Path Tracking Control of Dual-Steering Wheel AGV Based on T-S Fuzzy Weight Adaptive MPC

In order to improve the trajectory tracking performance of the diagonal dual-steering wheel automatic guided vehicle, a trajectory tracking control strategy based on T-S fuzzy variable weight model predictive control is proposed. Firstly, a mathematical description of the diagonal dual-steering wheel AGV was performed, its kinematic model was established, and its turning characteristics were analyzed with emphasis. Based on its kinematic model and Setting the steering angle of the front wheels as the primary control input, a trajectory tracking model of model predictive control was established to use the Side deviation and heading angle discrepancy are used as fuzzy inputs, and The weight of the objective function in the MPC controller is optimized through the T -S fuzzy system to improve the impact of the weight matrix on precision and stability of trajectory following. Through comparative analysis of simulation results, As observed, in comparison to the traditional MPC controller, the improved MPC outperforms the traditional MPC in tracking accuracy and tracking stability, and under different prediction time domain conditions, the designed AMPC control both devices significantly improved the reference trajectory tracking performance, indicating that the proposed algorithm has good control effects.