Intelligent Vehicle Lateral Control Strategy Research based on Feedforward + Predictive LQR Algorithm with GA optimisation and PID compensation

Abstract Targeting the lateral motion control problem in the intelligent vehicle autopilot structural system, this paper proposes a feedforward + predictive LQR algorithm for lateral motion control based on Genetic Algorithm (GA) parameter optimisation and PID steering angle compensation. Firstly, based on the vehicle dynamics tracking error model, the intelligent vehicle LQR lateral motion controller as well as the feedforward controller are designed, and upon which the predictive controller is added to eliminate the system lag.Subsequently, exploiting the advantage that the PID algorithm is not model-based, a PID steering angle compensation controller that can directly control and correct the lateral error is designed. Second, a LQR controller based on path tracking deviation is designed by using the parameter rectification method of genetic algorithm (GA), which optimizes the control parameters of the lateral motion controller and improves the adaptivity of the control accuracy. Finally, the simulation verification and analysis are carried out through the Carsim-Simulink joint simulation platform. The simulation outcomes demonstrate that, under the premise that the vehicle is capable of tracking the path in real time, compared with the feedforward+LQR control and the LQR controller, The lateral controller proposed in this paper can enhance the accuracy of lateral distance error control and heading error control effectively.