Abstract
Two different types of benchmarking proportional-integral-derivative PID controllers are used to compare the proposed methodology. In the first controller the proportional gain KP, the integral gain KI, and the derivative gain KD, are offline calculated based on the dynamics of the process under control using the Ziegler Nichols method. The second controller uses three type-1 fuzzy logic systems to estimate each one of the gains every control cycle. This paper proposes a fuzzy self-tuning PID controller: it has three singleton type-1 fuzzy logic systems to calculate each gain of the controller every control cycle, with the novel characteristics that each fuzzy rule base is updated and tuned each feedback cycle using the back-propagation (BP) algorithm. This proposal is named T1 SFLS PID-BP. The results show that the proposed controller presents better performance than the two benchmarking controllers: the PID and the T1 SFLS PID.
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Álvarez, A., Reyes, D., Rincón, E.J., Valderrama, J., Noradino, P., Méndez, G.M. (2018). PID Implemented by a Type-1 Fuzzy Logic System with Back-Propagation Algorithm for Online Tuning of Its Gains. In: Melin, P., Castillo, O., Kacprzyk, J., Reformat, M., Melek, W. (eds) Fuzzy Logic in Intelligent System Design. NAFIPS 2017. Advances in Intelligent Systems and Computing, vol 648. Springer, Cham. https://doi.org/10.1007/978-3-319-67137-6_28
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DOI: https://doi.org/10.1007/978-3-319-67137-6_28
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