Abstract

Aimed at air quantity requirement and energy conservation at normal ventilation as well as safety and quickly at methane discharging, this study discussed the design process of self learning fuzzy controller based on basic fuzzy model. Firstly, the control system block is described. Then basic fuzzy model is introduced. Auxiliary ventilation is time-varying parameters, nonlinear and large hysteresis system. Therefore, the design includes the normalization, reference model, time-delay, sample cycle, calculation method and control rule modification. The partial fan speed adjustment adopts Direct Torque Control (DTC). Based on theoretical analysis and simulation, combing DSP chip with Intelligent Power Module (IPM), auxiliary ventilation fuzzy control adjusting speed experiment system is established. Experimental results have shown that the system can safely and efficiently fulfill the function of normal ventilation and methane discharging.

Keywords:

Auxiliary ventilation, DTC, heading laneway, self learning fuzzy controller,

References

Competing interests

The authors have no competing interests.

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Copyright

The authors have no competing interests.