控制理论与应用2025，Vol.42Issue(9)：1807-1817,11.DOI:10.7641/CTA.2024.30806
基于强化学习的一类不确定非线性系统的最优输出调节
Optimal output regulation for a class of uncertain nonlinear systems based on reinforcement learning
摘要
Abstract
For the optimal output regulation problem of a class of nonlinear systems with unknown nonlinear functions and external disturbances driven by a linear neutral stabilized external system,an adaptive optimal control strategy based on the evaluation executive network algorithm in reinforcement learning and the backstepping method is proposed.First,according to the condition that the regulator equations are solvable and the coordinate transformation,the output regulation problem of uncertain nonlinear systems is transformed into a stabilization problem.A neural network adaptive observer is designed to estimate the unmeasured state by using a radial basis function neural network to approach an unknown nonlinear function.Then an adaptive internal model based on reinforcement learning is designed,and the cost function associated with the internal model is presented,and an approximate optimal algorithm based on the evaluation executive network is used in every step of the backstepping method,all virtual controllers are guaranteed to be optimal.At the same time,the complexity explosion problem in backstepping is avoided by incorporating the dynamic surface technique.Finally,the proposed value function is not only optimized by the optimal adaptive output feedback controller,but also the signal semi globally of the closed loop system is eventually uniformly bounded and the tracking error is within the desired arbitrary accuracy.Numerical simulations verify the effectiveness of the proposed method.关键词
输出调节/最优控制/强化学习/反步法Key words
output regulation/optimal control/reinforcement learning/backstepping引用本文复制引用
齐佳鑫,孟桂芝..基于强化学习的一类不确定非线性系统的最优输出调节[J].控制理论与应用,2025,42(9):1807-1817,11.基金项目
黑龙江省"百千万"工程科技重大专项项目(2020ZX10A03),黑龙江省重点研发计划指导类项目(GZ20220106),国家外国专家项目(G2022012008)资助.Supported by the Heilongjiang Province"Million and Ten Thousand"Engineering Science and Technology Major Project(2020ZX10A03),the Hei-longjiang Province Key R&D Plan Guidance Project(GZ20220106)and the National Foreign Expert Project(G2022012008). （2020ZX10A03）
