Abstract
Qualitative control is a promising technique for controlling dynamic systems which are ill-defined or too complex to be modelled analytically. In this paper, a Self Organizing Qualitative Control (SOQC) is proposed for controlling dynamic systems with incomplete knowledge on their parameters. This technique is based on a learning approach which uses a qualitative multimodel representation to reduce parametric uncertainty and synthesize a fine control action. The standard problems“benchmark examples” have been selected to apply the proposed control method. To show the potential of this method for controlling interconnected systems, the control of a two coupled tanks system is achieved using the same control technique. The simulation results are satisfactory for achieving tracking and regulation objectives.
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© 1993 Springer-Verlag
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Nagib, G., Gharieb, W., Binder, Z. (1993). Self-organizing qualitative multimodel control. In: Bouchon-Meunier, B., Valverde, L., Yager, R.R. (eds) IPMU '92—Advanced Methods in Artificial Intelligence. IPMU 1992. Lecture Notes in Computer Science, vol 682. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-56735-6_57
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DOI: https://doi.org/10.1007/3-540-56735-6_57
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