Fixed-time optimized control for nonlinear strict-feedback systems based on reinforcement learning and disturbance observer

IF 3.4 2区 数学 Q1 MATHEMATICS, APPLIED
Dong-Xiang Gao , Wen-Hua Cui , Li-Bing Wu , Yu-Jun Zhang , Ye Tao
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引用次数: 0

Abstract

The present study focuses on the fixed-time optimal control problem for a class of nonlinear strict-feedback systems subject to unknown external disturbances. First, a fuzzy state and disturbance observer is developed to estimate both unmeasurable states and external disturbances. To further improve estimation accuracy of external disturbances, a novel intermediate variable estimator incorporating a time-varying gain parameter is introduced. Subsequently, based on the disturbance-observer-critic-actor (DOCA) reinforcement learning architecture, a fixed-time optimal control strategy is proposed by integrating fuzzy approximation and backstepping techniques. This approach ensures optimality in both virtual and actual control of the controlled system while guaranteeing its fixed-time stability. Finally, the effectiveness of the proposed strategy is validated through theoretical and simulation studies.
基于强化学习和扰动观测器的非线性严格反馈系统定时优化控制
研究一类具有未知外部扰动的非线性严格反馈系统的固定时间最优控制问题。首先,建立了一种模糊状态和干扰观测器,用于估计不可测状态和外部干扰。为了进一步提高外部干扰的估计精度,引入了一种新的含时变增益参数的中间变量估计器。随后,基于干扰-观察者-关键-参与者(DOCA)强化学习架构,结合模糊逼近和反演技术,提出了一种固定时间最优控制策略。该方法既保证了被控系统的虚控和实控的最优性,又保证了系统的定时稳定性。最后,通过理论和仿真研究验证了所提策略的有效性。
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来源期刊
CiteScore
7.90
自引率
10.00%
发文量
755
审稿时长
36 days
期刊介绍: Applied Mathematics and Computation addresses work at the interface between applied mathematics, numerical computation, and applications of systems – oriented ideas to the physical, biological, social, and behavioral sciences, and emphasizes papers of a computational nature focusing on new algorithms, their analysis and numerical results. In addition to presenting research papers, Applied Mathematics and Computation publishes review articles and single–topics issues.
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