Adaptive control of heavy medium coal preparation without modelingdynamic compensation drive
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2023 No. 12
- 383
- 145
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Authors:
LI Weitao
GOU Xiaodong
Unit:
National Energy Group Wuhai Energy Co.,Ltd.,the Nei Monggol Autonomous Region
Guoneng Zhishen Control Technology Co.,Ltd.
Abstract:
The heavy medium coal preparation process is fraught with many uncertainties and disturbances, and its working conditions undergo complex dynamic changes. The traditional PID control falls short in effectively tracking and controlling ash content, which cannot meet production requirements. There is an urgent need for more advanced and intelligent control approaches to improve the performanceof ash tracking and controlling, thereby facilitating improved energy conservation and consumption reduction. The technological process ofheavy medium coal preparation process and the control property of coal ash content in heavy medium coal preparation process were analyzed. Aiming at the strong nonlinear and complex dynamic characteristics of heavy medium coal preparation process, a combination modelof low-order linear model and high-order unmodeled dynamic term was used to describe the ash control system model of heavy medium coal preparation process. By using the projection algorithm and the adaptive fuzzy system ( Adaptive Network-based Fuzzy Inference System, ANFIS) to alternately identify the parameters of the linear model and the unmodeled dynamic terms, an adaptive control system of heavy medium coal dressing driven by unmodeled dynamic compensation was designed to offset the influence of the unmodeled dynamic on the stability of the closed-loop system. Through heavy medium coal selection experiments, the control effects of unmodeled dynamic compensation driven heavy medium coal selection adaptive control and linear adaptive control were compared. The results show thatthe ash tracking control of the unmodeled dynamic compensation heavy medium coal selection process has a faster response, with an average output error absolute value of 0.316 5%, which is 13.67% lower than linear adaptive control, and has better steady-state performance.The study validates the effectiveness of estimation algorithm and adaptive control method of the proposed model for ash content control system.
Keywords:
unmodeled dynamic
adaptive control
heavy medium coal preparation
alternate identification
Citation format:
李伟涛(1984—),男,河北邢台人,工程师,硕士。E-mail:taoge.2008@163.com
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Citation format:
LI Weitao,GOU Xiaodong.Adaptive control of heavy medium coal preparation without modeling dynamic compensation drive[J].Clean Coal Technology,2023,29(12):128-135.