Optimization of the Intelligent Controller Rule Base Based on Fuzzy Clustering for Controlling an Object Operating in Changing Conditions
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Publisher
Springer International Publishing
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https://link.springer.com/content/pdf/10.1007/978-3-030-87034-8_12
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2. Xiong, N., Litz, L.: Reduction of fuzzy control rules by means of premise learning – method and case study. Fuzzy Sets Syst. 132, 217–231 (2002)
3. Civelek, Z.: Optimization of fuzzy logic (Takagi-Sugeno) blade pitch angle controller in wind turbines by genetic algorithm. Eng. Sci. Technol. Int. J. 23(1), 1–9 (2020). https://doi.org/10.1016/j.jestch.2019.04.010
4. Dutu, L., Mauris, G., Bolon, P.: A fast and accurate rule-base generation method for Mamdani fuzzy systems. IEEE Trans. Fuzzy Syst. 26(2), 715–733 (2018). https://doi.org/10.1109/TFUZZ.2017.2688349
5. Kudinov, Y., Kolesnikov, V., Pashchenko, F., Pashchenko, A., Papic, L.: Optimization of fuzzy PID controller’s parameters. In: XIIth International Symposium «Intelligent Systems», INTELS 2016, 5–7 October 2016, Moscow, Russia. Procedia Comput. Sci. 103, 618–622 (2017)
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