Application of an Adaptive Dynamic Sliding Surface Controller with Traction Tracking for a Mecanum Wheel Mobile Robot

Abstract

The paper introduces an algorithm application of an adaptive Dynamic Sliding Surface Controller that integrates neural networks and fuzzy logic systems with traction tracking for a Mecanum Wheel Mobile Robot. In this framework, neural networks are employed to approximate the uncertain nonlinear numerical aspects of MWMR, while fuzzy logic systems are utilized to adaptively. The stability of the closed-loop system is investigated using the Lyapunov criterion. The proposed controller is verified by numerical simulation. The simulation results show that the proposed controller performs better than the backstepping sliding controller in the case of uncertain model parameters and when there is an impact disturbance.