Abstract
Despite its excellent performance as a controller for linear and non-linear systems, the fuzzy logic controller has certain limitations. For instance, large-scale complex fuzzy systems like multi-input, single-output, or multi-output systems are used in various applications with large number of rules. Furthermore, the results also depend on the selected membership functions, etc. This paper presents a novel framework that instead of reducing the number of rules for a fuzzy logic controller, combines it with a fixed point transformation based adaptive control. The adopted approach is based on the Mamdani-type fuzzy controller and enhanced by the Sigmoid Generated Fixed Point Transformation control strategy to cope with modeling inaccuracies and external disturbances that can arise. The general procedure is applied to a nonlinear Kapitza pendulum. Numerical simulations are validating the applicability of the proposed scheme and demonstrating the controller’s performance.
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Acknowledgments
This work has been sponsored by the Hungarian National Scientific Fund (OTKA 105846). This publication is also the partial result of the Research and Development Operational Programme for the project “Modernisation and Improvement of Technical Infrastructure for Research and Development of J. Selye University in the Fields of Nanotechnology and Intelligent Space”, ITMS 26210120042, co-funded by the European Regional Development Fund.
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Dineva, A., Várkonyi-Kóczy, A., Tar, J.K., Piuri, V. (2017). Performance Enhancement of Fuzzy Logic Controller Using Robust Fixed Point Transformation. In: Jabłoński, R., Szewczyk, R. (eds) Recent Global Research and Education: Technological Challenges. Advances in Intelligent Systems and Computing, vol 519. Springer, Cham. https://doi.org/10.1007/978-3-319-46490-9_55
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DOI: https://doi.org/10.1007/978-3-319-46490-9_55
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