基于神经网络的无刷直流电动机速度控制系统研究

Shuangqiao Xiong, Gao Junguo, C. Jian, J. Biao
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引用次数: 6

摘要

针对传统PID控制器在无刷直流电动机调速系统中精度低、响应滞后、控制不稳定等缺点,设计了一种将rbf神经网络与PID控制器相结合的智能控制器。分析了无刷直流电动机的工作原理,推导了控制器的传递函数模型。给出了所设计控制器的控制程序和控制模型。最后通过Mat lab软件对所设计的控制器进行了仿真验证。在仿真过程中,采用rbf神经网络对PID的三个参数进行了明显的调整。仿真结果表明,所设计的控制器比传统的PID控制器更有效地提高了控制性能和响应速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Speed Control System of Brushless DC Motor Based on Neural Network
Considering the shortcomings of low precision, response lag and control instability of conventional PID controller in brushless dc motor speed control system, an intelligent controller is designed, which is combines RBFneural network with PID controller. This paper analyzed operating principle of the brushless dc motor, and deduced transfer function model of the controller. The control programs and control model of the designed controller were also provided. At last, the designed controller was validated through Mat lab software in the simulation. In the process of simulation, three parameters of PID were adjusted obviously by RBF-Neural Network. The results of simulation show that the designed controller is more effectively in improving the control performance and faster in response than conventional PID controller.
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