Adaptive optimal output regulation of linear discrete-time systems based on event-triggered output-feedback
Adaptive optimal output regulation of linear discrete-time systems based on event-triggered output-feedback
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DOI：
10.1016/j.automatica.2021.110103
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发表时间：
2022-03
期刊：
影响因子：
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通讯作者：
Fuyu Zhao;Weinan Gao;Tengfei Liu;Zhong-Ping Jiang
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文献类型：
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作者：
Fuyu Zhao;Weinan Gao;Tengfei Liu;Zhong-Ping Jiang
针对一类线性离散时间系统的自适应最优输出调节问题，提出了一种新颖的事件触发控制方法。与大多数现有的输出调节问题的研究不同，已开发的自适应最优控制方法基于(1)输出反馈而不是全状态或部分状态反馈，(2)自适应动态规划(ADP)，它提供最优控制问题的近似解，而不需要精确的被控对象动态知识，(3)事件触发机制，减少控制器与被控对象之间的通信。证明了所设计的控制器使闭环系统在利益平衡点渐近稳定，跟踪误差渐近收敛到零。此外，闭环系统的次优性直接由相对阈值决定，相对阈值是触发阈值与实际状态之比。数值仿真算例验证了所提方法的有效性。
This paper presents novel event-triggered control approaches to solve the adaptive optimal output regulation problem for a class of linear discrete-time systems. Different from most existing research on output regulation problems, the developed adaptive optimal control approaches are based on (1) output-feedback instead of full-state or partial-state feedback, (2) adaptive dynamic programming (ADP) which provides approximate solutions of the optimal control problem without requiring the precise knowledge of the plant dynamics, and (3) an event-triggering mechanism that reduces the communication between the controller and the plant. It is shown that the system in closed-loop with the developed controllers is asymptotically stable at an equilibrium of interest, and the tracking errors asymptotically converge to zero. Moreover, the suboptimality of the closed-loop system is directly determined by the relative threshold, which is a ratio between the triggering threshold and the actual state. A numerical simulation example is employed to verify the effectiveness of the proposed methodologies.