The issue of event-based asymmetric predetermined performance control (PPC) has been addressed for p-normal nonlinear systems with time-varying unknown control coefficients. A set of Nussbaum functions is introduced, capable of addressing both single and multiple unknown control coefficients. To achieve asymmetric PPC, a switching constraint scheme is proposed. Subsequently, an adaptive fuzzy controller based on dynamic events is developed. Improved techniques for approximating the unknowns of a system using fuzzy logic systems (FLSs), while dynamic events are employed to reduce the frequency of controller updates. Using Lyapunov stability theory, it is proven that all signals in the closed-loop system remain bounded, and the tracking error is confined within the specified asymmetric boundaries. Eventually, the effectiveness of the present scheme is demonstrated by the simulation of three examples.

中文翻译：

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通过动态事件控制系数未知的 p 正态系统的自适应模糊预定性能控制


对于具有时变未知控制系数的 p 正态非线性系统，基于事件的非对称预定性能控制 (PPC) 问题已得到解决。引入了一组 Nussbaum 函数，能够处理单个和多个未知控制系数。为了实现非对称PPC，提出了切换约束方案。随后，开发了基于动态事件的自适应模糊控制器。使用模糊逻辑系统 (FLS) 来近似系统未知数的改进技术，同时采用动态事件来降低控制器更新的频率。利用李亚普诺夫稳定性理论证明了闭环系统中的所有信号都保持有界，并且跟踪误差被限制在指定的不对称边界内。最后通过三个算例的仿真验证了该方案的有效性。