Design of adaptive neural fuzzy formation controller for multi-robot systems

Abstract

This paper aims to investigate the formation control of multi-robot systems, where the first-order kinematic model of a differential wheeled robot is considered. Based on the graph theory and consensus algorithm, an adaptive neural fuzzy formation controller is designed with the capability of on-line learning. The learning rules of controller parameters can be derived from the analyzing of Lyapunov stability. Simulations are adopted to verify the feasibility of proposed techniques. From simulation results, the proposed adaptive neural fuzzy controller can provide better formation responses compared to conventional consensus algorithm.