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Study of a Single Neuron Fuzzy PID DC Motor Control Method

机译:单神经元模糊PID直流电动机控制方法的研究

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摘要

As the brush less DC motor is more and more widely used, relating control algorithm need more and more precise and intelligence. In this paper, after studying the fuzzy control and the neural network theory, a single neuron fuzzy self-adaptive PID control algorithm is presented for speed control of the brush less DC motor. The Matlab software simulation results show that the single neuron fuzzy self-adaptive PID control algorithm has more robustness, faster response speed and more excellent adaptive capacity than increment PID, and PID based on quadratic performance index learning algorithm of single neuron adaptive. Thus the algorithm can be widely applied to the actual control system.
机译:随着无刷直流电动机的越来越广泛的应用,相关的控制算法需要越来越精确和智能。本文在研究了模糊控制和神经网络理论的基础上,提出了一种用于无刷直流电动机速度控制的单神经元模糊自适应PID控制算法。 Matlab软件仿真结果表明,单神经元模糊自适应PID控制算法比增量PID和基于单神经元自适应二次性能指标学习算法的PID具有更高的鲁棒性,更快的响应速度和更优异的自适应能力。因此该算法可广泛应用于实际控制系统。

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