Hierarchical Fuzzy Sliding-Mode Adaptive Control for the Trajectory Tracking of Differential-Driven Mobile Robots

Abstract

The trajectory tracking of a differential-driven mobile robot (DDMR) with uncertainties and unknown dynamics is investigated using a hierarchical fuzzy sliding-mode adaptive controller (HFSMAC). First, the position error between the actual DDMR and the virtual reference DDMR with respect to the world frame is determined. Based on the aforementioned position error, fuzzy sliding-mode control is used to generate the virtual reference input and attain position tracking. It is well known that the performance and stability of a closed-loop system often deteriorate in the presence of uncertainties. Therefore, a function approximation technique (FAT)-based adaptive controller is used here to learn the unknown dynamics and deals with the external uncertainties via a set of Fourier series to achieve velocity tracking. The proposed HFSMAC has been verified to lead to good robustness levels, effective learning, and accurate trajectory tracking. Computer simulations have been conducted to validate the theoretical developments confirming the efficacy and robustness of the proposed scheme. Finally, a comparative study with a PID controller is presented to further prove the superior performance of the proposed HFSMAC.