一种车辆主动横摆力矩的神经网络控制方法

Neural network control approach for vehicle active yaw moment

用二自由度车辆动力学状态方程建立了车辆横摆角速度跟踪控制模型.用横摆角速度与其期望值的差值建立了该问题的性能指标并设计了神经网络控制器,用该模型计算了车辆在急速转向操纵时的横摆角速度以及车辆质心的侧偏角响应,计算结果表明此时车辆的操纵稳定性得到了有效改善.最后给出了进一步研究工作所要采用的半实物仿真试验的设计.

A yaw rate tracking control model has been developed based on two degrees of freedom vehicle dynamic state equation. By using the differential term between the yaw rate value and the desired value,a performance index was given and the neural network controller was designed. The proposed model was employed to calculate the yaw angular velocity and slip angle response characteristics of a vehicle under severe cornering maneuver. It shows that the handling stability is significantly improved as compared to the uncontrolled one. At last, the design of a semi-physical simulation experiment for further study is described.