Research on Dynamic Control Method of Loom Spindle Braking System Based on Fuzzy Neural Network

Aiming at the problems of slow response speed of loom electromagnetic braking system and low accuracy of parking angle after braking, resulting in driving marks and thin and dense roads of fabrics, a braking control system based on fuzzy theory and back propagation (BP) neural network is proposed to improve the response speed and control accuracy of the braking system. Firstly, the transmission torque in the braking process of the loom is dynamically analyzed by establishing the mathematical model of electromagnetic braking and the Ansoft electromagnetic finite element model. The causes of braking angle slip are explored, and the driving mechanism of the electromagnetic clutch control circuit based on PWM pulse is analyzed. Based on the control strategy of excitation current, by introducing the fuzzy theory and BP neural network, a fuzzy electromagnetic braking control system based on a neural network is proposed to improve the adaptive ability of the system. At the same time, the improved bat algorithm (IBA-BP) algorithm is used to train the neural network to avoid the generation of local optimization and improve the control accuracy of the system. The simulation and experimental results show that compared with PID control and fuzzy PID control, the neural network method based on fuzzy theory has a smaller braking slip angle, and the accuracy of parking angle after braking action is less than 10 °, which improves the control accuracy of loom electromagnetic braking system and weaving quality.