Adaptive Intelligent Control-Based Consensus Tracking for a Class of Switched Nonstrict Feedback Nonlinear Multiagent Systems With Unmodeled Dynamics

Based on the adaptive intelligent control technique, we develop an adaptive consensus tracking control scheme for the distributed switched nonstrict feedback nonlinear multiagent systems (MASs) with unmodeled dynamics. According to the properties of Gaussian functions, a fresh scheme is utilized to handle the nonstrict feedback form. Based on the characters of unmodeled dynamics, a dynamic signal is designed to resolve the design difficulties caused by the unmodeled dynamics. In the design process of the adaptive switching controllers, the backstepping technique is adopted and the unknown nonlinear functions are estimated by utilizing the radial basis function neural networks' intelligent technique. Besides, a common Lyapunov function is constructed to analyze the system's stability. Under the Lyapunov stability theory, it is rigorously demonstrated that all signals of the closed-loop switched MAS are cooperatively semiglobal uniformly ultimately bounded and the outputs of all the followers eventually track the leader's output. Finally, the simulation results of a practical example is presented to confirm the efficiency of the proposed control scheme.