Disturbance Observer-Based Fuzzy Adaptive Containment Control of Nonlinear Multi-agent Systems with Input Quantization

This paper addresses the fuzzy adaptive containment control problem for nonlinear multi-agent systems with unknown external disturbance and input quantization under a directed graph. Firstly, the quantized input signal and unknown external disturbance are simultaneously considered in the pure-feedback multi-agent systems. Fuzzy logic systems and disturbance observers are used to deal with unknown nonlinear functions and external disturbances, respectively. By using the second-order tracking differentiators, the containment control scheme is developed to guarantee that all followers converge to the dynamic convex hull formed by the leaders, and containment errors can converge to the boundary with prescribed performance. It is theoretically shown that all the signals of the closed-loop system are semi-globally uniformly bounded. Finally, a comparative simulation example is given to verify the effectiveness and superiority of the proposed method.