A novel optimal tracking control scheme for a class of discrete-time nonlinear systems using generalised policy iteration adaptive dynamic programming algorithm

doi:10.1080/00207721.2016.1188177

CASIA OpenIR > 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

	A novel optimal tracking control scheme for a class of discrete-time nonlinear systems using generalised policy iteration adaptive dynamic programming algorithm
	Lin, Qiao1 ; Wei, Qinglai1 ; Liu, Derong 2
发表期刊	INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE
	2017
卷号	48 期号:3 页码:525-534
文章类型	Article
摘要	In this paper, a novel iterative adaptive dynamic programming (ADP) algorithm, called generalised policy iteration ADP algorithm, is developed to solve optimal tracking control problems for discrete-time nonlinear systems. The idea is to use two iteration procedures, including an i-iteration and a j-iteration, to obtain the iterative tracking control laws and the iterative value functions. By system transformation, we first convert the optimal tracking control problem into an optimal regulation problem. Then the generalised policy iteration ADP algorithm, which is a general idea of interacting policy and value iteration algorithms, is introduced to deal with the optimal regulation problem. The convergence and optimality properties of the generalised policy iteration algorithm are analysed. Three neural networks are used to implement the developed algorithm. Finally, simulation examples are given to illustrate the performance of the present algorithm.
关键词	Adaptive Dynamic Programming Affine Nonlinear Systems Discrete-time Generalised Policy Iteration Neural Network Tracking Control
WOS标题词	Science & Technology ; Technology
DOI	10.1080/00207721.2016.1188177
关键词[WOS]	CRITIC DESIGNS
收录类别	SCI
语种	英语
项目资助者	National Natural Science Foundation of China(61233001 ; Beijing Natural Science Foundation(4132078) ; Early Career Development Award of SKLMCCS ; 61273140 ; 61304086 ; 61374105 ; 61533017)
WOS研究方向	Automation & Control Systems ; Computer Science ; Operations Research & Management Science
WOS类目	Automation & Control Systems ; Computer Science, Theory & Methods ; Operations Research & Management Science
WOS记录号	WOS:000385940700008
引用统计	被引频次：34[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/173211/13331
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	1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China 2.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing, Peoples R China
第一作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Lin, Qiao,Wei, Qinglai,Liu, Derong. A novel optimal tracking control scheme for a class of discrete-time nonlinear systems using generalised policy iteration adaptive dynamic programming algorithm[J]. INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE,2017,48(3):525-534.
APA	Lin, Qiao,Wei, Qinglai,&Liu, Derong.(2017).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,48(3),525-534.
MLA	Lin, Qiao,et al."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 48.3(2017):525-534.

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