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.
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.