LQR Optimal Composite Control for Mobile Robot Trajectory Tracking System Based on LPV Model

The four-wheel steerable mobile robots (FSMR) have found extensive applications in industrial, agricultural and military fields with their high efficiency and flexibility. However, considering the complexity of industrial scenes, FSMR are faced with parameter uncertainties and environmental disturbances, which pose significant challenges for trajectory tracking control. These challenges are addressed in this paper by establishing an improved optimal composite control scheme for FSMR. The trajectory tracking model is formulated as a linear parameter varying representation, accounting for variations in longitudinal speed and road friction coefficient, so as to configure appropriate control laws for different operational conditions. Then, utilizing the linear quadratic regulator approach, a closed-loop composite controller comprising state feedback and feedforward compensation is proposed. The stability of the controller is proven through Lyapunov theory. Finally, experiments of the FSMR are conducted based on the Carsim-Simulink co-simulation platform and demonstrate the effectiveness of the proposed algorithm in ensuring trajectory tracking accuracy under varying longitudinal speed and friction coefficient.