Mold level fuzzy control algorithm based on disturbance compensation
The mold level control system is a critical component of the continuous casting automation system,with level stability directly impacting the quality of the final product.Fluctuations in the mold level are often induced by multiple sources of disturbance,yet the effective compensation for these disturbances remains inadequately addressed.To address this issue,this paper proposed a disturb-ance compensation-based fuzzy control algorithm for mold level control.Initially,a data-driven feature selection method is employed,in conjunction with mechanism analysis,to identify key variables close-ly related to the mold level.Subsequently,the partial cross mapping method is utilized to analyze the direct causal relationship in level fluctuations,pinpointing major sources of disturbance.Based on this analysis,a fuzzy control method integrated with a long short-term memory(LSTM)network is further developed.By accurately estimating and compensating for disturbances,this approach significantly enhances control precision.Simulation results demonstrate that,compared to traditional methods,the proposed method reduces overshoot from 40.2％to 15.4％and decreases recovery time from 7.6 s to 4.2 s,while effectively suppressing environmental disturbances to maintain stable mold levels.This improvement in system stability contributes to enhanced product quality and production efficiency.
mold levelfeature selectioncausal analysisdisturbance compensationfuzzy control
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