Abstract
Performance of controlled laminar cooling is usually poor because of the difficulty in continuous online temperature measurement and the complex nature of the laminar cooling process (e.g., highly nonlinear, time varying). This paper developed a hybrid control strategy for the laminar cooling process that integrates Radial Basis Function (RBF) networks and Case-Based Reasoning (CBR). The spraying pattern and the first activated headers are found by a case-based reasoner, while the number of activated headers is calculated in real time by RBF networks. Experimental studies using production data from a hot strip mill show the superior performance of the proposed control strategy.
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Tan, M., Li, S., Chai, T. (2006). Hybrid Intelligent Control Strategy of the Laminar Cooling Process. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3973. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11760191_125
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DOI: https://doi.org/10.1007/11760191_125
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-34482-7
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