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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
Conference Namethe 14th International Symposium on Neural Networks (ISNN 2017)
Conference Date2017-6-21
Conference PlaceSapporo, Hokkaido, Japan
AbstractIn 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.
Indexed ByEI
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/14349
Collection复杂系统管理与控制国家重点实验室_平行控制
AffiliationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
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.
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