Unified adaptive event‐triggered control of uncertain multi‐input multi‐output nonlinear systems with dynamic and static constraints
Tianping Zhang, Yu Hua, Xiaonan Xia, Yang Yi
Abstract
Abstract 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.