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检索条件"主题词=Adaptive Dynamic Programming"

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Multi-Sensor Scheduling for Target Tracking based on Constrained ADP in Energy Harvesting WSN 13

Multi-Sensor Scheduling for Target Tracking based on Constra...

引用

13th IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Liu, Fen Jiang, Chengpeng Chen, Shuai Xiao, Wendong Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China Beijing Engn Res Ctr Ind Spectrum Imaging Beijing 100083 Peoples R China

ISBN: (纸本)9781538637586

With the development of energy harvesting technologies, the building of wireless sensor networks (WSN) based on energy harvesting has become possible, and helps to weaken the limitation of battery energy in WSN. The main objective of target tracking is to improve the tracking accuracy and to optimize the resource utilization, hence sensor scheduling is essential. Based on an artificial neural network energy acquisition model and extended Kalman filter (EKF) estimation for sensor data fusion, this paper will propose a novel constrained adaptive dynamic programming (ADP) algorithm for multi-sensor scheduling of energy harvesting WSN to optimize the tracking accuracy and resource utilization. Simulation results show that the proposed algorithm is feasible and efficient.

关键词： energy harvesting wireless sensor networks adaptive dynamic programming target tracking extended Kalman filter multi-sensor scheduling

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Online Optimal Event-triggered Tracking Control with Actuator Saturation via ADP 9

Online Optimal Event-triggered Tracking Control with Actuato...

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9th IEEE Data Driven Control and Learning Systems Conference (DDCLS)

作者： Liu, Lu Song, Ruizhuo Ren, Yi Zhao, Yong Song, Biao Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China China Commun Construct Intelligence Transportat C Tianjin 300210 Peoples R China Univ Sci & Technol Beijing Beijing Inst Comp Applicat Beijing 100083 Peoples R China

ISBN: (纸本)9781728159225

This paper comes up with an optimal tracking control mechanism with saturation controller for some continuous nonlinear systems based on the event-triggered (ET) mechanism via adaptive dynamic programming (ADP). To begin with, the constrained tracking control problems are able to be transformed into common event-triggered optimal control through designing an appropriate cost function. Next, a single critic network is to estimate the cost function. Moreover, taking the appropriate triggering condition as the prerequisite, the stability proof of the system is proved according to Lyapunov theory. In addition, the simulations verify the excellent performance of ET-ADP algorithm because the optimal control law is only updated at the required times influenced by the devised triggering condition, which can accomplish high efficiency of resources and energy consumption of the system.

关键词： Optimal Tracking Control Event-Triggered adaptive dynamic programming

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A Model-Free Resilient Tracking Control Scheme for Non-Affine Nonlinear Continuous Systems with Uncertainties 41

A Model-Free Resilient Tracking Control Scheme for Non-Affin...

引用

第41届中国控制会议

作者： Kun Zhang Wenchao Xue Ran Zhang Cui Wei School of Astronautics Beihang University Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of Sciences Institute of Intelligent Manufacturing Nanjing Tech University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,a model-free integral reinforcement learning(IRL) resilient tracking control scheme has been proposed for a class of non-affine nonlinear systems with *** using the precompensation technique,the actual working control has been transformed into the state of compensator,and an augmented tracking system converts the optimal tracking control problem into an optimal regulation *** applying the reinforcement learning(RL) technique,the designed method can avoid the dynamic information directly during the iteration learning process,and obtain the model-free resilient tracking ***,the developed algorithm overcomes the limitations and strict assumptions of conventional optimal tracking control in dealing with a non-affine nonlinear ***,with the use of polynomial approximation structure and the least square method,practicability in the implementing process has been guaranteed ***,two examples in the simulation are given to demonstrate the validity and feasibility of the proposed model-free IRL resilient tracking control.

关键词： adaptive dynamic programming Resilient control Nonlinear system Tracking control Integral reinforcement learning

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adaptive Optimal Control of UAV Formation Based on Policy Iteration 34

Adaptive Optimal Control of UAV Formation Based on Policy It...

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34th Chinese Control and Decision Conference (CCDC)

作者： Xu, Guangyan Zhang, Shugang Lin, Hao Shenyang Aerosp Univ Sch Automat Shenyang 110136 Peoples R China

ISBN: (纸本)9781665478960

In this paper, aiming at the problem of UAV formation control, a method based on policy iteration is proposed to study the optimal control policy of UAV formation. When the system model is unknown, this algorithm transforms the problem into online solving the Algebraic Riccati Equation. Through online iteration, the value function and the control policy can be updated at the same time. Finally, the optimal control policy is obtained and the nonlinear system is converged. Experimental results show that compared with the traditional control policy, the controller improves the stability of the UAV formation. The convergence speed and robustness of the system are also significantly enhanced, and the control performance is more optimized. At last, the simulation results verify the effectiveness of the proposed method.

关键词： Policy iteration adaptive dynamic programming Optimal control UAV formation

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Optimal synchronization control for nonlinear multi-agent systems with input delay 29

Optimal synchronization control for nonlinear multi-agent sy...

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第29届中国控制与决策会议

作者： Huaipin Zhang Dong Yue Wei Zhao School of Automation Huazhong University of Science and Technology Institute of Advanced Technology Nanjing University of Posts and Telecommunications School of Mechanical Science and Engineering Huazhong University of Science and Technology

ISBN: (纸本)9781509046584

In this paper,optimal synchronization problem of multi-agent systems(MASs) with time-varying input delay is *** remove the effect of input delay,the delayed MAS model is firstly transformed into a new discretetime delay-free *** we estabhsh an equivalence relation on the performance indexes of the two systems so as to formulate a new optimal consensus control problem of the transformed delay-free *** on the Bellman optimality theorem,we derive optimal consensus control policies from the coupled HJB equations.A policy iteration algorithm is introduced to learn the solutions to the HJB equations in *** execute iterative ADP method,the critic neural networks(NN) are utilized to approximate the value functions and help to calculate the control ***,a numerical simulation is provided to show the effectiveness of the proposed approach.

关键词： Synchronization adaptive dynamic programming HJB equation input delay

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Optimal Fault Tolerant Control of Reconfigurable Manipulator with Actuator Saturation 32

Optimal Fault Tolerant Control of Reconfigurable Manipulator...

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32nd Chinese Control And Decision Conference (CCDC)

作者： Nie, Fujie Zhou, Fan Dong, Bo An, Tianjiao Li, Yuanchun Changchun Univ Technol Dept Control Sci & Engn Changchun 130000 Peoples R China

ISBN: (纸本)9781728158556

In this paper, an optimal active fault tolerant control (FTC) method is presented for reconfigurable manipulator with actuator saturation based on the adaptive dynamic programming (ADP) approach. First, the saturation constraints of the manipulator systems are tackled by using hyperbolic tangent functions. Second, an actuator fault function, which is estimated via a fault observer, is used to construct the performance index function. Then, the solution of Hamiltonian-Jacobi-Bellman (HJB) equation is solved by using ADP and policy iteration (PI) methods, and the optimal performance index function is approximated by establishing a critic neural network (NN). Based on the Lyapunov theory, the closed-loop manipulator system is proved to be asymptotic stable under the optimal FTC system. Finally, simulation results are demonstrated the validity of the proposed scheme.

关键词： adaptive dynamic programming reconfigurable manipulators actuator saturation optimal fault tolerant control neural network

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ADP-based active optimal fault-tolerant control for modular manipulator with multiple sensor failure

ADP-based active optimal fault-tolerant control for modular ...

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Chinese Automation Congress (CAC)

作者： Li, Bing Fang, Tao Zhou, Fan Dong, Bo Li, Yuanchun Changchun Univ Technol Dept Control Sci & Engn Changchun Peoples R China Chanchun Univ Sci & Techonlgy Dept Elect Informat Engn Changchun Peoples R China

ISBN: (纸本)9781728140940

In this paper, we propose a novel active fault-tolerant control (AFTC) method for modular manipulators with multiple sensor failure, which is based on adaptive dynamic programming (ADP). Combining the principle of diffeomorphism, a first-order filter is introduced to convert sensor faults into pseudo-actuator faults. Combine the sensor faults estimated by the adaptive sensor fault observer to establish the Hamilton-Jacobi-Bellman (HJB) equation. Based on the ADP, the online policy iteration (PI) algorithm is applied to solve the HJB equation by establishing a critic neural network. It is proved that the closed-loop modular manipulators system is asymptotic stability according to the Lyapunov theory. Simulation results of 2-DOF modular manipulator systems with two configurations demonstrate the validity of the proposed algorithm finally.

关键词： adaptive dynamic programming fault-tolerant control modular manipulators PI algorithm critic neural network

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adaptive Optimal Control of Nonlinear Active Suspension Systems with Completely Unknown dynamics 33

Adaptive Optimal Control of Nonlinear Active Suspension Syst...

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33rd Chinese Control and Decision Conference (CCDC)

作者： Chen, Xin Huang, Yingbo Na, Jing Gao, Guanbin Zhao, Jun Kunming Univ Sci & Technol Fac Mech & Elect Engn Kunming 650500 Yunnan Peoples R China

ISBN: (纸本)9781665440899

Ride comfort, tire deflection and suspension stroke are generally conflicting in the active suspension control. To achieve a compromise among the three requirements, a novel online adaptive optimal control method is developed for the nonlinear active suspension systems subject to completely unknown dynamics. Based on the adaptive dynamic programming (ADP) algorithm, this paper proposes an identifier-critic structure with a dual neural network (NN) to realize the active suspension optimal control. To this end, a cost function concerning ride comfort, suspension stroke and control input is constructed. Then, an identifier NN with a novel adaptive law based on the parameter estimation error is used to approximate the unknown nonlinear dynamics. To obtain the optimal solution, a critic NN with the proposed adaptive law is suggested to design the optimal controller. Simulation results are provided to verify the effectiveness of the proposed method.

关键词： Active suspension systems optimal control active suspension control adaptive dynamic programming

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Neural Network adaptive Critic Control With Disturbance Rejection 29

Neural Network Adaptive Critic Control With Disturbance Reje...

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第29届中国控制与决策会议

作者： Ding Wang Chaoxu Mu Derong Liu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences School of Electrical and Information Engineering Tianjin University School of Automation and Electrical Engineering University of Science and Technology Beijing

ISBN: (纸本)9781509046584

A neural-network-based adaptive critic control method is established for continuous-time input-affine uncertain nonlinear systems to achieve disturbance *** present problem can be formulated as a two-player zero-sum differential game and the adaptive critic mechanism is employed to solve the minimax optimization problem.A neural network identifier is developed to reconstruct the unknown dynamical *** optimal control law and the worst-case disturbance law are designed by introducing and training a critic neural *** effectiveness of the present self-learning control method is also illustrated by a simulation experiment.

关键词： adaptive critic control adaptive dynamic programming Approximate dynamic programming Disturbance rejection Learning systems Neural networks Nonlinear control

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Event-Driven Optimal Regulation with SNAC Framework for Constrained Nonlinear Plants 40

Event-Driven Optimal Regulation with SNAC Framework for Cons...

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40th Chinese Control Conference (CCC)

作者： Hu, Lingzhi Wang, Ding Zhao, Mingming Ren, Jin Beijing Univ Technol Fac Informat Technol Beijing 100124 Peoples R China Bejing Univ Technol Beijing Key Lab Computat Intelligence & Intellige Beijing 100124 Peoples R China Beijing Univ Technol Beijing Inst Artificial Intelligence Beijing 100124 Peoples R China

ISBN: (纸本)9789881563804

In order to reduce the computational burden effectively and ensure that the system has good control performance, an event-driven near-optimal control algorithm is developed for discrete-time nonlinear systems with input constraints. A single network adaptive critic algorithm is adopted to address the constrained optimal control problem. First, the optimal cost function and the optimal control strategy are obtained theoretically through the iterative algorithm. Then, an appropriate triggering threshold is established, so that the system satisfies the event-driven mechanism. In addition, the action network of classical adaptive dynamic programming is omitted. The derivative of the approximate cost function is the output of the critic network and then is used to obtain the approximate optimal control law. Furthermore, the convergence analysis of the iterative algorithm is proved. Finally, a simulation example is conducted to verify the effectiveness of the proposed scheme.

关键词： adaptive dynamic programming Control Constraints Discrete-Time Systems Event-Driven Control Neural Networks Single Network adaptive Critic

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