基于粒子群优化算法 PID 参数优化的双电机耦合驱动履带车辆转向控制

In order to improve the accuracy of the steering control system of electric tracked vehicle and the sensitivity of vehicle steering, a steering control strategy is studied, and a dynamic analysis is made on a dual-motor coupling drive electric tracked vehicle. A steering dynamics model of electric tracked vehicle is established based on Mathematical simulation software. Then a steering control strategy based on PID parameter optimization of particle swarm optimization algorithm is designed. The improved ITAE index is used as the objective function of particle swarm optimization algorithm to optimize the control parameters in the PID steering control strategy in real time, and the control parameters are dynamically adjusted to realize the optimal output of vehicle steering control system. Finally, the hardware-in-the-loop simulation platform and real vehicle test are used to verify the control strategy. The test results shows that the steering control strategy is effective.