Adaptive Fuzzy Iterative Learning Consensus Control for Leader-Following Nonlinear Multi-Agent Systems with Uncertain External Disturbances
Xiongfeng Deng, Liang Tao, Yuan Ge, Wenzhan Li · 2021
This paper addresses a class of leader-following multi-agent systems, where the model of each following agent consists of unknown nonlinear dynamics and uncertain external disturbances. An adaptive fuzzy iterative learning control protocol is designed to sovle the tracking control problem. It is assumed that the dynamics of leader agent is unknown for each following agent. The nonlinear dynamics and uncertain external disturbances of agents are approximated by introducing the fuzzy logic systems, and a re-designed Lyapunov function is considered to analyze the convergence of the presented control protocol. In addition, the adaptive updating control laws for the introduced parameters are presented. Finally, the effectiveness of theoretical results is verified by one simulation example.