Collision-Free Adaptive Fuzzy Formation Control for Stochastic Nonlinear Multiagent Systems
Wei Wu, Shaocheng Tong
Abstract
This article considers the collision-free fuzzy output-feedback formation control problem for stochastic nonlinear multiagent systems (MASs) with immeasurable states. The fuzzy state observers are established to estimate the unmeasurable states of MASs, and fuzzy-logic systems (FLSs) are utilized to identify the unknown internal dynamics. The prescribed performance functions (PPFs) are introduced to establish the collision avoidance conditions between the follower agent and its leader agent. Then, a novel collision-free adaptive output-feedback formation controller is constructed by utilizing a suitable error transformation. The presented formation control method can guarantee all the variables of the stochastic nonlinear MASs are bounded in probability and each follower agent and the leader agent are free of collision. Finally, the presented formation control method is applied to the unmanned surface vehicle (USV) systems, and the effectiveness and superiorities are checked by the simulation results and comprehensive comparisons.