Abstract
The problems of control systems intellectualization are observed. The necessity of intellectualization of a wide range of systems and control methods is proved. The hierarchy of levels of intellectual control observed and comparison analysis of different artificial intelligence devices given. Importance of target setting’s automation problems’ solving in control systems is pointed out, as well as intellectualization of anthropocentric systems, including the ones based on fuzzy logic and case-based reasoning. The logical-linguistic and analytical, fuzzy controllers are considered, based on fuzzy logics of Zadeh, implication of Mamdani and Lukasiewicz. An overview of the Mamdani-type controllers, controllers based on TS-model is provided. The conditions of optimality and stability of control systems with Mamdani fuzzy controllers are analyzed. The Sugeno dynamic models and the ANFIS adaptive models and the methods of learning developed on the basis of fuzzy controllers are considered.
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This work was supported by the Russian Science Foundation, project no. 14-19-01772, and Russian Foundation for Basic Research, project no. 16-29-04-415.
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Russian Text © The Author(s), 2017, published in Datchiki i Sistemy, 2017, No. 5, pp. 4–19.
The article provides an extended review on the materials of the plenary report presented at the XII Intelligent Systems Symposium-2016, Moscow, Russia, October 5–7, 2016.
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Vassilyev, S.N., Kudinov, Y.I., Pashchenko, F.F. et al. Intelligent Control Systems and Fuzzy Controllers. I. Fuzzy Models, Logical-Linguistic and Analytical Regulators. Autom Remote Control 81, 171–191 (2020). https://doi.org/10.1134/S0005117920010142
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DOI: https://doi.org/10.1134/S0005117920010142