Adaptive Fuzzy Leader-Following Consensus Quantized Control for High-Order Nonlinear Multi-Agent Systems

This paper investigates the adaptive fuzzy leader-following consensus control problem for a class of high-order nonlinear multi-agent systems with quantized input signals. Considering the complex dynamics of high-order nonlinear multi-agent systems, a novel adaptive fuzzy control strategy with equivalent virtual controller is proposed to achieve the consensus tracking performance and guarantee the uniform ultimate boundedness of the closed-loop nonlinear system. During the control design process, only the states information from the subsystem itself and its neighbors and part of the information from the reference signals are available. In addition, the hysteresis quantizer is utilized to reduce the chattering phenomenon. Finally, a numerical simulation example is given to show the effectiveness of the proposed control strategy.