电磁离合器电流的神经网络整定PID控制

针对电磁离合器驱动电路存在的非线性,及汽车运行时复杂环境使其应用传统的PID控制难以在控制参数整定上达到最优的问题,依据神经网络收敛速度快,全局逼近能力强的优点,提出了基于径向基函数(Radial Basis Function)神经网络整定PID控制电磁离合器电流的方法,在保留传统PID控制优点的同时,利用RBF神经网络对PID控制参数进行在线整定.仿真与试验结果证明,基于该方法驱动控制的电磁离合器电流动态效果与跟踪效果较好,抗干扰能力好于传统的PID控制,系统具有较好的自适应性.

PID control on the current of electromagnetic clutch tuned by neural network

The driver circuit of the electromagnetism clutch has some nonlinearity,and the running environment of vehicles is complex,so the traditional PID(proportioual-integral-derivative) control strategy couldn't work at its best on parameter tuning.The Neural Network(NN) is global optimum and has best approximation performance,as well as fast convergence speed.Accordingly a PID tuning strategy to control the current of the clutch based on the radial basis function Neural Networks(RBF NN) is proposed in this paper,which keeps the advantages of traditional PID controllers.In addition,parameters of PID controller can be tuned on-line.Simulation and experiments prove that the dynamic and tracing performance of electromagnetic clutch driver is good,the anti-jamming ability is better than that of traditional PID control strategy,and the system has nice adaptability.