Abstract
The goal of the work is presentation and discussion of the idea of innovative approach to industrial control system based on data processing. The key issue of proposed control system is the analysis of a history of considered industrial process, it means the analysis of registered data (process parameters and signals) during the past production. The system searches similarities among the current production period and registered past production episodes (episodes are atomic periods of production). Each of episodes is characterized by controlled and measured signals. An episode which is similar to the present period and which is characterized by the best possible value of quality criterion is being selected and becomes a pattern for control of the present production. The searching procedure was based on the multi-agent methodology, while the control function of the chosen episode was modeled using the artificial neural network. The developed idea of the control system was implemented and tested using the data obtained by simulation of the virtual industrial experiment.
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Rojek, G., Kusiak, J. (2012). Industrial Control System Based on Data Processing. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2012. Lecture Notes in Computer Science(), vol 7268. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29350-4_60
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DOI: https://doi.org/10.1007/978-3-642-29350-4_60
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