Error Bounds of Adaptive Dynamic Programming Algorithms for Solving Undiscounted Optimal Control Problems
Liu, Derong; Li, Hongliang; Wang, Ding
发表期刊IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
2015-06-01
卷号26期号:6页码:1323-1334
文章类型Article
摘要In this paper, we establish error bounds of adaptive dynamic programming algorithms for solving undiscounted infinite-horizon optimal control problems of discrete-time deterministic nonlinear systems. We consider approximation errors in the update equations of both value function and control policy. We utilize a new assumption instead of the contraction assumption in discounted optimal control problems. We establish the error bounds for approximate value iteration based on a new error condition. Furthermore, we also establish the error bounds for approximate policy iteration and approximate optimistic policy iteration algorithms. It is shown that the iterative approximate value function can converge to a finite neighborhood of the optimal value function under some conditions. To implement the developed algorithms, critic and action neural networks are used to approximate the value function and control policy, respectively. Finally, a simulation example is given to demonstrate the effectiveness of the developed algorithms.
关键词Adaptive Critic Designs Adaptive Dynamic Programming (Adp) Approximate Dynamic Programming Neural Networks Neurodynamic Programming Nonlinear Systems Optimal Control
WOS标题词Science & Technology ; Technology
关键词[WOS]TIME NONLINEAR-SYSTEMS ; MARKOV DECISION-PROCESSES ; OPTIMAL TRACKING CONTROL ; ZERO-SUM GAMES ; POLICY ITERATION ; LAPLACIAN FRAMEWORK ; UNKNOWN DYNAMICS ; FEEDBACK-CONTROL ; CONTROL SCHEME ; HJB SOLUTION
收录类别SCI
语种英语
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Artificial Intelligence ; Computer Science, Hardware & Architecture ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号WOS:000354957000017
引用统计
被引频次:48[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/7924
专题多模态人工智能系统全国重点实验室_复杂系统智能机理与平行控制团队
作者单位Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
第一作者单位中国科学院自动化研究所
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GB/T 7714
Liu, Derong,Li, Hongliang,Wang, Ding. Error Bounds of Adaptive Dynamic Programming Algorithms for Solving Undiscounted Optimal Control Problems[J]. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,2015,26(6):1323-1334.
APA Liu, Derong,Li, Hongliang,&Wang, Ding.(2015).Error Bounds of Adaptive Dynamic Programming Algorithms for Solving Undiscounted Optimal Control Problems.IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS,26(6),1323-1334.
MLA Liu, Derong,et al."Error Bounds of Adaptive Dynamic Programming Algorithms for Solving Undiscounted Optimal Control Problems".IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 26.6(2015):1323-1334.
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