电机温度时滞耦合系统自抗扰控制仿真研究

电机温度过高会造成绝缘性能老化,电机安全性能下降;电机控制系统是典型的非线性系统,电机温度也因此具有时滞性和耦合性的特点,难以建立准确的数学模型;传统的方法对电机温度的控制精度较差,从而导致电机温度失控;为此,提出基于BP神经网络自抗扰控制算法的电机时滞耦合关系下温度控制方法;将BP神经网络与PID控制方法相结合建立电机温度网络自抗扰控制器模型,利用梯度下降法修正电机温度控制器模型的权值系数,从而实现了BP神经网络自抗扰控制器参数的实时调整;实验结果表明,利用BP神经网络自抗扰算法进行电机时滞耦合关系下温度调整,能够有效提高控制的精确度,缩短了控制过程中的时间延时。

The motor temperature since the immunity for coupling systems with time delay control simulation studyRong Tao 1,Hongbao Du2

the motor temperature is too high will cause insulation aging, electrical safety performance degradation.Motor control system is a typical nonlinear system, temperature and so has the characteristics of time lag and coupling, it is difficult to establish accurate mathematical model.The traditional methods for motor temperature control accuracy is poorer, resulting in motor temperature abuse.Therefore, based on BP neural network adaptive control algorithm of motor delay coupling relationship under temperature control method.Combining the BP neural network and PID control method to establish the motor temperature network adaptive controller model, using the gradient descent method modified the weight coefficient of motor temperature controller model, so as to realize the BP neural network adaptive controller parameters real-time adjustment.The experimental results show that the use of BP neural network adaptive algorithm motor delay under the coupling temperature adjustment, can effectively improve the control accuracy, shorten the time delay in the control process.