Decentralized Control for Second-Order Uncertain Nonlinear Multi-agent Systems Consensus Problem Based on Fuzzy Adaptive High-Gain Observer

A novel decentralized control approach for second-order uncertain nonlinear multi-agent systems is presented. The communication topology of the multi-agent system that describes completely unknown nonlinear dynamics and unmeasured states is described by a directed graph. The proposed decentralized control algorithm is developed based on high-gain observer theory and fuzzy adaptive control algorithm. The high-gain observer is introduced to estimate the agents´ unmeasured states. The fuzzy logic systems are used as the approximator to deal with the nonlinear unknown dynamics. By the Lyapunov theory and consensus analysis, we can prove the consensus errors and the observer errors can be reduced as small as desired by choosing the appropriate design parameters. Finally, the effectiveness of the proposed approach is illustrated by the simulation example.