Adaptive fuzzy leader-following consensus for nonlinear multi-agent systems via state-constraint impulsive control

摘要

This paper investigates the adaptive fuzzy leader-following consensus problem of multi-agent systems (MASs) with unknown nonlinear dynamics via state-constraint impulsive control. The fuzzy logic systems(FLSs) are established to estimate the unknown nonlinear dynamics. Meanwhile, the purpose of designing one adaptive parameter is to reduce the impact on uncertain factors of FLSs, where this parameter is constantly adjusted by exchanging required information between follower agents and its neighbors. The impulsive control theory is applied to reduce the cost of continuous communication due to the achievement of discontinuous control, where follower agents only communicate with leader agent at fixed impulsive instants. To consider the physical or environmental constraints in real control systems, the state-constraint based on saturation function is introduced to MASs. Then, both adaptive fuzzy control and state-constraint impulsive control are employed to guarantee that total agents can converge to consensus. Finally, some numerical simulations are given to illustrate the feasibility of the theoretical results.