Optimized Backstepping Fuzzy Sliding Mode Controller for Trajectory Tracking of Mobile Manipulator

Abstract

ABSTRACT This article presents a robust control technique for a Mobile Manipulator (MM), consisting of a robotic manipulator mounted on a mobile robot capable of operating in diverse environments such as land, air, space, or underwater. By leveraging the platform's mobility, the workspace of the manipulator is significantly expanded, allowing for optimal placement and enhanced task execution. To simultaneously control the end‐effector motion and platform velocity, a two‐step control approach is proposed. First, kinematic velocity control generates desired trajectories for the system. Second, a fuzzy sliding mode torque controller, integrated with backstepping, ensures the end‐effector position and platform velocity converge to these trajectories. The control parameters are optimized using Particle Swarm Optimization (PSO), with stability guaranteed through Lyapunov theory. Simulation results in MATLAB/SIMULINK demonstrate that the Optimized Backstepping Fuzzy Sliding Mode Control (OBFSMC) outperforms the Backstepping Sliding Mode Control (BSMC) in tracking accuracy, achieving a 31.6% performance improvement. The proposed controller effectively mitigates external disturbances and tolerates parametric uncertainties, confirming its robustness and efficiency in trajectory tracking under challenging conditions.