Abstract
According to the problems in the on-line measurement and automatic control of component content in rare-earth countercurrent extraction process, soft sensor strategies based on the mechanism modeling of the extraction process and neural network technology are proposed. On this basis, the intelligent optimal control strategy is provided by combining the technologies based on soft sensor and CBR (case-based reasoning) for the extraction process. The application of this system to a HAB yttrium extraction production process is successful and the optimal control, optimal operation and remarkable benefits are realized.
The work is supported by the National Natural Science Foundation of China (50474020), the National Tenth Five-Year-Plan of Key Technology (2002BA315A).
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© 2005 Springer-Verlag Berlin Heidelberg
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Yang, H., Yang, C., Song, C., Chai, T. (2005). Intelligent Optimal Control in Rare-Earth Countercurrent Extraction Process via Soft-Sensor. In: Wang, L., Chen, K., Ong, Y.S. (eds) Advances in Natural Computation. ICNC 2005. Lecture Notes in Computer Science, vol 3611. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11539117_33
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DOI: https://doi.org/10.1007/11539117_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28325-6
Online ISBN: 978-3-540-31858-3
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