无人车运动稳定性的模糊神经网络PID控制

Fuzzy Neural Network PID Control for Movement Stability of Unmanned Vehicle

受转向或侧向风影响,无人驾驶车在运行的过程中易产生失稳.采用了模糊神经网络PID算法,将系统输出偏差的变化量,经模糊化后输入到神经网络PID控制器中,对车辆的质心侧偏角、横摆角速度进行调整,达到控制车辆平稳运行的目的.在不同的工况下对算法的有效性进行了试验分析.结果表明,该算法使系统响应超调减少,反应时间加快,具有较强的抗干扰性.

When impacted by the steering or lateral winds,unmanned vehicle easily leads instability.A PID algorithm of fuzzy neural network is used to solve the problems.The deviation is input,after fuzzification,to the neural network PID controller to control vehicle stable operation——adjustting the vehicle sideslip angle and yaw rate.The validity of the algorithm is tested in different conditions.The results show that the algorithm makes the response overshoot reduced,reaction time accelerated and anti interference performance strengthen.