控制理论与应用2011，Vol.28Issue(8)：1187-1192,6.
基于执行器-评价器学习的自适应PID控制
A novel adaptive PID controller based on Actor-Critic learning
摘要
Abstract
Owing to the lack of the self-tuning for PID parameters in typical PID（T-PID） controllers, a self tuning PID control strategy using Actor-Critic learning（AC-PID） is proposed. Actor-Critic learning is used to tune PID parameters of the controller in an adaptive way. The policy function of Actor and the value function of Critic are approximated by a simple radial basis function neural network. The system error, the first and the second-order differences of system error are employed as inputs to the radial basis function network. The mapping from the system states to PID parameters is realized by the Actor, and the temporal difference（TD） error is evaluated by the Critic. Based on the structure of Actor-Critic learning and TD error performance index, the block diagram of the controller is developed. Two simulation results show that the proposed controller is efficient and perfectly adaptable with fast responses, providing better performances than the typical PID controller.关键词
强化学习/执行器-评价器/自适应PID控制Key words
reinforcement learning/Actor-Critic/adaptive PID control分类
信息技术与安全科学引用本文复制引用
陈学松,杨宜民..基于执行器-评价器学习的自适应PID控制[J].控制理论与应用,2011,28(8):1187-1192,6.基金项目
国家自然科学基金资助项目 （）
广东省自然科学基金资助项目（9451009001002686）. （）
