基于BP神经网络的无刷直流电机控制器优化设计

The Improved Design of Brushless DC Motors Controller Based on BP Neural Network

无刷直流电机是一个多变量、强耦合的非线性系统,用常规的线性控制方法很难达到理想的控制效果。为了克服常规PID控制方法的不足,应用了BP神经网络对速度控制器的PID参数进行了优化设计。使用MATLAB仿真结果表明,采用BP神经网络这种控制方式的无刷直流电机调速系统具有良好的动态性能和稳态精度,能达到进一步优化控制系统性能的目的。

The brushless DC motor is a multi-variable,strong coupling and non-linear system.With conventional linear control methods are difficult to achieve the desired results.To overcome the shortage of conventional PID control method,use BP neural network improved the PID parameters of speed controller.MATLAB simulation results show that the BP neural networks using in the brushless DC motor speed control system has good dynamic performance and steady precision,and achieve the purpose of optimizing the control system performance.