An Adaptive Fuzzy Dynamic Surface Control Tracking Algorithm for Mecanum Wheeled Mobile Robot

This paper presents an Adaptive Fuzzy Dynamic Surface Control (AFDSC) algorithm for trajectory tracking of a four-Mecanum Wheeled Mobile Robot (MWMR). Firstly, the kinematics and dynamics equations for the robot mecanum can be constructed based on the Lagrange equation. Next, the proposed algorithm combines the advantages of dynamic surface control and fuzzy logic to enhance the tracking performance and robustness of the robot system. By incorporating a fuzzy logic system, the control algorithm is able to adaptively adjust the controller parameters based on the changing dynamics and uncertainties of the MWMR. The dynamic surface control technique effectively mitigates the "explosion of complexity" problem associated with traditional backstepping control methods, allowing for a simpler and more computationally efficient control architecture. The designed control algorithm is implemented and verified on a MWMR platform, and its performance is compared against other existing Dynamic Sliding Surface Control (DSC) methods. The simulation results demonstrated that the proposed adaptive fuzzy DSC algorithm achieves superior trajectory tracking accuracy, and improved convergence properties. The experimental results on Gazebo simulator further proved the feasibility of the proposed algorithm.