order to increase the computational speed of the tracking system, the techniques is named Controllable Region of interest based on Circular Hough Transform (CRCHT). Moreover, a new mathematical formula is introduced for updating the depth information of the vision system during the object tracking process. For more reliable and accurate tracking, a simplex optimization technique was employed for the calculation of the parameters for camera to robotic transformation matrix. The results obtained show the applicability of the proposed approach to track the moving robot with an overall tracking error of 0.25 mm. Also, the effectiveness of CRCHT technique in saving up to 60% of the overall time required for image processing. PMID:28067860

Bayesian Tracking of Emerging Epidemics Using Ensemble Optimal Statistical Interpolation

PubMed Central

Cobb, Loren; Krishnamurthy, Ashok; Mandel, Jan; Beezley, Jonathan D.

2014-01-01

We present a preliminary test of the Ensemble Optimal Statistical Interpolation (EnOSI) method for the statistical tracking of an emerging epidemic, with a comparison to its popular relative for Bayesian data assimilation, the Ensemble Kalman Filter (EnKF). The spatial data for this test was generated by a spatial susceptible-infectious-removed (S-I-R) epidemic model of an airborne infectious disease. Both tracking methods in this test employed Poisson rather than Gaussian noise, so as to handle epidemic data more accurately. The EnOSI and EnKF tracking methods worked well on the main body of the simulated spatial epidemic, but the EnOSI was able to detect and track a distant secondary focus of infection that the EnKF missed entirely. PMID:25113590

Presentation and assessment of rideability of a novel single-track vehicle: the Anaconda

NASA Astrophysics Data System (ADS)

Verlinden, O.; Kabeya, P.

2012-08-01

In this paper, a new single-track vehicle, the Anaconda, is presented and modelled according to a multibody theory. This articulated vehicle begins with a traditional bicycle, called the head module, followed by a succession of so-called pedal modules (PMs) equipped with one rear-steered wheel. Each module is connected to the preceding one by a spherical joint. To assess its dynamic behaviour, the model of an Anaconda with two PMs is simulated under the EasyDyn framework, a multibody library based on the minimal coordinates approach. The simulation of such a vehicle cannot be performed without the riders' action, consisting of the torques applied on the handlebars. The latter is implemented through controllers designed by optimal control, from the out-of-plane dynamics of the vehicle going straight ahead at 20 km/h. First, two optimal controllers are determined separately for the Head Module alone on one hand and for the Pedal Module alone on the other hand. They are then implemented on the Anaconda and it appears that the vehicle is close to instability and that the handling of the pedal modules is delicate but humanly possible. Finally, the difficulty in riding the Anaconda is evaluated through the so-called rideability index, which increases, as expected, with the amount of PMs, and shows that good psycho-motor skills will be needed to drive the Anaconda.

Leader-Follower Output Synchronization of Linear Heterogeneous Systems With Active Leader Using Reinforcement Learning.

PubMed

Yang, Yongliang; Modares, Hamidreza; Wunsch, Donald C; Yin, Yixin

2018-06-01

This paper develops optimal control protocols for the distributed output synchronization problem of leader-follower multiagent systems with an active leader. Agents are assumed to be heterogeneous with different dynamics and dimensions. The desired trajectory is assumed to be preplanned and is generated by the leader. Other follower agents autonomously synchronize to the leader by interacting with each other using a communication network. The leader is assumed to be active in the sense that it has a nonzero control input so that it can act independently and update its control to keep the followers away from possible danger. A distributed observer is first designed to estimate the leader's state and generate the reference signal for each follower. Then, the output synchronization of leader-follower systems with an active leader is formulated as a distributed optimal tracking problem, and inhomogeneous algebraic Riccati equations (AREs) are derived to solve it. The resulting distributed optimal control protocols not only minimize the steady-state error but also optimize the transient response of the agents. An off-policy reinforcement learning algorithm is developed to solve the inhomogeneous AREs online in real time and without requiring any knowledge of the agents' dynamics. Finally, two simulation examples are conducted to illustrate the effectiveness of the proposed algorithm.

Optimal Quantization Scheme for Data-Efficient Target Tracking via UWSNs Using Quantized Measurements.

PubMed

Zhang, Senlin; Chen, Huayan; Liu, Meiqin; Zhang, Qunfei

2017-11-07

Target tracking is one of the broad applications of underwater wireless sensor networks (UWSNs). However, as a result of the temporal and spatial variability of acoustic channels, underwater acoustic communications suffer from an extremely limited bandwidth. In order to reduce network congestion, it is important to shorten the length of the data transmitted from local sensors to the fusion center by quantization. Although quantization can reduce bandwidth cost, it also brings about bad tracking performance as a result of information loss after quantization. To solve this problem, this paper proposes an optimal quantization-based target tracking scheme. It improves the tracking performance of low-bit quantized measurements by minimizing the additional covariance caused by quantization. The simulation demonstrates that our scheme performs much better than the conventional uniform quantization-based target tracking scheme and the increment of the data length affects our scheme only a little. Its tracking performance improves by only 4.4% from 2- to 3-bit, which means our scheme weakly depends on the number of data bits. Moreover, our scheme also weakly depends on the number of participate sensors, and it can work well in sparse sensor networks. In a 6 × 6 × 6 sensor network, compared with 4 × 4 × 4 sensor networks, the number of participant sensors increases by 334.92%, while the tracking accuracy using 1-bit quantized measurements improves by only 50.77%. Overall, our optimal quantization-based target tracking scheme can achieve the pursuit of data-efficiency, which fits the requirements of low-bandwidth UWSNs.

Optimized Assistive Human-Robot Interaction Using Reinforcement Learning.

PubMed

Modares, Hamidreza; Ranatunga, Isura; Lewis, Frank L; Popa, Dan O

2016-03-01

An intelligent human-robot interaction (HRI) system with adjustable robot behavior is presented. The proposed HRI system assists the human operator to perform a given task with minimum workload demands and optimizes the overall human-robot system performance. Motivated by human factor studies, the presented control structure consists of two control loops. First, a robot-specific neuro-adaptive controller is designed in the inner loop to make the unknown nonlinear robot behave like a prescribed robot impedance model as perceived by a human operator. In contrast to existing neural network and adaptive impedance-based control methods, no information of the task performance or the prescribed robot impedance model parameters is required in the inner loop. Then, a task-specific outer-loop controller is designed to find the optimal parameters of the prescribed robot impedance model to adjust the robot's dynamics to the operator skills and minimize the tracking error. The outer loop includes the human operator, the robot, and the task performance details. The problem of finding the optimal parameters of the prescribed robot impedance model is transformed into a linear quadratic regulator (LQR) problem which minimizes the human effort and optimizes the closed-loop behavior of the HRI system for a given task. To obviate the requirement of the knowledge of the human model, integral reinforcement learning is used to solve the given LQR problem. Simulation results on an x - y table and a robot arm, and experimental implementation results on a PR2 robot confirm the suitability of the proposed method.

''Illusion of control'' in Time-Horizon Minority and Parrondo Games

NASA Astrophysics Data System (ADS)

Satinover, J. B.; Sornette, D.

2007-12-01

Human beings like to believe they are in control of their destiny. This ubiquitous trait seems to increase motivation and persistence, and is probably evolutionarily adaptive [J.D. Taylor, S.E. Brown, Psych. Bull. 103, 193 (1988); A. Bandura, Self-efficacy: the exercise of control (WH Freeman, New York, 1997)]. But how good really is our ability to control? How successful is our track record in these areas? There is little understanding of when and under what circumstances we may over-estimate [E. Langer, J. Pers. Soc. Psych. 7, 185 (1975)] or even lose our ability to control and optimize outcomes, especially when they are the result of aggregations of individual optimization processes. Here, we demonstrate analytically using the theory of Markov Chains and by numerical simulations in two classes of games, the Time-Horizon Minority Game [M.L. Hart, P. Jefferies, N.F. Johnson, Phys. A 311, 275 (2002)] and the Parrondo Game [J.M.R. Parrondo, G.P. Harmer, D. Abbott, Phys. Rev. Lett. 85, 5226 (2000); J.M.R. Parrondo, How to cheat a bad mathematician (ISI, Italy, 1996)], that agents who optimize their strategy based on past information may actually perform worse than non-optimizing agents. In other words, low-entropy (more informative) strategies under-perform high-entropy (or random) strategies. This provides a precise definition of the “illusion of control” in certain set-ups a priori defined to emphasize the importance of optimization.

Optimization of illumination schemes in a head-mounted display integrated with eye tracking capabilities

NASA Astrophysics Data System (ADS)

Pansing, Craig W.; Hua, Hong; Rolland, Jannick P.

2005-08-01

Head-mounted display (HMD) technologies find a variety of applications in the field of 3D virtual and augmented environments, 3D scientific visualization, as well as wearable displays. While most of the current HMDs use head pose to approximate line of sight, we propose to investigate approaches and designs for integrating eye tracking capability into HMDs from a low-level system design perspective and to explore schemes for optimizing system performance. In this paper, we particularly propose to optimize the illumination scheme, which is a critical component in designing an eye tracking-HMD (ET-HMD) integrated system. An optimal design can improve not only eye tracking accuracy, but also robustness. Using LightTools, we present the simulation of a complete eye illumination and imaging system using an eye model along with multiple near infrared LED (IRLED) illuminators and imaging optics, showing the irradiance variation of the different eye structures. The simulation of dark pupil effects along with multiple 1st-order Purkinje images will be presented. A parametric analysis is performed to investigate the relationships between the IRLED configurations and the irradiance distribution at the eye, and a set of optimal configuration parameters is recommended. The analysis will be further refined by actual eye image acquisition and processing.

Enhanced index tracking modeling in portfolio optimization with mixed-integer programming z approach

NASA Astrophysics Data System (ADS)

Siew, Lam Weng; Jaaman, Saiful Hafizah Hj.; Ismail, Hamizun bin

2014-09-01

Enhanced index tracking is a popular form of portfolio management in stock market investment. Enhanced index tracking aims to construct an optimal portfolio to generate excess return over the return achieved by the stock market index without purchasing all of the stocks that make up the index. The objective of this paper is to construct an optimal portfolio using mixed-integer programming model which adopts regression approach in order to generate higher portfolio mean return than stock market index return. In this study, the data consists of 24 component stocks in Malaysia market index which is FTSE Bursa Malaysia Kuala Lumpur Composite Index from January 2010 until December 2012. The results of this study show that the optimal portfolio of mixed-integer programming model is able to generate higher mean return than FTSE Bursa Malaysia Kuala Lumpur Composite Index return with only selecting 30% out of the total stock market index components.

Design of Distributed Controllers Seeking Optimal Power Flow Solutions Under Communication Constraints

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

Dall'Anese, Emiliano; Simonetto, Andrea; Dhople, Sairaj

This paper focuses on power distribution networks featuring inverter-interfaced distributed energy resources (DERs), and develops feedback controllers that drive the DER output powers to solutions of time-varying AC optimal power flow (OPF) problems. Control synthesis is grounded on primal-dual-type methods for regularized Lagrangian functions, as well as linear approximations of the AC power-flow equations. Convergence and OPF-solution-tracking capabilities are established while acknowledging: i) communication-packet losses, and ii) partial updates of control signals. The latter case is particularly relevant since it enables asynchronous operation of the controllers where DER setpoints are updated at a fast time scale based on local voltagemore » measurements, and information on the network state is utilized if and when available, based on communication constraints. As an application, the paper considers distribution systems with high photovoltaic integration, and demonstrates that the proposed framework provides fast voltage-regulation capabilities, while enabling the near real-time pursuit of solutions of AC OPF problems.« less

Design of Distributed Controllers Seeking Optimal Power Flow Solutions under Communication Constraints: Preprint

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

Dall'Anese, Emiliano; Simonetto, Andrea; Dhople, Sairaj

This paper focuses on power distribution networks featuring inverter-interfaced distributed energy resources (DERs), and develops feedback controllers that drive the DER output powers to solutions of time-varying AC optimal power flow (OPF) problems. Control synthesis is grounded on primal-dual-type methods for regularized Lagrangian functions, as well as linear approximations of the AC power-flow equations. Convergence and OPF-solution-tracking capabilities are established while acknowledging: i) communication-packet losses, and ii) partial updates of control signals. The latter case is particularly relevant since it enables asynchronous operation of the controllers where DER setpoints are updated at a fast time scale based on local voltagemore » measurements, and information on the network state is utilized if and when available, based on communication constraints. As an application, the paper considers distribution systems with high photovoltaic integration, and demonstrates that the proposed framework provides fast voltage-regulation capabilities, while enabling the near real-time pursuit of solutions of AC OPF problems.« less

Neural networks for feedback feedforward nonlinear control systems.

PubMed

Parisini, T; Zoppoli, R

1994-01-01

This paper deals with the problem of designing feedback feedforward control strategies to drive the state of a dynamic system (in general, nonlinear) so as to track any desired trajectory joining the points of given compact sets, while minimizing a certain cost function (in general, nonquadratic). Due to the generality of the problem, conventional methods are difficult to apply. Thus, an approximate solution is sought by constraining control strategies to take on the structure of multilayer feedforward neural networks. After discussing the approximation properties of neural control strategies, a particular neural architecture is presented, which is based on what has been called the "linear-structure preserving principle". The original functional problem is then reduced to a nonlinear programming one, and backpropagation is applied to derive the optimal values of the synaptic weights. Recursive equations to compute the gradient components are presented, which generalize the classical adjoint system equations of N-stage optimal control theory. Simulation results related to nonlinear nonquadratic problems show the effectiveness of the proposed method.

A coarse-to-fine kernel matching approach for mean-shift based visual tracking

NASA Astrophysics Data System (ADS)

Liangfu, L.; Zuren, F.; Weidong, C.; Ming, J.

2009-03-01

Mean shift is an efficient pattern match algorithm. It is widely used in visual tracking fields since it need not perform whole search in the image space. It employs gradient optimization method to reduce the time of feature matching and realize rapid object localization, and uses Bhattacharyya coefficient as the similarity measure between object template and candidate template. This thesis presents a mean shift algorithm based on coarse-to-fine search for the best kernel matching. This paper researches for object tracking with large motion area based on mean shift. To realize efficient tracking of such an object, we present a kernel matching method from coarseness to fine. If the motion areas of the object between two frames are very large and they are not overlapped in image space, then the traditional mean shift method can only obtain local optimal value by iterative computing in the old object window area, so the real tracking position cannot be obtained and the object tracking will be disabled. Our proposed algorithm can efficiently use a similarity measure function to realize the rough location of motion object, then use mean shift method to obtain the accurate local optimal value by iterative computing, which successfully realizes object tracking with large motion. Experimental results show its good performance in accuracy and speed when compared with background-weighted histogram algorithm in the literature.

Clustering of financial time series with application to index and enhanced index tracking portfolio

NASA Astrophysics Data System (ADS)

Dose, Christian; Cincotti, Silvano

2005-09-01

A stochastic-optimization technique based on time series cluster analysis is described for index tracking and enhanced index tracking problems. Our methodology solves the problem in two steps, i.e., by first selecting a subset of stocks and then setting the weight of each stock as a result of an optimization process (asset allocation). Present formulation takes into account constraints on the number of stocks and on the fraction of capital invested in each of them, whilst not including transaction costs. Computational results based on clustering selection are compared to those of random techniques and show the importance of clustering in noise reduction and robust forecasting applications, in particular for enhanced index tracking.

UAV formation control design with obstacle avoidance in dynamic three-dimensional environment.

PubMed

Chang, Kai; Xia, Yuanqing; Huang, Kaoli

2016-01-01

This paper considers the artificial potential field method combined with rotational vectors for a general problem of multi-unmanned aerial vehicle (UAV) systems tracking a moving target in dynamic three-dimensional environment. An attractive potential field is generated between the leader and the target. It drives the leader to track the target based on the relative position of them. The other UAVs in the formation are controlled to follow the leader by the attractive control force. The repulsive force affects among the UAVs to avoid collisions and distribute the UAVs evenly on the spherical surface whose center is the leader-UAV. Specific orders or positions of the UAVs are not required. The trajectories of avoidance obstacle can be obtained through two kinds of potential field with rotation vectors. Every UAV can choose the optimal trajectory to avoid the obstacle and reconfigure the formation after passing the obstacle. Simulations study on UAV are presented to demonstrate the effectiveness of proposed method.

Quadcopter Path Following Control Design Using Output Feedback with Command Generator Tracker LOS Based At Square Path

NASA Astrophysics Data System (ADS)

Nugraha, A. T.; Agustinah, T.

2018-01-01

Quadcopter an unstable system, underactuated and nonlinear in quadcopter control research developments become an important focus of attention. In this study, following the path control method for position on the X and Y axis, used structure-Generator Tracker Command (CGT) is tested. Attitude control and position feedback quadcopter is compared using the optimal output. The addition of the H∞ performance optimal output feedback control is used to maintain the stability and robustness of quadcopter. Iterative numerical techniques Linear Matrix Inequality (LMI) is used to find the gain controller. The following path control problems is solved using the method of LQ regulators with output feedback. Simulations show that the control system can follow the paths that have been defined in the form of a reference signal square shape. The result of the simulation suggest that the method which used can bring the yaw angle at the expected value algorithm. Quadcopter can do automatically following path with cross track error mean X=0.5 m and Y=0.2 m.

Performance Assessment of Model-Based Optimal Feedforward and Feedback Current Profile Control in NSTX-U using the TRANSP Code

NASA Astrophysics Data System (ADS)

Ilhan, Z.; Wehner, W. P.; Schuster, E.; Boyer, M. D.; Gates, D. A.; Gerhardt, S.; Menard, J.

2015-11-01

Active control of the toroidal current density profile is crucial to achieve and maintain high-performance, MHD-stable plasma operation in NSTX-U. A first-principles-driven, control-oriented model describing the temporal evolution of the current profile has been proposed earlier by combining the magnetic diffusion equation with empirical correlations obtained at NSTX-U for the electron density, electron temperature, and non-inductive current drives. A feedforward + feedback control scheme for the requlation of the current profile is constructed by embedding the proposed nonlinear, physics-based model into the control design process. Firstly, nonlinear optimization techniques are used to design feedforward actuator trajectories that steer the plasma to a desired operating state with the objective of supporting the traditional trial-and-error experimental process of advanced scenario planning. Secondly, a feedback control algorithm to track a desired current profile evolution is developed with the goal of adding robustness to the overall control scheme. The effectiveness of the combined feedforward + feedback control algorithm for current profile regulation is tested in predictive simulations carried out in TRANSP. Supported by PPPL.

Strategic Adaptation to Task Characteristics, Incentives, and Individual Differences in Dual-Tasking

PubMed Central

Janssen, Christian P.; Brumby, Duncan P.

2015-01-01

We investigate how good people are at multitasking by comparing behavior to a prediction of the optimal strategy for dividing attention between two concurrent tasks. In our experiment, 24 participants had to interleave entering digits on a keyboard with controlling a randomly moving cursor with a joystick. The difficulty of the tracking task was systematically varied as a within-subjects factor. Participants were also exposed to different explicit reward functions that varied the relative importance of the tracking task relative to the typing task (between-subjects). Results demonstrate that these changes in task characteristics and monetary incentives, together with individual differences in typing ability, influenced how participants choose to interleave tasks. This change in strategy then affected their performance on each task. A computational cognitive model was used to predict performance for a wide set of alternative strategies for how participants might have possibly interleaved tasks. This allowed for predictions of optimal performance to be derived, given the constraints placed on performance by the task and cognition. A comparison of human behavior with the predicted optimal strategy shows that participants behaved near optimally. Our findings have implications for the design and evaluation of technology for multitasking situations, as consideration should be given to the characteristics of the task, but also to how different users might use technology depending on their individual characteristics and their priorities. PMID:26161851

Modeling and Development of INS-Aided PLLs in a GNSS/INS Deeply-Coupled Hardware Prototype for Dynamic Applications

PubMed Central

Zhang, Tisheng; Niu, Xiaoji; Ban, Yalong; Zhang, Hongping; Shi, Chuang; Liu, Jingnan

2015-01-01

A GNSS/INS deeply-coupled system can improve the satellite signals tracking performance by INS aiding tracking loops under dynamics. However, there was no literature available on the complete modeling of the INS branch in the INS-aided tracking loop, which caused the lack of a theoretical tool to guide the selections of inertial sensors, parameter optimization and quantitative analysis of INS-aided PLLs. This paper makes an effort on the INS branch in modeling and parameter optimization of phase-locked loops (PLLs) based on the scalar-based GNSS/INS deeply-coupled system. It establishes the transfer function between all known error sources and the PLL tracking error, which can be used to quantitatively evaluate the candidate inertial measurement unit (IMU) affecting the carrier phase tracking error. Based on that, a steady-state error model is proposed to design INS-aided PLLs and to analyze their tracking performance. Based on the modeling and error analysis, an integrated deeply-coupled hardware prototype is developed, with the optimization of the aiding information. Finally, the performance of the INS-aided PLLs designed based on the proposed steady-state error model is evaluated through the simulation and road tests of the hardware prototype. PMID:25569751

TH-AB-202-09: Direct-Aperture Optimization for Combined MV+kV Dose Planning in Fluoroscopic Real-Time Tumor-Tracking Radiation Therapy

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

Liu, X; Belcher, AH; Grelewicz, Z

Purpose: Real-time kV fluoroscopic tumor tracking has the benefit of direct tumor position monitoring. However, there is clinical concern over the excess kV imaging dose cost to the patient when imaging in continuous fluoroscopic mode. This work addresses this specific issue by proposing a combined MV+kV direct-aperture optimization (DAO) approach to integrate the kV imaging beam into a treatment planning such that the kV radiation is considered as a contributor to the overall dose delivery. Methods: The combined MV+kV DAO approach includes three algorithms. First, a projected Quasi-Newton algorithm (L-BFGS) is used to find optimized fluence with MV+kV dose formore » the best possible dose distribution. Then, Engel’s algorithm is applied to optimize the total number of monitor units and heuristically optimize the number of apertures. Finally, an aperture shape optimization (ASO) algorithm is applied to locally optimize the leaf positions of MLC. Results: Compared to conventional DAO MV plans with continuous kV fluoroscopic tracking, combined MV+kV DAO plan leads to a reduction in the total number of MV monitor units due to inclusion of kV dose as part of the PTV, and was also found to reduce the mean and maximum doses on the organs at risk (OAR). Compared to conventional DAO MV plan without kV tracking, the OAR dose in the combined MV+kV DAO plan was only slightly higher. DVH curves show that combined MV+kV DAO plan provided about the same PTV coverage as that in the conventional DAO plans without kV imaging. Conclusion: We report a combined MV+kV DAO approach that allows real time kV imager tumor tracking with only a trivial increasing on the OAR doses while providing the same coverage to PTV. The approach is suitable for clinic implementation.« less

Real time PI-backstepping induction machine drive with efficiency optimization.

PubMed

Farhani, Fethi; Ben Regaya, Chiheb; Zaafouri, Abderrahmen; Chaari, Abdelkader

2017-09-01

This paper describes a robust and efficient speed control of a three phase induction machine (IM) subjected to load disturbances. First, a Multiple-Input Multiple-Output (MIMO) PI-Backstepping controller is proposed for a robust and highly accurate tracking of the mechanical speed and rotor flux. Asymptotic stability of the control scheme is proven by Lyapunov Stability Theory. Second, an active online optimization algorithm is used to optimize the efficiency of the drive system. The efficiency improvement approach consists of adjusting the rotor flux with respect to the load torque in order to minimize total losses in the IM. A dSPACE DS1104 R&D board is used to implement the proposed solution. The experimental results released on 3kW squirrel cage IM, show that the reference speed as well as the rotor flux are rapidly achieved with a fast transient response and without overshoot. A good load disturbances rejection response and IM parameters variation are fairly handled. The improvement of drive system efficiency reaches up to 180% at light load. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

SIFT-based dense pixel tracking on 0.35 T cine-MR images acquired during image-guided radiation therapy with application to gating optimization

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

Mazur, Thomas R., E-mail: tmazur@radonc.wustl.edu, E-mail: hli@radonc.wustl.edu; Fischer-Valuck, Benjamin W.; Wang, Yuhe

Purpose: To first demonstrate the viability of applying an image processing technique for tracking regions on low-contrast cine-MR images acquired during image-guided radiation therapy, and then outline a scheme that uses tracking data for optimizing gating results in a patient-specific manner. Methods: A first-generation MR-IGRT system—treating patients since January 2014—integrates a 0.35 T MR scanner into an annular gantry consisting of three independent Co-60 sources. Obtaining adequate frame rates for capturing relevant patient motion across large fields-of-view currently requires coarse in-plane spatial resolution. This study initially (1) investigate the feasibility of rapidly tracking dense pixel correspondences across single, sagittal planemore » images (with both moderate signal-to-noise and spatial resolution) using a matching objective for highly descriptive vectors called scale-invariant feature transform (SIFT) descriptors associated to all pixels that describe intensity gradients in local regions around each pixel. To more accurately track features, (2) harmonic analysis was then applied to all pixel trajectories within a region-of-interest across a short training period. In particular, the procedure adjusts the motion of outlying trajectories whose relative spectral power within a frequency bandwidth consistent with respiration (or another form of periodic motion) does not exceed a threshold value that is manually specified following the training period. To evaluate the tracking reliability after applying this correction, conventional metrics—including Dice similarity coefficients (DSCs), mean tracking errors (MTEs), and Hausdorff distances (HD)—were used to compare target segmentations obtained via tracking to manually delineated segmentations. Upon confirming the viability of this descriptor-based procedure for reliably tracking features, the study (3) outlines a scheme for optimizing gating parameters—including relative target position and a tolerable margin about this position—derived from a probability density function that is constructed using tracking results obtained just prior to treatment. Results: The feasibility of applying the matching objective for SIFT descriptors toward pixel-by-pixel tracking on cine-MR acquisitions was first retrospectively demonstrated for 19 treatments (spanning various sites). Both with and without motion correction based on harmonic analysis, sub-pixel MTEs were obtained. A mean DSC value spanning all patients of 0.916 ± 0.001 was obtained without motion correction, with DSC values exceeding 0.85 for all patients considered. While most patients show accurate tracking without motion correction, harmonic analysis does yield substantial gain in accuracy (defined using HDs) for three particularly challenging subjects. An application of tracking toward a gating optimization procedure was then demonstrated that should allow a physician to balance beam-on time and tissue sparing in a patient-specific manner by tuning several intuitive parameters. Conclusions: Tracking results show high fidelity in assessing intrafractional motion observed on cine-MR acquisitions. Incorporating harmonic analysis during a training period improves the robustness of the tracking for challenging targets. The concomitant gating optimization procedure should allow for physicians to quantitatively assess gating effectiveness quickly just prior to treatment in a patient-specific manner.« less

On the Efficiency Costs of De-Tracking Secondary Schools in Europe

ERIC Educational Resources Information Center

Brunello, Giorgio; Rocco, Lorenzo; Ariga, Kenn; Iwahashi, Roki

2012-01-01

Many European countries have delayed the time when school tracking starts in order to pursue equality of opportunity. What are the efficiency costs of de-tracking secondary schools? This paper builds a stylized model of the optimal time of tracking, estimates the relevant parameters using micro data for 11 European countries and computes the…

Performance optimization of a photovoltaic chain conversion by the PWM control

NASA Astrophysics Data System (ADS)

Rezoug, M. R.; Chenni, R.

2017-02-01

The interest of the research technique of maximum power point tracking, exposed by this article, lays in the fact of work instantly on the real characteristic of the photovoltaic module. This work is based on instantaneous measurements of its terminals' current & voltage as well as the exploitation of the characteristic "Power - Duty Cycle" to define rapidly the Duty cycle in which power reaches its maximum value. To ensure instantaneous tracking of the point of maximum power, we use "DC/DC Converter" based on "Pulse Wave Modulation's (PWM) Command" controlled by an algorithm implanted in a microcontroller's memory. This algorithm responds to the quick changes in climate (sunlight and temperature). To identify the control parameters "VPV & IPV" at any change in operating conditions, sensors are projected. this algorithm applied to the Duty cycle of the static converter enables the control of power supplied by the photovoltaic generator thanks to oscillatory movement around the MPP. Our article highlights the importance of this technique which lays in its simplicity and performance in changing climatic conditions. This efficiency is confirmed by experimental tests and this technique will improve its predecessors.

Trajectory Tracking of a Planer Parallel Manipulator by Using Computed Force Control Method

NASA Astrophysics Data System (ADS)

Bayram, Atilla

2017-03-01

Despite small workspace, parallel manipulators have some advantages over their serial counterparts in terms of higher speed, acceleration, rigidity, accuracy, manufacturing cost and payload. Accordingly, this type of manipulators can be used in many applications such as in high-speed machine tools, tuning machine for feeding, sensitive cutting, assembly and packaging. This paper presents a special type of planar parallel manipulator with three degrees of freedom. It is constructed as a variable geometry truss generally known planar Stewart platform. The reachable and orientation workspaces are obtained for this manipulator. The inverse kinematic analysis is solved for the trajectory tracking according to the redundancy and joint limit avoidance. Then, the dynamics model of the manipulator is established by using Virtual Work method. The simulations are performed to follow the given planar trajectories by using the dynamic equations of the variable geometry truss manipulator and computed force control method. In computed force control method, the feedback gain matrices for PD control are tuned with fixed matrices by trail end error and variable ones by means of optimization with genetic algorithm.

Study of Flexible Load Dispatch to Improve the Capacity of Wind Power Absorption

NASA Astrophysics Data System (ADS)

Yunlei, Yang; Shifeng, Zhang; Xiao, Chang; Da, Lei; Min, Zhang; Jinhao, Wang; Shengwen, Li; Huipeng, Li

2017-05-01

The dispatch method which track the trend of load demand by arranging the generation scheme of controllable hydro or thermal units faces great difficulties and challenges. With the increase of renewable energy sources such as wind power and photovoltaic power introduced to grid, system has to arrange much more spinning reserve units to compensate the unbalanced power. How to exploit the peak-shaving potential of flexible load which can be shifted with time or storage energy has become many scholars’ research direction. However, the modelling of different kinds of load and control strategy is considerably difficult, this paper choose the Air Conditioner with compressor which can storage energy in fact to study. The equivalent thermal parameters of Air Conditioner has been established. And with the use of “loop control” strategies, we can predict the regulated power of Air Conditioner. Then we established the Gen-Load optimal scheduling model including flexible load based on traditional optimal scheduling model. At last, an improved IEEE-30 case is used to verify. The result of simulation shows that flexible load can fast-track renewable power changes. More than that, with flexible load and reasonable incentive method to consumers, the operating cost of the system can be greatly cut down.

PSO Based PI Controller Design for a Solar Charger System

PubMed Central

Yau, Her-Terng; Lin, Chih-Jer; Liang, Qin-Cheng

2013-01-01

Due to global energy crisis and severe environmental pollution, the photovoltaic (PV) system has become one of the most important renewable energy sources. Many previous studies on solar charger integrated system only focus on load charge control or switching Maximum Power Point Tracking (MPPT) and charge control modes. This study used two-stage system, which allows the overall portable solar energy charging system to implement MPPT and optimal charge control of Li-ion battery simultaneously. First, this study designs a DC/DC boost converter of solar power generation, which uses variable step size incremental conductance method (VSINC) to enable the solar cell to track the maximum power point at any time. The voltage was exported from the DC/DC boost converter to the DC/DC buck converter, so that the voltage dropped to proper voltage for charging the battery. The charging system uses constant current/constant voltage (CC/CV) method to charge the lithium battery. In order to obtain the optimum PI charge controller parameters, this study used intelligent algorithm to determine the optimum parameters. According to the simulation and experimental results, the control parameters resulted from PSO have better performance than genetic algorithms (GAs). PMID:23766713

PSO based PI controller design for a solar charger system.

PubMed

Yau, Her-Terng; Lin, Chih-Jer; Liang, Qin-Cheng

2013-01-01

Due to global energy crisis and severe environmental pollution, the photovoltaic (PV) system has become one of the most important renewable energy sources. Many previous studies on solar charger integrated system only focus on load charge control or switching Maximum Power Point Tracking (MPPT) and charge control modes. This study used two-stage system, which allows the overall portable solar energy charging system to implement MPPT and optimal charge control of Li-ion battery simultaneously. First, this study designs a DC/DC boost converter of solar power generation, which uses variable step size incremental conductance method (VSINC) to enable the solar cell to track the maximum power point at any time. The voltage was exported from the DC/DC boost converter to the DC/DC buck converter, so that the voltage dropped to proper voltage for charging the battery. The charging system uses constant current/constant voltage (CC/CV) method to charge the lithium battery. In order to obtain the optimum PI charge controller parameters, this study used intelligent algorithm to determine the optimum parameters. According to the simulation and experimental results, the control parameters resulted from PSO have better performance than genetic algorithms (GAs).

Point-and-stare operation and high-speed image acquisition in real-time hyperspectral imaging

NASA Astrophysics Data System (ADS)

Driver, Richard D.; Bannon, David P.; Ciccone, Domenic; Hill, Sam L.

2010-04-01

The design and optical performance of a small-footprint, low-power, turnkey, Point-And-Stare hyperspectral analyzer, capable of fully automated field deployment in remote and harsh environments, is described. The unit is packaged for outdoor operation in an IP56 protected air-conditioned enclosure and includes a mechanically ruggedized fully reflective, aberration-corrected hyperspectral VNIR (400-1000 nm) spectrometer with a board-level detector optimized for point and stare operation, an on-board computer capable of full system data-acquisition and control, and a fully functioning internal hyperspectral calibration system for in-situ system spectral calibration and verification. Performance data on the unit under extremes of real-time survey operation and high spatial and high spectral resolution will be discussed. Hyperspectral acquisition including full parameter tracking is achieved by the addition of a fiber-optic based downwelling spectral channel for solar illumination tracking during hyperspectral acquisition and the use of other sensors for spatial and directional tracking to pinpoint view location. The system is mounted on a Pan-And-Tilt device, automatically controlled from the analyzer's on-board computer, making the HyperspecTM particularly adaptable for base security, border protection and remote deployments. A hyperspectral macro library has been developed to control hyperspectral image acquisition, system calibration and scene location control. The software allows the system to be operated in a fully automatic mode or under direct operator control through a GigE interface.

Aerodynamic load control strategy of wind turbine in microgrid

NASA Astrophysics Data System (ADS)

Wang, Xiangming; Liu, Heshun; Chen, Yanfei

2017-12-01

A control strategy is proposed in the paper to optimize the aerodynamic load of the wind turbine in micro-grid. In grid-connection mode, the wind turbine adopts a new individual variable pitch control strategy. The pitch angle of the blade is rapidly given by the controller, and the pitch angle of each blade is fine tuned by the weight coefficient distributor. In islanding mode, according to the requirements of energy storage system, a given power tracking control method based on fuzzy PID control is proposed. Simulation result shows that this control strategy can effectively improve the axial aerodynamic load of the blade under rated wind speed in grid-connection mode, and ensure the smooth operation of the micro-grid in islanding mode.

Image Edge Tracking via Ant Colony Optimization

NASA Astrophysics Data System (ADS)

Li, Ruowei; Wu, Hongkun; Liu, Shilong; Rahman, M. A.; Liu, Sanchi; Kwok, Ngai Ming

2018-04-01

A good edge plot should use continuous thin lines to describe the complete contour of the captured object. However, the detection of weak edges is a challenging task because of the associated low pixel intensities. Ant Colony Optimization (ACO) has been employed by many researchers to address this problem. The algorithm is a meta-heuristic method developed by mimicking the natural behaviour of ants. It uses iterative searches to find the optimal solution that cannot be found via traditional optimization approaches. In this work, ACO is employed to track and repair broken edges obtained via conventional Sobel edge detector to produced a result with more connected edges.

Impact of random pointing and tracking errors on the design of coherent and incoherent optical intersatellite communication links

NASA Technical Reports Server (NTRS)

Chen, Chien-Chung; Gardner, Chester S.

1989-01-01

Given the rms transmitter pointing error and the desired probability of bit error (PBE), it can be shown that an optimal transmitter antenna gain exists which minimizes the required transmitter power. Given the rms local oscillator tracking error, an optimum receiver antenna gain can be found which optimizes the receiver performance. The impact of pointing and tracking errors on the design of direct-detection pulse-position modulation (PPM) and heterodyne noncoherent frequency-shift keying (NCFSK) systems are then analyzed in terms of constraints on the antenna size and the power penalty incurred. It is shown that in the limit of large spatial tracking errors, the advantage in receiver sensitivity for the heterodyne system is quickly offset by the smaller antenna gain and the higher power penalty due to tracking errors. In contrast, for systems with small spatial tracking errors, the heterodyne system is superior because of the higher receiver sensitivity.

Autonomous Guidance of Agile Small-scale Rotorcraft

NASA Technical Reports Server (NTRS)

Mettler, Bernard; Feron, Eric

2004-01-01

This report describes a guidance system for agile vehicles based on a hybrid closed-loop model of the vehicle dynamics. The hybrid model represents the vehicle dynamics through a combination of linear-time-invariant control modes and pre-programmed, finite-duration maneuvers. This particular hybrid structure can be realized through a control system that combines trim controllers and a maneuvering control logic. The former enable precise trajectory tracking, and the latter enables trajectories at the edge of the vehicle capabilities. The closed-loop model is much simpler than the full vehicle equations of motion, yet it can capture a broad range of dynamic behaviors. It also supports a consistent link between the physical layer and the decision-making layer. The trajectory generation was formulated as an optimization problem using mixed-integer-linear-programming. The optimization is solved in a receding horizon fashion. Several techniques to improve the computational tractability were investigate. Simulation experiments using NASA Ames 'R-50 model show that this approach fully exploits the vehicle's agility.

Commande optimale minimisant la consommation d'energie d'un drone utilise comme relai de communication

NASA Astrophysics Data System (ADS)

Mechirgui, Monia

The purpose of this project is to implement an optimal control regulator, particularly the linear quadratic regulator in order to control the position of an unmanned aerial vehicle known as a quadrotor. This type of UAV has a symmetrical and simple structure. Thus, its control is relatively easy compared to conventional helicopters. Optimal control can be proven to be an ideal controller to reconcile between the tracking performance and energy consumption. In practice, the linearity requirements are not met, but some elaborations of the linear quadratic regulator have been used in many nonlinear applications with good results. The linear quadratic controller used in this thesis is presented in two forms: simple and adapted to the state of charge of the battery. Based on the traditional structure of the linear quadratic regulator, we introduced a new criterion which relies on the state of charge of the battery, in order to optimize energy consumption. This command is intended to be used to monitor and maintain the desired trajectory during several maneuvers while minimizing energy consumption. Both simple and adapted, linear quadratic controller are implemented in Simulink in discrete time. The model simulates the dynamics and control of a quadrotor. Performance and stability of the system are analyzed with several tests, from the simply hover to the complex trajectories in closed loop.

Dynamic ADMM for Real-Time Optimal Power Flow: Preprint

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

Dall-Anese, Emiliano; Zhang, Yijian; Hong, Mingyi

This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearizations of the AC power flow equations, and it leverages the so-called alternating direction method of multipliers (ADMM). The steps of the ADMM, however, are suitably modified to accommodate appropriate measurements from the distribution network and the DERs. With the aid of these measurements, the resultant algorithm can enforce given operational constraints in spite of inaccuracies in the representation ofmore » the AC power flows, and it avoids ubiquitous metering to gather the state of non-controllable resources. Optimality and convergence of the propose algorithm are established in terms of tracking of the solution of a convex surrogate of the AC optimal power flow problem.« less

Towards Real-Time Maneuver Detection: Automatic State and Dynamics Estimation with the Adaptive Optimal Control Based Estimator

NASA Astrophysics Data System (ADS)

Lubey, D.; Scheeres, D.

Tracking objects in Earth orbit is fraught with complications. This is due to the large population of orbiting spacecraft and debris that continues to grow, passive (i.e. no direct communication) and data-sparse observations, and the presence of maneuvers and dynamics mismodeling. Accurate orbit determination in this environment requires an algorithm to capture both a system's state and its state dynamics in order to account for mismodelings. Previous studies by the authors yielded an algorithm called the Optimal Control Based Estimator (OCBE) - an algorithm that simultaneously estimates a system's state and optimal control policies that represent dynamic mismodeling in the system for an arbitrary orbit-observer setup. The stochastic properties of these estimated controls are then used to determine the presence of mismodelings (maneuver detection), as well as characterize and reconstruct the mismodelings. The purpose of this paper is to develop the OCBE into an accurate real-time orbit tracking and maneuver detection algorithm by automating the algorithm and removing its linear assumptions. This results in a nonlinear adaptive estimator. In its original form the OCBE had a parameter called the assumed dynamic uncertainty, which is selected by the user with each new measurement to reflect the level of dynamic mismodeling in the system. This human-in-the-loop approach precludes real-time application to orbit tracking problems due to their complexity. This paper focuses on the Adaptive OCBE, a version of the estimator where the assumed dynamic uncertainty is chosen automatically with each new measurement using maneuver detection results to ensure that state uncertainties are properly adjusted to account for all dynamic mismodelings. The paper also focuses on a nonlinear implementation of the estimator. Originally, the OCBE was derived from a nonlinear cost function then linearized about a nominal trajectory, which is assumed to be ballistic (i.e. the nominal optimal control policy is zero for all times). In this paper, we relax this assumption on the nominal trajectory in order to allow for controlled nominal trajectories. This allows the estimator to be iterated to obtain a more accurate nonlinear solution for both the state and control estimates. Beyond these developments to the estimator, this paper also introduces a modified distance metric for maneuver detection. The original metric used in the OCBE only accounted for the estimated control and its uncertainty. This new metric accounts for measurement deviation and a priori state deviations, such that it accounts for all three major forms of uncertainty in orbit determination. This allows the user to understand the contributions of each source of uncertainty toward the total system mismodeling so that the user can properly account for them. Together these developments create an accurate orbit determination algorithm that is automated, robust to mismodeling, and capable of detecting and reconstructing the presence of mismodeling. These qualities make this algorithm a good foundation from which to approach the problem of real-time maneuver detection and reconstruction for Space Situational Awareness applications. This is further strengthened by the algorithm's general formulation that allows it to be applied to problems with an arbitrary target and observer.

Controllers, observers, and applications thereof

NASA Technical Reports Server (NTRS)

Gao, Zhiqiang (Inventor); Zhou, Wankun (Inventor); Miklosovic, Robert (Inventor); Radke, Aaron (Inventor); Zheng, Qing (Inventor)

2011-01-01

Controller scaling and parameterization are described. Techniques that can be improved by employing the scaling and parameterization include, but are not limited to, controller design, tuning and optimization. The scaling and parameterization methods described here apply to transfer function based controllers, including PID controllers. The parameterization methods also apply to state feedback and state observer based controllers, as well as linear active disturbance rejection (ADRC) controllers. Parameterization simplifies the use of ADRC. A discrete extended state observer (DESO) and a generalized extended state observer (GESO) are described. They improve the performance of the ESO and therefore ADRC. A tracking control algorithm is also described that improves the performance of the ADRC controller. A general algorithm is described for applying ADRC to multi-input multi-output systems. Several specific applications of the control systems and processes are disclosed.

Development of an integrated automated retinal surgical laser system.

PubMed

Barrett, S F; Wright, C H; Oberg, E D; Rockwell, B A; Cain, C; Rylander, H G; Welch, A J

1996-01-01

Researchers at the University of Texas and the USAF Academy have worked toward the development of a retinal robotic laser system. The overall goal of this ongoing project is to precisely place and control the depth of laser lesions for the treatment of various retinal diseases such as diabetic retinopathy and retinal tears. Separate low speed prototype subsystems have been developed to control lesion depth using lesion reflectance feedback parameters and lesion placement using retinal vessels as tracking landmarks. Both subsystems have been successfully demonstrated in vivo on pigmented rabbits using an argon continuous wave laser. Preliminary testing on rhesus primate subjects have been accomplished with the CW argon laser and also the ultrashort pulse laser. Recent efforts have concentrated on combining the two subsystems into a single prototype capable of simultaneously controlling both lesion depth and placement. We have designated this combined system CALOSOS for Computer Aided Laser Optics System for Ophthalmic Surgery. Several interesting areas of study have developed in integrating the two subsystems: 1) "doughnut" shaped lesions that occur under certain combinations of laser power, spot size, and irradiation time complicating measurements of central lesion reflectance, 2) the optimal retinal field of view (FOV) to achieve both tracking and lesion parameter control, and 3) development of a hybrid analog/digital tracker using confocal reflectometry to achieve retinal tracking speeds of up to 100 dgs. This presentation will discuss these design issues of this clinically significant prototype system. Details of the hybrid prototype system are provided in "Hybrid Eye Tracking for Computer-Aided Retinal Surgery" at this conference. The paper will close with remaining technical hurdles to clear prior to testing the full-up clinical prototype system.

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.

Design and Synthesis of Gold Nanoparticle Contrast Agents for Atherosclerosis Imaging with Computed tomography

NASA Astrophysics Data System (ADS)

Chhour, Peter

Cell tracking offers the opportunity to study migration and localization of cells in vivo, allowing investigations of disease mechanisms and drug efficacy. Monocytes play a key role in the progression of atherosclerotic plaques in the coronary arteries. While x-ray computed tomography (CT) is commonly used to clinically assess coronary plaque burden, cell tracking with CT is mostly unexplored. The establishment of monocyte cell tracking tools would allow for the direct investigation of gene and drug therapies aimed at monocyte recruitment in atherosclerosis. In this thesis, we present the design and optimization of gold nanoparticles as CT contrast agents for cell tracking of monocyte recruitment to atherosclerotic plaques. Gold nanoparticle polymer constructs with controlled localization are evaluated as potential monocyte labels. However, cytotoxic effects were observed at concentrations necessary for cell labeling. Therefore, variations in physical and chemical properties of gold nanoparticles were explored as cell labels for monocyte tracking. Each formulation was screened for effects on cell viability, cell function and uptake in monocytes. The uptake in monocytes revealed a complex relationship with nanoparticle size behavior dependent on the surface ligand used. This led to the selection of an optimal size and coating for monocyte labeling, 11-mercaptoundecanoic acid coated 15 nm gold nanoparticles. This formulation was further investigated for cell viability, function, and uptake with isolated primary monocytes. Moreover, primary monocytes labeled with this formulation were used to observe monocyte recruitment in atherosclerotic mice. Mice with early atherosclerotic plaques received intravenously injections of gold labeled monocytes and their recruitment to plaques were observed over 5 days with CT. Increases in CT attenuation in the plaque and transmission electron microscopy of plaque sections indicated the presence of gold labeled monocytes in the plaque. These results demonstrate the feasibility of using CT to track ex-vivo labeled cells non-invasively with CT and could further be used to investigate drugs aimed at modulating monocyte recruitment in the treatment of atherosclerosis. This work expands the applications of cell tracking and may lead to additional uses in other diseases.

Aerial robot intelligent control method based on back-stepping

NASA Astrophysics Data System (ADS)

Zhou, Jian; Xue, Qian

2018-05-01

The aerial robot is characterized as strong nonlinearity, high coupling and parameter uncertainty, a self-adaptive back-stepping control method based on neural network is proposed in this paper. The uncertain part of the aerial robot model is compensated online by the neural network of Cerebellum Model Articulation Controller and robust control items are designed to overcome the uncertainty error of the system during online learning. At the same time, particle swarm algorithm is used to optimize and fix parameters so as to improve the dynamic performance, and control law is obtained by the recursion of back-stepping regression. Simulation results show that the designed control law has desired attitude tracking performance and good robustness in case of uncertainties and large errors in the model parameters.

An Expert System And Simulation Approach For Sensor Management & Control In A Distributed Surveillance Network

NASA Astrophysics Data System (ADS)

Leon, Barbara D.; Heller, Paul R.

1987-05-01

A surveillance network is a group of multiplatform sensors cooperating to improve network performance. Network control is distributed as a measure to decrease vulnerability to enemy threat. The network may contain diverse sensor types such as radar, ESM (Electronic Support Measures), IRST (Infrared search and track) and E-0 (Electro-Optical). Each platform may contain a single sensor or suite of sensors. In a surveillance network it is desirable to control sensors to make the overall system more effective. This problem has come to be known as sensor management and control (SM&C). Two major facets of network performance are surveillance and survivability. In a netted environment, surveillance can be enhanced if information from all sensors is combined and sensor operating conditions are controlled to provide a synergistic effect. In contrast, when survivability is the main concern for the network, the best operating status for all sensors would be passive or off. Of course, improving survivability tends to degrade surveillance. Hence, the objective of SM&C is to optimize surveillance and survivability of the network. Too voluminous data of various formats and the quick response time are two characteristics of this problem which make it an ideal application for Artificial Intelligence. A solution to the SM&C problem, presented as a computer simulation, will be presented in this paper. The simulation is a hybrid production written in LISP and FORTRAN. It combines the latest conventional computer programming methods with Artificial Intelligence techniques to produce a flexible state-of-the-art tool to evaluate network performance. The event-driven simulation contains environment models coupled with an expert system. These environment models include sensor (track-while-scan and agile beam) and target models, local tracking, and system tracking. These models are used to generate the environment for the sensor management and control expert system. The expert system, driven by a forward chaining inference engine, makes decisions based on the global database. The global database contains current track and sensor information supplied by the simulation. At present, the rule base emphasizes the surveillance features with rules grouped into three main categories: maintenance and enhancing track on prioritized targets; filling coverage holes and countering jamming; and evaluating sensor status. The paper will describe the architecture used for the expert system and the reasons for selecting the chosen methods. The SM&C simulation produces a graphical representation of sensors and their associated tracks such that the benefits of the sensor management and control expert system are evident. Jammer locations are also part of the display. The paper will describe results from several scenarios that best illustrate the sensor management and control concepts.

Multi-Window Controllers for Autonomous Space Systems

NASA Technical Reports Server (NTRS)

Lurie, B, J.; Hadaegh, F. Y.

1997-01-01

Multi-window controllers select between elementary linear controllers using nonlinear windows based on the amplitude and frequency content of the feedback error. The controllers are relatively simple to implement and perform much better than linear controllers. The commanders for such controllers only order the destination point and are freed from generating the command time-profiles. The robotic missions rely heavily on the tasks of acquisition and tracking. For autonomous and optimal control of the spacecraft, the control bandwidth must be larger while the feedback can (and, therefore, must) be reduced.. Combining linear compensators via multi-window nonlinear summer guarantees minimum phase character of the combined transfer function. It is shown that the solution may require using several parallel branches and windows. Several examples of multi-window nonlinear controller applications are presented.

Nonlinear robust controller design for multi-robot systems with unknown payloads

NASA Technical Reports Server (NTRS)

Song, Y. D.; Anderson, J. N.; Homaifar, A.; Lai, H. Y.

1992-01-01

This work is concerned with the control problem of a multi-robot system handling a payload with unknown mass properties. Force constraints at the grasp points are considered. Robust control schemes are proposed that cope with the model uncertainty and achieve asymptotic path tracking. To deal with the force constraints, a strategy for optimally sharing the task is suggested. This strategy basically consists of two steps. The first detects the robots that need help and the second arranges that help. It is shown that the overall system is not only robust to uncertain payload parameters, but also satisfies the force constraints.

Belavkin filter for mixture of quadrature and photon counting process with some control techniques

NASA Astrophysics Data System (ADS)

Garg, Naman; Parthasarathy, Harish; Upadhyay, D. K.

2018-03-01

The Belavkin filter for the H-P Schrödinger equation is derived when the measurement process consists of a mixture of quantum Brownian motions and conservation/Poisson process. Higher-order powers of the measurement noise differentials appear in the Belavkin dynamics. For simulation, we use a second-order truncation. Control of the Belavkin filtered state by infinitesimal unitary operators is achieved in order to reduce the noise effects in the Belavkin filter equation. This is carried out along the lines of Luc Bouten. Various optimization criteria for control are described like state tracking and Lindblad noise removal.

Research of MPPT for photovoltaic generation based on two-dimensional cloud model

NASA Astrophysics Data System (ADS)

Liu, Shuping; Fan, Wei

2013-03-01

The cloud model is a mathematical representation to fuzziness and randomness in linguistic concepts. It represents a qualitative concept with expected value Ex, entropy En and hyper entropy He, and integrates the fuzziness and randomness of a linguistic concept in a unified way. This model is a new method for transformation between qualitative and quantitative in the knowledge. This paper is introduced MPPT (maximum power point tracking, MPPT) controller based two- dimensional cloud model through analysis of auto-optimization MPPT control of photovoltaic power system and combining theory of cloud model. Simulation result shows that the cloud controller is simple and easy, directly perceived through the senses, and has strong robustness, better control performance.

Head-target tracking control of well drilling

NASA Astrophysics Data System (ADS)

Agzamov, Z. V.

2018-05-01

The method of directional drilling trajectory control for oil and gas wells using predictive models is considered in the paper. The developed method does not apply optimization and therefore there is no need for the high-performance computing. Nevertheless, it allows following the well-plan with high precision taking into account process input saturation. Controller output is calculated both from the present target reference point of the well-plan and from well trajectory prediction with using the analytical model. This method allows following a well-plan not only on angular, but also on the Cartesian coordinates. Simulation of the control system has confirmed the high precision and operation performance with a wide range of random disturbance action.

A Review on Sensor, Signal, and Information Processing Algorithms (PREPRINT)

DTIC Science & Technology

2010-01-01

processing [214], ambi- guity surface averaging [215], optimum uncertain field tracking, and optimal minimum variance track - before - detect [216]. In [217, 218...2) (2001) 739–746. [216] S. L. Tantum, L. W. Nolte, J. L. Krolik, K. Harmanci, The performance of matched-field track - before - detect methods using

Object tracking based on harmony search: comparative study

NASA Astrophysics Data System (ADS)

Gao, Ming-Liang; He, Xiao-Hai; Luo, Dai-Sheng; Yu, Yan-Mei

2012-10-01

Visual tracking can be treated as an optimization problem. A new meta-heuristic optimal algorithm, Harmony Search (HS), was first applied to perform visual tracking by Fourie et al. As the authors point out, many subjects are still required in ongoing research. Our work is a continuation of Fourie's study, with four prominent improved variations of HS, namely Improved Harmony Search (IHS), Global-best Harmony Search (GHS), Self-adaptive Harmony Search (SHS) and Differential Harmony Search (DHS) adopted into the tracking system. Their performances are tested and analyzed on multiple challenging video sequences. Experimental results show that IHS is best, with DHS ranking second among the four improved trackers when the iteration number is small. However, the differences between all four reduced gradually, along with the increasing number of iterations.

How to optimize the economic viability of thyroid surgery in a French public hospital?

PubMed

D'Hubert, E; Proske, J-M

2010-08-01

Physicians in France have been asked to change their day-to-day medical practice to reduce overall costs. We examine ways to achieve this goal in thyroid surgery. We defined and implemented a clinical pathway to optimize the economic viability of thyroid surgery by increasing revenues and lowering expenses. An increase in revenue was achieved by decreasing patient length of stay (LOS) through the use of a fast-track rehabilitation protocol. Expenses were decreased by performing all pre-operative work-up in the out-patient setting and by decreasing costs in the operating room. For 292 consecutive patients who underwent thyroidectomy, the average LOS has been decreased over time to a mean of 2.03 days in 2008; 96% of patients were discharged on the first postoperative day. These results were primarily achieved by using a fast-track rehabilitation clinical pathway, and no increase in postoperative morbidity was noted. Operating time was decreased by 20% through the use of a second surgical assistant and hemostatic scissors but this improvement did not translate into better daily utilization of the operating room. The economic profitability of thyroid surgery is improved when mean LOS is reduced to 2 days through a fast-track protocol. Decreasing the duration of hospitalization was more effective than decreasing operative duration in controlling overall costs. Copyright © 2010 Elsevier Masson SAS. All rights reserved.

The pathway to intelligent implants: osteoblast response to nano silicon-doped hydroxyapatite patterning

PubMed Central

Munir, G.; Koller, G.; Di Silvio, L.; Edirisinghe, M. J.; Bonfield, W.; Huang, J.

2011-01-01

Bioactive hydroxyapatite (HA) with addition of silicon (Si) in the crystal structure (silicon-doped hydroxyapatite (SiHA)) has become a highly attractive alternative to conventional HA in bone replacement owing to the significant improvement in the in vivo bioactivity and osteoconductivity. Nanometre-scaled SiHA (nanoSiHA), which closely resembles the size of bone mineral, has been synthesized in this study. Thus, the silicon addition provides an extra chemical cue to stimulate and enhance bone formation for new generation coatings, and the next stage in metallic implantation design is to further improve cellular adhesion and proliferation by control of cell alignment. Topography has been found to provide a powerful set of signals for cells and form contact guidance. Using the recently developed novel technique of template-assisted electrohydrodynamic atomization (TAEA), patterns of pillars and tracks of various dimensions of nanoSiHA were achieved. Modifying the parameters of TAEA, the resolution of pattern structures was controlled, enabling the topography of a substrate to be modified accordingly. Spray time, flow rate and distance between the needle and substrate were varied to improve the pattern formation of pillars and tracks. The 15 min deposition time provided the most consistent patterned topography with a distance of 50 mm and flow rate of 4 µl min−1. A titanium substrate was patterned with pillars and tracks of varying widths, line lengths and distances under the optimized TAEA processing condition. A fast bone-like apatite formation rate was found on nanoSiHA after immersion in simulated body fluid, thus demonstrating its high in vitro bioactivity. Primary human osteoblast (HOB) cells responded to SiHA patterns by stretching of the filopodia between track and pillar, attaching to the apex of the pillar pattern and stretching between two. HOB cells responded to the track pattern by elongating along and between the track, and the length of HOB cells was proportional to the gaps between track patterns, but this relationship was not observed on the pillar patterns. The study has therefore provided an insight for future design of next generation implant surfaces to control and guide cellular responses, while TAEA patterning provides a controllable technique to provide topography to medical implants. PMID:21208969

A Class of Prediction-Correction Methods for Time-Varying Convex Optimization

NASA Astrophysics Data System (ADS)

Simonetto, Andrea; Mokhtari, Aryan; Koppel, Alec; Leus, Geert; Ribeiro, Alejandro

2016-09-01

This paper considers unconstrained convex optimization problems with time-varying objective functions. We propose algorithms with a discrete time-sampling scheme to find and track the solution trajectory based on prediction and correction steps, while sampling the problem data at a constant rate of $1/h$, where $h$ is the length of the sampling interval. The prediction step is derived by analyzing the iso-residual dynamics of the optimality conditions. The correction step adjusts for the distance between the current prediction and the optimizer at each time step, and consists either of one or multiple gradient steps or Newton steps, which respectively correspond to the gradient trajectory tracking (GTT) or Newton trajectory tracking (NTT) algorithms. Under suitable conditions, we establish that the asymptotic error incurred by both proposed methods behaves as $O(h^2)$, and in some cases as $O(h^4)$, which outperforms the state-of-the-art error bound of $O(h)$ for correction-only methods in the gradient-correction step. Moreover, when the characteristics of the objective function variation are not available, we propose approximate gradient and Newton tracking algorithms (AGT and ANT, respectively) that still attain these asymptotical error bounds. Numerical simulations demonstrate the practical utility of the proposed methods and that they improve upon existing techniques by several orders of magnitude.

Cascaded Optimization for a Persistent Data Ferrying Unmanned Aircraft

NASA Astrophysics Data System (ADS)

Carfang, Anthony

This dissertation develops and assesses a cascaded method for designing optimal periodic trajectories and link schedules for an unmanned aircraft to ferry data between stationary ground nodes. This results in a fast solution method without the need to artificially constrain system dynamics. Focusing on a fundamental ferrying problem that involves one source and one destination, but includes complex vehicle and Radio-Frequency (RF) dynamics, a cascaded structure to the system dynamics is uncovered. This structure is exploited by reformulating the nonlinear optimization problem into one that reduces the independent control to the vehicle's motion, while the link scheduling control is folded into the objective function and implemented as an optimal policy that depends on candidate motion control. This formulation is proven to maintain optimality while reducing computation time in comparison to traditional ferry optimization methods. The discrete link scheduling problem takes the form of a combinatorial optimization problem that is known to be NP-Hard. A derived necessary condition for optimality guides the development of several heuristic algorithms, specifically the Most-Data-First Algorithm and the Knapsack Adaptation. These heuristics are extended to larger ferrying scenarios, and assessed analytically and through Monte Carlo simulation, showing better throughput performance in the same order of magnitude of computation time in comparison to other common link scheduling policies. The cascaded optimization method is implemented with a novel embedded software system on a small, unmanned aircraft to validate the simulation results with field experiments. To address the sensitivity of results on trajectory tracking performance, a system that combines motion and link control with waypoint-based navigation is developed and assessed through field experiments. The data ferrying algorithms are further extended by incorporating a Gaussian process to opportunistically learn the RF environment. By continuously improving RF models, the cascaded planner can continually improve the ferrying system's overall performance.

Adaptive track scheduling to optimize concurrency and vectorization in GeantV

DOE PAGES

Apostolakis, J.; Bandieramonte, M.; Bitzes, G.; ...

2015-05-22

The GeantV project is focused on the R&D of new particle transport techniques to maximize parallelism on multiple levels, profiting from the use of both SIMD instructions and co-processors for the CPU-intensive calculations specific to this type of applications. In our approach, vectors of tracks belonging to multiple events and matching different locality criteria must be gathered and dispatched to algorithms having vector signatures. While the transport propagates tracks and changes their individual states, data locality becomes harder to maintain. The scheduling policy has to be changed to maintain efficient vectors while keeping an optimal level of concurrency. The modelmore » has complex dynamics requiring tuning the thresholds to switch between the normal regime and special modes, i.e. prioritizing events to allow flushing memory, adding new events in the transport pipeline to boost locality, dynamically adjusting the particle vector size or switching between vector to single track mode when vectorization causes only overhead. Lastly, this work requires a comprehensive study for optimizing these parameters to make the behaviour of the scheduler self-adapting, presenting here its initial results.« less

Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight

PubMed Central

Guo, Siqiu; Zhang, Tao; Song, Yulong

2018-01-01

This paper presents a particle swarm tracking algorithm with improved inertia weight based on color features. The weighted color histogram is used as the target feature to reduce the contribution of target edge pixels in the target feature, which makes the algorithm insensitive to the target non-rigid deformation, scale variation, and rotation. Meanwhile, the influence of partial obstruction on the description of target features is reduced. The particle swarm optimization algorithm can complete the multi-peak search, which can cope well with the object occlusion tracking problem. This means that the target is located precisely where the similarity function appears multi-peak. When the particle swarm optimization algorithm is applied to the object tracking, the inertia weight adjustment mechanism has some limitations. This paper presents an improved method. The concept of particle maturity is introduced to improve the inertia weight adjustment mechanism, which could adjust the inertia weight in time according to the different states of each particle in each generation. Experimental results show that our algorithm achieves state-of-the-art performance in a wide range of scenarios. PMID:29690610

Color Feature-Based Object Tracking through Particle Swarm Optimization with Improved Inertia Weight.

PubMed

Guo, Siqiu; Zhang, Tao; Song, Yulong; Qian, Feng

2018-04-23

This paper presents a particle swarm tracking algorithm with improved inertia weight based on color features. The weighted color histogram is used as the target feature to reduce the contribution of target edge pixels in the target feature, which makes the algorithm insensitive to the target non-rigid deformation, scale variation, and rotation. Meanwhile, the influence of partial obstruction on the description of target features is reduced. The particle swarm optimization algorithm can complete the multi-peak search, which can cope well with the object occlusion tracking problem. This means that the target is located precisely where the similarity function appears multi-peak. When the particle swarm optimization algorithm is applied to the object tracking, the inertia weight adjustment mechanism has some limitations. This paper presents an improved method. The concept of particle maturity is introduced to improve the inertia weight adjustment mechanism, which could adjust the inertia weight in time according to the different states of each particle in each generation. Experimental results show that our algorithm achieves state-of-the-art performance in a wide range of scenarios.

Motion-compensated speckle tracking via particle filtering

NASA Astrophysics Data System (ADS)

Liu, Lixin; Yagi, Shin-ichi; Bian, Hongyu

2015-07-01

Recently, an improved motion compensation method that uses the sum of absolute differences (SAD) has been applied to frame persistence utilized in conventional ultrasonic imaging because of its high accuracy and relative simplicity in implementation. However, high time consumption is still a significant drawback of this space-domain method. To seek for a more accelerated motion compensation method and verify if it is possible to eliminate conventional traversal correlation, motion-compensated speckle tracking between two temporally adjacent B-mode frames based on particle filtering is discussed. The optimal initial density of particles, the least number of iterations, and the optimal transition radius of the second iteration are analyzed from simulation results for the sake of evaluating the proposed method quantitatively. The speckle tracking results obtained using the optimized parameters indicate that the proposed method is capable of tracking the micromotion of speckle throughout the region of interest (ROI) that is superposed with global motion. The computational cost of the proposed method is reduced by 25% compared with that of the previous algorithm and further improvement is necessary.

Trip optimization system and method for a train

DOEpatents

Kumar, Ajith Kuttannair; Shaffer, Glenn Robert; Houpt, Paul Kenneth; Movsichoff, Bernardo Adrian; Chan, David So Keung

2017-08-15

A system for operating a train having one or more locomotive consists with each locomotive consist comprising one or more locomotives, the system including a locator element to determine a location of the train, a track characterization element to provide information about a track, a sensor for measuring an operating condition of the locomotive consist, a processor operable to receive information from the locator element, the track characterizing element, and the sensor, and an algorithm embodied within the processor having access to the information to create a trip plan that optimizes performance of the locomotive consist in accordance with one or more operational criteria for the train.

Effect of handling characteristics on minimum time cornering with torque vectoring

NASA Astrophysics Data System (ADS)

Smith, E. N.; Velenis, E.; Tavernini, D.; Cao, D.

2018-02-01

In this paper, the effect of both passive and actively-modified vehicle handling characteristics on minimum time manoeuvring for vehicles with 4-wheel torque vectoring (TV) capability is studied. First, a baseline optimal TV strategy is sought, independent of any causal control law. An optimal control problem (OCP) is initially formulated considering 4 independent wheel torque inputs, together with the steering angle rate, as the control variables. Using this formulation, the performance benefit using TV against an electric drive train with a fixed torque distribution, is demonstrated. The sensitivity of TV-controlled manoeuvre time to the passive understeer gradient of the vehicle is then studied. A second formulation of the OCP is introduced where a closed-loop TV controller is incorporated into the system dynamics of the OCP. This formulation allows the effect of actively modifying a vehicle's handling characteristic via TV on its minimum time cornering performance of the vehicle to be assessed. In particular, the effect of the target understeer gradient as the key tuning parameter of the literature-standard steady-state linear single-track model yaw rate reference is analysed.

Site Optimization Tracker: Crossley Farm Superfund Site, Hereford and Washington Townships, Berks County, Pennsylvania

EPA Pesticide Factsheets

Pilot Region-Based Optimization Program for Fund-Lead Sites in EPA Region 3. Site Optimization Tracking information for Crossley Farm Superfund Site, Hereford and Washington Townships, Berks County, Pennsylvania.

An ℋ∞ full information approach for the feedforward controller design of a large blended wing body flexible aircraft

NASA Astrophysics Data System (ADS)

Westermayer, C.; Schirrer, A.; Hemedi, M.; Kozek, M.

2013-12-01

An ℋ∞ full information feedforward design approach for longitudinal motion prefilter design of a large flexible blended wing body (BWB) aircraft is presented. An existing onset is extended such that specifications concerning command tracking, limited control energy, and manoeuvre load reduction can be addressed simultaneously. Therefore, the utilized design architecture is provided and manual tuning aspects are considered. In order to increase controller tuning efficiency, an automated tuning process based on several optimization criteria is proposed. Moreover, two design methodologies for the parameter-varying design case are investigated. The obtained controller is validated on a high-order nonlinear model, indicating the high potential of the presented approach for flexible aircraft control.

Prediction of STN-DBS Electrode Implantation Track in Parkinson's Disease by Using Local Field Potentials

PubMed Central

Telkes, Ilknur; Jimenez-Shahed, Joohi; Viswanathan, Ashwin; Abosch, Aviva; Ince, Nuri F.

2016-01-01

Optimal electrophysiological placement of the DBS electrode may lead to better long term clinical outcomes. Inter-subject anatomical variability and limitations in stereotaxic neuroimaging increase the complexity of physiological mapping performed in the operating room. Microelectrode single unit neuronal recording remains the most common intraoperative mapping technique, but requires significant expertise and is fraught by potential technical difficulties including robust measurement of the signal. In contrast, local field potentials (LFPs), owing to their oscillatory and robust nature and being more correlated with the disease symptoms, can overcome these technical issues. Therefore, we hypothesized that multiple spectral features extracted from microelectrode-recorded LFPs could be used to automate the identification of the optimal track and the STN localization. In this regard, we recorded LFPs from microelectrodes in three tracks from 22 patients during DBS electrode implantation surgery at different depths and aimed to predict the track selected by the neurosurgeon based on the interpretation of single unit recordings. A least mean square (LMS) algorithm was used to de-correlate LFPs in each track, in order to remove common activity between channels and increase their spatial specificity. Subband power in the beta band (11–32 Hz) and high frequency range (200–450 Hz) were extracted from the de-correlated LFP data and used as features. A linear discriminant analysis (LDA) method was applied both for the localization of the dorsal border of STN and the prediction of the optimal track. By fusing the information from these low and high frequency bands, the dorsal border of STN was localized with a root mean square (RMS) error of 1.22 mm. The prediction accuracy for the optimal track was 80%. Individual beta band (11–32 Hz) and the range of high frequency oscillations (200–450 Hz) provided prediction accuracies of 72 and 68% respectively. The best prediction result obtained with monopolar LFP data was 68%. These results establish the initial evidence that LFPs can be strategically fused with computational intelligence in the operating room for STN localization and the selection of the track for chronic DBS electrode implantation. PMID:27242404

Patients with rib fractures: use of incentive spirometry volumes to guide care.

PubMed

Brown, Sheree D; Walters, Madonna R

2012-01-01

Rib fractures pose significant risk to trauma patients. Effective pain control and the ability to take deep breaths are crucial for optimal recovery, and these are key elements in current clinical guidelines. These guidelines use incentive spirometry volumes along with other assessment values to guide patient care. However, despite current guidelines, nurses do not routinely document inspired respiratory volumes. This article provides trauma nurses with the rationale for documenting and tracking incentive spirometry volumes to improve outcomes for patients with rib fractures. This promotes early detection of respiratory decline and early interventions to improve pain control and pulmonary function.

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.

Use of Linear Perspective Scene Cues in a Simulated Height Regulation Task

NASA Technical Reports Server (NTRS)

Levison, W. H.; Warren, R.

1984-01-01

As part of a long-term effort to quantify the effects of visual scene cuing and non-visual motion cuing in flight simulators, an experimental study of the pilot's use of linear perspective cues in a simulated height-regulation task was conducted. Six test subjects performed a fixed-base tracking task with a visual display consisting of a simulated horizon and a perspective view of a straight, infinitely-long roadway of constant width. Experimental parameters were (1) the central angle formed by the roadway perspective and (2) the display gain. The subject controlled only the pitch/height axis; airspeed, bank angle, and lateral track were fixed in the simulation. The average RMS height error score for the least effective display configuration was about 25% greater than the score for the most effective configuration. Overall, larger and more highly significant effects were observed for the pitch and control scores. Model analysis was performed with the optimal control pilot model to characterize the pilot's use of visual scene cues, with the goal of obtaining a consistent set of independent model parameters to account for display effects.

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.

The Effects of Longitudinal Control-System Dynamics on Pilot Opinion and Response Characteristics as Determined from Flight Tests and from Ground Simulator Studies

NASA Technical Reports Server (NTRS)

Sadoff, Melvin

1958-01-01

The results of a fixed-base simulator study of the effects of variable longitudinal control-system dynamics on pilot opinion are presented and compared with flight-test data. The control-system variables considered in this investigation included stick force per g, time constant, and dead-band, or stabilizer breakout force. In general, the fairly good correlation between flight and simulator results for two pilots demonstrates the validity of fixed-base simulator studies which are designed to complement and supplement flight studies and serve as a guide in control-system preliminary design. However, in the investigation of certain problem areas (e.g., sensitive control-system configurations associated with pilot- induced oscillations in flight), fixed-base simulator results did not predict the occurrence of an instability, although the pilots noted the system was extremely sensitive and unsatisfactory. If it is desired to predict pilot-induced-oscillation tendencies, tests in moving-base simulators may be required. It was found possible to represent the human pilot by a linear pilot analog for the tracking task assumed in the present study. The criterion used to adjust the pilot analog was the root-mean-square tracking error of one of the human pilots on the fixed-base simulator. Matching the tracking error of the pilot analog to that of the human pilot gave an approximation to the variation of human-pilot behavior over a range of control-system dynamics. Results of the pilot-analog study indicated that both for optimized control-system dynamics (for poor airplane dynamics) and for a region of good airplane dynamics, the pilot response characteristics are approximately the same.

Iterative Track Fitting Using Cluster Classification in Multi Wire Proportional Chamber

NASA Astrophysics Data System (ADS)

Primor, David; Mikenberg, Giora; Etzion, Erez; Messer, Hagit

2007-10-01

This paper addresses the problem of track fitting of a charged particle in a multi wire proportional chamber (MWPC) using cathode readout strips. When a charged particle crosses a MWPC, a positive charge is induced on a cluster of adjacent strips. In the presence of high radiation background, the cluster charge measurements may be contaminated due to background particles, leading to less accurate hit position estimation. The least squares method for track fitting assumes the same position error distribution for all hits and thus loses its optimal properties on contaminated data. For this reason, a new robust algorithm is proposed. The algorithm first uses the known spatial charge distribution caused by a single charged particle over the strips, and classifies the clusters into ldquocleanrdquo and ldquodirtyrdquo clusters. Then, using the classification results, it performs an iterative weighted least squares fitting procedure, updating its optimal weights each iteration. The performance of the suggested algorithm is compared to other track fitting techniques using a simulation of tracks with radiation background. It is shown that the algorithm improves the track fitting performance significantly. A practical implementation of the algorithm is presented for muon track fitting in the cathode strip chamber (CSC) of the ATLAS experiment.

[A review of progress of real-time tumor tracking radiotherapy technology based on dynamic multi-leaf collimator].

PubMed

Liu, Fubo; Li, Guangjun; Shen, Jiuling; Li, Ligin; Bai, Sen

2017-02-01

While radiation treatment to patients with tumors in thorax and abdomen is being performed, further improvement of radiation accuracy is restricted by the tumor intra-fractional motion due to respiration. Real-time tumor tracking radiation is an optimal solution to tumor intra-fractional motion. A review of the progress of real-time dynamic multi-leaf collimator(DMLC) tracking is provided in the present review, including DMLC tracking method, time lag of DMLC tracking system, and dosimetric verification.

A novel constrained H2 optimization algorithm for mechatronics design in flexure-linked biaxial gantry.

PubMed

Ma, Jun; Chen, Si-Lu; Kamaldin, Nazir; Teo, Chek Sing; Tay, Arthur; Mamun, Abdullah Al; Tan, Kok Kiong

2017-11-01

The biaxial gantry is widely used in many industrial processes that require high precision Cartesian motion. The conventional rigid-link version suffers from breaking down of joints if any de-synchronization between the two carriages occurs. To prevent above potential risk, a flexure-linked biaxial gantry is designed to allow a small rotation angle of the cross-arm. Nevertheless, the chattering of control signals and inappropriate design of the flexure joint will possibly induce resonant modes of the end-effector. Thus, in this work, the design requirements in terms of tracking accuracy, biaxial synchronization, and resonant mode suppression are achieved by integrated optimization of the stiffness of flexures and PID controller parameters for a class of point-to-point reference trajectories with same dynamics but different steps. From here, an H 2 optimization problem with defined constraints is formulated, and an efficient iterative solver is proposed by hybridizing direct computation of constrained projection gradient and line search of optimal step. Comparative experimental results obtained on the testbed are presented to verify the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

How unrealistic optimism is maintained in the face of reality.

PubMed

Sharot, Tali; Korn, Christoph W; Dolan, Raymond J

2011-10-09

Unrealistic optimism is a pervasive human trait that influences domains ranging from personal relationships to politics and finance. How people maintain unrealistic optimism, despite frequently encountering information that challenges those biased beliefs, is unknown. We examined this question and found a marked asymmetry in belief updating. Participants updated their beliefs more in response to information that was better than expected than to information that was worse. This selectivity was mediated by a relative failure to code for errors that should reduce optimism. Distinct regions of the prefrontal cortex tracked estimation errors when those called for positive update, both in individuals who scored high and low on trait optimism. However, highly optimistic individuals exhibited reduced tracking of estimation errors that called for negative update in right inferior prefrontal gyrus. These findings indicate that optimism is tied to a selective update failure and diminished neural coding of undesirable information regarding the future.

Experiment definition phase shuttle laboratory LDRL-10.6 experiment. [using a molniya satellite and ground communication links

NASA Technical Reports Server (NTRS)

1975-01-01

The acquisition and tracking links of shuttle to molniya satellite and shuttle to ground are established. Link parameters and tolerance are analyzed. A 10-micromillimeter optomechanical subsystem brassboard model was designed and measured for optical properties and weight optimization. The design incorporates an afocal rotating Gregorian telescope in a two-gimbal berylium structure with beam steering control mechanisms. Parameters for both the optomechanical subsystem and spaceborne terminals are included.

A Fuzzy Logic Optimal Control Law Solution to the CMMCA Tracking Problem

DTIC Science & Technology

1993-03-01

or from a transfer function. Many times, however, the resulting algorithms are so complex as to be completely or essentially useless. Applications...implemented in a nearly real time computer simulation. Located within the LQ framework are all the performance data for both the ClMCA and the CX...repuired nor desired. 34 - / k more general and less exacting framework was used. In order to concentrate on tho theory and problem solution, it was

Optimal Control of Electrodynamic Tethers

DTIC Science & Technology

2008-06-01

the out-of- plane component of the magnetic field which produces the required in- track thrust is reduced (see Eq. as th sp lo e a (4... the same orbital plane using an EDT. For the sake of testing the algorithm against a known solution we seek the maximum altitude an EDT can reach...be incl planes co gnetic equatorial plane ent of latit and m mi ains constant as the EDT ity the Eart e tilted with respect to the

Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

PubMed

Tsai, Jason Sheng-Hong; Du, Yan-Yi; Huang, Pei-Hsiang; Guo, Shu-Mei; Shieh, Leang-San; Chen, Yuhua

2011-07-01

In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system. In order to enhance the tracking performance of the digital tracker at specified sampling instants, we apply the iterative learning control (ILC) to train the control input via continual learning. As a result, the proposed iterative learning-based decentralized adaptive tracker not only has robust closed-loop decoupled property but also possesses good tracking performance at both transient and steady state. Besides, evolutionary programming is applied to search for a good learning gain to speed up the learning process of ILC. Copyright © 2011 ISA. Published by Elsevier Ltd. All rights reserved.

On the formation features, microstructure and microhardness of single laser tracks formed by laser cladding of a NiCrBSi self-fluxing alloy

NASA Astrophysics Data System (ADS)

Devojno, O. G.; Feldshtein, E.; Kardapolava, M. A.; Lutsko, N. I.

2018-07-01

In the present paper, the influence of laser cladding conditions on the powder flow conditions, as well as the microstructure, phases and microhardness of an Ni-based self-fluxing alloy coating are described. The optimal granulations of a self-fluxing alloy powder and the relationship between the flow of powder of various fractions and the flow rate and pressure of the transporting gas have been determined. The laser beam speed, track pitch and the distance from the nozzle to the coated surface influence the height and width of single tracks. Regularities in the formation of microstructure under different cladding conditions are defined, as well as regularity of distribution of elements over the track depth and in the transient zone. The patterns of microhardness distribution over the track depth for different cladding conditions are found. These patterns as well as the optimal laser spot pitch allowed obtaining a uniform cladding layer.

Consensus-based distributed cooperative learning from closed-loop neural control systems.

PubMed

Chen, Weisheng; Hua, Shaoyong; Zhang, Huaguang

2015-02-01

In this paper, the neural tracking problem is addressed for a group of uncertain nonlinear systems where the system structures are identical but the reference signals are different. This paper focuses on studying the learning capability of neural networks (NNs) during the control process. First, we propose a novel control scheme called distributed cooperative learning (DCL) control scheme, by establishing the communication topology among adaptive laws of NN weights to share their learned knowledge online. It is further proved that if the communication topology is undirected and connected, all estimated weights of NNs can converge to small neighborhoods around their optimal values over a domain consisting of the union of all state orbits. Second, as a corollary it is shown that the conclusion on the deterministic learning still holds in the decentralized adaptive neural control scheme where, however, the estimated weights of NNs just converge to small neighborhoods of the optimal values along their own state orbits. Thus, the learned controllers obtained by DCL scheme have the better generalization capability than ones obtained by decentralized learning method. A simulation example is provided to verify the effectiveness and advantages of the control schemes proposed in this paper.

Improved Space Surveillance Network (SSN) Scheduling using Artificial Intelligence Techniques

NASA Astrophysics Data System (ADS)

Stottler, D.

There are close to 20,000 cataloged manmade objects in space, the large majority of which are not active, functioning satellites. These are tracked by phased array and mechanical radars and ground and space-based optical telescopes, collectively known as the Space Surveillance Network (SSN). A better SSN schedule of observations could, using exactly the same legacy sensor resources, improve space catalog accuracy through more complementary tracking, provide better responsiveness to real-time changes, better track small debris in low earth orbit (LEO) through efficient use of applicable sensors, efficiently track deep space (DS) frequent revisit objects, handle increased numbers of objects and new types of sensors, and take advantage of future improved communication and control to globally optimize the SSN schedule. We have developed a scheduling algorithm that takes as input the space catalog and the associated covariance matrices and produces a globally optimized schedule for each sensor site as to what objects to observe and when. This algorithm is able to schedule more observations with the same sensor resources and have those observations be more complementary, in terms of the precision with which each orbit metric is known, to produce a satellite observation schedule that, when executed, minimizes the covariances across the entire space object catalog. If used operationally, the results would be significantly increased accuracy of the space catalog with fewer lost objects with the same set of sensor resources. This approach inherently can also trade-off fewer high priority tasks against more lower-priority tasks, when there is benefit in doing so. Currently the project has completed a prototyping and feasibility study, using open source data on the SSN's sensors, that showed significant reduction in orbit metric covariances. The algorithm techniques and results will be discussed along with future directions for the research.

Towards photorealistic and immersive virtual-reality environments for simulated prosthetic vision: integrating recent breakthroughs in consumer hardware and software.

PubMed

Zapf, Marc P; Matteucci, Paul B; Lovell, Nigel H; Zheng, Steven; Suaning, Gregg J

2014-01-01

Simulated prosthetic vision (SPV) in normally sighted subjects is an established way of investigating the prospective efficacy of visual prosthesis designs in visually guided tasks such as mobility. To perform meaningful SPV mobility studies in computer-based environments, a credible representation of both the virtual scene to navigate and the experienced artificial vision has to be established. It is therefore prudent to make optimal use of existing hardware and software solutions when establishing a testing framework. The authors aimed at improving the realism and immersion of SPV by integrating state-of-the-art yet low-cost consumer technology. The feasibility of body motion tracking to control movement in photo-realistic virtual environments was evaluated in a pilot study. Five subjects were recruited and performed an obstacle avoidance and wayfinding task using either keyboard and mouse, gamepad or Kinect motion tracking. Walking speed and collisions were analyzed as basic measures for task performance. Kinect motion tracking resulted in lower performance as compared to classical input methods, yet results were more uniform across vision conditions. The chosen framework was successfully applied in a basic virtual task and is suited to realistically simulate real-world scenes under SPV in mobility research. Classical input peripherals remain a feasible and effective way of controlling the virtual movement. Motion tracking, despite its limitations and early state of implementation, is intuitive and can eliminate between-subject differences due to familiarity to established input methods.

Optimal reproducibility of gated sestamibi and thallium myocardial perfusion study left ventricular ejection fractions obtained on a solid-state CZT cardiac camera requires operator input.

PubMed

Cherk, Martin H; Ky, Jason; Yap, Kenneth S K; Campbell, Patrina; McGrath, Catherine; Bailey, Michael; Kalff, Victor

2012-08-01

To evaluate the reproducibility of serial re-acquisitions of gated Tl-201 and Tc-99m sestamibi left ventricular ejection fraction (LVEF) measurements obtained on a new generation solid-state cardiac camera system during myocardial perfusion imaging and the importance of manual operator optimization of left ventricular wall tracking. Resting blinded automated (auto) and manual operator optimized (opt) LVEF measurements were measured using ECT toolbox (ECT) and Cedars-Sinai QGS software in two separate cohorts of 55 Tc-99m sestamibi (MIBI) and 50 thallium (Tl-201) myocardial perfusion studies (MPS) acquired in both supine and prone positions on a cadmium zinc telluride (CZT) solid-state camera system. Resting supine and prone automated LVEF measurements were similarly obtained in a further separate cohort of 52 gated cardiac blood pool scans (GCBPS) for validation of methodology and comparison. Appropriate use of Bland-Altman, chi-squared and Levene's equality of variance tests was used to analyse the resultant data comparisons. For all radiotracer and software combinations, manual checking and optimization of valve planes (+/- centre radius with ECT software) resulted in significant improvement in MPS LVEF reproducibility that approached that of planar GCBPS. No difference was demonstrated between optimized MIBI/Tl-201 QGS and planar GCBPS LVEF reproducibility (P = .17 and P = .48, respectively). ECT required significantly more manual optimization compared to QGS software in both supine and prone positions independent of radiotracer used (P < .02). Reproducibility of gated sestamibi and Tl-201 LVEF measurements obtained during myocardial perfusion imaging with ECT toolbox or QGS software packages using a new generation solid-state cardiac camera with improved image quality approaches that of planar GCBPS however requires visual quality control and operator optimization of left ventricular wall tracking for best results. Using this superior cardiac technology, Tl-201 reproducibility also appears at least equivalent to sestamibi for measuring LVEF.

Air traffic surveillance and control using hybrid estimation and protocol-based conflict resolution

NASA Astrophysics Data System (ADS)

Hwang, Inseok

The continued growth of air travel and recent advances in new technologies for navigation, surveillance, and communication have led to proposals by the Federal Aviation Administration (FAA) to provide reliable and efficient tools to aid Air Traffic Control (ATC) in performing their tasks. In this dissertation, we address four problems frequently encountered in air traffic surveillance and control; multiple target tracking and identity management, conflict detection, conflict resolution, and safety verification. We develop a set of algorithms and tools to aid ATC; These algorithms have the provable properties of safety, computational efficiency, and convergence. Firstly, we develop a multiple-maneuvering-target tracking and identity management algorithm which can keep track of maneuvering aircraft in noisy environments and of their identities. Secondly, we propose a hybrid probabilistic conflict detection algorithm between multiple aircraft which uses flight mode estimates as well as aircraft current state estimates. Our algorithm is based on hybrid models of aircraft, which incorporate both continuous dynamics and discrete mode switching. Thirdly, we develop an algorithm for multiple (greater than two) aircraft conflict avoidance that is based on a closed-form analytic solution and thus provides guarantees of safety. Finally, we consider the problem of safety verification of control laws for safety critical systems, with application to air traffic control systems. We approach safety verification through reachability analysis, which is a computationally expensive problem. We develop an over-approximate method for reachable set computation using polytopic approximation methods and dynamic optimization. These algorithms may be used either in a fully autonomous way, or as supporting tools to increase controllers' situational awareness and to reduce their work load.

Use telecommunications for real-time process control

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

Zilberman, I.; Bigman, J.; Sela, I.

1996-05-01

Process operators design real-time accurate information to monitor and control product streams and to optimize unit operations. The challenge is how to cost-effectively install sophisticated analytical equipment in harsh environments such as process areas and maintain system reliability. Incorporating telecommunications technology with near infrared (NIR) spectroscopy may be the bridge to help operations achieve their online control goals. Coupling communications fiber optics with NIR analyzers enables the probe and sampling system to remain in the field and crucial analytical equipment to be remotely located in a general purpose area without specialized protection provisions. The case histories show how two refineriesmore » used NIR spectroscopy online to track octane levels for reformate streams.« less

Development of a 750x750 pixels CMOS imager sensor for tracking applications

NASA Astrophysics Data System (ADS)

Larnaudie, Franck; Guardiola, Nicolas; Saint-Pé, Olivier; Vignon, Bruno; Tulet, Michel; Davancens, Robert; Magnan, Pierre; Corbière, Franck; Martin-Gonthier, Philippe; Estribeau, Magali

2017-11-01

Solid-state optical sensors are now commonly used in space applications (navigation cameras, astronomy imagers, tracking sensors...). Although the charge-coupled devices are still widely used, the CMOS image sensor (CIS), which performances are continuously improving, is a strong challenger for Guidance, Navigation and Control (GNC) systems. This paper describes a 750x750 pixels CMOS image sensor that has been specially designed and developed for star tracker and tracking sensor applications. Such detector, that is featuring smart architecture enabling very simple and powerful operations, is built using the AMIS 0.5μm CMOS technology. It contains 750x750 rectangular pixels with 20μm pitch. The geometry of the pixel sensitive zone is optimized for applications based on centroiding measurements. The main feature of this device is the on-chip control and timing function that makes the device operation easier by drastically reducing the number of clocks to be applied. This powerful function allows the user to operate the sensor with high flexibility: measurement of dark level from masked lines, direct access to the windows of interest… A temperature probe is also integrated within the CMOS chip allowing a very precise measurement through the video stream. A complete electro-optical characterization of the sensor has been performed. The major parameters have been evaluated: dark current and its uniformity, read-out noise, conversion gain, Fixed Pattern Noise, Photo Response Non Uniformity, quantum efficiency, Modulation Transfer Function, intra-pixel scanning. The characterization tests are detailed in the paper. Co60 and protons irradiation tests have been also carried out on the image sensor and the results are presented. The specific features of the 750x750 image sensor such as low power CMOS design (3.3V, power consumption<100mW), natural windowing (that allows efficient and robust tracking algorithms), simple proximity electronics (because of the on-chip control and timing function) enabling a high flexibility architecture, make this imager a good candidate for high performance tracking applications.

Novel probabilistic and distributed algorithms for guidance, control, and nonlinear estimation of large-scale multi-agent systems

NASA Astrophysics Data System (ADS)

Bandyopadhyay, Saptarshi

Multi-agent systems are widely used for constructing a desired formation shape, exploring an area, surveillance, coverage, and other cooperative tasks. This dissertation introduces novel algorithms in the three main areas of shape formation, distributed estimation, and attitude control of large-scale multi-agent systems. In the first part of this dissertation, we address the problem of shape formation for thousands to millions of agents. Here, we present two novel algorithms for guiding a large-scale swarm of robotic systems into a desired formation shape in a distributed and scalable manner. These probabilistic swarm guidance algorithms adopt an Eulerian framework, where the physical space is partitioned into bins and the swarm's density distribution over each bin is controlled using tunable Markov chains. In the first algorithm - Probabilistic Swarm Guidance using Inhomogeneous Markov Chains (PSG-IMC) - each agent determines its bin transition probabilities using a time-inhomogeneous Markov chain that is constructed in real-time using feedback from the current swarm distribution. This PSG-IMC algorithm minimizes the expected cost of the transitions required to achieve and maintain the desired formation shape, even when agents are added to or removed from the swarm. The algorithm scales well with a large number of agents and complex formation shapes, and can also be adapted for area exploration applications. In the second algorithm - Probabilistic Swarm Guidance using Optimal Transport (PSG-OT) - each agent determines its bin transition probabilities by solving an optimal transport problem, which is recast as a linear program. In the presence of perfect feedback of the current swarm distribution, this algorithm minimizes the given cost function, guarantees faster convergence, reduces the number of transitions for achieving the desired formation, and is robust to disturbances or damages to the formation. We demonstrate the effectiveness of these two proposed swarm guidance algorithms using results from numerical simulations and closed-loop hardware experiments on multiple quadrotors. In the second part of this dissertation, we present two novel discrete-time algorithms for distributed estimation, which track a single target using a network of heterogeneous sensing agents. The Distributed Bayesian Filtering (DBF) algorithm, the sensing agents combine their normalized likelihood functions using the logarithmic opinion pool and the discrete-time dynamic average consensus algorithm. Each agent's estimated likelihood function converges to an error ball centered on the joint likelihood function of the centralized multi-sensor Bayesian filtering algorithm. Using a new proof technique, the convergence, stability, and robustness properties of the DBF algorithm are rigorously characterized. The explicit bounds on the time step of the robust DBF algorithm are shown to depend on the time-scale of the target dynamics. Furthermore, the DBF algorithm for linear-Gaussian models can be cast into a modified form of the Kalman information filter. In the Bayesian Consensus Filtering (BCF) algorithm, the agents combine their estimated posterior pdfs multiple times within each time step using the logarithmic opinion pool scheme. Thus, each agent's consensual pdf minimizes the sum of Kullback-Leibler divergences with the local posterior pdfs. The performance and robust properties of these algorithms are validated using numerical simulations. In the third part of this dissertation, we present an attitude control strategy and a new nonlinear tracking controller for a spacecraft carrying a large object, such as an asteroid or a boulder. If the captured object is larger or comparable in size to the spacecraft and has significant modeling uncertainties, conventional nonlinear control laws that use exact feed-forward cancellation are not suitable because they exhibit a large resultant disturbance torque. The proposed nonlinear tracking control law guarantees global exponential convergence of tracking errors with finite-gain Lp stability in the presence of modeling uncertainties and disturbances, and reduces the resultant disturbance torque. Further, this control law permits the use of any attitude representation and its integral control formulation eliminates any constant disturbance. Under small uncertainties, the best strategy for stabilizing the combined system is to track a fuel-optimal reference trajectory using this nonlinear control law, because it consumes the least amount of fuel. In the presence of large uncertainties, the most effective strategy is to track the derivative plus proportional-derivative based reference trajectory, because it reduces the resultant disturbance torque. The effectiveness of the proposed attitude control law is demonstrated by using results of numerical simulation based on an Asteroid Redirect Mission concept. The new algorithms proposed in this dissertation will facilitate the development of versatile autonomous multi-agent systems that are capable of performing a variety of complex tasks in a robust and scalable manner.

A nonlinear optimal control approach for chaotic finance dynamics

NASA Astrophysics Data System (ADS)

Rigatos, G.; Siano, P.; Loia, V.; Tommasetti, A.; Troisi, O.

2017-11-01

A new nonlinear optimal control approach is proposed for stabilization of the dynamics of a chaotic finance model. The dynamic model of the financial system, which expresses interaction between the interest rate, the investment demand, the price exponent and the profit margin, undergoes approximate linearization round local operating points. These local equilibria are defined at each iteration of the control algorithm and consist of the present value of the systems state vector and the last value of the control inputs vector that was exerted on it. The approximate linearization makes use of Taylor series expansion and of the computation of the associated Jacobian matrices. The truncation of higher order terms in the Taylor series expansion is considered to be a modelling error that is compensated by the robustness of the control loop. As the control algorithm runs, the temporary equilibrium is shifted towards the reference trajectory and finally converges to it. The control method needs to compute an H-infinity feedback control law at each iteration, and requires the repetitive solution of an algebraic Riccati equation. Through Lyapunov stability analysis it is shown that an H-infinity tracking performance criterion holds for the control loop. This implies elevated robustness against model approximations and external perturbations. Moreover, under moderate conditions the global asymptotic stability of the control loop is proven.

Concept and realization of unmanned aerial system with different modes of operation

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

Czyba, Roman; Szafrański, Grzegorz; Janusz, Wojciech

2014-12-10

In this paper we describe the development process of unmanned aerial system, its mechanical components, electronics and software solutions. During the stage of design, we have formulated some necessary requirements for the multirotor vehicle and ground control station in order to build an optimal system which can be used for the reconnaissance missions. Platform is controlled by use of the ground control station (GCS) and has possibility of accomplishing video based observation tasks. In order to fulfill this requirement the on-board payload consists of mechanically stabilized camera augmented with machine vision algorithms to enable object tracking tasks. Novelty of themore » system are four modes of flight, which give full functionality of the developed UAV system. Designed ground control station is consisted not only of the application itself, but also a built-in dedicated components located inside the chassis, which together creates an advanced UAV system supporting the control and management of the flight. Mechanical part of quadrotor is designed to ensure its robustness while meeting objectives of minimizing weight of the platform. Finally the designed electronics allows for implementation of control and estimation algorithms without the needs for their excessive computational optimization.« less

Application of level set method to optimal vibration control of plate structures

NASA Astrophysics Data System (ADS)

Ansari, M.; Khajepour, A.; Esmailzadeh, E.

2013-02-01

Vibration control plays a crucial role in many structures, especially in the lightweight ones. One of the most commonly practiced method to suppress the undesirable vibration of structures is to attach patches of the constrained layer damping (CLD) onto the surface of the structure. In order to consider the weight efficiency of a structure, the best shapes and locations of the CLD patches should be determined to achieve the optimum vibration suppression with minimum usage of the CLD patches. This paper proposes a novel topology optimization technique that can determine the best shape and location of the applied CLD patches, simultaneously. Passive vibration control is formulated in the context of the level set method, which is a numerical technique to track shapes and locations concurrently. The optimal damping set could be found in a structure, in its fundamental vibration mode, such that the maximum modal loss factor of the system is achieved. Two different plate structures will be considered and the damping patches will be optimally located on them. At the same time, the best shapes of the damping patches will be determined too. In one example, the numerical results will be compared with those obtained from the experimental tests to validate the accuracy of the proposed method. This comparison reveals the effectiveness of the level set approach in finding the optimum shape and location of the CLD patches.

Chaos Quantum-Behaved Cat Swarm Optimization Algorithm and Its Application in the PV MPPT

PubMed Central

2017-01-01

Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of “premature convergence,” that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In order to surmount the shortcomings of CSO, Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed in this paper. Firstly, Quantum-behaved Cat Swarm Optimization (QCSO) algorithm improves the accuracy of the CSO algorithm, because it is easy to fall into the local optimum in the later stage. Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed by introducing tent map for jumping out of local optimum in this paper. Secondly, CQCSO has been applied in the simulation of five different test functions, showing higher accuracy and less time consumption than CSO and QCSO. Finally, photovoltaic MPPT model and experimental platform are established and global maximum power point tracking control strategy is achieved by CQCSO algorithm, the effectiveness and efficiency of which have been verified by both simulation and experiment. PMID:29181020

Chaos Quantum-Behaved Cat Swarm Optimization Algorithm and Its Application in the PV MPPT.

PubMed

Nie, Xiaohua; Wang, Wei; Nie, Haoyao

2017-01-01

Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of "premature convergence," that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In order to surmount the shortcomings of CSO, Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed in this paper. Firstly, Quantum-behaved Cat Swarm Optimization (QCSO) algorithm improves the accuracy of the CSO algorithm, because it is easy to fall into the local optimum in the later stage. Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed by introducing tent map for jumping out of local optimum in this paper. Secondly, CQCSO has been applied in the simulation of five different test functions, showing higher accuracy and less time consumption than CSO and QCSO. Finally, photovoltaic MPPT model and experimental platform are established and global maximum power point tracking control strategy is achieved by CQCSO algorithm, the effectiveness and efficiency of which have been verified by both simulation and experiment.

Full-Carpet Design of a Low-Boom Demonstrator Concept

NASA Technical Reports Server (NTRS)

Ordaz, Irian; Wintzer, Mathias; Rallabhandi, Sriram K.

2015-01-01

The Cart3D adjoint-based design framework is used to mitigate the undesirable o -track sonic boom properties of a demonstrator concept designed for low-boom directly under the flight path. First, the requirements of a Cart3D design mesh are determined using a high-fidelity mesh adapted to minimize the discretization error of the CFD analysis. Low-boom equivalent area targets are then generated at the under-track and one off-track azimuthal position for the baseline configuration. The under-track target is generated using a trim- feasible low-boom target generation process, ensuring that the final design is not only low-boom, but also trimmed at the specified flight condition. The o -track equivalent area target is generated by minimizing the A-weighted loudness using an efficient adjoint-based approach. The configuration outer mold line is then parameterized and optimized to match the off-body pressure distributions prescribed by the low-boom targets. The numerical optimizer uses design gradients which are calculated using the Cart3D adjoint- based design capability. Optimization constraints are placed on the geometry to satisfy structural feasibility. The low-boom properties of the final design are verified using the adaptive meshing approach. This analysis quantifies the error associated with the CFD mesh that is used for design. Finally, an alternate mesh construction and target positioning approach offering greater computational efficiency is demonstrated and verified.

Optimal marker placement in hadrontherapy: intelligent optimization strategies with augmented Lagrangian pattern search.

PubMed

Altomare, Cristina; Guglielmann, Raffaella; Riboldi, Marco; Bellazzi, Riccardo; Baroni, Guido

2015-02-01

In high precision photon radiotherapy and in hadrontherapy, it is crucial to minimize the occurrence of geometrical deviations with respect to the treatment plan in each treatment session. To this end, point-based infrared (IR) optical tracking for patient set-up quality assessment is performed. Such tracking depends on external fiducial points placement. The main purpose of our work is to propose a new algorithm based on simulated annealing and augmented Lagrangian pattern search (SAPS), which is able to take into account prior knowledge, such as spatial constraints, during the optimization process. The SAPS algorithm was tested on data related to head and neck and pelvic cancer patients, and that were fitted with external surface markers for IR optical tracking applied for patient set-up preliminary correction. The integrated algorithm was tested considering optimality measures obtained with Computed Tomography (CT) images (i.e. the ratio between the so-called target registration error and fiducial registration error, TRE/FRE) and assessing the marker spatial distribution. Comparison has been performed with randomly selected marker configuration and with the GETS algorithm (Genetic Evolutionary Taboo Search), also taking into account the presence of organs at risk. The results obtained with SAPS highlight improvements with respect to the other approaches: (i) TRE/FRE ratio decreases; (ii) marker distribution satisfies both marker visibility and spatial constraints. We have also investigated how the TRE/FRE ratio is influenced by the number of markers, obtaining significant TRE/FRE reduction with respect to the random configurations, when a high number of markers is used. The SAPS algorithm is a valuable strategy for fiducial configuration optimization in IR optical tracking applied for patient set-up error detection and correction in radiation therapy, showing that taking into account prior knowledge is valuable in this optimization process. Further work will be focused on the computational optimization of the SAPS algorithm toward fast point-of-care applications. Copyright © 2014 Elsevier Inc. All rights reserved.

Determining residual reduction algorithm kinematic tracking weights for a sidestep cut via numerical optimization.

PubMed

Samaan, Michael A; Weinhandl, Joshua T; Bawab, Sebastian Y; Ringleb, Stacie I

2016-12-01

Musculoskeletal modeling allows for the determination of various parameters during dynamic maneuvers by using in vivo kinematic and ground reaction force (GRF) data as inputs. Differences between experimental and model marker data and inconsistencies in the GRFs applied to these musculoskeletal models may not produce accurate simulations. Therefore, residual forces and moments are applied to these models in order to reduce these differences. Numerical optimization techniques can be used to determine optimal tracking weights of each degree of freedom of a musculoskeletal model in order to reduce differences between the experimental and model marker data as well as residual forces and moments. In this study, the particle swarm optimization (PSO) and simplex simulated annealing (SIMPSA) algorithms were used to determine optimal tracking weights for the simulation of a sidestep cut. The PSO and SIMPSA algorithms were able to produce model kinematics that were within 1.4° of experimental kinematics with residual forces and moments of less than 10 N and 18 Nm, respectively. The PSO algorithm was able to replicate the experimental kinematic data more closely and produce more dynamically consistent kinematic data for a sidestep cut compared to the SIMPSA algorithm. Future studies should use external optimization routines to determine dynamically consistent kinematic data and report the differences between experimental and model data for these musculoskeletal simulations.

A novel adaptive needle insertion sequencing for robotic, single needle MR-guided high-dose-rate prostate brachytherapy

NASA Astrophysics Data System (ADS)

Borot de Battisti, M.; de Senneville, B. Denis; Hautvast, G.; Binnekamp, D.; Lagendijk, J. J. W.; Maenhout, M.; Moerland, M. A.

2017-05-01

MR-guided high-dose-rate (HDR) brachytherapy has gained increasing interest as a treatment for patients with localized prostate cancer because of the superior value of MRI for tumor and surrounding tissues localization. To enable needle insertion into the prostate with the patient in the MR bore, a single needle MR-compatible robotic system involving needle-by-needle dose delivery has been developed at our institution. Throughout the intervention, dose delivery may be impaired by: (1) sub-optimal needle positioning caused by e.g. needle bending, (2) intra-operative internal organ motion such as prostate rotations or swelling, or intra-procedural rectum or bladder filling. This may result in failure to reach clinical constraints. To assess the first aforementioned challenge, a recent study from our research group demonstrated that the deposited dose may be greatly improved by real-time adaptive planning with feedback on the actual needle positioning. However, the needle insertion sequence is left to the doctor and therefore, this may result in sub-optimal dose delivery. In this manuscript, a new method is proposed to determine and update automatically the needle insertion sequence. This strategy is based on the determination of the most sensitive needle track. The sensitivity of a needle track is defined as its impact on the dose distribution in case of sub-optimal positioning. A stochastic criterion is thus presented to determine each needle track sensitivity based on needle insertion simulations. To assess the proposed sequencing strategy, HDR prostate brachytherapy was simulated on 11 patients with varying number of needle insertions. Sub-optimal needle positioning was simulated at each insertion (modeled by typical random angulation errors). In 91% of the scenarios, the dose distribution improved when the needle was inserted into the most compared to the least sensitive needle track. The computation time for sequencing was less than 6 s per needle track. The proposed needle insertion sequencing can therefore assist in delivering an optimal dose in HDR prostate brachytherapy.

Optimal Battery Charging for Damage Mitigation

NASA Technical Reports Server (NTRS)

Hartley, Tom T.; Lorenzo, Carl F.

2003-01-01

Our control philosophy is to charge the NiH2 cell in such a way that the damage incurred during the charging period is minimized, thus extending its cycle life. This requires nonlinear dynamic model of NiH2 cell and a damage rate model. We must do this first. This control philosophy is generally considered damage mitigating control or life-extending control. This presentation covers how NiH2 cells function, electrode behavior, an essentialized model, damage mechanisms for NiH2 batteries, battery continuum damage modeling, and battery life models. The presentation includes graphs and a chart illustrating how charging a NiH2 battery with different voltages and currents affects damages the battery and affects its life. The presentation concludes with diagrams of control system architectures for tracking battery recharging.

Adaptive neural control for a class of nonlinear time-varying delay systems with unknown hysteresis.

PubMed

Liu, Zhi; Lai, Guanyu; Zhang, Yun; Chen, Xin; Chen, Chun Lung Philip

2014-12-01

This paper investigates the fusion of unknown direction hysteresis model with adaptive neural control techniques in face of time-delayed continuous time nonlinear systems without strict-feedback form. Compared with previous works on the hysteresis phenomenon, the direction of the modified Bouc-Wen hysteresis model investigated in the literature is unknown. To reduce the computation burden in adaptation mechanism, an optimized adaptation method is successfully applied to the control design. Based on the Lyapunov-Krasovskii method, two neural-network-based adaptive control algorithms are constructed to guarantee that all the system states and adaptive parameters remain bounded, and the tracking error converges to an adjustable neighborhood of the origin. In final, some numerical examples are provided to validate the effectiveness of the proposed control methods.

Application of optimal control principles to describe the supervisory control behavior of AAA crew members

NASA Technical Reports Server (NTRS)

Hale, C.; Valentino, G. J.

1982-01-01

Supervisory decision making and control behavior within a C(3) oriented, ground based weapon system is being studied. The program involves empirical investigation of the sequence of control strategies used during engagement of aircraft targets. An engagement is conceptually divided into several stages which include initial information processing activity, tracking, and ongoing adaptive control decisions. Following a brief description of model parameters, two experiments which served as initial investigation into the accuracy of assumptions regarding the importance of situation assessment in procedure selection are outlined. Preliminary analysis of the results upheld the validity of the assumptions regarding strategic information processing and cue-criterion relationship learning. These results indicate that this model structure should be useful in studies of supervisory decision behavior.

An efficient fluorescent single-particle position tracking system for long-term pulsed measurements of nitrogen-vacancy centers in diamond

NASA Astrophysics Data System (ADS)

Kim, Kiho; Yun, Jiwon; Lee, Donghyuck; Kim, Dohun

2018-02-01

A simple and convenient design enables real-time three-dimensional position tracking of nitrogen-vacancy (NV) centers in diamond. The system consists entirely of commercially available components (a single-photon counter, a high-speed digital-to-analog converter, a phase-sensitive detector-based feedback device, and a piezo stage), eliminating the need for custom programming or rigorous optimization processes. With a large input range of counters and trackers combined with high sensitivity of single-photon counting, high-speed position tracking (upper bound recovery time of 0.9 s upon 250 nm of step-like positional shift) not only of bright ensembles, but also of low-photon-collection-efficiency single to few NV centers (down to 103 s-1) is possible. The tracking requires position modulation of only 10 nm, which allows simultaneous position tracking and pulsed measurements in the long term. Therefore, this tracking system enables measuring a single-spin magnetic resonance and Rabi oscillations at a very high resolution even without photon collection optimization. The system is widely applicable to various fields related to NV center quantum manipulation research such as NV optical trapping, NV tracking in fluid dynamics, and biological sensing using NV centers inside a biological cell.

DEMONSTRATION AND TESTING OF AN EER OPTIMIZER SYSTEM FOR DX AIR-CONDITIONERS

DTIC Science & Technology

2017-10-07

Performance-Based Maintenance PCS Power Current Sensor PLC Programmable Logic Controller ppm Parts Per Million PSIG Pounds per Square Inch Gauge PVS Power...all utilities and facilities at Patrick AFB, Cape Canaveral AFS, Jonathan Dickinson Military Tracking Annex, Malabar Annex, Ramey Solar Observatory...Cost 8,057 0 Annual O&M Cost 453 1191 Annual FD&D Monitoring 880 ‐ BLCC LIFE CYCLE RESULTS Energy Savings $12,317 O&M Net Savings $493 PV  Life Cycle

Stabilization of business cycles of finance agents using nonlinear optimal control

NASA Astrophysics Data System (ADS)

Rigatos, G.; Siano, P.; Ghosh, T.; Sarno, D.

2017-11-01

Stabilization of the business cycles of interconnected finance agents is performed with the use of a new nonlinear optimal control method. First, the dynamics of the interacting finance agents and of the associated business cycles is described by a modeled of coupled nonlinear oscillators. Next, this dynamic model undergoes approximate linearization round a temporary operating point which is defined by the present value of the system's state vector and the last value of the control inputs vector that was exerted on it. The linearization procedure is based on Taylor series expansion of the dynamic model and on the computation of Jacobian matrices. The modelling error, which is due to the truncation of higher-order terms in the Taylor series expansion is considered as a disturbance which is compensated by the robustness of the control loop. Next, for the linearized model of the interacting finance agents, an H-infinity feedback controller is designed. The computation of the feedback control gain requires the solution of an algebraic Riccati equation at each iteration of the control algorithm. Through Lyapunov stability analysis it is proven that the control scheme satisfies an H-infinity tracking performance criterion, which signifies elevated robustness against modelling uncertainty and external perturbations. Moreover, under moderate conditions the global asymptotic stability features of the control loop are proven.

A Bayesian Framework for Human Body Pose Tracking from Depth Image Sequences

PubMed Central

Zhu, Youding; Fujimura, Kikuo

2010-01-01

This paper addresses the problem of accurate and robust tracking of 3D human body pose from depth image sequences. Recovering the large number of degrees of freedom in human body movements from a depth image sequence is challenging due to the need to resolve the depth ambiguity caused by self-occlusions and the difficulty to recover from tracking failure. Human body poses could be estimated through model fitting using dense correspondences between depth data and an articulated human model (local optimization method). Although it usually achieves a high accuracy due to dense correspondences, it may fail to recover from tracking failure. Alternately, human pose may be reconstructed by detecting and tracking human body anatomical landmarks (key-points) based on low-level depth image analysis. While this method (key-point based method) is robust and recovers from tracking failure, its pose estimation accuracy depends solely on image-based localization accuracy of key-points. To address these limitations, we present a flexible Bayesian framework for integrating pose estimation results obtained by methods based on key-points and local optimization. Experimental results are shown and performance comparison is presented to demonstrate the effectiveness of the proposed approach. PMID:22399933

Feasibility study of RFID technology for construction load tracking.

DOT National Transportation Integrated Search

2010-12-01

ADOT&PF is seeking more efficient business practices and processes to increase its speed in delivering supplies to work sites, optimize the workforce, and minimize : costs. The current tracking process uses a computer-generated ticket carried by the ...

Optimal pacing for running 400- and 800-m track races

NASA Astrophysics Data System (ADS)

Reardon, James

2013-06-01

We present a toy model of anaerobic glycolysis that utilizes appropriate physiological and mathematical consideration while remaining useful to the athlete. The toy model produces an optimal pacing strategy for 400-m and 800-m races that is analytically calculated via the Euler-Lagrange equation. The calculation of the optimum v(t) is presented in detail, with an emphasis on intuitive arguments in order to serve as a bridge between the basic techniques presented in undergraduate physics textbooks and the more advanced techniques of control theory. Observed pacing strategies in 400-m and 800-m world-record races are found to be well-fit by the toy model, which allows us to draw a new physiological interpretation for the advantages of common weight-training practices.

Model-based occluded object recognition using Petri nets

NASA Astrophysics Data System (ADS)

Zhou, Chuan; Hura, Gurdeep S.

1998-09-01

This paper discusses the use of Petri nets to model the process of the object matching between an image and a model under different 2D geometric transformations. This transformation finds its applications in sensor-based robot control, flexible manufacturing system and industrial inspection, etc. A description approach for object structure is presented by its topological structure relation called Point-Line Relation Structure (PLRS). It has been shown how Petri nets can be used to model the matching process, and an optimal or near optimal matching can be obtained by tracking the reachability graph of the net. The experiment result shows that object can be successfully identified and located under 2D transformation such as translations, rotations, scale changes and distortions due to object occluded partially.

An embedded real-time red peach detection system based on an OV7670 camera, ARM cortex-M4 processor and 3D look-up tables.

PubMed

Teixidó, Mercè; Font, Davinia; Pallejà, Tomàs; Tresanchez, Marcel; Nogués, Miquel; Palacín, Jordi

2012-10-22

This work proposes the development of an embedded real-time fruit detection system for future automatic fruit harvesting. The proposed embedded system is based on an ARM Cortex-M4 (STM32F407VGT6) processor and an Omnivision OV7670 color camera. The future goal of this embedded vision system will be to control a robotized arm to automatically select and pick some fruit directly from the tree. The complete embedded system has been designed to be placed directly in the gripper tool of the future robotized harvesting arm. The embedded system will be able to perform real-time fruit detection and tracking by using a three-dimensional look-up-table (LUT) defined in the RGB color space and optimized for fruit picking. Additionally, two different methodologies for creating optimized 3D LUTs based on existing linear color models and fruit histograms were implemented in this work and compared for the case of red peaches. The resulting system is able to acquire general and zoomed orchard images and to update the relative tracking information of a red peach in the tree ten times per second.

An Embedded Real-Time Red Peach Detection System Based on an OV7670 Camera, ARM Cortex-M4 Processor and 3D Look-Up Tables

PubMed Central

Teixidó, Mercè; Font, Davinia; Pallejà, Tomàs; Tresanchez, Marcel; Nogués, Miquel; Palacín, Jordi

2012-01-01

This work proposes the development of an embedded real-time fruit detection system for future automatic fruit harvesting. The proposed embedded system is based on an ARM Cortex-M4 (STM32F407VGT6) processor and an Omnivision OV7670 color camera. The future goal of this embedded vision system will be to control a robotized arm to automatically select and pick some fruit directly from the tree. The complete embedded system has been designed to be placed directly in the gripper tool of the future robotized harvesting arm. The embedded system will be able to perform real-time fruit detection and tracking by using a three-dimensional look-up-table (LUT) defined in the RGB color space and optimized for fruit picking. Additionally, two different methodologies for creating optimized 3D LUTs based on existing linear color models and fruit histograms were implemented in this work and compared for the case of red peaches. The resulting system is able to acquire general and zoomed orchard images and to update the relative tracking information of a red peach in the tree ten times per second. PMID:23202040

Multi Objective Controller Design for Linear System via Optimal Interpolation

NASA Technical Reports Server (NTRS)

Ozbay, Hitay

1996-01-01

We propose a methodology for the design of a controller which satisfies a set of closed-loop objectives simultaneously. The set of objectives consists of: (1) pole placement, (2) decoupled command tracking of step inputs at steady-state, and (3) minimization of step response transients with respect to envelope specifications. We first obtain a characterization of all controllers placing the closed-loop poles in a prescribed region of the complex plane. In this characterization, the free parameter matrix Q(s) is to be determined to attain objectives (2) and (3). Objective (2) is expressed as determining a Pareto optimal solution to a vector valued optimization problem. The solution of this problem is obtained by transforming it to a scalar convex optimization problem. This solution determines Q(O) and the remaining freedom in choosing Q(s) is used to satisfy objective (3). We write Q(s) = (l/v(s))bar-Q(s) for a prescribed polynomial v(s). Bar-Q(s) is a polynomial matrix which is arbitrary except that Q(O) and the order of bar-Q(s) are fixed. Obeying these constraints bar-Q(s) is now to be 'shaped' to minimize the step response characteristics of specific input/output pairs according to the maximum envelope violations. This problem is expressed as a vector valued optimization problem using the concept of Pareto optimality. We then investigate a scalar optimization problem associated with this vector valued problem and show that it is convex. The organization of the report is as follows. The next section includes some definitions and preliminary lemmas. We then give the problem statement which is followed by a section including a detailed development of the design procedure. We then consider an aircraft control example. The last section gives some concluding remarks. The Appendix includes the proofs of technical lemmas, printouts of computer programs, and figures.

Performance evaluation of an asynchronous multisensor track fusion filter

NASA Astrophysics Data System (ADS)

Alouani, Ali T.; Gray, John E.; McCabe, D. H.

2003-08-01

Recently the authors developed a new filter that uses data generated by asynchronous sensors to produce a state estimate that is optimal in the minimum mean square sense. The solution accounts for communications delay between sensors platform and fusion center. It also deals with out of sequence data as well as latent data by processing the information in a batch-like manner. This paper compares, using simulated targets and Monte Carlo simulations, the performance of the filter to the optimal sequential processing approach. It was found that the new asynchronous Multisensor track fusion filter (AMSTFF) performance is identical to that of the extended sequential Kalman filter (SEKF), while the new filter updates its track at a much lower rate than the SEKF.

A novel track-before-detect algorithm based on optimal nonlinear filtering for detecting and tracking infrared dim target

NASA Astrophysics Data System (ADS)

Tian, Yuexin; Gao, Kun; Liu, Ying; Han, Lu

2015-08-01

Aiming at the nonlinear and non-Gaussian features of the real infrared scenes, an optimal nonlinear filtering based algorithm for the infrared dim target tracking-before-detecting application is proposed. It uses the nonlinear theory to construct the state and observation models and uses the spectral separation scheme based Wiener chaos expansion method to resolve the stochastic differential equation of the constructed models. In order to improve computation efficiency, the most time-consuming operations independent of observation data are processed on the fore observation stage. The other observation data related rapid computations are implemented subsequently. Simulation results show that the algorithm possesses excellent detection performance and is more suitable for real-time processing.

Near-optimal strategies for sub-decimeter satellite tracking with GPS

NASA Technical Reports Server (NTRS)

Yunck, Thomas P.; Wu, Sien-Chong; Wu, Jiun-Tsong

1986-01-01

Decimeter tracking of low Earth orbiters using differential Global Positioning System (GPS) techniques is discussed. A precisely known global network of GPS ground receivers and a receiver aboard the user satellite are needed, and all techniques simultaneously estimate the user and GPS satellite orbits. Strategies include a purely geometric, a fully dynamic, and a hybrid strategy. The last combines dynamic GPS solutions with a geometric user solution. Two powerful extensions of the hybrid strategy show the most promise. The first uses an optimized synthesis of dynamics and geometry in the user solution, while the second uses a gravity adjustment method to exploit data from repeat ground tracks. These techniques promise to deliver subdecimeter accuracy down to the lowest satellite altitudes.

Optimal Configuration of Human Motion Tracking Systems: A Systems Engineering Approach

NASA Technical Reports Server (NTRS)

Henderson, Steve

2005-01-01

Human motion tracking systems represent a crucial technology in the area of modeling and simulation. These systems, which allow engineers to capture human motion for study or replication in virtual environments, have broad applications in several research disciplines including human engineering, robotics, and psychology. These systems are based on several sensing paradigms, including electro-magnetic, infrared, and visual recognition. Each of these paradigms requires specialized environments and hardware configurations to optimize performance of the human motion tracking system. Ideally, these systems are used in a laboratory or other facility that was designed to accommodate the particular sensing technology. For example, electromagnetic systems are highly vulnerable to interference from metallic objects, and should be used in a specialized lab free of metal components.

Application of precomputed control laws in a reconfigurable aircraft flight control system

NASA Technical Reports Server (NTRS)

Moerder, Daniel D.; Halyo, Nesim; Broussard, John R.; Caglayan, Alper K.

1989-01-01

A self-repairing flight control system concept in which the control law is reconfigured after actuator and/or control surface damage to preserve stability and pilot command tracking is described. A key feature of the controller is reconfigurable multivariable feedback. The feedback gains are designed off-line and scheduled as a function of the aircraft control impairment status so that reconfiguration is performed simply by updating the gain schedule after detection of an impairment. A novel aspect of the gain schedule design procedure is that the schedule is calculated using a linear quadratic optimization-based simultaneous stabilization algorithm in which the scheduled gain is constrained to stabilize a collection of plant models representing the aircraft in various control failure modes. A description and numerical evaluation of a controller design for a model of a statically unstable high-performance aircraft are given.

Cubesat Constellation Design for Air Traffic Monitoring

NASA Technical Reports Server (NTRS)

Nag, Sreeja; Rios, Joseph Lucio; Gerhardt, David; Pham, Camvu

2015-01-01

Suitably equipped global and local air traffic can be tracked. The tracking information may then be used for control from ground-based stations by receiving the Automatic Dependent Surveillance-Broadcast (ADS-B) signal. The ADS-B signal, emitted from the aircraft's Mode-S transponder, is currently tracked by terrestrial based receivers but not over remote oceans or sparsely populated regions such as Alaska or the Pacific Ocean. Lack of real-time aircraft time/location information in remote areas significantly hinders optimal planning and control because bigger "safety bubbles" (lateral and vertical separation) are required around the aircraft until they reach radar-controlled airspace. Moreover, it presents a search-and-rescue bottleneck. Aircraft in distress, e.g. Air France AF449 that crashed in 2009, take days to be located or cannot be located at all, e.g. Malaysia Airlines MH370 in 2014. In this paper, we describe a tool for designing a constellation of small satellites which demonstrates, through high-fidelity modeling based on simulated air traffic data, the value of space-based ADS-B monitoring and provides recommendations for cost-efficient deployment of a constellation of small satellites to increase safety and situational awareness in the currently poorly-served surveillance area of Alaska. Air traffic data has been obtained from the Future ATM Concepts Evaluation Tool (FACET), developed at NASA Ames Research Center, simulated over the Alaskan airspace over a period of one day. The simulation is driven by MATLAB with satellites propagated and coverage calculated using AGI's Satellite ToolKit(STK10).

Optimal spacecraft formation establishment and reconfiguration propelled by the geomagnetic Lorentz force

NASA Astrophysics Data System (ADS)

Huang, Xu; Yan, Ye; Zhou, Yang

2014-12-01

The Lorentz force acting on an electrostatically charged spacecraft as it moves through the planetary magnetic field could be utilized as propellantless electromagnetic propulsion for orbital maneuvering, such as spacecraft formation establishment and formation reconfiguration. By assuming that the Earth's magnetic field could be modeled as a tilted dipole located at the center of Earth that corotates with Earth, a dynamical model that describes the relative orbital motion of Lorentz spacecraft is developed. Based on the proposed dynamical model, the energy-optimal open-loop trajectories of control inputs, namely, the required specific charges of Lorentz spacecraft, for Lorentz-propelled spacecraft formation establishment or reconfiguration problems with both fixed and free final conditions constraints are derived via Gauss pseudospectral method. The effect of the magnetic dipole tilt angle on the optimal control inputs and the relative transfer trajectories for formation establishment or reconfiguration is also investigated by comparisons with the results derived from a nontilted dipole model. Furthermore, a closed-loop integral sliding mode controller is designed to guarantee the trajectory tracking in the presence of external disturbances and modeling errors. The stability of the closed-loop system is proved by a Lyapunov-based approach. Numerical simulations are presented to verify the validity of the proposed open-loop control methods and demonstrate the performance of the closed-loop controller. Also, the results indicate the dipole tilt angle should be considered when designing control strategies for Lorentz-propelled spacecraft formation establishment or reconfiguration.

Optimal dynamic voltage scaling for wireless sensor nodes with real-time constraints

NASA Astrophysics Data System (ADS)

Cassandras, Christos G.; Zhuang, Shixin

2005-11-01

Sensors are increasingly embedded in manufacturing systems and wirelessly networked to monitor and manage operations ranging from process and inventory control to tracking equipment and even post-manufacturing product monitoring. In building such sensor networks, a critical issue is the limited and hard to replenish energy in the devices involved. Dynamic voltage scaling is a technique that controls the operating voltage of a processor to provide desired performance while conserving energy and prolonging the overall network's lifetime. We consider such power-limited devices processing time-critical tasks which are non-preemptive, aperiodic and have uncertain arrival times. We treat voltage scaling as a dynamic optimization problem whose objective is to minimize energy consumption subject to hard or soft real-time execution constraints. In the case of hard constraints, we build on prior work (which engages a voltage scaling controller at task completion times) by developing an intra-task controller that acts at all arrival times of incoming tasks. We show that this optimization problem can be decomposed into two simpler ones whose solution leads to an algorithm that does not actually require solving any nonlinear programming problems. In the case of soft constraints, this decomposition must be partly relaxed, but it still leads to a scalable (linear in the number of tasks) algorithm. Simulation results are provided to illustrate performance improvements in systems with intra-task controllers compared to uncontrolled systems or those using inter-task control.

A post-processing system for automated rectification and registration of spaceborne SAR imagery

NASA Technical Reports Server (NTRS)

Curlander, John C.; Kwok, Ronald; Pang, Shirley S.

1987-01-01

An automated post-processing system has been developed that interfaces with the raw image output of the operational digital SAR correlator. This system is designed for optimal efficiency by using advanced signal processing hardware and an algorithm that requires no operator interaction, such as the determination of ground control points. The standard output is a geocoded image product (i.e. resampled to a specified map projection). The system is capable of producing multiframe mosaics for large-scale mapping by combining images in both the along-track direction and adjacent cross-track swaths from ascending and descending passes over the same target area. The output products have absolute location uncertainty of less than 50 m and relative distortion (scale factor and skew) of less than 0.1 per cent relative to local variations from the assumed geoid.

Direct power control of DFIG wind turbine systems based on an intelligent proportional-integral sliding mode control.

PubMed

Li, Shanzhi; Wang, Haoping; Tian, Yang; Aitouch, Abdel; Klein, John

2016-09-01

This paper presents an intelligent proportional-integral sliding mode control (iPISMC) for direct power control of variable speed-constant frequency wind turbine system. This approach deals with optimal power production (in the maximum power point tracking sense) under several disturbance factors such as turbulent wind. This controller is made of two sub-components: (i) an intelligent proportional-integral module for online disturbance compensation and (ii) a sliding mode module for circumventing disturbance estimation errors. This iPISMC method has been tested on FAST/Simulink platform of a 5MW wind turbine system. The obtained results demonstrate that the proposed iPISMC method outperforms the classical PI and intelligent proportional-integral control (iPI) in terms of both active power and response time. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Error mapping controller: a closed loop neuroprosthesis controlled by artificial neural networks.

PubMed

Pedrocchi, Alessandra; Ferrante, Simona; De Momi, Elena; Ferrigno, Giancarlo

2006-10-09

The design of an optimal neuroprostheses controller and its clinical use presents several challenges. First, the physiological system is characterized by highly inter-subjects varying properties and also by non stationary behaviour with time, due to conditioning level and fatigue. Secondly, the easiness to use in routine clinical practice requires experienced operators. Therefore, feedback controllers, avoiding long setting procedures, are required. The error mapping controller (EMC) here proposed uses artificial neural networks (ANNs) both for the design of an inverse model and of a feedback controller. A neuromuscular model is used to validate the performance of the controllers in simulations. The EMC performance is compared to a Proportional Integral Derivative (PID) included in an anti wind-up scheme (called PIDAW) and to a controller with an ANN as inverse model and a PID in the feedback loop (NEUROPID). In addition tests on the EMC robustness in response to variations of the Plant parameters and to mechanical disturbances are carried out. The EMC shows improvements with respect to the other controllers in tracking accuracy, capability to prolong exercise managing fatigue, robustness to parameter variations and resistance to mechanical disturbances. Different from the other controllers, the EMC is capable of balancing between tracking accuracy and mapping of fatigue during the exercise. In this way, it avoids overstressing muscles and allows a considerable prolongation of the movement. The collection of the training sets does not require any particular experimental setting and can be introduced in routine clinical practice.

A Closed-Loop Proportional-Integral (PI) Control Software for Fully Mechanically Controlled Automated Electron Microscopic Tomography

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

REN, GANG; LIU, JINXIN; LI, HONGCHANG

A closed-loop proportional-integral (PI) control software is provided for fully mechanically controlled automated electron microscopic tomography. The software is developed based on Gatan DigitalMicrograph, and is compatible with Zeiss LIBRA 120 transmission electron microscope. However, it can be expanded to other TEM instrument with modification. The software consists of a graphical user interface, a digital PI controller, an image analyzing unit, and other drive units (i.e.: image acquire unit and goniometer drive unit). During a tomography data collection process, the image analyzing unit analyzes both the accumulated shift and defocus value of the latest acquired image, and provides the resultsmore » to the digital PI controller. The digital PI control compares the results with the preset values and determines the optimum adjustments of the goniometer. The goniometer drive unit adjusts the spatial position of the specimen according to the instructions given by the digital PI controller for the next tilt angle and image acquisition. The goniometer drive unit achieves high precision positioning by using a backlash elimination method. The major benefits of the software are: 1) the goniometer drive unit keeps pre-aligned/optimized beam conditions unchanged and achieves position tracking solely through mechanical control; 2) the image analyzing unit relies on only historical data and therefore does not require additional images/exposures; 3) the PI controller enables the system to dynamically track the imaging target with extremely low system error.« less

Error mapping controller: a closed loop neuroprosthesis controlled by artificial neural networks

PubMed Central

Pedrocchi, Alessandra; Ferrante, Simona; De Momi, Elena; Ferrigno, Giancarlo

2006-01-01

Background The design of an optimal neuroprostheses controller and its clinical use presents several challenges. First, the physiological system is characterized by highly inter-subjects varying properties and also by non stationary behaviour with time, due to conditioning level and fatigue. Secondly, the easiness to use in routine clinical practice requires experienced operators. Therefore, feedback controllers, avoiding long setting procedures, are required. Methods The error mapping controller (EMC) here proposed uses artificial neural networks (ANNs) both for the design of an inverse model and of a feedback controller. A neuromuscular model is used to validate the performance of the controllers in simulations. The EMC performance is compared to a Proportional Integral Derivative (PID) included in an anti wind-up scheme (called PIDAW) and to a controller with an ANN as inverse model and a PID in the feedback loop (NEUROPID). In addition tests on the EMC robustness in response to variations of the Plant parameters and to mechanical disturbances are carried out. Results The EMC shows improvements with respect to the other controllers in tracking accuracy, capability to prolong exercise managing fatigue, robustness to parameter variations and resistance to mechanical disturbances. Conclusion Different from the other controllers, the EMC is capable of balancing between tracking accuracy and mapping of fatigue during the exercise. In this way, it avoids overstressing muscles and allows a considerable prolongation of the movement. The collection of the training sets does not require any particular experimental setting and can be introduced in routine clinical practice. PMID:17029636

Data-driven model reference control of MIMO vertical tank systems with model-free VRFT and Q-Learning.

PubMed

Radac, Mircea-Bogdan; Precup, Radu-Emil; Roman, Raul-Cristian

2018-02-01

This paper proposes a combined Virtual Reference Feedback Tuning-Q-learning model-free control approach, which tunes nonlinear static state feedback controllers to achieve output model reference tracking in an optimal control framework. The novel iterative Batch Fitted Q-learning strategy uses two neural networks to represent the value function (critic) and the controller (actor), and it is referred to as a mixed Virtual Reference Feedback Tuning-Batch Fitted Q-learning approach. Learning convergence of the Q-learning schemes generally depends, among other settings, on the efficient exploration of the state-action space. Handcrafting test signals for efficient exploration is difficult even for input-output stable unknown processes. Virtual Reference Feedback Tuning can ensure an initial stabilizing controller to be learned from few input-output data and it can be next used to collect substantially more input-state data in a controlled mode, in a constrained environment, by compensating the process dynamics. This data is used to learn significantly superior nonlinear state feedback neural networks controllers for model reference tracking, using the proposed Batch Fitted Q-learning iterative tuning strategy, motivating the original combination of the two techniques. The mixed Virtual Reference Feedback Tuning-Batch Fitted Q-learning approach is experimentally validated for water level control of a multi input-multi output nonlinear constrained coupled two-tank system. Discussions on the observed control behavior are offered. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Enhanced condensation heat transfer with wettability patterning

NASA Astrophysics Data System (ADS)

Sinha Mahapatra, Pallab; Ghosh, Aritra; Ganguly, Ranjan; Megaridis, Constantine

2015-11-01

Condensation of water vapor on metal surfaces is useful for many engineering applications. A facile and scalable method is proposed for removing condensate from a vertical plate during dropwise condensation (DWC) in the presence of non-condensable gases (NCG). We use wettability-patterned superhydrophilic tracks (filmwise condensing domains) on a mirror-finish (hydrophilic) aluminum surface that promotes DWC. Tapered, horizontal ``collection'' tracks are laid to create a Laplace pressure driven flow, which collects condensate from the mirror-finish domains and sends it to vertical ``drainage tracks'' for gravity-induced shedding. An optimal design is achieved by changing the fractional area of superhydrophilic tracks with respect to the overall plate surface, and augmenting capillary-driven condensate-drainage by adjusting the track spatial layout. The design facilitates pump-less condensate drainage and enhances DWC heat transfer on the mirror-finish regions. The study highlights the relative influences of the promoting and retarding effects of dropwise and filmwise condensation zones on the overall heat transfer improvement on the substrate. The study demonstrated ~ 34% heat transfer improvement on Aluminum surface for the optimized design.

Tracking Virus Particles in Fluorescence Microscopy Images Using Multi-Scale Detection and Multi-Frame Association.

PubMed

Jaiswal, Astha; Godinez, William J; Eils, Roland; Lehmann, Maik Jorg; Rohr, Karl

2015-11-01

Automatic fluorescent particle tracking is an essential task to study the dynamics of a large number of biological structures at a sub-cellular level. We have developed a probabilistic particle tracking approach based on multi-scale detection and two-step multi-frame association. The multi-scale detection scheme allows coping with particles in close proximity. For finding associations, we have developed a two-step multi-frame algorithm, which is based on a temporally semiglobal formulation as well as spatially local and global optimization. In the first step, reliable associations are determined for each particle individually in local neighborhoods. In the second step, the global spatial information over multiple frames is exploited jointly to determine optimal associations. The multi-scale detection scheme and the multi-frame association finding algorithm have been combined with a probabilistic tracking approach based on the Kalman filter. We have successfully applied our probabilistic tracking approach to synthetic as well as real microscopy image sequences of virus particles and quantified the performance. We found that the proposed approach outperforms previous approaches.

Robust control of dielectric elastomer diaphragm actuator for human pulse signal tracking

NASA Astrophysics Data System (ADS)

Ye, Zhihang; Chen, Zheng; Asmatulu, Ramazan; Chan, Hoyin

2017-08-01

Human pulse signal tracking is an emerging technology that is needed in traditional Chinese medicine. However, soft actuation with multi-frequency tracking capability is needed for tracking human pulse signal. Dielectric elastomer (DE) is one type of soft actuating that has great potential in human pulse signal tracking. In this paper, a DE diaphragm actuator was designed and fabricated to track human pulse pressure signal. A physics-based and control-oriented model has been developed to capture the dynamic behavior of DE diaphragm actuator. Using the physical model, an H-infinity robust control was designed for the actuator to reject high-frequency sensing noises and disturbances. The robust control was then implemented in real-time to track a multi-frequency signal, which verified the tracking capability and robustness of the control system. In the human pulse signal tracking test, a human pulse signal was measured at the City University of Hong Kong and then was tracked using DE actuator at Wichita State University in the US. Experimental results have verified that the DE actuator with its robust control is capable of tracking human pulse signal.

Fully Mechanically Controlled Automated Electron Microscopic Tomography

DOE PAGES

Liu, Jinxin; Li, Hongchang; Zhang, Lei; ...

2016-07-11

Knowledge of three-dimensional (3D) structures of each individual particles of asymmetric and flexible proteins is essential in understanding those proteins' functions; but their structures are difficult to determine. Electron tomography (ET) provides a tool for imaging a single and unique biological object from a series of tilted angles, but it is challenging to image a single protein for three-dimensional (3D) reconstruction due to the imperfect mechanical control capability of the specimen goniometer under both a medium to high magnification (approximately 50,000-160,000×) and an optimized beam coherence condition. Here, we report a fully mechanical control method for automating ET data acquisitionmore » without using beam tilt/shift processes. This method could reduce the accumulation of beam tilt/shift that used to compensate the error from the mechanical control, but downgraded the beam coherence. Our method was developed by minimizing the error of the target object center during the tilting process through a closed-loop proportional-integral (PI) control algorithm. The validations by both negative staining (NS) and cryo-electron microscopy (cryo-EM) suggest that this method has a comparable capability to other ET methods in tracking target proteins while maintaining optimized beam coherence conditions for imaging.« less

A three-level support method for smooth switching of the micro-grid operation model

NASA Astrophysics Data System (ADS)

Zong, Yuanyang; Gong, Dongliang; Zhang, Jianzhou; Liu, Bin; Wang, Yun

2018-01-01

Smooth switching of micro-grid between the grid-connected operation mode and off-grid operation mode is one of the key technologies to ensure it runs flexible and efficiently. The basic control strategy and the switching principle of micro-grid are analyzed in this paper. The reasons for the fluctuations of the voltage and the frequency in the switching process are analyzed from views of power balance and control strategy, and the operation mode switching strategy has been improved targeted. From the three aspects of controller’s current inner loop reference signal, voltage outer loop control strategy optimization and micro-grid energy balance management, a three-level security strategy for smooth switching of micro-grid operation mode is proposed. From the three aspects of controller’s current inner loop reference signal tracking, voltage outer loop control strategy optimization and micro-grid energy balance management, a three-level strategy for smooth switching of micro-grid operation mode is proposed. At last, it is proved by simulation that the proposed control strategy can make the switching process smooth and stable, the fluctuation problem of the voltage and frequency has been effectively improved.

Optimal digital filtering for tremor suppression.

PubMed

Gonzalez, J G; Heredia, E A; Rahman, T; Barner, K E; Arce, G R

2000-05-01

Remote manually operated tasks such as those found in teleoperation, virtual reality, or joystick-based computer access, require the generation of an intermediate electrical signal which is transmitted to the controlled subsystem (robot arm, virtual environment, or a cursor in a computer screen). When human movements are distorted, for instance, by tremor, performance can be improved by digitally filtering the intermediate signal before it reaches the controlled device. This paper introduces a novel tremor filtering framework in which digital equalizers are optimally designed through pursuit tracking task experiments. Due to inherent properties of the man-machine system, the design of tremor suppression equalizers presents two serious problems: 1) performance criteria leading to optimizations that minimize mean-squared error are not efficient for tremor elimination and 2) movement signals show ill-conditioned autocorrelation matrices, which often result in useless or unstable solutions. To address these problems, a new performance indicator in the context of tremor is introduced, and the optimal equalizer according to this new criterion is developed. Ill-conditioning of the autocorrelation matrix is overcome using a novel method which we call pulled-optimization. Experiments performed with artificially induced vibrations and a subject with Parkinson's disease show significant improvement in performance. Additional results, along with MATLAB source code of the algorithms, and a customizable demo for PC joysticks, are available on the Internet at http:¿tremor-suppression.com.

Tonopah Test Range - Index

Science.gov Websites

Capabilities Test Operations Center Test Director Range Control Track Control Communications Tracking Radars Us Range Videos/Photos Range Capabilities Test Operations Center Test Director Range Control Track Control Communications Tracking Radars Optical Systems Cinetheodolites Telescopes R&D Telescopes

Prototype Test Results for the Single Photon Detection SLR2000 Satellite Laser Ranging System

NASA Technical Reports Server (NTRS)

Zagwodzki, Thomas W.; McGarry, Jan F.; Degnan, John J.; Cheek, Jack W.; Dunn, Peter J.; Patterson, Don; Donovan, Howard

2004-01-01

NASA's aging Satellite Laser Ranging (SLR) network is scheduled to be replaced over the next few years with a fully automated single photon detection system. A prototype of this new system, called SLR2000, is currently undergoing field trials at the Goddard Space Flight Center in Greenbelt, Maryland to evaluate photon counting techniques and determine system hardware, software, and control algorithm performance levels and limitations. Newly developed diode pumped microchip lasers and quadrant microchannel plate-based photomultiplier tubes have enabled the development of this high repetition rate single photon detection SLR system. The SLR2000 receiver threshold is set at the single photoelectron (pe) level but tracks satellites with an average signal level typically much less than 1 pe. The 2 kHz laser fire rate aids in satellite acquisition and tracking and will enable closed loop tracking by accumulating single photon count statistics in a quadrant detector and using this information to correct for pointing errors. Laser transmitter beamwidths of 10 arcseconds (FWHM) or less are currently being used to maintain an adequate signal level for tracking while the receiver field of view (FOV) has been opened to 40 arcseconds to accommodate point ahead/look behind angular offsets. In the near future, the laser transmitter point ahead will be controlled by a pair of Risley prisms. This will allow the telescope to point behind and enable closure of the receiver FOV to roughly match the transmitter beam divergence. Bandpass filters (BPF) are removed for night tracking operations while 0.2 nm or 1 nm filters are used during daylight operation. Both day and night laser tracking of Low Earth Orbit (LEO) satellites has been achieved with a laser transmitter energy of only 65 microjoules per pulse. Satellite tracking is presently limited to LEO satellites until the brassboard laser transmitter can be upgraded or replaced. Simultaneous tracks have also been observed with NASA s SLR standard, MOBLAS 7, for the purposes of data comparison and identification of biases. Work continues to optimize the receive optics; upgrade or replace the laser transmitter; calibrate the quadrant detector, the point ahead Risley prisms, and event timer verniers; and test normal point generation with SLR2000 data. This paper will report on the satellite tracking results to date, issues yet to be resolved, and future plans for the SLR2000 system.

Flexible Fusion Structure-Based Performance Optimization Learning for Multisensor Target Tracking

PubMed Central

Ge, Quanbo; Wei, Zhongliang; Cheng, Tianfa; Chen, Shaodong; Wang, Xiangfeng

2017-01-01

Compared with the fixed fusion structure, the flexible fusion structure with mixed fusion methods has better adjustment performance for the complex air task network systems, and it can effectively help the system to achieve the goal under the given constraints. Because of the time-varying situation of the task network system induced by moving nodes and non-cooperative target, and limitations such as communication bandwidth and measurement distance, it is necessary to dynamically adjust the system fusion structure including sensors and fusion methods in a given adjustment period. Aiming at this, this paper studies the design of a flexible fusion algorithm by using an optimization learning technology. The purpose is to dynamically determine the sensors’ numbers and the associated sensors to take part in the centralized and distributed fusion processes, respectively, herein termed sensor subsets selection. Firstly, two system performance indexes are introduced. Especially, the survivability index is presented and defined. Secondly, based on the two indexes and considering other conditions such as communication bandwidth and measurement distance, optimization models for both single target tracking and multi-target tracking are established. Correspondingly, solution steps are given for the two optimization models in detail. Simulation examples are demonstrated to validate the proposed algorithms. PMID:28481243

Application of RFID in the area of agricultural products quality traceability and tracking and the anti-collision algorithm

NASA Astrophysics Data System (ADS)

Wang, Zu-liang; Zhang, Ting; Xie, Shi-yang

2017-01-01

In order to improve the agricultural tracing efficiency and reduce tracking and monitoring cost, agricultural products quality tracking and tracing based on Radio-Frequency Identification(RFID) technology is studied, then tracing and tracking model is set up. Three-layer structure model is established to realize the high quality of agricultural products traceability and tracking. To solve the collision problems between multiple RFID tags and improve the identification efficiency a new reservation slot allocation mechanism is proposed. And then we analyze and optimize the parameter by numerical simulation method.

Cluster flight control for fractionated spacecraft on an elliptic orbit

NASA Astrophysics Data System (ADS)

Xu, Ming; Liang, Yuying; Tan, Tian; Wei, Lixin

2016-08-01

This paper deals with the stabilization of cluster flight on an elliptic reference orbit by the Hamiltonian structure-preserving control using the relative position measurement only. The linearized Melton's relative equation is utilized to derive the controller and then the full nonlinear relative dynamics are employed to numerically evaluate the controller's performance. In this paper, the hyperbolic and elliptic eigenvalues and their manifolds are treated without distinction notations. This new treatment not only contributes to solving the difficulty in feedback of the unfixed-dimensional manifolds, but also allows more opportunities to set the controlled frequencies of foundational motions or to optimize control gains. Any initial condition can be stabilized on a Kolmogorov-Arnold-Moser torus near a controlled elliptic equilibrium. The motions are stabilized around the natural relative trajectories rather than track a reference relative configuration. In addition, the bounded quasi-periodic trajectories generated by the controller have advantages in rapid reconfiguration and unpredictable evolution.

Nonlinear Adaptive PID Control for Greenhouse Environment Based on RBF Network

PubMed Central

Zeng, Songwei; Hu, Haigen; Xu, Lihong; Li, Guanghui

2012-01-01

This paper presents a hybrid control strategy, combining Radial Basis Function (RBF) network with conventional proportional, integral, and derivative (PID) controllers, for the greenhouse climate control. A model of nonlinear conservation laws of enthalpy and matter between numerous system variables affecting the greenhouse climate is formulated. RBF network is used to tune and identify all PID gain parameters online and adaptively. The presented Neuro-PID control scheme is validated through simulations of set-point tracking and disturbance rejection. We compare the proposed adaptive online tuning method with the offline tuning scheme that employs Genetic Algorithm (GA) to search the optimal gain parameters. The results show that the proposed strategy has good adaptability, strong robustness and real-time performance while achieving satisfactory control performance for the complex and nonlinear greenhouse climate control system, and it may provide a valuable reference to formulate environmental control strategies for actual application in greenhouse production. PMID:22778587

A variable structure approach to robust control of VTOL aircraft

NASA Technical Reports Server (NTRS)

Calise, A. J.; Kramer, F.

1982-01-01

This paper examines the application of variable structure control theory to the design of a flight control system for the AV-8A Harrier in a hover mode. The objective in variable structure design is to confine the motion to a subspace of the total state space. The motion in this subspace is insensitive to system parameter variations and external disturbances that lie in the range space of the control. A switching type of control law results from the design procedure. The control system was designed to track a vector velocity command defined in the body frame. For comparison purposes, a proportional controller was designed using optimal linear regulator theory. Both control designs were first evaluated for transient response performance using a linearized model, then a nonlinear simulation study of a hovering approach to landing was conducted. Wind turbulence was modeled using a 1052 destroyer class air wake model.

Pilot modeling and closed-loop analysis of flexible aircraft in the pitch tracking task

NASA Technical Reports Server (NTRS)

Schmidt, D. K.

1983-01-01

The issue addressed in the appropriate modeling technique for pilot vehicle analysis of large flexible aircraft, when the frequency separation between the rigid-body mode and the dynamic aeroelastic modes is reduced. This situation was shown to have significant effects on pitch-tracking performance and subjective rating of the task, obtained via fixed base simulation. Further, the dynamics in these cases are not well modeled with a rigid-body-like model obtained by including only 'static elastic' effects, for example. It is shown that pilot/vehicle analysis of this data supports the hypothesis that an appropriate pilot-model structure is an optimal-control pilot model of full order. This is in contrast to the contention that a representative model is of reduced order when the subject is controlling high-order dynamics as in a flexible vehicle. The key appears to be in the correct assessment of the pilot's objective of attempting to control 'rigid-body' vehicle response, a response that must be estimated by the pilot from observations contaminated by aeroelastic dynamics. Finally, a model-based metric is shown to correlate well with the pilot's subjective ratings.

Contrast and assimilation in motion perception and smooth pursuit eye movements.

PubMed

Spering, Miriam; Gegenfurtner, Karl R

2007-09-01

The analysis of visual motion serves many different functions ranging from object motion perception to the control of self-motion. The perception of visual motion and the oculomotor tracking of a moving object are known to be closely related and are assumed to be controlled by shared brain areas. We compared perceived velocity and the velocity of smooth pursuit eye movements in human observers in a paradigm that required the segmentation of target object motion from context motion. In each trial, a pursuit target and a visual context were independently perturbed simultaneously to briefly increase or decrease in speed. Observers had to accurately track the target and estimate target speed during the perturbation interval. Here we show that the same motion signals are processed in fundamentally different ways for perception and steady-state smooth pursuit eye movements. For the computation of perceived velocity, motion of the context was subtracted from target motion (motion contrast), whereas pursuit velocity was determined by the motion average (motion assimilation). We conclude that the human motion system uses these computations to optimally accomplish different functions: image segmentation for object motion perception and velocity estimation for the control of smooth pursuit eye movements.

Mathematical model of marine diesel engine simulator for a new methodology of self propulsion tests

NASA Astrophysics Data System (ADS)

Izzuddin, Nur; Sunarsih, Priyanto, Agoes

2015-05-01

As a vessel operates in the open seas, a marine diesel engine simulator whose engine rotation is controlled to transmit through propeller shaft is a new methodology for the self propulsion tests to track the fuel saving in a real time. Considering the circumstance, this paper presents the real time of marine diesel engine simulator system to track the real performance of a ship through a computer-simulated model. A mathematical model of marine diesel engine and the propeller are used in the simulation to estimate fuel rate, engine rotating speed, thrust and torque of the propeller thus achieve the target vessel's speed. The input and output are a real time control system of fuel saving rate and propeller rotating speed representing the marine diesel engine characteristics. The self-propulsion tests in calm waters were conducted using a vessel model to validate the marine diesel engine simulator. The simulator then was used to evaluate the fuel saving by employing a new mathematical model of turbochargers for the marine diesel engine simulator. The control system developed will be beneficial for users as to analyze different condition of vessel's speed to obtain better characteristics and hence optimize the fuel saving rate.

The detrimental effect of friction on space microgravity robotics

NASA Technical Reports Server (NTRS)

Newman, Wyatt S.; Glosser, Gregory D.; Miller, Jeffrey H.; Rohn, Douglas

1992-01-01

The authors present an analysis of why control systems are ineffective in compensating for acceleration disturbances due to Coulomb friction. Linear arguments indicate that the effects of Coulomb friction on a body are most difficult to reject when the control actuator is separated from the body of compliance. The linear arguments were illustrated in a nonlinear simulation of optimal linear tracking control in the presence of nonlinear friction. The results of endpoint acceleration measurements for four robot designs are presented and are compared with simulation and to equivalent measurements on a human. It is concluded that Coulomb friction in common bearings and transmission induces unacceptable levels of endpoint acceleration, that these accelerations cannot be adequately attenuated by control, and that robots for microgravity work will require special design considerations for inherently low friction.

Innovative Technologies for Efficient Pharmacotherapeutic Management in Space

NASA Technical Reports Server (NTRS)

Putcha, Lakshmi; Daniels, Vernie

2014-01-01

Current and future Space exploration missions and extended human presence in space aboard the ISS will expose crew to risks that differ both quantitatively and qualitatively from those encountered before by space travelers and will impose an unknown risk of safety and crew health. The technology development challenges for optimizing therapeutics in space must include the development of pharmaceuticals with extended stability, optimal efficacy and bioavailability with minimal toxicity and side effects. Innovative technology development goals may include sustained/chronic delivery preventive health care products and vaccines, low-cost high-efficiency noninvasive, non-oral dosage forms with radio-protective formulation matrices and dispensing technologies coupled with self-reliant tracking technologies for quality assurance and quality control assessment. These revolutionary advances in pharmaceutical technology will assure human presence in space and healthy living on Earth. Additionally, the Joint Commission on Accreditation of Healthcare Organizations advocates the use of health information technologies to effectively execute all aspects of medication management (prescribing, dispensing, and administration). The advent of personalized medicine and highly streamlined treatment regimens stimulated interest in new technologies for medication management. Intelligent monitoring devices enhance medication accountability compliance, enable effective drug use, and offer appropriate storage and security conditions for dangerous drug and controlled substance medications in remote sites where traditional pharmacies are unavailable. These features are ideal for Exploration Medical Capabilities. This presentation will highlight current novel commercial off-the-shelf (COTS) intelligent medication management devices for the unique dispensing, therapeutic drug monitoring, medication tracking, and drug delivery demands of exploration space medical operations.

CD and defect improvement challenges for immersion processes

NASA Astrophysics Data System (ADS)

Ehara, Keisuke; Ema, Tatsuhiko; Yamasaki, Toshinari; Nakagawa, Seiji; Ishitani, Seiji; Morita, Akihiko; Kim, Jeonghun; Kanaoka, Masashi; Yasuda, Shuichi; Asai, Masaya

2009-03-01

The intention of this study is to develop an immersion lithography process using advanced track solutions to achieve world class critical dimension (CD) and defectivity performance in a state of the art manufacturing facility. This study looks at three important topics for immersion lithography: defectivity, CD control, and wafer backside contamination. The topic of defectivity is addressed through optimization of coat, develop, and rinse processes as well as implementation of soak steps and bevel cleaning as part of a comprehensive defect solution. Develop and rinse processing techniques are especially important in the effort to achieve a zero defect solution. Improved CD control is achieved using a biased hot plate (BHP) equipped with an electrostatic chuck. This electrostatic chuck BHP (eBHP) is not only able to operate at a very uniform temperature, but it also allows the user to bias the post exposure bake (PEB) temperature profile to compensate for systematic within-wafer (WiW) CD non-uniformities. Optimized CD results, pre and post etch, are presented for production wafers. Wafer backside particles can cause focus spots on an individual wafer or migrate to the exposure tool's wafer stage and cause problems for a multitude of wafers. A basic evaluation of the cleaning efficiency of a backside scrubber unit located on the track was performed as a precursor to a future study examining the impact of wafer backside condition on scanner focus errors as well as defectivity in an immersion scanner.

Ares-I Bending Filter Design using a Constrained Optimization Approach

NASA Technical Reports Server (NTRS)

Hall, Charles; Jang, Jiann-Woei; Hall, Robert; Bedrossian, Nazareth

2008-01-01

The Ares-I launch vehicle represents a challenging flex-body structural environment for control system design. Software filtering of the inertial sensor output is required to ensure adequate stable response to guidance commands while minimizing trajectory deviations. This paper presents a design methodology employing numerical optimization to develop the Ares-I bending filters. The design objectives include attitude tracking accuracy and robust stability with respect to rigid body dynamics, propellant slosh, and flex. Under the assumption that the Ares-I time-varying dynamics and control system can be frozen over a short period of time, the bending filters are designed to stabilize all the selected frozen-time launch control systems in the presence of parameter uncertainty. To ensure adequate response to guidance command, step response specifications are introduced as constraints in the optimization problem. Imposing these constrains minimizes performance degradation caused by the addition of the bending filters. The first stage bending filter design achieves stability by adding lag to the first structural frequency to phase stabilize the first flex mode while gain stabilizing the higher modes. The upper stage bending filter design gain stabilizes all the flex bending modes. The bending filter designs provided here have been demonstrated to provide stable first and second stage control systems in both Draper Ares Stability Analysis Tool (ASAT) and the MSFC MAVERIC 6DOF nonlinear time domain simulation.

The scheduling of tracking times for interplanetary spacecraft on the Deep Space Network

NASA Technical Reports Server (NTRS)

Webb, W. A.

1978-01-01

The Deep Space Network (DSN) is a network of tracking stations, located throughout the globe, used to track spacecraft for NASA's interplanetary missions. This paper describes a computer program, DSNTRAK, which provides an optimum daily tracking schedule for the DSN given the view periods at each station for a mission set of n spacecraft, where n is between 2 and 6. The objective function is specified in terms of relative total daily tracking time requirements between the n spacecraft. Linear programming is used to maximize the total daily tracking time and determine an optimal daily tracking schedule consistent with DSN station capabilities. DSNTRAK is used as part of a procedure to provide DSN load forecasting information for proposed future NASA mission sets.

Minimal time change detection algorithm for reconfigurable control system and application to aerospace

NASA Technical Reports Server (NTRS)

Kim, Sungwan

1994-01-01

System parameters should be tracked on-line to build a reconfigurable control system even though there exists an abrupt change. For this purpose, a new performance index that we are studying is the speed of adaptation- how quickly does the system determine that a change has occurred? In this paper, a new, robust algorithm that is optimized to minimize the time delay in detecting a change for fixed false alarm probability is proposed. Simulation results for the aircraft lateral motion with a known or unknown change in control gain matrices, in the presence of doublet input, indicate that the algorithm works fairly well. One of its distinguishing properties is that detection delay of this algorithm is superior to that of Whiteness Test.

Analysis of a Dynamic Multi-Track Airway Concept for Air Traffic Management

NASA Technical Reports Server (NTRS)

Wing, David J.; Smith, Jeremy C.; Ballin, Mark G.

2008-01-01

The Dynamic Multi-track Airways (DMA) Concept for Air Traffic Management (ATM) proposes a network of high-altitude airways constructed of multiple, closely spaced, parallel tracks designed to increase en-route capacity in high-demand airspace corridors. Segregated from non-airway operations, these multi-track airways establish high-priority traffic flow corridors along optimal routes between major terminal areas throughout the National Airspace System (NAS). Air traffic controllers transition aircraft equipped for DMA operations to DMA entry points, the aircraft use autonomous control of airspeed to fly the continuous-airspace airway and achieve an economic benefit, and controllers then transition the aircraft from the DMA exit to the terminal area. Aircraft authority within the DMA includes responsibility for spacing and/or separation from other DMA aircraft. The DMA controller is responsible for coordinating the entry and exit of traffic to and from the DMA and for traffic flow management (TFM), including adjusting DMA routing on a daily basis to account for predicted weather and wind patterns and re-routing DMAs in real time to accommodate unpredicted weather changes. However, the DMA controller is not responsible for monitoring the DMA for traffic separation. This report defines the mature state concept, explores its feasibility and performance, and identifies potential benefits. The report also discusses (a) an analysis of a single DMA, which was modeled within the NAS to assess capacity and determine the impact of a single DMA on regional sector loads and conflict potential; (b) a demand analysis, which was conducted to determine likely city-pair candidates for a nationwide DMA network and to determine the expected demand fraction; (c) two track configurations, which were modeled and analyzed for their operational characteristic; (d) software-prototype airborne capabilities developed for DMA operations research; (e) a feasibility analysis of key attributes in the concept design; (f) a near-term, transitional application of the DMA concept as a proving ground for new airborne technologies; and (g) conclusions. The analysis indicates that the operational feasibility of a national DMA network faces significant challenges, especially for interactions between DMAs and between DMA and non-DMA traffic. Provided these issues are resolved, sectors near DMAs could experience significant local capacity benefits.

Kalman Orbit Optimized Loop Tracking

NASA Technical Reports Server (NTRS)

Young, Lawrence E.; Meehan, Thomas K.

2011-01-01

Under certain conditions of low signal power and/or high noise, there is insufficient signal to noise ratio (SNR) to close tracking loops with individual signals on orbiting Global Navigation Satellite System (GNSS) receivers. In addition, the processing power available from flight computers is not great enough to implement a conventional ultra-tight coupling tracking loop. This work provides a method to track GNSS signals at very low SNR without the penalty of requiring very high processor throughput to calculate the loop parameters. The Kalman Orbit-Optimized Loop (KOOL) tracking approach constitutes a filter with a dynamic model and using the aggregate of information from all tracked GNSS signals to close the tracking loop for each signal. For applications where there is not a good dynamic model, such as very low orbits where atmospheric drag models may not be adequate to achieve the required accuracy, aiding from an IMU (inertial measurement unit) or other sensor will be added. The KOOL approach is based on research JPL has done to allow signal recovery from weak and scintillating signals observed during the use of GPS signals for limb sounding of the Earth s atmosphere. That approach uses the onboard PVT (position, velocity, time) solution to generate predictions for the range, range rate, and acceleration of the low-SNR signal. The low- SNR signal data are captured by a directed open loop. KOOL builds on the previous open loop tracking by including feedback and observable generation from the weak-signal channels so that the MSR receiver will continue to track and provide PVT, range, and Doppler data, even when all channels have low SNR.

Robust motion tracking based on adaptive speckle decorrelation analysis of OCT signal.

PubMed

Wang, Yuewen; Wang, Yahui; Akansu, Ali; Belfield, Kevin D; Hubbi, Basil; Liu, Xuan

2015-11-01

Speckle decorrelation analysis of optical coherence tomography (OCT) signal has been used in motion tracking. In our previous study, we demonstrated that cross-correlation coefficient (XCC) between Ascans had an explicit functional dependency on the magnitude of lateral displacement (δx). In this study, we evaluated the sensitivity of speckle motion tracking using the derivative of function XCC(δx) on variable δx. We demonstrated the magnitude of the derivative can be maximized. In other words, the sensitivity of OCT speckle tracking can be optimized by using signals with appropriate amount of decorrelation for XCC calculation. Based on this finding, we developed an adaptive speckle decorrelation analysis strategy to achieve motion tracking with optimized sensitivity. Briefly, we used subsequently acquired Ascans and Ascans obtained with larger time intervals to obtain multiple values of XCC and chose the XCC value that maximized motion tracking sensitivity for displacement calculation. Instantaneous motion speed can be calculated by dividing the obtained displacement with time interval between Ascans involved in XCC calculation. We implemented the above-described algorithm in real-time using graphic processing unit (GPU) and demonstrated its effectiveness in reconstructing distortion-free OCT images using data obtained from a manually scanned OCT probe. The adaptive speckle tracking method was validated in manually scanned OCT imaging, on phantom as well as in vivo skin tissue.

Robust motion tracking based on adaptive speckle decorrelation analysis of OCT signal

PubMed Central

Wang, Yuewen; Wang, Yahui; Akansu, Ali; Belfield, Kevin D.; Hubbi, Basil; Liu, Xuan

2015-01-01

Speckle decorrelation analysis of optical coherence tomography (OCT) signal has been used in motion tracking. In our previous study, we demonstrated that cross-correlation coefficient (XCC) between Ascans had an explicit functional dependency on the magnitude of lateral displacement (δx). In this study, we evaluated the sensitivity of speckle motion tracking using the derivative of function XCC(δx) on variable δx. We demonstrated the magnitude of the derivative can be maximized. In other words, the sensitivity of OCT speckle tracking can be optimized by using signals with appropriate amount of decorrelation for XCC calculation. Based on this finding, we developed an adaptive speckle decorrelation analysis strategy to achieve motion tracking with optimized sensitivity. Briefly, we used subsequently acquired Ascans and Ascans obtained with larger time intervals to obtain multiple values of XCC and chose the XCC value that maximized motion tracking sensitivity for displacement calculation. Instantaneous motion speed can be calculated by dividing the obtained displacement with time interval between Ascans involved in XCC calculation. We implemented the above-described algorithm in real-time using graphic processing unit (GPU) and demonstrated its effectiveness in reconstructing distortion-free OCT images using data obtained from a manually scanned OCT probe. The adaptive speckle tracking method was validated in manually scanned OCT imaging, on phantom as well as in vivo skin tissue. PMID:26600996

Node Depth Adjustment Based Target Tracking in UWSNs Using Improved Harmony Search.

PubMed

Liu, Meiqin; Zhang, Duo; Zhang, Senlin; Zhang, Qunfei

2017-12-04

Underwater wireless sensor networks (UWSNs) can provide a promising solution to underwater target tracking. Due to the limited computation and bandwidth resources, only a small part of nodes are selected to track the target at each interval. How to improve tracking accuracy with a small number of nodes is a key problem. In recent years, a node depth adjustment system has been developed and applied to issues of network deployment and routing protocol. As far as we know, all existing tracking schemes keep underwater nodes static or moving with water flow, and node depth adjustment has not been utilized for underwater target tracking yet. This paper studies node depth adjustment method for target tracking in UWSNs. Firstly, since a Fisher Information Matrix (FIM) can quantify the estimation accuracy, its relation to node depth is derived as a metric. Secondly, we formulate the node depth adjustment as an optimization problem to determine moving depth of activated node, under the constraint of moving range, the value of FIM is used as objective function, which is aimed to be minimized over moving distance of nodes. Thirdly, to efficiently solve the optimization problem, an improved Harmony Search (HS) algorithm is proposed, in which the generating probability is modified to improve searching speed and accuracy. Finally, simulation results are presented to verify performance of our scheme.

Node Depth Adjustment Based Target Tracking in UWSNs Using Improved Harmony Search

PubMed Central

Zhang, Senlin; Zhang, Qunfei

2017-01-01

Underwater wireless sensor networks (UWSNs) can provide a promising solution to underwater target tracking. Due to the limited computation and bandwidth resources, only a small part of nodes are selected to track the target at each interval. How to improve tracking accuracy with a small number of nodes is a key problem. In recent years, a node depth adjustment system has been developed and applied to issues of network deployment and routing protocol. As far as we know, all existing tracking schemes keep underwater nodes static or moving with water flow, and node depth adjustment has not been utilized for underwater target tracking yet. This paper studies node depth adjustment method for target tracking in UWSNs. Firstly, since a Fisher Information Matrix (FIM) can quantify the estimation accuracy, its relation to node depth is derived as a metric. Secondly, we formulate the node depth adjustment as an optimization problem to determine moving depth of activated node, under the constraint of moving range, the value of FIM is used as objective function, which is aimed to be minimized over moving distance of nodes. Thirdly, to efficiently solve the optimization problem, an improved Harmony Search (HS) algorithm is proposed, in which the generating probability is modified to improve searching speed and accuracy. Finally, simulation results are presented to verify performance of our scheme. PMID:29207541

Automated tracking for advanced satellite laser ranging systems

NASA Astrophysics Data System (ADS)

McGarry, Jan F.; Degnan, John J.; Titterton, Paul J., Sr.; Sweeney, Harold E.; Conklin, Brion P.; Dunn, Peter J.

1996-06-01

NASA's Satellite Laser Ranging Network was originally developed during the 1970's to track satellites carrying corner cube reflectors. Today eight NASA systems, achieving millimeter ranging precision, are part of a global network of more than 40 stations that track 17 international satellites. To meet the tracking demands of a steadily growing satellite constellation within existing resources, NASA is embarking on a major automation program. While manpower on the current systems will be reduced to a single operator, the fully automated SLR2000 system is being designed to operate for months without human intervention. Because SLR2000 must be eyesafe and operate in daylight, tracking is often performed in a low probability of detection and high noise environment. The goal is to automatically select the satellite, setup the tracking and ranging hardware, verify acquisition, and close the tracking loop to optimize data yield. TO accomplish the autotracking tasks, we are investigating (1) improved satellite force models, (2) more frequent updates of orbital ephemerides, (3) lunar laser ranging data processing techniques to distinguish satellite returns from noise, and (4) angular detection and search techniques to acquire the satellite. A Monte Carlo simulator has been developed to allow optimization of the autotracking algorithms by modeling the relevant system errors and then checking performance against system truth. A combination of simulator and preliminary field results will be presented.

Influence of ultrasound speckle tracking strategies for motion and strain estimation.

PubMed

Curiale, Ariel H; Vegas-Sánchez-Ferrero, Gonzalo; Aja-Fernández, Santiago

2016-08-01

Speckle Tracking is one of the most prominent techniques used to estimate the regional movement of the heart based on ultrasound acquisitions. Many different approaches have been proposed, proving their suitability to obtain quantitative and qualitative information regarding myocardial deformation, motion and function assessment. New proposals to improve the basic algorithm usually focus on one of these three steps: (1) the similarity measure between images and the speckle model; (2) the transformation model, i.e. the type of motion considered between images; (3) the optimization strategies, such as the use of different optimization techniques in the transformation step or the inclusion of structural information. While many contributions have shown their good performance independently, it is not always clear how they perform when integrated in a whole pipeline. Every step will have a degree of influence over the following and hence over the final result. Thus, a Speckle Tracking pipeline must be analyzed as a whole when developing novel methods, since improvements in a particular step might be undermined by the choices taken in further steps. This work presents two main contributions: (1) We provide a complete analysis of the influence of the different steps in a Speckle Tracking pipeline over the motion and strain estimation accuracy. (2) The study proposes a methodology for the analysis of Speckle Tracking systems specifically designed to provide an easy and systematic way to include other strategies. We close the analysis with some conclusions and recommendations that can be used as an orientation of the degree of influence of the models for speckle, the transformation models, interpolation schemes and optimization strategies over the estimation of motion features. They can be further use to evaluate and design new strategy into a Speckle Tracking system. Copyright © 2016 Elsevier B.V. All rights reserved.

All-automatic swimmer tracking system based on an optimized scaled composite JTC technique

NASA Astrophysics Data System (ADS)

Benarab, D.; Napoléon, T.; Alfalou, A.; Verney, A.; Hellard, P.

2016-04-01

In this paper, an all-automatic optimized JTC based swimmer tracking system is proposed and evaluated on real video database outcome from national and international swimming competitions (French National Championship, Limoges 2015, FINA World Championships, Barcelona 2013 and Kazan 2015). First, we proposed to calibrate the swimming pool using the DLT algorithm (Direct Linear Transformation). DLT calculates the homography matrix given a sufficient set of correspondence points between pixels and metric coordinates: i.e. DLT takes into account the dimensions of the swimming pool and the type of the swim. Once the swimming pool is calibrated, we extract the lane. Then we apply a motion detection approach to detect globally the swimmer in this lane. Next, we apply our optimized Scaled Composite JTC which consists of creating an adapted input plane that contains the predicted region and the head reference image. This latter is generated using a composite filter of fin images chosen from the database. The dimension of this reference will be scaled according to the ratio between the head's dimension and the width of the swimming lane. Finally, applying the proposed approach improves the performances of our previous tracking method by adding a detection module in order to achieve an all-automatic swimmer tracking system.

Cadence Tracking and Disturbance Rejection in Functional Electrical Stimulation Cycling for Paraplegic Subjects: A Case Study.

PubMed

Fonseca, Lucas O da; Bó, Antônio P L; Guimarães, Juliana A; Gutierrez, Miguel E; Fachin-Martins, Emerson

2017-11-01

Functional electrical stimulation cycling has been proposed as an assistive technology with numerous health and fitness benefits for people with spinal cord injury, such as improvement in cardiovascular function, increase in muscular mass, and reduction of bone mass loss. However, some limitations, for example, lack of optimal control strategies that would delay fatigue, may still prevent this technology from achieving its full potential. In this work, we performed experiments on a person with complete spinal cord injury using a stationary tadpole trike when both cadence tracking and disturbance rejection were evaluated. In addition, two sets of experiments were conducted 6 months apart and considering activation of different muscles. The results showed that reference tracking is achieved above the cadence of 25 rpm with mean absolute errors between 1.9 and 10% when only quadriceps are activated. The disturbance test revealed that interferences may drop the cadence but do not interrupt a continuous movement if the cadence does not drop below 25 rpm, again when only quadriceps are activated. When other muscle groups were added, strong spasticity caused larger errors on reference tracking, but not when a disturbance was applied. In addition, spasticity caused the last experiments to result in less smooth cycling. © 2017 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Photochemical grid model implementation and application of ...

EPA Pesticide Factsheets

For the purposes of developing optimal emissions control strategies, efficient approaches are needed to identify the major sources or groups of sources that contribute to elevated ozone (O3) concentrations. Source-based apportionment techniques implemented in photochemical grid models track sources through the physical and chemical processes important to the formation and transport of air pollutants. Photochemical model source apportionment has been used to track source impacts of specific sources, groups of sources (sectors), sources in specific geographic areas, and stratospheric and lateral boundary inflow on O3. The implementation and application of a source apportionment technique for O3 and its precursors, nitrogen oxides (NOx) and volatile organic compounds (VOCs), for the Community Multiscale Air Quality (CMAQ) model are described here. The Integrated Source Apportionment Method (ISAM) O3 approach is a hybrid of source apportionment and source sensitivity in that O3 production is attributed to precursor sources based on O3 formation regime (e.g., for a NOx-sensitive regime, O3 is apportioned to participating NOx emissions). This implementation is illustrated by tracking multiple emissions source sectors and lateral boundary inflow. NOx, VOC, and O3 attribution to tracked sectors in the application are consistent with spatial and temporal patterns of precursor emissions. The O3 ISAM implementation is further evaluated through comparisons of apportioned am

Implementation of fuzzy-sliding mode based control of a grid connected photovoltaic system.

PubMed

Menadi, Abdelkrim; Abdeddaim, Sabrina; Ghamri, Ahmed; Betka, Achour

2015-09-01

The present work describes an optimal operation of a small scale photovoltaic system connected to a micro-grid, based on both sliding mode and fuzzy logic control. Real time implementation is done through a dSPACE 1104 single board, controlling a boost chopper on the PV array side and a voltage source inverter (VSI) on the grid side. The sliding mode controller tracks permanently the maximum power of the PV array regardless of atmospheric condition variations, while The fuzzy logic controller (FLC) regulates the DC-link voltage, and ensures via current control of the VSI a quasi-total transit of the extracted PV power to the grid under a unity power factor operation. Simulation results, carried out via Matlab-Simulink package were approved through experiment, showing the effectiveness of the proposed control techniques. Copyright © 2015. Published by Elsevier Ltd.

Real-Time Minimization of Tracking Error for Aircraft Systems

NASA Technical Reports Server (NTRS)

Garud, Sumedha; Kaneshige, John T.; Krishnakumar, Kalmanje S.; Kulkarni, Nilesh V.; Burken, John

2013-01-01

This technology presents a novel, stable, discrete-time adaptive law for flight control in a Direct adaptive control (DAC) framework. Where errors are not present, the original control design has been tuned for optimal performance. Adaptive control works towards achieving nominal performance whenever the design has modeling uncertainties/errors or when the vehicle suffers substantial flight configuration change. The baseline controller uses dynamic inversion with proportional-integral augmentation. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to a dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. If the system senses that at least one aircraft component is experiencing an excursion and the return of this component value toward its reference value is not proceeding according to the expected controller characteristics, then the neural network (NN) modeling of aircraft operation may be changed.

Planning 4D intensity-modulated arc therapy for tumor tracking with a multileaf collimator

NASA Astrophysics Data System (ADS)

Niu, Ying; Betzel, Gregory T.; Yang, Xiaocheng; Gui, Minzhi; Parke, William C.; Yi, Byongyong; Yu, Cedric X.

2017-02-01

This study introduces a practical four-dimensional (4D) planning scheme of IMAT using 4D computed tomography (4D CT) for planning tumor tracking with dynamic multileaf beam collimation. We assume that patients can breathe regularly, i.e. the same way as during 4D CT with an unchanged period and amplitude, and that the start of 4D-IMAT delivery can be synchronized with a designated respiratory phase. Each control point of the IMAT-delivery process can be associated with an image set of 4D CT at a specified respiratory phase. Target is contoured at each respiratory phase without a motion-induced margin. A 3D-IMAT plan is first optimized on a reference-phase image set of 4D CT. Then, based on the projections of the planning target volume in the beam’s eye view at different respiratory phases, a 4D-IMAT plan is generated by transforming the segments of the optimized 3D plan by using a direct aperture deformation method. Compensation for both translational and deformable tumor motion is accomplished, and the smooth delivery of the transformed plan is ensured by forcing connectivity between adjacent angles (control points). It is envisioned that the resultant plans can be delivered accurately using the dose rate regulated tracking method which handles breathing irregularities (Yi et al 2008 Med. Phys. 35 3955-62).This planning process is straightforward and only adds a small step to current clinical 3D planning practice. Our 4D planning scheme was tested on three cases to evaluate dosimetric benefits. The created 4D-IMAT plans showed similar dose distributions as compared with the 3D-IMAT plans on a single static phase, indicating that our method is capable of eliminating the dosimetric effects of breathing induced target motion. Compared to the 3D-IMAT plans with large treatment margins encompassing respiratory motion, our 4D-IMAT plans reduced radiation doses to surrounding normal organs and tissues.

Linear Quadratic Gaussian Controller Design Using a Graphical User Interface: Application to the Beam-Waveguide Antennas

NASA Astrophysics Data System (ADS)

Maneri, E.; Gawronski, W.

1999-10-01

The linear quadratic Gaussian (LQG) design algorithms described in [2] and [5] have been used in the controller design of JPL's beam-waveguide [5] and 70-m [6] antennas. This algorithm significantly improves tracking precision in a windy environment. This article describes the graphical user interface (GUI) software for the design LQG controllers. It consists of two parts: the basic LQG design and the fine-tuning of the basic design using a constrained optimization algorithm. The presented GUI was developed to simplify the design process, to make the design process user-friendly, and to enable design of an LQG controller for one with a limited control engineering background. The user is asked to manipulate the GUI sliders and radio buttons to watch the antenna performance. Simple rules are given at the GUI display.

Gain-Scheduled Fault Tolerance Control Under False Identification

NASA Technical Reports Server (NTRS)

Shin, Jong-Yeob; Belcastro, Christine (Technical Monitor)

2006-01-01

An active fault tolerant control (FTC) law is generally sensitive to false identification since the control gain is reconfigured for fault occurrence. In the conventional FTC law design procedure, dynamic variations due to false identification are not considered. In this paper, an FTC synthesis method is developed in order to consider possible variations of closed-loop dynamics under false identification into the control design procedure. An active FTC synthesis problem is formulated into an LMI optimization problem to minimize the upper bound of the induced-L2 norm which can represent the worst-case performance degradation due to false identification. The developed synthesis method is applied for control of the longitudinal motions of FASER (Free-flying Airplane for Subscale Experimental Research). The designed FTC law of the airplane is simulated for pitch angle command tracking under a false identification case.

Multilevel adaptive control of nonlinear interconnected systems.

PubMed

Motallebzadeh, Farzaneh; Ozgoli, Sadjaad; Momeni, Hamid Reza

2015-01-01

This paper presents an adaptive backstepping-based multilevel approach for the first time to control nonlinear interconnected systems with unknown parameters. The system consists of a nonlinear controller at the first level to neutralize the interaction terms, and some adaptive controllers at the second level, in which the gains are optimally tuned using genetic algorithm. The presented scheme can be used in systems with strong couplings where completely ignoring the interactions leads to problems in performance or stability. In order to test the suitability of the method, two case studies are provided: the uncertain double and triple coupled inverted pendulums connected by springs with unknown parameters. The simulation results show that the method is capable of controlling the system effectively, in both regulation and tracking tasks. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

TH-AB-202-03: A Novel Tool for Computing Deliverable Doses in Dynamic MLC Tracking Treatments

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

Fast, M; Kamerling, C; Menten, M

2016-06-15

Purpose: In tracked dynamic multi-leaf collimator (MLC) treatments, segments are continuously adapted to the target centroid motion in beams-eye-view. On-the-fly segment adaptation, however, potentially induces dosimetric errors due to the finite MLC leaf width and non-rigid target motion. In this study, we outline a novel tool for computing the 4d dose of lung SBRT plans delivered with MLC tracking. Methods: The following automated workflow was developed: A) centroid tracking, where the initial segments are morphed to each 4dCT phase based on the beams-eye-view GTV shift (followed by a dose calculation on each phase); B) re-optimized tracking, in which all morphedmore » initial plans from (A) are further optimised (“warm-started”) in each 4dCT phase using the initial optimisation parameters but phase-specific volume definitions. Finally, both dose sets are accumulated to the reference phase using deformable image registration. Initial plans were generated according to the RTOG-1021 guideline (54Gy, 3-Fx, equidistant 9-beam IMRT) on the peak-exhale (reference) phase of a phase-binned 4dCT. Treatment planning and delivery simulations were performed in RayStation (research v4.6) using our in-house segment-morphing algorithm, which directly links to RayStation through a native C++ interface. Results: Computing the tracking plans and 4d dose distributions via the in-house interface takes 5 and 8 minutes respectively for centroid and re-optimized tracking. For a sample lung SBRT patient with 14mm peak-to-peak motion in sup-inf direction, mainly perpendicular leaf motion (0-collimator) resulted in small dose changes for PTV-D95 (−13cGy) and GTV-D98 (+18cGy) for the centroid tracking case compared to the initial plan. Modest reductions of OAR doses (e.g. spinal cord D2: −11cGy) were achieved in the idealized tracking case. Conclusion: This study presents an automated “1-click” workflow for computing deliverable MLC tracking doses in RayStation. Adding a non-deliverable re-optimized tracking scenario is expected to help quantify plan robustness for more challenging patients with anatomy deformations. We acknowledge support of the MLC tracking research from Elekta AB. MFF is supported by Cancer Research UK under Programme C33589/A19908. Research at ICR is also supported by Cancer Research UK under Programme C33589/A19727 and NHS funding to the NIHR Biomedical Research Centre at RMH and ICR.« less

Optimization of MLS receivers for multipath environments

NASA Technical Reports Server (NTRS)

Mcalpine, G. A.; Highfill, J. H., III

1976-01-01

The design of a microwave landing system (MLS) aircraft receiver, capable of optimal performance in multipath environments found in air terminal areas, is reported. Special attention was given to the angle tracking problem of the receiver and includes tracking system design considerations, study and application of locally optimum estimation involving multipath adaptive reception and then envelope processing, and microcomputer system design. Results show processing is competitive in this application with i-f signal processing performance-wise and is much more simple and cheaper. A summary of the signal model is given.

Heliostat field cost reduction by `slope drive' optimization

NASA Astrophysics Data System (ADS)

Arbes, Florian; Weinrebe, Gerhard; Wöhrbach, Markus

2016-05-01

An algorithm to optimize power tower heliostat fields employing heliostats with so-called slope drives is presented. It is shown that a field using heliostats with the slope drive axes configuration has the same performance as a field with conventional azimuth-elevation tracking heliostats. Even though heliostats with the slope drive configuration have a limited tracking range, field groups of heliostats with different axes or different drives are not needed for different positions in the heliostat field. The impacts of selected parameters on a benchmark power plant (PS10 near Seville, Spain) are analyzed.

Non-rigid Reconstruction of Casting Process with Temperature Feature

NASA Astrophysics Data System (ADS)

Lin, Jinhua; Wang, Yanjie; Li, Xin; Wang, Ying; Wang, Lu

2017-09-01

Off-line reconstruction of rigid scene has made a great progress in the past decade. However, the on-line reconstruction of non-rigid scene is still a very challenging task. The casting process is a non-rigid reconstruction problem, it is a high-dynamic molding process lacking of geometric features. In order to reconstruct the casting process robustly, an on-line fusion strategy is proposed for dynamic reconstruction of casting process. Firstly, the geometric and flowing feature of casting are parameterized in manner of TSDF (truncated signed distance field) which is a volumetric block, parameterized casting guarantees real-time tracking and optimal deformation of casting process. Secondly, data structure of the volume grid is extended to have temperature value, the temperature interpolation function is build to generate the temperature of each voxel. This data structure allows for dynamic tracking of temperature of casting during deformation stages. Then, the sparse RGB features is extracted from casting scene to search correspondence between geometric representation and depth constraint. The extracted color data guarantees robust tracking of flowing motion of casting. Finally, the optimal deformation of the target space is transformed into a nonlinear regular variational optimization problem. This optimization step achieves smooth and optimal deformation of casting process. The experimental results show that the proposed method can reconstruct the casting process robustly and reduce drift in the process of non-rigid reconstruction of casting.

A new energy-efficient control approach for astronomical telescope drive system

NASA Astrophysics Data System (ADS)

Zhou, W.; Wang, Y.

2012-12-01

Drive control makes the astronomical telescope accurately tracking celestial bodies in spite of external and internal disturbances, which is a key technique to the performance of telescopes. In this paper, we propose a nonlinear ad, aptive observer based on power reversible approach for high precision telescope position tracking. The nonlinear adaptive observer automatically estimates the disturbances in drive system, and the observed value is applied to compensate for the real disturbances. With greatly reduced disturbances, the control precision can be evidently improved. In conventional drive control, the brake device is often used to slow down the reaction wheel and may waste enormous energy. To avoid those disadvantages, an H-bridge is put forward for wheel speed regulation. Such H-bridge has four independent sections, and each section mainly consists of a power electronic switch and an anti-parallel diode. During the period of the mount slowing down, the armature current of drive motor goes through the two path-wise diodes to charge the battery. Thus, energy waste is avoided. Based on the disturbance compensation, an optimal controller is designed to minimize an evaluation function which is made up of a weighted sum of position errors and energy consumption.The outputs of the controller are applied to control the H-bridge. Simulations are performed in MATLAB language. The results show that high precision control can be obtained by the proposed approach. And the energy consumption will be remarkably reduced.

Joint Sensing/Sampling Optimization for Surface Drifting Mine Detection with High-Resolution Drift Model

DTIC Science & Technology

2012-09-01

as potential tools for large area detection coverage while being moderately inexpensive (Wettergren, Performance of Search via Track - Before - Detect for...via Track - Before - Detect for Distribute 34 Sensor Networks, 2008). These statements highlight three specific needs to further sensor network research...Bay hydrography. Journal of Marine Systems, 12, 221–236. Wettergren, T. A. (2008). Performance of search via track - before - detect for distributed

MODAS Validation in Littoral Areas Using GRASP

DTIC Science & Technology

2002-09-30

result (4 hr) is guiding new work on calculation efficiency. Figure 4. Near-optimal coordinated passive search plan against a complex transitor ... Transitor tracks form a river of roughly parallel potential paths. The two searcher tracks criss- cross this river like shoe lacings over much of

Robotic fish tracking method based on suboptimal interval Kalman filter

NASA Astrophysics Data System (ADS)

Tong, Xiaohong; Tang, Chao

2017-11-01

Autonomous Underwater Vehicle (AUV) research focused on tracking and positioning, precise guidance and return to dock and other fields. The robotic fish of AUV has become a hot application in intelligent education, civil and military etc. In nonlinear tracking analysis of robotic fish, which was found that the interval Kalman filter algorithm contains all possible filter results, but the range is wide, relatively conservative, and the interval data vector is uncertain before implementation. This paper proposes a ptimization algorithm of suboptimal interval Kalman filter. Suboptimal interval Kalman filter scheme used the interval inverse matrix with its worst inverse instead, is more approximate nonlinear state equation and measurement equation than the standard interval Kalman filter, increases the accuracy of the nominal dynamic system model, improves the speed and precision of tracking system. Monte-Carlo simulation results show that the optimal trajectory of sub optimal interval Kalman filter algorithm is better than that of the interval Kalman filter method and the standard method of the filter.

Radiation modelling and performance evaluations of fixed, single- and double-axis tracking surfaces: a case study for Dhahran city, Saudi Arabia

NASA Astrophysics Data System (ADS)

Abdulsalam, Alrowashed; Idris, Azni Bin; Ahmad, Thamer; Ahsan, Amimul

2017-01-01

This work overviews the solar radiation basics and insolation of different surfaces is presented. A complete solar radiation modelling and investigation on the effect of horizontal plate, yearly tilt, monthly tilt, and single-axis and double-axis tracking surface on the insolation are carried out to conduct performance evaluation using the case study in Dhahran city of Saudi Arabia. The increments received by insolation for the yearly tilt, monthly tilt, and single-axis and dual-axis tracking surface with respect to traditional flat-plate collector is estimated. The results show that the yearly optimal tilt angle due to the south is close to the 0.913 time latitude of Dhahran. It is found that the yearly irradiation gains using yearly and monthly optimal tilts relative to flat panel installation are 7% and 14%, respectively. The yearly insulation gains made by single-axis and dual-axis continuous tracking surfaces are 33% and 48%, respectively.

Adaptive quaternion tracking with nonlinear extended state observer

NASA Astrophysics Data System (ADS)

Bai, Yu-liang; Wang, Xiao-gang; Xu, Jiang-tao; Cui, Nai-gang

2017-10-01

This paper addresses the problem of attitude tracking for spacecraft in the presence of uncertainties in moments of inertia and environmental disturbances. An adaptive quaternion tracking control is combined with a nonlinear extended state observer and the disturbances compensated for in each sampling period. The tracking controller is proved to asymptotically track a prescribed motion in the presence of these uncertainties. Simulations of a nano-spacecraft demonstrate a significant improvement in pointing accuracy and tracking error when compared to a conventional attitude controller. The proposed tracking control is completely deterministic, simple to implement, does not require knowledge of the uncertainties and does not suffer from chattering.

Ares I Flight Control System Design

NASA Technical Reports Server (NTRS)

Jang, Jiann-Woei; Alaniz, Abran; Hall, Robert; Bedrossian, Nazareth; Hall, Charles; Ryan, Stephen; Jackson, Mark

2010-01-01

The Ares I launch vehicle represents a challenging flex-body structural environment for flight control system design. This paper presents a design methodology for employing numerical optimization to develop the Ares I flight control system. The design objectives include attitude tracking accuracy and robust stability with respect to rigid body dynamics, propellant slosh, and flex. Under the assumption that the Ares I time-varying dynamics and control system can be frozen over a short period of time, the flight controllers are designed to stabilize all selected frozen-time launch control systems in the presence of parametric uncertainty. Flex filters in the flight control system are designed to minimize the flex components in the error signals before they are sent to the attitude controller. To ensure adequate response to guidance command, step response specifications are introduced as constraints in the optimization problem. Imposing these constraints minimizes performance degradation caused by the addition of the flex filters. The first stage bending filter design achieves stability by adding lag to the first structural frequency to phase stabilize the first flex mode while gain stabilizing the higher modes. The upper stage bending filter design gain stabilizes all the flex bending modes. The flight control system designs provided here have been demonstrated to provide stable first and second stage control systems in both Draper Ares Stability Analysis Tool (ASAT) and the MSFC 6DOF nonlinear time domain simulation.

Concurrent musculoskeletal dynamics and finite element analysis predicts altered gait patterns to reduce foot tissue loading.

PubMed

Halloran, Jason P; Ackermann, Marko; Erdemir, Ahmet; van den Bogert, Antonie J

2010-10-19

Current computational methods for simulating locomotion have primarily used muscle-driven multibody dynamics, in which neuromuscular control is optimized. Such simulations generally represent joints and soft tissue as simple kinematic or elastic elements for computational efficiency. These assumptions limit application in studies such as ligament injury or osteoarthritis, where local tissue loading must be predicted. Conversely, tissue can be simulated using the finite element method with assumed or measured boundary conditions, but this does not represent the effects of whole body dynamics and neuromuscular control. Coupling the two domains would overcome these limitations and allow prediction of movement strategies guided by tissue stresses. Here we demonstrate this concept in a gait simulation where a musculoskeletal model is coupled to a finite element representation of the foot. Predictive simulations incorporated peak plantar tissue deformation into the objective of the movement optimization, as well as terms to track normative gait data and minimize fatigue. Two optimizations were performed, first without the strain minimization term and second with the term. Convergence to realistic gait patterns was achieved with the second optimization realizing a 44% reduction in peak tissue strain energy density. The study demonstrated that it is possible to alter computationally predicted neuromuscular control to minimize tissue strain while including desired kinematic and muscular behavior. Future work should include experimental validation before application of the methodology to patient care. Copyright © 2010 Elsevier Ltd. All rights reserved.

Muscle optimization techniques impact the magnitude of calculated hip joint contact forces.

PubMed

Wesseling, Mariska; Derikx, Loes C; de Groote, Friedl; Bartels, Ward; Meyer, Christophe; Verdonschot, Nico; Jonkers, Ilse

2015-03-01

In musculoskeletal modelling, several optimization techniques are used to calculate muscle forces, which strongly influence resultant hip contact forces (HCF). The goal of this study was to calculate muscle forces using four different optimization techniques, i.e., two different static optimization techniques, computed muscle control (CMC) and the physiological inverse approach (PIA). We investigated their subsequent effects on HCFs during gait and sit to stand and found that at the first peak in gait at 15-20% of the gait cycle, CMC calculated the highest HCFs (median 3.9 times peak GRF (pGRF)). When comparing calculated HCFs to experimental HCFs reported in literature, the former were up to 238% larger. Both static optimization techniques produced lower HCFs (median 3.0 and 3.1 pGRF), while PIA included muscle dynamics without an excessive increase in HCF (median 3.2 pGRF). The increased HCFs in CMC were potentially caused by higher muscle forces resulting from co-contraction of agonists and antagonists around the hip. Alternatively, these higher HCFs may be caused by the slightly poorer tracking of the net joint moment by the muscle moments calculated by CMC. We conclude that the use of different optimization techniques affects calculated HCFs, and static optimization approached experimental values best. © 2014 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

SU-G-JeP1-10: Feasibility of CyberKnife Tracking Using the Previously-Implanted Permanent Brachytherapy Seed Cloud

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

Cheung, J; Cunha, J; Sudhyadhom, A

Purpose: Robotic radiosurgery is a salvage treatment option for patients with recurrent prostate cancer. We explored the feasibility of tracking the bolus of permanent prostate implants (PPI) using image recognition software optimized to track spinal anatomy. Methods: Forty-five inert iodine seeds were implanted into a gelatin-based prostate phantom. Four superficial gold seeds were inserted to provide ground-truth alignment. A CT scan of the phantom (120 kVp, 1 mm slice thickness) was acquired and a single-energy iterative metal artifact reduction (MAR) algorithm was used to enhance the quality of the DRR used for tracking. CyberKnife treatment plans were generated from themore » MAR CT and regular CT (no-MAR) using spine tracking. The spine-tracking grid was centered on the bolus of seeds and resized to encompass the full seed cloud. A third plan was created from the regular CT scan, using fiducial tracking based on the 4 superficial gold seeds with identical align-center coordinates. The phantom was initially aligned using the fiducial-tracking plan. Then the MAR and no-MAR spine-tracking plans were loaded without moving the phantom. Differences in couch correction parameters were recorded in the case of perfect alignment and after the application of known rotations and translations (roll/pitch of 2 degrees; translations XYZ of 2 cm). Results: The spine tracking software was able to lock on to the bolus of seeds and provide couch corrections both in the MAR and no-MAR plans. In all cases, differences in the couch correction parameters from fiducial alignment were <0.5 mm in translations and <1 degree in rotations. Conclusion: We were able to successfully track the bolus of seeds with the spine-tracking grid in phantom experiments. For clinical applications, further investigation and developments to adapt the spine-tracking algorithm to optimize for PPI seed cloud tracking is needed to provide reliable tracking in patients. One of the authors (MD) has received research support and speaker honoraria from Accuray.« less

Alcohol Warning Label Awareness and Attention: A Multi-method Study.

PubMed

Pham, Cuong; Rundle-Thiele, Sharyn; Parkinson, Joy; Li, Shanshi

2018-01-01

Evaluation of alcohol warning labels requires careful consideration ensuring that research captures more than awareness given that labels may not be prominent enough to attract attention. This study investigates attention of current in market alcohol warning labels and examines whether attention can be enhanced through theoretically informed design. Attention scores obtained through self-report methods are compared to objective measures (eye-tracking). A multi-method experimental design was used delivering four conditions, namely control, colour, size and colour and size. The first study (n = 559) involved a self-report survey to measure attention. The second study (n = 87) utilized eye-tracking to measure fixation count and duration and time to first fixation. Analysis of Variance (ANOVA) was utilized. Eye-tracking identified that 60% of participants looked at the current in market alcohol warning label while 81% looked at the optimized design (larger and red). In line with observed attention self-reported attention increased for the optimized design. The current study casts doubt on dominant practices (largely self-report), which have been used to evaluate alcohol warning labels. Awareness cannot be used to assess warning label effectiveness in isolation in cases where attention does not occur 100% of the time. Mixed methods permit objective data collection methodologies to be triangulated with surveys to assess warning label effectiveness. Attention should be incorporated as a measure in warning label effectiveness evaluations. Colour and size changes to the existing Australian warning labels aided by theoretically informed design increased attention. © The Author 2017. Medical Council on Alcohol and Oxford University Press. All rights reserved.

HIRES the high-resolution spectrograph for the E-ELT: dynamics and control of the repositioning mechanism for the E-ELT HIRES polarimeter

NASA Astrophysics Data System (ADS)

Di Varano, I.; Strassmeier, K. G.; Woche, M.

2016-08-01

A full Stokes dual channel polarimeter for the E-ELT HIRES spectrograph has been envisioned for the intermediate focus f/4.4, operating within a spectral range of 0.4-1.6 μ. It will feed the EELT- HIRES instrument located on the Nasmyth platform via two pairs of dedicated fibers: one fibre pair optimized for the BVRI, the other one optimized for the JH band or any other feasible combination. The instrument must be retractable within a workspace in fulfillment with the ESO requirements on the allocated volume and the dynamic response of the AO tower. For such purpose a swinging arm has been designed with a rotation provided by 5 revolute joints and a jackscrew. Moreover repeatability in repositioning has to be guaranteed by a parallel manipulator, performing an alignment procedure mainly along 5 axes. Dynamics and control criteria with a feed forward chain to compensate for vibration forces and feedback chain for tracking procedure are hereafter presented.

Different types of maximum power point tracking techniques for renewable energy systems: A survey

NASA Astrophysics Data System (ADS)

Khan, Mohammad Junaid; Shukla, Praveen; Mustafa, Rashid; Chatterji, S.; Mathew, Lini

2016-03-01

Global demand for electricity is increasing while production of energy from fossil fuels is declining and therefore the obvious choice of the clean energy source that is abundant and could provide security for development future is energy from the sun. In this paper, the characteristic of the supply voltage of the photovoltaic generator is nonlinear and exhibits multiple peaks, including many local peaks and a global peak in non-uniform irradiance. To keep global peak, MPPT is the important component of photovoltaic systems. Although many review articles discussed conventional techniques such as P & O, incremental conductance, the correlation ripple control and very few attempts have been made with intelligent MPPT techniques. This document also discusses different algorithms based on fuzzy logic, Ant Colony Optimization, Genetic Algorithm, artificial neural networks, Particle Swarm Optimization Algorithm Firefly, Extremum seeking control method and hybrid methods applied to the monitoring of maximum value of power at point in systems of photovoltaic under changing conditions of irradiance.

A Traction Control Strategy with an Efficiency Model in a Distributed Driving Electric Vehicle

PubMed Central

Lin, Cheng

2014-01-01

Both active safety and fuel economy are important issues for vehicles. This paper focuses on a traction control strategy with an efficiency model in a distributed driving electric vehicle. In emergency situation, a sliding mode control algorithm was employed to achieve antislip control through keeping the wheels' slip ratios below 20%. For general longitudinal driving cases, an efficiency model aiming at improving the fuel economy was built through an offline optimization stream within the two-dimensional design space composed of the acceleration pedal signal and the vehicle speed. The sliding mode control strategy for the joint roads and the efficiency model for the typical drive cycles were simulated. Simulation results show that the proposed driving control approach has the potential to apply to different road surfaces. It keeps the wheels' slip ratios within the stable zone and improves the fuel economy on the premise of tracking the driver's intention. PMID:25197697

A traction control strategy with an efficiency model in a distributed driving electric vehicle.

PubMed

Lin, Cheng; Cheng, Xingqun

2014-01-01

Both active safety and fuel economy are important issues for vehicles. This paper focuses on a traction control strategy with an efficiency model in a distributed driving electric vehicle. In emergency situation, a sliding mode control algorithm was employed to achieve antislip control through keeping the wheels' slip ratios below 20%. For general longitudinal driving cases, an efficiency model aiming at improving the fuel economy was built through an offline optimization stream within the two-dimensional design space composed of the acceleration pedal signal and the vehicle speed. The sliding mode control strategy for the joint roads and the efficiency model for the typical drive cycles were simulated. Simulation results show that the proposed driving control approach has the potential to apply to different road surfaces. It keeps the wheels' slip ratios within the stable zone and improves the fuel economy on the premise of tracking the driver's intention.

Distributed control system for parallel-connected DC boost converters

DOEpatents

Goldsmith, Steven

2017-08-15

The disclosed invention is a distributed control system for operating a DC bus fed by disparate DC power sources that service a known or unknown load. The voltage sources vary in v-i characteristics and have time-varying, maximum supply capacities. Each source is connected to the bus via a boost converter, which may have different dynamic characteristics and power transfer capacities, but are controlled through PWM. The invention tracks the time-varying power sources and apportions their power contribution while maintaining the DC bus voltage within the specifications. A central digital controller solves the steady-state system for the optimal duty cycle settings that achieve a desired power supply apportionment scheme for a known or predictable DC load. A distributed networked control system is derived from the central system that utilizes communications among controllers to compute a shared estimate of the unknown time-varying load through shared bus current measurements and bus voltage measurements.

Subsonic flight test evaluation of a propulsion system parameter estimation process for the F100 engine

NASA Technical Reports Server (NTRS)

Orme, John S.; Gilyard, Glenn B.

1992-01-01

Integrated engine-airframe optimal control technology may significantly improve aircraft performance. This technology requires a reliable and accurate parameter estimator to predict unmeasured variables. To develop this technology base, NASA Dryden Flight Research Facility (Edwards, CA), McDonnell Aircraft Company (St. Louis, MO), and Pratt & Whitney (West Palm Beach, FL) have developed and flight-tested an adaptive performance seeking control system which optimizes the quasi-steady-state performance of the F-15 propulsion system. This paper presents flight and ground test evaluations of the propulsion system parameter estimation process used by the performance seeking control system. The estimator consists of a compact propulsion system model and an extended Kalman filter. The extended Laman filter estimates five engine component deviation parameters from measured inputs. The compact model uses measurements and Kalman-filter estimates as inputs to predict unmeasured propulsion parameters such as net propulsive force and fan stall margin. The ability to track trends and estimate absolute values of propulsion system parameters was demonstrated. For example, thrust stand results show a good correlation, especially in trends, between the performance seeking control estimated and measured thrust.

Simulation of process identification and controller tuning for flow control system

NASA Astrophysics Data System (ADS)

Chew, I. M.; Wong, F.; Bono, A.; Wong, K. I.

2017-06-01

PID controller is undeniably the most popular method used in controlling various industrial processes. The feature to tune the three elements in PID has allowed the controller to deal with specific needs of the industrial processes. This paper discusses the three elements of control actions and improving robustness of controllers through combination of these control actions in various forms. A plant model is simulated using the Process Control Simulator in order to evaluate the controller performance. At first, the open loop response of the plant is studied by applying a step input to the plant and collecting the output data from the plant. Then, FOPDT of physical model is formed by using both Matlab-Simulink and PRC method. Then, calculation of controller’s setting is performed to find the values of Kc and τi that will give satisfactory control in closed loop system. Then, the performance analysis of closed loop system is obtained by set point tracking analysis and disturbance rejection performance. To optimize the overall physical system performance, a refined tuning of PID or detuning is further conducted to ensure a consistent resultant output of closed loop system reaction to the set point changes and disturbances to the physical model. As a result, the PB = 100 (%) and τi = 2.0 (s) is preferably chosen for setpoint tracking while PB = 100 (%) and τi = 2.5 (s) is selected for rejecting the imposed disturbance to the model. In a nutshell, selecting correlation tuning values is likewise depended on the required control’s objective for the stability performance of overall physical model.

Physical activity measured by physical activity monitoring system correlates with glucose trends reconstructed from continuous glucose monitoring.

PubMed

Zecchin, Chiara; Facchinetti, Andrea; Sparacino, Giovanni; Dalla Man, Chiara; Manohar, Chinmay; Levine, James A; Basu, Ananda; Kudva, Yogish C; Cobelli, Claudio

2013-10-01

In type 1 diabetes mellitus (T1DM), physical activity (PA) lowers the risk of cardiovascular complications but hinders the achievement of optimal glycemic control, transiently boosting insulin action and increasing hypoglycemia risk. Quantitative investigation of relationships between PA-related signals and glucose dynamics, tracked using, for example, continuous glucose monitoring (CGM) sensors, have been barely explored. In the clinic, 20 control and 19 T1DM subjects were studied for 4 consecutive days. They underwent low-intensity PA sessions daily. PA was tracked by the PA monitoring system (PAMS), a system comprising accelerometers and inclinometers. Variations on glucose dynamics were tracked estimating first- and second-order time derivatives of glucose concentration from CGM via Bayesian smoothing. Short-time effects of PA on glucose dynamics were quantified through the partial correlation function in the interval (0, 60 min) after starting PA. Correlation of PA with glucose time derivatives is evident. In T1DM, the negative correlation with the first-order glucose time derivative is maximal (absolute value) after 15 min of PA, whereas the positive correlation is maximal after 40-45 min. The negative correlation between the second-order time derivative and PA is maximal after 5 min, whereas the positive correlation is maximal after 35-40 min. Control subjects provided similar results but with positive and negative correlation peaks anticipated of 5 min. Quantitative information on correlation between mild PA and short-term glucose dynamics was obtained. This represents a preliminary important step toward incorporation of PA information in more realistic physiological models of the glucose-insulin system usable in T1DM simulators, in development of closed-loop artificial pancreas control algorithms, and in CGM-based prediction algorithms for generation of hypoglycemic alerts.

Enhancing the Gaming Experience Using 3D Spatial User Interface Technologies.

PubMed

Kulshreshth, Arun; Pfeil, Kevin; LaViola, Joseph J

2017-01-01

Three-dimensional (3D) spatial user interface technologies have the potential to make games more immersive and engaging and thus provide a better user experience. Although technologies such as stereoscopic 3D display, head tracking, and gesture-based control are available for games, it is still unclear how their use affects gameplay and if there are any user performance benefits. The authors have conducted several experiments on these technologies in game environments to understand how they affect gameplay and how we can use them to optimize the gameplay experience.

Experimental Demonstration of Frequency Regulation by Commercial Buildings – Part I: Modeling and Hierarchical Control Design

DOE PAGES

Vrettos, Evangelos; Kara, Emre C.; MacDonald, Jason; ...

2016-11-15

Here, this paper is the first part of a two-part series in which we present results from one of the first worldwide experimental demonstrations of frequency regulation in a commercial building test facility. We demonstrate that commercial buildings can track a frequency regulation signal with high accuracy and minimal occupant discomfort in a realistic environment. In addition, we show that buildings can determine the reserve capacity and baseline power a priori, and identify the optimal tradeoff between frequency regulation and energy efficiency.

A computer simulation approach to measurement of human control strategy

NASA Technical Reports Server (NTRS)

Green, J.; Davenport, E. L.; Engler, H. F.; Sears, W. E., III

1982-01-01

Human control strategy is measured through use of a psychologically-based computer simulation which reflects a broader theory of control behavior. The simulation is called the human operator performance emulator, or HOPE. HOPE was designed to emulate control learning in a one-dimensional preview tracking task and to measure control strategy in that setting. When given a numerical representation of a track and information about current position in relation to that track, HOPE generates positions for a stick controlling the cursor to be moved along the track. In other words, HOPE generates control stick behavior corresponding to that which might be used by a person learning preview tracking.

Robust Power Management Control for Stand-Alone Hybrid Power Generation System

NASA Astrophysics Data System (ADS)

Kamal, Elkhatib; Adouane, Lounis; Aitouche, Abdel; Mohammed, Walaa

2017-01-01

This paper presents a new robust fuzzy control of energy management strategy for the stand-alone hybrid power systems. It consists of two levels named centralized fuzzy supervisory control which generates the power references for each decentralized robust fuzzy control. Hybrid power systems comprises: a photovoltaic panel and wind turbine as renewable sources, a micro turbine generator and a battery storage system. The proposed control strategy is able to satisfy the load requirements based on a fuzzy supervisor controller and manage power flows between the different energy sources and the storage unit by respecting the state of charge and the variation of wind speed and irradiance. Centralized controller is designed based on If-Then fuzzy rules to manage and optimize the hybrid power system production by generating the reference power for photovoltaic panel and wind turbine. Decentralized controller is based on the Takagi-Sugeno fuzzy model and permits us to stabilize each photovoltaic panel and wind turbine in presence of disturbances and parametric uncertainties and to optimize the tracking reference which is given by the centralized controller level. The sufficient conditions stability are formulated in the format of linear matrix inequalities using the Lyapunov stability theory. The effectiveness of the proposed Strategy is finally demonstrated through a SAHPS (stand-alone hybrid power systems) to illustrate the effectiveness of the overall proposed method.

Continuous fractional-order Zero Phase Error Tracking Control.

PubMed

Liu, Lu; Tian, Siyuan; Xue, Dingyu; Zhang, Tao; Chen, YangQuan

2018-04-01

A continuous time fractional-order feedforward control algorithm for tracking desired time varying input signals is proposed in this paper. The presented controller cancels the phase shift caused by the zeros and poles of controlled closed-loop fractional-order system, so it is called Fractional-Order Zero Phase Tracking Controller (FZPETC). The controlled systems are divided into two categories i.e. with and without non-cancellable (non-minimum-phase) zeros which stand in unstable region or on stability boundary. Each kinds of systems has a targeted FZPETC design control strategy. The improved tracking performance has been evaluated successfully by applying the proposed controller to three different kinds of fractional-order controlled systems. Besides, a modified quasi-perfect tracking scheme is presented for those systems which may not have available future tracking trajectory information or have problem in high frequency disturbance rejection if the perfect tracking algorithm is applied. A simulation comparison and a hardware-in-the-loop thermal peltier platform are shown to validate the practicality of the proposed quasi-perfect control algorithm. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

On the Impact of Localization and Density Control Algorithms in Target Tracking Applications for Wireless Sensor Networks

PubMed Central

Campos, Andre N.; Souza, Efren L.; Nakamura, Fabiola G.; Nakamura, Eduardo F.; Rodrigues, Joel J. P. C.

2012-01-01

Target tracking is an important application of wireless sensor networks. The networks' ability to locate and track an object is directed linked to the nodes' ability to locate themselves. Consequently, localization systems are essential for target tracking applications. In addition, sensor networks are often deployed in remote or hostile environments. Therefore, density control algorithms are used to increase network lifetime while maintaining its sensing capabilities. In this work, we analyze the impact of localization algorithms (RPE and DPE) and density control algorithms (GAF, A3 and OGDC) on target tracking applications. We adapt the density control algorithms to address the k-coverage problem. In addition, we analyze the impact of network density, residual integration with density control, and k-coverage on both target tracking accuracy and network lifetime. Our results show that DPE is a better choice for target tracking applications than RPE. Moreover, among the evaluated density control algorithms, OGDC is the best option among the three. Although the choice of the density control algorithm has little impact on the tracking precision, OGDC outperforms GAF and A3 in terms of tracking time. PMID:22969329

Technology forecasting for space communication. Task one report: Cost and weight tradeoff studies for EOS and TDRS

NASA Technical Reports Server (NTRS)

1974-01-01

Weight and cost optimized EOS communication links are determined for 2.25, 7.25, 14.5, 21, and 60 GHz systems and for a 10.6 micron homodyne detection laser system. EOS to ground links are examined for 556, 834, and 1112 km EOS orbits, with ground terminals at the Network Test and Tracking Facility and at Goldstone. Optimized 21 GHz and 10.6 micron links are also examined. For the EOS to Tracking and Data Relay Satellite to ground link, signal-to-noise ratios of the uplink and downlink are also optimized for minimum overall cost or spaceborne weight. Finally, the optimized 21 GHz EOS to ground link is determined for various precipitation rates. All system performance parameters and mission dependent constraints are presented, as are the system cost and weight functional dependencies. The features and capabilities of the computer program to perform the foregoing analyses are described.

Robust tracking and distributed synchronization control of a multi-motor servomechanism with H-infinity performance.

PubMed

Wang, Minlin; Ren, Xuemei; Chen, Qiang

2018-01-01

The multi-motor servomechanism (MMS) is a multi-variable, high coupling and nonlinear system, which makes the controller design challenging. In this paper, an adaptive robust H-infinity control scheme is proposed to achieve both the load tracking and multi-motor synchronization of MMS. This control scheme consists of two parts: a robust tracking controller and a distributed synchronization controller. The robust tracking controller is constructed by incorporating a neural network (NN) K-filter observer into the dynamic surface control, while the distributed synchronization controller is designed by combining the mean deviation coupling control strategy with the distributed technique. The proposed control scheme has several merits: 1) by using the mean deviation coupling synchronization control strategy, the tracking controller and the synchronization controller can be designed individually without any coupling problem; 2) the immeasurable states and unknown nonlinearities are handled by a NN K-filter observer, where the number of NN weights is largely reduced by using the minimal learning parameter technique; 3) the H-infinity performances of tracking error and synchronization error are guaranteed by introducing a robust term into the tracking controller and the synchronization controller, respectively. The stabilities of the tracking and synchronization control systems are analyzed by the Lyapunov theory. Simulation and experimental results based on a four-motor servomechanism are conducted to demonstrate the effectiveness of the proposed method. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Novel Approaches to Improve Iris Recognition System Performance Based on Local Quality Evaluation and Feature Fusion

PubMed Central

2014-01-01

For building a new iris template, this paper proposes a strategy to fuse different portions of iris based on machine learning method to evaluate local quality of iris. There are three novelties compared to previous work. Firstly, the normalized segmented iris is divided into multitracks and then each track is estimated individually to analyze the recognition accuracy rate (RAR). Secondly, six local quality evaluation parameters are adopted to analyze texture information of each track. Besides, particle swarm optimization (PSO) is employed to get the weights of these evaluation parameters and corresponding weighted coefficients of different tracks. Finally, all tracks' information is fused according to the weights of different tracks. The experimental results based on subsets of three public and one private iris image databases demonstrate three contributions of this paper. (1) Our experimental results prove that partial iris image cannot completely replace the entire iris image for iris recognition system in several ways. (2) The proposed quality evaluation algorithm is a self-adaptive algorithm, and it can automatically optimize the parameters according to iris image samples' own characteristics. (3) Our feature information fusion strategy can effectively improve the performance of iris recognition system. PMID:24693243

Novel approaches to improve iris recognition system performance based on local quality evaluation and feature fusion.

PubMed

Chen, Ying; Liu, Yuanning; Zhu, Xiaodong; Chen, Huiling; He, Fei; Pang, Yutong

2014-01-01

For building a new iris template, this paper proposes a strategy to fuse different portions of iris based on machine learning method to evaluate local quality of iris. There are three novelties compared to previous work. Firstly, the normalized segmented iris is divided into multitracks and then each track is estimated individually to analyze the recognition accuracy rate (RAR). Secondly, six local quality evaluation parameters are adopted to analyze texture information of each track. Besides, particle swarm optimization (PSO) is employed to get the weights of these evaluation parameters and corresponding weighted coefficients of different tracks. Finally, all tracks' information is fused according to the weights of different tracks. The experimental results based on subsets of three public and one private iris image databases demonstrate three contributions of this paper. (1) Our experimental results prove that partial iris image cannot completely replace the entire iris image for iris recognition system in several ways. (2) The proposed quality evaluation algorithm is a self-adaptive algorithm, and it can automatically optimize the parameters according to iris image samples' own characteristics. (3) Our feature information fusion strategy can effectively improve the performance of iris recognition system.

Damping Estimation from Free Decay Responses of Cables with MR Dampers.

PubMed

Weber, Felix; Distl, Hans

2015-01-01

This paper discusses the damping measurements on cables with real-time controlled MR dampers that were performed on a laboratory scale single strand cable and on cables of the Sutong Bridge, China. The control approach aims at producing amplitude and frequency independent cable damping which is confirmed by the tests. The experimentally obtained cable damping in comparison to the theoretical value due to optimal linear viscous damping reveals that support conditions of the cable anchors, force tracking errors in the actual MR damper force, energy spillover to higher modes, and excitation and sensor cables hanging on the stay cable must be taken into consideration for the interpretation of the identified cable damping values.

Damping Estimation from Free Decay Responses of Cables with MR Dampers

PubMed Central

Weber, Felix; Distl, Hans

2015-01-01

This paper discusses the damping measurements on cables with real-time controlled MR dampers that were performed on a laboratory scale single strand cable and on cables of the Sutong Bridge, China. The control approach aims at producing amplitude and frequency independent cable damping which is confirmed by the tests. The experimentally obtained cable damping in comparison to the theoretical value due to optimal linear viscous damping reveals that support conditions of the cable anchors, force tracking errors in the actual MR damper force, energy spillover to higher modes, and excitation and sensor cables hanging on the stay cable must be taken into consideration for the interpretation of the identified cable damping values. PMID:26167537

A pilot modeling technique for handling-qualities research

NASA Technical Reports Server (NTRS)

Hess, R. A.

1980-01-01

A brief survey of the more dominant analysis techniques used in closed-loop handling-qualities research is presented. These techniques are shown to rely on so-called classical and modern analytical models of the human pilot which have their foundation in the analysis and design principles of feedback control. The optimal control model of the human pilot is discussed in some detail and a novel approach to the a priori selection of pertinent model parameters is discussed. Frequency domain and tracking performance data from 10 pilot-in-the-loop simulation experiments involving 3 different tasks are used to demonstrate the parameter selection technique. Finally, the utility of this modeling approach in handling-qualities research is discussed.

Optimal Reference Strain Structure for Studying Dynamic Responses of Flexible Rockets

NASA Technical Reports Server (NTRS)

Tsushima, Natsuki; Su, Weihua; Wolf, Michael G.; Griffin, Edwin D.; Dumoulin, Marie P.

2017-01-01

In the proposed paper, the optimal design of reference strain structures (RSS) will be performed targeting for the accurate observation of the dynamic bending and torsion deformation of a flexible rocket. It will provide the detailed description of the finite-element (FE) model of a notional flexible rocket created in MSC.Patran. The RSS will be attached longitudinally along the side of the rocket and to track the deformation of the thin-walled structure under external loads. An integrated surrogate-based multi-objective optimization approach will be developed to find the optimal design of the RSS using the FE model. The Kriging method will be used to construct the surrogate model. For the data sampling and the performance evaluation, static/transient analyses will be performed with MSC.Natran/Patran. The multi-objective optimization will be solved with NSGA-II to minimize the difference between the strains of the launch vehicle and RSS. Finally, the performance of the optimal RSS will be evaluated by checking its strain-tracking capability in different numerical simulations of the flexible rocket.

Adaptive critic learning techniques for engine torque and air-fuel ratio control.

PubMed

Liu, Derong; Javaherian, Hossein; Kovalenko, Olesia; Huang, Ting

2008-08-01

A new approach for engine calibration and control is proposed. In this paper, we present our research results on the implementation of adaptive critic designs for self-learning control of automotive engines. A class of adaptive critic designs that can be classified as (model-free) action-dependent heuristic dynamic programming is used in this research project. The goals of the present learning control design for automotive engines include improved performance, reduced emissions, and maintained optimum performance under various operating conditions. Using the data from a test vehicle with a V8 engine, we developed a neural network model of the engine and neural network controllers based on the idea of approximate dynamic programming to achieve optimal control. We have developed and simulated self-learning neural network controllers for both engine torque (TRQ) and exhaust air-fuel ratio (AFR) control. The goal of TRQ control and AFR control is to track the commanded values. For both control problems, excellent neural network controller transient performance has been achieved.

Three-dimensional data-tracking dynamic optimization simulations of human locomotion generated by direct collocation.

PubMed

Lin, Yi-Chung; Pandy, Marcus G

2017-07-05

The aim of this study was to perform full-body three-dimensional (3D) dynamic optimization simulations of human locomotion by driving a neuromusculoskeletal model toward in vivo measurements of body-segmental kinematics and ground reaction forces. Gait data were recorded from 5 healthy participants who walked at their preferred speeds and ran at 2m/s. Participant-specific data-tracking dynamic optimization solutions were generated for one stride cycle using direct collocation in tandem with an OpenSim-MATLAB interface. The body was represented as a 12-segment, 21-degree-of-freedom skeleton actuated by 66 muscle-tendon units. Foot-ground interaction was simulated using six contact spheres under each foot. The dynamic optimization problem was to find the set of muscle excitations needed to reproduce 3D measurements of body-segmental motions and ground reaction forces while minimizing the time integral of muscle activations squared. Direct collocation took on average 2.7±1.0h and 2.2±1.6h of CPU time, respectively, to solve the optimization problems for walking and running. Model-computed kinematics and foot-ground forces were in good agreement with corresponding experimental data while the calculated muscle excitation patterns were consistent with measured EMG activity. The results demonstrate the feasibility of implementing direct collocation on a detailed neuromusculoskeletal model with foot-ground contact to accurately and efficiently generate 3D data-tracking dynamic optimization simulations of human locomotion. The proposed method offers a viable tool for creating feasible initial guesses needed to perform predictive simulations of movement using dynamic optimization theory. The source code for implementing the model and computational algorithm may be downloaded at http://simtk.org/home/datatracking. Copyright © 2017 Elsevier Ltd. All rights reserved.