Research on Trajectory Tracking Control of Forklift-Type AGV Based on Fuzzy MPC

In order to address the problem of achieving high tracking precision for forklift-type Automated Guided Vehicle (AGVs) along variable curvature trajectories, this paper proposes a trajectory tracking control method based on fuzzy MPC for forklift-type AGVs. Firstly, a kinematic model of the forklift-type AGV with single-wheel steering is established, and the kinematic equations of single-wheel steering are derived. Subsequently, a traditional linear MPC controller based on Model Predictive Control theory is established to control the steering angle of the single-wheel. Furthermore, the impact of different weighting coefficients Q and R on the tracking accuracy of variable curvature trajectories are investigated. Finally, a fuzzy MPC controller is designed to adaptively adjust the weighting coefficients according to actual working conditions. Simulation results demonstrate that when tracking at speeds of 1 m/s and 2 m/s, maximum lateral errors were reduced by 79.5% and 76.4% respectively. Compared with traditional MPC, the adaptive weighting coefficient MPC achieves superior tracking performance, which bears practical significance in real-world applications.