Adaptive backstepping decentralized formation control using fuzzy wavelet neural networks for uncertain mecanum-wheeled omnidirectional multi-vehicles

This paper presents a decentralized consensus formation control using fuzzy wavelet neural networks (FWNN) for a group of homogenous, mobile four-Mecanum-wheeled omnidirectional vehicles (MWOVs) with uncertainties. The dynamic behavior of each MWOV is remodeled by a three-input-three-output second-order system model and the multi-MWOV system is modeled by graph theory. By online learning the system uncertainties using FWNN and using backstepping techniques, an intelligent adaptive, cooperative consensus-based control approach is presented to carry out formation control in the presence of uncertainties. Simulations are conducted to show the effectiveness and merits of the proposed method.