Optimal Tracking Control for Reconfigurable Manipulators Based on Critic-only Policy Iteration Algorithm

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• 英文论文题名：Optimal Tracking Control for Reconfigurable Manipulators Based on Critic-only Policy Iteration Algorithm
• 论文作者：Hongbing Xia ; Bo Zhao ; Yuanchun Li
• 英文论文作者：Hongbing Xia ; Bo Zhao ; Yuanchun Li ; Department of Control Science and Engineering ; Changchun University of Technology ; The State Key Laboratory of Management and Control for Complex Systems ; Institute of Automation ; Chinese Academy of Sciences
• 年：2017
• 作者机构：Department of Control Science and Engineering,Changchun University of Technology;The State Key Laboratory of Management and Control for Complex Systems,Institute of Automation,Chinese Academy of Sciences;
• 英文论文关键词：Adaptive dynamic programming ; Reconfigurable manipulators ; Optimal tracking control ; Policy iteration ; Neural networks
• 会议召开时间：2017-07-26
• 会议录名称：第36届中国控制会议论文集（B）
• 英文会议录名称：Proceedings of the 36th Chinese Control Conference（B）
• 语种：英文
• 分类号：TP242
• 学会代码：KZLL
• 会议名称：第36届中国控制会议
• 会议地点：中国辽宁大连
• 主办单位：中国自动化学会控制理论专业委员会
• 学会名称：中国自动化学会控制理论专业委员会
• 页数：6
• 文件大小：318k
• 原文格式：D
• 会议级别：全国

摘要

This paper tackles the optimal tracking control problem for reconfigurable manipulators based on critic-only policy iteration(Co PI) algorithm. By system transformation, the optimal tracking control problem is transformed into an optimal regulation problem. The optimal tracking controller is composed of the desired controller and the approximate optimal feedback one. The desired controller is developed to maintain the desired tracking performance at the steady-state, while the approximate optimal feedback controller is designed to stabilize the tracking error dynamics in an optimal manner. Then, a critic neural network is used to estimate the optimal performance index function, and the optimal feedback control is obtained by the Co PI algorithm. The convergence of the proposed method is analyzed and it is shown that the closed-loop system based on Co PI is uniformly ultimately bounded by using the Lyapunov approach. Finally, simulation studies are given to show the effectiveness of the developed method.
This paper tackles the optimal tracking control problem for reconfigurable manipulators based on critic-only policy iteration(Co PI) algorithm. By system transformation, the optimal tracking control problem is transformed into an optimal regulation problem. The optimal tracking controller is composed of the desired controller and the approximate optimal feedback one. The desired controller is developed to maintain the desired tracking performance at the steady-state, while the approximate optimal feedback controller is designed to stabilize the tracking error dynamics in an optimal manner. Then, a critic neural network is used to estimate the optimal performance index function, and the optimal feedback control is obtained by the Co PI algorithm. The convergence of the proposed method is analyzed and it is shown that the closed-loop system based on Co PI is uniformly ultimately bounded by using the Lyapunov approach. Finally, simulation studies are given to show the effectiveness of the developed method.

引文

[1]T.M.Roehr,F.Cordes and F.Kirchner,Reconfigurable integrated multi-robot exploration system:heterogeneous modular reconfigurable robots for space exploration,Journal of Field Robotics,31(1):3–34 2014.
    [2]N.Tan,R.Nicolas,E.M.Rajesh,V.Kee,and R.Sosa,Nested reconfigurable robots:theory,design,and realization,International Journal of Advanced Robotic Systems,12:1-12,2015.
    [3]M.Biglarbegian,W.Melek and J.M.Mendel,Design of novel interval type-2 fuzzy controllers for modular and reconfigurable robots:theory and experiments.IEEE Transactions on Industrial Electronics,58(4):1371–1384,2011.
    [4]B.Zhao and Y.Li,Local joint information based active fault tolerant control for reconfigurable manipulator,Nonlinear Dynamics,77(3):859–876,2014.
    [5]W.Kasprzak,W.Szynkiewicz,D.Zlatanov and T.Zieli n′ska,A hierarchical CSP search for path planning of cooperating self-reconfigurable mobile fixtures,Engineering Applications of Artificial Intelligence,34(9):85–98,2014.
    [6]P.J.Werbos,Approximate dynamic programming for real-time control and neural modeling,Handbook of Intelligent Control Neural Fuzzy and Adaptive Approaches,1992,chapter 13.
    [7]D.Vrabie and F.L.Lewis,Adaptive dynamic programming for online solution of a zero-sum differential game,Journal of Control Theory and Applications,9(3):353–360,2011.
    [8]D.Liu and Q.Wei,Policy iteration adaptive dynamic programming algorithm for discrete-time nonlinear systems,IEEE Transactions on Neural Networks and Learning Systems,25(3):621–634,2014.
    [9]C.Qin,H.Zhang and Y.Luo,Optimal tracking control of a class of nonlinear discrete-time switched systems using adaptive dynamic programming,Neural Computing and Applications,24(3):531–538,2014.
    [10]Q.Lin,Q.Wei and D.Liu,A novel optimal tracking control scheme for a class of discrete-time nonlinear systems using generalised policy iteration adaptive dynamic programming algorithm,International Journal of Systems Science,Doi:10.1080/00207721.2016.1188177,2016.
    [11]G.S.Lakshmikanth,R.Padhi,J.M.Watkins and J.E.Steck,Single network adaptive critic aided nonlinear dynamic inversion for suboptimal command tracking,2011 IEEE International Symposium on Intelligent Control,CO,USA,September28–30,2011:1347–1352.
    [12]D.Liu,D.Wang and H.Li,Decentralized stabilization for a class of continuous-time nonlinear interconnected systems using online learning optimal control approach,IEEE Transactions on Neural Networks and Learning Systems,25(2):411–428,2014.
    [13]B.Zhao,D.Liu and Y.Li,Online fault compensation control based on policy iteration algorithm for a class of affine nonlinear systems with actuator failures,IET Control Theory&Applications,10(15):1816–1823,2016.
    [14]H.Zhang,L.Cui,X.Zhang and Y.Luo,Data-driven robust approximate optimal tracking control for unknown general nonlinear systems using adaptive dynamic programming method,IEEE Transactions on Neural Networks,22(12):2226–2236,2011.
    [15]M.Abu-Khalaf and F.L.Lewis,Nearly optimal control laws for nonlinear systems with saturating actuators using a neural network HJB approach,Automatica,4(15):779–791,2005.
    [16]K.G.Vamvoudakis and F.L.Lewis,Online actor-critic algorithm to solve the continuous-time infinite horizon optimal control problem,Automatica,46(5):878–888,2010.