The article proposes a dynamic event-triggered adaptive predefined time output feedback control technique for uncertain switching multi-input multi-output (MIMO) nonlinear systems with strict feedback forms. In contrast to previous event-triggered output feedback control, the control technique proposed in this study not only enables the system to reach steady state within a predefined time, but also further saves communication resources. Subsequently, the unpredictable states of the system are modeled using a neural network (NN) state observer. In the framework of backstepping control, an output feedback control strategy based on command filtering is proposed. Finally, the stability for a switched nonlinear system has been demonstrated using predefined time stability theory and average dwell time (ADT). The results concern this semi-global practically predefined time stabilization (SGPPTS) of all signals in the closed-loop system. Simulations and comparisons are utilized to verify the predefined time control characteristics.

中文翻译：

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基于命令滤波器的神经网络，用于具有事件触发机制的开关非线性系统的预定义时间控制


本文提出了一种动态事件触发的自适应预定义时间输出反馈控制技术，用于具有严格反馈形式的不确定开关多输入多输出 （MIMO） 非线性系统。与以往的事件触发输出反馈控制相比，本研究提出的控制技术不仅使系统能够在预定时间内达到稳态，而且进一步节省了通信资源。随后，使用神经网络 （NN） 状态观察器对系统的不可预测状态进行建模。在反步控制的框架下，提出了一种基于命令滤波的输出反馈控制策略。最后，使用预定义的时间稳定性理论和平均驻留时间 （ADT） 证明了开关非线性系统的稳定性。结果涉及闭环系统中所有信号的半全局实际预定义时间稳定 （SGPPTS）。利用仿真和比较来验证预定义的时间控制特性。