利用自适应动态编程实现反线性系统的输出反馈控制

Li Yu, Hai Wang
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引用次数: 0

摘要

本文介绍了离散时间反线性系统(ALS)的自适应优化反馈控制方法。该方法利用采样和可测量的输入输出数据。通过采用自适应动态编程(ADP)技术,本研究对离散时间代数反里卡提方程(AARE)进行了迭代求解。首先,建立了 ALS 的输出反馈模型,并在此基础上开发了基于模型的算法。该算法的可行性建立在系统动态信息完全已知的前提下。随后,针对模型未知的情况,我们进一步开发了一种无模型 ADP 算法,专门用于解决模型不确定情况下的最优控制问题。有了这种算法,即使在缺乏详细系统动态信息的情况下,我们也能实现有效的控制优化。最后,我们通过仿真实验验证了该算法的可行性和有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Output feedback control of anti‐linear systems using adaptive dynamic programming
This paper introduces an adaptive optimal feedback control approach for discrete‐time anti‐linear systems (ALSs). The method utilizes sampling and measurable input–output data. By employing the Adaptive Dynamic Programming (ADP) technique, this study iteratively solves the discrete‐time algebraic Anti‐Riccati equation (AARE). Initially, an output feedback model is established for ALSs, and a model‐based algorithm is developed based on this model. The feasibility of this algorithm is based on the premise that the system dynamic information is completely known. Subsequently, for the scenario where the model is unknown, we further developed a model‐free ADP algorithm specifically designed to address optimal control problems in the presence of model uncertainty. With this algorithm, we achieve effective control optimization even in cases where detailed system dynamics information is lacking. Finally, through simulation experiments, we validated the feasibility and effectiveness of this algorithm.
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