Optimal Control for Discrete-Time Nonlinear Systems with Actuator Saturation Based on Generalized Policy Iteration Adaptive Dynamic Programming Algorithm

	Optimal Control for Discrete-Time Nonlinear Systems with Actuator Saturation Based on Generalized Policy Iteration Adaptive Dynamic Programming Algorithm
	Lin Q(林桥); Qinglai Wei; Bo Zhao
	2017
会议名称	the 14th International Symposium on Neural Networks (ISNN 2017)
会议日期	2017-6-21
会议地点	Sapporo, Hokkaido, Japan
摘要	In this study, a nonquadratic performance function is introduced to overcome the saturation nonlinearity in actuators. Then, a novel generalized policy iteration Adaptive dynamic programming algorithm is developed to deal with the optimal control problem. Two neural networks are introduced to approximate the control law and performance index function and one simulation example is given to illustrate the convergence and feasibility 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/173211/14349
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	Institute of Automation, Chinese Academy of Sciences
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 Q,Qinglai Wei,Bo Zhao. Optimal Control for Discrete-Time Nonlinear Systems with Actuator Saturation Based on Generalized Policy Iteration Adaptive Dynamic Programming Algorithm[C],2017.