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.

本文通过状态约束脉冲控制研究了具有未知非线性动力学的多智能体系统 (MAS) 的自适应模糊领导者跟随共识问题。建立模糊逻辑系统(FLSs)来估计未知的非线性动力学。同时，设计一个自适应参数的目的是减少对 FLS 不确定因素的影响，通过在跟随代理与其邻居之间交换所需的信息来不断调整该参数。由于实现了不连续控制，脉冲控制理论被应用于降低连续通信的成本，其中跟随代理仅在固定的脉冲时刻与领导代理通信。考虑实际控制系统中的物理或环境约束，将基于饱和函数的状态约束引入到 MAS 中。然后，采用自适应模糊控制和状态约束脉冲控制来保证总代理能够收敛到共识。最后，给出了一些数值模拟来说明理论结果的可行性。