Abstract
In this paper, some results concerning analytical methods of fuzzy modeling, especially so called P1-TS fuzzy rule-based systems are described. The basic notions and facts concerning the theory of fuzzy systems are briefly recalled, including a method for overcoming or at least weakening the curse of dimensionality. A P1-TS system performing the function of the fuzzy JK flip-flop, as well as optimal controller for the 2nd order dynamical plant are described. Next, we show how to use the idea of P1-TS system for identification of some class of nonlinear dynamical systems. We briefly characterize FPGA hardware implementation of the P1-TS system. A result of a mobile robot navigation system design is described, as well. Finally, we show how to obtain a highly interpretable fuzzy classifier as a medical decision support system, by using both the theory of P1-TS system with a large number of inputs in conjunction with the idea of meta-rules, and gene expression programming method.
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Kluska, J. (2015). Selected Applications of P1-TS Fuzzy Rule-Based Systems. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L., Zurada, J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science(), vol 9119. Springer, Cham. https://doi.org/10.1007/978-3-319-19324-3_18
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DOI: https://doi.org/10.1007/978-3-319-19324-3_18
Publisher Name: Springer, Cham
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