Abstract
In order to address the difficulty induced by controller parameter uncertainty in trajectory tracking control of four-wheel steering vehicles(4WS), a trajectory tracking control method for unmanned vehicles based on particle swarm optimization (PSO) is proposed to improve the robustness of the controller. The approach involves the use of model predictive control (MPC) for implementing trajectory tracking control for the unmanned vehicle. Iterative optimization is conducted by utilizing the integral time absolute error (ITAE) as the objective function, which involves multiplying the time integral of lateral deviation and yaw rate deviation. This process ultimately determines the optimized MPC weight matrix parameters. Co-simulation using CarSim/Simulink reveals a remarkable reduction of 46.1% in the maximum longitudinal error, and the optimization proves effective across various vehicle speed conditions. Experimental results validate the effectiveness of the proposed control strategy, with the 4WS control strategy yielding a maximum longitudinal error of 0.28 meters, affirming that the overall controller design successfully accomplishes its intended objectives.
Published Version
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
