Optimized TVLQ Trajectory Tracking and Robustness Evaluation for a 4ISW4IAW Mobile Robot

Abstract

This paper investigates trajectory tracking control for a mobile robot with four independently steered and four independently actuated wheels. A time-varying linear quadratic (TVLQ) tracking controller is first reproduced using a chained-form model and a numerical optimization procedure. The controller weighting matrices are then systematically tuned using constrained nonlinear optimization and particle swarm optimization to improve nominal tracking performance. Simulation results on straight-line, circular, and rose-shaped trajectories show that the optimized controller preserves accurate nominal tracking and improves performance over manually selected weighting matrices. A robustness study is also carried out by comparing the optimized TVLQ controller with a stable super-twisting sliding mode controller (STA-SMC) under external disturbances. The results show a clear trade-off: the optimized TVLQ controller provides smooth tracking with low control effort in nominal conditions, whereas the STA-SMC achieves stronger disturbance rejection and lower tracking error at the cost of much higher control activity. These findings highlight the importance of weight tuning for nominal optimal control and the practical trade-off between efficiency and robustness in trajectory tracking of four-wheel steering mobile robots.