The Research Based On Fuzzy Predictive Control Of Coal Mine Local Ventilator Air Volume Regulating System

Local ventilation is a very important part of the underground tunneling miningprocess; the underground toxic and harmful gases can be ruled out and diluted by a goodventilation, for the normal breathing of the underground work staff to ensure theeffective exploitation of coal mine safety.However, local ventilation is a complex andpower-hungry process. In order to meet the normal ventilation requirements, themajority of our local fan often work in high-power constant-speed running state, it willnot only serious energy waste, but also easy to form the gas accumulation in the uppercorner, resulting in a safety hazard. For this problem, a fuzzy generalized predictivecontrol of the local fan air volume control system is designed which can adjust the fanflow according to the underground gas concentration changes in a timely manner, butalso to achieve the purpose of saving energy in the coal mine production safety at thesame time.First, use the input and output data of nominal object as the identification data of T-Sfuzzy model of mine local ventilator air volume control system,and identify preconditionstructure and parameter of T-S model with GK clustering algorithm in the fuzzyC-means clustering algorithm based on improved and the conclusion parameter with theorthogonal least squares algorithm. Then, the T-S fuzzy model of the identification oflocal ventilator air volume control system is linear into suitable generalized predictivecontrol of CARIMA to control, this control system simulation.Simulation results show that fuzzy generalized predictive control for air volumesystem, does not rely on the accurate mathematical model of the controlled object, forthe large time delay, large inertia, much interfere problems of air volume control system,This control system is stable, good adaptability, strong anti-interference ability.