Adaptive recursive terminal sliding mode control with fuzzy optimization for trajectory tracking of Mecanum-wheeled mobile robots.

Abstract

This paper proposes an adaptive recursive terminal sliding mode control method for the trajectory tracking of Mecanum-wheeled mobile robots. To effectively alleviate control chattering and avoid adaptive overcompensation, a leakage-type adaptive law is introduced to dynamically adjust the control gains. Uncertainties, including parameter uncertainties, external disturbances, and unmodeled dynamics, are characterized using fuzzy set theory, based on which a fuzzy-set-based optimization strategy is developed. This strategy quantifies the impact of control parameters on trajectory tracking performance and control effort, thereby achieving an optimal trade-off between tracking performance and control effort. Finally, experiments conducted on a physical Mecanum-wheeled mobile robot platform demonstrate the effectiveness of the proposed method.