This article focuses on the event-triggered (ET) fuzzy tracking control for uncertain state constrained strict-feedback systems with unknown control directions. A novel nonlinear transformed function is developed to transform the constrained system states into the counterpart without any constraints. An ingenious adaptation law is developed to co-design the control law and the ET rule, thereby effectively compensating the sampling error caused by the ET rule under unknown control directions. Based on the presented adaptation law and the Nussbaum gain technique, a novel ET fuzzy tracking control strategy is proposed, which can handle the situations with and without state constraints in a unified way without readjusting the control scheme. Subsequently, the nonlinear transformed function is extended to the time-varying state constraints, and the corresponding ET fuzzy control scheme is also modified to guarantee the closed-loop boundedness. The proposed two control strategies guarantee the satisfactory tracking performance, avoid the violation of the prescribed state constraints, and decrease the communication load effectively. Finally, the usefulness of the developed methods is verified through two simulation examples.

中文翻译：

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周期性边界条件下拟线性抛物型偏微分方程系统的静态配置分段模糊控制设计


本文重点研究控制方向未知的不确定状态约束严格反馈系统的事件触发（ET）模糊跟踪控制。开发了一种新颖的非线性变换函数，可以将受约束的系统状态转换为不受任何约束的对应系统状态。提出了一种巧妙的自适应律来共同设计控制律和ET规则，从而有效地补偿ET规则在未知控制方向下引起的采样误差。基于所提出的自适应律和Nussbaum增益技术，提出了一种新颖的ET模糊跟踪控制策略，该策略可以统一处理有状态约束和无状态约束的情况，而无需重新调整控制方案。随后，将非线性变换函数推广到时变状态约束，并修改相应的ET模糊控制方案以保证闭环有界性。所提出的两种控制策略保证了令人满意的跟踪性能，避免违反规定的状态约束，并有效地降低了通信负载。最后，通过两个仿真例子验证了所开发方法的实用性。