Study on adjustment speed control system of auxiliary fan

Combining with ventilation requirements and airflow regulation in coalmine, control strategy which aims at both safety and energy saving was established at length. Moreover, conventional double fuzzy control model was found to carry out two work mode, normal ventilation and gas discharging. Since four input signals affect output in different degree, three layer BP neural network was employed to compute weight. Based on conventional fuzzy model, self learning fuzzy model for auxiliary fan was built to tackle with normal ventilation and gas discharging problem. Direct torque control style was applied to perform speed adjusting of auxiliary fan. In order to testify the control strategy, an experiment platform including DSP and IPM was founded. The experiment results show that the control strategy is effective to fulfill the function of ventilation and gas discharge in heading laneway.