Policy Iteration for Optimal Control of Weakly Coupled Nonlinear Systems with Completely Unknown Dynamics

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

	Policy Iteration for Optimal Control of Weakly Coupled Nonlinear Systems with Completely Unknown Dynamics
	Li, Chao1 ; Wang, Ding1 ; Liu, Derong 2; He, Haibo 3
	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	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 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
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	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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