Abstract
Based on the data-driven modeling theory, the integrated modeling and intelligent control method of the coke oven collector pressure is carried out in the paper. The system includes the regression predictive model of coke oven global collector pressure based on support vector machine (SVM), the subtractive clustering algorithm based operation pattern extraction and migration reconfiguration strategy and the self-tuning PID decoupling controller based on the improved glowworm swarm optimization (GSO) algorithm of the coke oven collector pressure. Simulation results and industrial application experiments clearly show the feasibility and effectiveness of control methods and satisfy the real-time control requirements of the coke oven collector pressure system.
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References
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Wang, J., Gao, X., Liu, L., Liu, G. (2013). Integrated Intelligent Control Method of Coke Oven Collector Pressure. In: Guo, C., Hou, ZG., Zeng, Z. (eds) Advances in Neural Networks – ISNN 2013. ISNN 2013. Lecture Notes in Computer Science, vol 7952. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39068-5_30
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DOI: https://doi.org/10.1007/978-3-642-39068-5_30
Publisher Name: Springer, Berlin, Heidelberg
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