Policy Iteration for Optimal Control of Weakly Coupled Nonlinear Systems with Completely Unknown Dynamics
Li, Chao1; Wang, Ding1; Liu, Derong2; He, Haibo3
2016
会议名称2016 American Control Conference
会议日期July 6-8, 2016
会议地点Boston, MA, USA
摘要In this paper, an online learning algorithm based on policy iteration is established to solve the optimal control problem for weakly coupled nonlinear continuous-time systems. Using the weak coupling theory, the original problem is transformed into three reduced-order optimal control problems. To obtain the optimal control laws without system dynamics, we construct an online data-based integral policy iteration algorithm which is used to solve the decoupled optimal control problems. The actor-critic technique based on neural networks and the least squares method are used to implement the model-free learning algorithm. A simulation example is given to verify the applicability of the developed algorithm.
收录类别EI
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/14315
专题复杂系统管理与控制国家重点实验室_平行控制
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100190, Peoples R China
2.Univ Sci & Technol Beijing, Sch Automat & Elect Engn, Beijing 100083, Peoples R China
3.University of Rhode Island, Kingston, RI 02881 USA
推荐引用方式
GB/T 7714
Li, Chao,Wang, Ding,Liu, Derong,et al. Policy Iteration for Optimal Control of Weakly Coupled Nonlinear Systems with Completely Unknown Dynamics[C],2016.
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