CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 平行控制
Generalized Policy Iteration Adaptive Dynamic Programming Algorithm for Optimal Tracking Control of a Class of Nonlinear Systems
Lin Q(林桥)1; Qinglai Wei1; Derong Liu2
2016-08
Conference NameControl and Decision Conference (CCDC)
Conference Date2016-5-28
Conference PlaceYinchuan, China
AbstractThis paper deals with optimal tracking control problems for a class of discrete-time nonlinear systems using a generalized policy iteration adaptive dynamic programming (ADP) algorithm. First, by system transformation, the optimal tracking control problem is transformed into an optimal regulation problem. Then the generalized policy iteration ADP algorithm is employed to obtain the optimal tracking controller with convergence and optimality analysis. The developed algorithm uses the idea of two iteration procedures to obtain the iterative tracking control laws and the iterative value functions. Three neural networks, including model network, critic network and action network, are used to implement the developed algorithm. At last, an simulation example is given to demonstrate the effectiveness of the developed method.
Indexed ByEI
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14347
Collection复杂系统管理与控制国家重点实验室_平行控制
Affiliation1.Institute of Automation, Chinese Academy of Sciences
2.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing, Peoples R China
Recommended Citation
GB/T 7714
Lin Q,Qinglai Wei,Derong Liu. Generalized Policy Iteration Adaptive Dynamic Programming Algorithm for Optimal Tracking Control of a Class of Nonlinear Systems[C],2016.
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