基于神经网络控制器和PID控制器的无刷直流电动机速度控制

Archana Mamadapur, G. Unde Mahadev
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引用次数: 16

摘要

本文的主要目的是利用人工神经网络(ANN)控制器和PID控制器对无刷直流电动机进行转速控制。根据两种方法的仿真结果进行了详细的分析。通过分析无刷直流电动机的数学模型,设计了一种基于神经网络控制的无刷直流电动机速度控制系统。在MATLAB的Simulink软件中对无刷直流电机驱动系统的人工神经网络模块进行辨识。设计参考控制模型,给出控制系统响应指令信号时控制参数的理想值。在MATLAB Simulink环境下,将PID控制器和人工神经网络控制器的性能结果与无刷直流电机驱动系统的参考模型输出进行了比较。对比研究表明,基于人工神经网络的速度控制方法消除了超调,缩短了系统响应的稳定时间。结果表明,基于人工神经网络的仿真结果比基于PID的仿真结果更接近理想参考控制模型的响应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Speed Control of BLDC Motor Using Neural Network Controller and PID Controller
The primary aim of this paper is to control the speed of brushless DC motor using Artificial Neural Network (ANN) controller and PID controller. Detailed analysis is performed based on the simulation results of both the methods. A neural control based speed control system of brushless DC motor is designed by analyzing the mathematical model of BLDC motor. Plant model identification is done in Simulink software of MATLAB to identify the ANN block of BLDC motor drive system. Reference control model is designed to give the ideal values of control parameters when the control system responds to the command signal. The performance results of PID controller and ANN controller are compared with reference model output of BLDC motor drive system in MATLAB Simulink environment. Comparative study concludes that ANN based speed control method eliminates the overshoot, reduces the settling time of the system response. It is observed that the ANN based simulation results are closer to the ideal reference control model response than PID based.
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