Study of a Single Neuron Fuzzy PID DC Motor Control Method

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.