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Research on brushless DC motor control system based on fuzzy parameter adaptive PI algorithm

机译:基于模糊参数自适应PI算法的无刷直流电机控制系统研究

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As a complex system with multiple variables, nonlinearity, and strong coupling, the BLDCM (Brushless Direct Current Motor) has many problems, such as bad parameter tuning, poor adaptability, low control accuracy, and weak anti-interference ability by using the double closed loop traditional PI (Proportional Integral) control algorithm. In order to obtain good control performance, a fuzzy parameter adaptive PI algorithm based on speed loop was designed by combining fuzzy control with traditional PI control. This paper analyzes the mathematical model and operating characteristics of the BLDCM and designs a fuzzy system that takes the deviation e and deviation change rate ec of the reference speed and feedback speed as input and takes the corresponding PI adjustment parameters as output. The step response of the BLDCM at different reference speeds is analyzed. The variable speed response with the initial speed of 4000 r/min under different control algorithms and the changes in the three-phase current, back electromotive force, and electromagnetic torque in this state are compared. The results show that the designed fuzzy parameter adaptive PI algorithm based on the speed loop can make the motor have a faster response time, a smaller overshoot, and a steady-state error when the motor achieves the stable operation. The proposed algorithm also has better control effect, robustness, and stable operation under variable speed conditions.
机译:作为具有多个变量,非线性和强耦合的复杂系统,BLDCM(无刷直流电动机)具有许多问题,如不良参数调谐,适应性差,低控制精度差,抗干扰能力较弱,使用双闭环路传统PI(比例积分)控制算法。为了获得良好的控制性能,通过将模糊控制与传统PI控制相结合,设计了一种基于速度环的模糊参数自适应PI算法。本文分析了BLDCM的数学模型和操作特性,并设计了一种模糊系统,该系统将参考速度和反馈速度的偏差E和偏差变化率EC作为输入,并将相应的PI调整参数作为输出。分析了BLDCM以不同参考速度的阶跃响应。比较了不同控制算法下的初始速度为4000 r / min的变速响应和该状态下三相电流,背部电动势和电磁扭矩的变化。结果表明,基于速度环的设计模糊参数自适应PI算法可以使电动机具有更快的响应时间,较小的过冲,当电动机实现稳定运行时的稳态误差。该算法还具有更好的控制效果,鲁棒性和在变速条件下的稳定运行。

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