控制理论(社会学)
反推
计算机科学
前馈
估计员
跟踪误差
外稃(植物学)
自适应控制
补偿(心理学)
事件(粒子物理)
控制(管理)
控制工程
工程类
数学
人工智能
统计
物理
精神分析
生物
量子力学
禾本科
生态学
心理学
作者
Lianhua Li,Kai Zhao,Zhirong Zhang,Yongduan Song
标识
DOI:10.1109/tac.2023.3328167
摘要
In this note, we present an event-triggered robust adaptive control method with flexible prescribed performance for strict-feedback nonlinear systems. Unlike most existing event-triggered control results with only the inputs being triggered, here we introduce a triggering mechanism into the control law and the parameter estimator simultaneously, so that the communication resources are saved. It is worth noting that under the proposed triggering conditions, there are some challenges and difficulties in directly applying the backstepping technique, as the intermittent (triggering) parameter adaptive law introduces additional sampling errors. To address this issue, a decomposition technique for the event-triggered adaptive law and a new lemma for handling the event error are introduced, with which the execution error is gracefully counteracted with a properly designed compensation unit. Moreover, to ensure the flexible prescribed tracking performance, we incorporate a series of functional transformations into the control design. It is shown that, with the fixed control structure, only by adjusting the key parameters and time-varying function, the proposed control can generate multiple kinds of prescribed performance behaviors, which is more general and flexible than the existing prescribed performance controls. The effectiveness of our control scheme is verified by simulation results.
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