Design an intelligent proportional-derivative (PD) feedback linearization control for nonholonomic-wheeled mobile robot

Abstract

This paper proposes a novel optimal Proportional–derivative (PD) Feedback linearization controller to achieve the best trajectory tracking for nonholonomic Wheeled Mobile Robots (WMRs). In the core of the proposed method, a novel population-based optimization technique, called Teaching-Learning-Based Optimization (TLBO), is employed for evolving the PD controller. The proposed controller can handle the problem of the integrated kinematic and dynamic tracking difficulty. To show the effectiveness of the proposed method, the performance of the optimal TLBO-PD controller is compared with the optimal PSO-PD controller. Simulation results demonstrate the superiority of the proposed control scheme.