In this article, a unified adaptive neural event‐triggered control strategy is presented for uncertain multi‐input multi‐output (MIMO) nonlinear systems with dynamic and static constraints in the presence of unmodeled dynamics. By introducing an invertible nonlinear mapping based on hyperbolic tangent function, the constrained original system is transformed into an equivalent unconstrained MIMO pure‐feedback system. A dynamic signal is employed to dispose of the dynamical uncertainties in the novel system. Based on the transformed system, unified adaptive event‐triggered controller is formed by using modified dynamic surface control technique and the bounded characteristic of Gaussian function. Using the introduced compact set in stability analysis and Lyapunov function method, all signals in the closed‐loop system are proved to be the semiglobal uniform ultimate boundedness. Furthermore, all states and output signals can strictly comply with the defined constraint conditions. Simulations of two numerical examples including 2‐link rigid manipulator are provided to verify and clarify the theoretical results.

中文翻译：

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具有动态和静态约束的不确定多输入多输出非线性系统的统一自适应事件触发控制

在本文中，针对具有动态和静态约束的不确定多输入多输出（MIMO）非线性系统，在存在未建模动力学的情况下，提出了一种统一的自适应神经事件触发控制策略。通过引入基于双曲正切函数的可逆非线性映射，将受约束的原始系统转换为等效的无约束MIMO纯反馈系统。在新系统中采用动态信号来处理动态不确定性。基于改造后的系统，利用改进的动态表面控制技术和高斯函数的有界特性，形成统一的自适应事件触发控制器。使用引入的紧定集进行稳定性分析和Lyapunov函数方法，闭环系统中的所有信号都被证明是半全局一致的最终有界度。此外，所有状态和输出信号都可以严格遵守定义的约束条件。提供了两个数值示例（包括2连杆刚性机械手）的仿真，以验证和阐明理论结果。