Optimal control of brushless DC motor based on short feedback fractional PID sliding mode

DOI:	10.11809/bqzbgcxb2024.09.037
Keywords:	brushless DC motor; grey prediction; fractional order control; sliding mode control; ultra short feedback algorithm; improving the dung beetle algorithm
Abstract:	Brushless DC motor (BLDCM) has complex characteristics such as nonlinearity leading to poor control performance of their speed control systems. A gray predictive short feedback fractional order PID sliding mode optimal control algorithm is designed, in order to improve the deficiencies in the control system. The sliding mode control achieves intermittent control through the switching law, which has strong robustness. Fractional order theory can achieve more margin control, which can improve the flexibility of the control system and enhance the system control performance. At the same time, it overcomes the jitter problem due to sliding mode control. The ultrashort feedback algorithm in endocrine hormone regulation is introduced to constitute a two layer feedback mechanism of the system to compensate its own output signal. In the system feedback session, the GM(1,1) model gray prediction is introduced. The gray predictions are used to replace the measured values for the override control operation. For the fractional order PID type sliding mode convergence law parameters, an improved dung beetle optimization algorithm is proposed for optimization search to achieve more accurate control in this paper. Comparative experiments through simulation show that the brushless DC motor speed control system under gray predictive short feedback fractional order PID sliding mode control optimized by the dung beetle algorithm has better performance in terms of response speed, control accuracy, and robustness than conventional PID control.
Published:	2024-09-30
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