控制理论与应用2023，Vol.40Issue(2)：220-230,11.DOI:10.7641/CTA.2022.11292
非零和微分博弈系统的事件触发最优跟踪控制
Event-triggered optimal tracking control for nonzero-sum differential game systems
摘要
Abstract
Recently,for the tracking problem of nonzero-sum differential game systems with unknown dynamics,it has been discussed that these methods are time-triggered,which is not ideal in an environment with limited transmission band-width and computing resources.In this paper,an integral reinforcement learning based event-triggered adaptive dynamic programming scheme is developed for continuous-time nonlinear nonzero-sum differential game systems with unknown dynamics.The strategy is inspired by the gradient descent method and the experience replay technique and uses the histori-cal and current data to update the neural network weight.This method can improve the convergence speed of neural network weight and remove the assumption of initial admissible control often used in general literature design.In the meantime,the algorithm proposes a persistent excitation condition(commonly called PE)that is easy to check online,which avoids the traditional PE condition that is not easy to check.Based on the Lyapunov theory,the uniform ultimate boundedness(UUB)properties of the tracking error and the critic neural network estimation error have been proved.Finally,a numerical simulation example is given to verify the feasibility of the proposed method.关键词
非零和博弈/积分强化学习/最优跟踪控制/神经网络/事件触发Key words
nonzero-sum games/integral reinforcement learning/optimal tracking control/neural network/event-triggered引用本文复制引用
石义博,王朝立..非零和微分博弈系统的事件触发最优跟踪控制[J].控制理论与应用,2023,40(2):220-230,11.基金项目
Supported by the National Defense Basic Research Program(JCKY2019413D001),the Natural Science Foundation(6217023627,62003214,62173054)and the Shanghai Natural Science Foundation(19ZR1436000). （JCKY2019413D001）
