Abstract
Fuzzy control is an intelligent software performed to tune a process and make it react in a desirable way. Nowadays, many researchers are interested in the Fuzzy Proportional-Integral-Derivative (FPID) controller because of its performance and simple structure. FPID controller, as fuzzy controller, is based on the Compositional Rule of Inference (CRI) that allows to infer with fuzzy data. As defined by Zadeh, the CRI contains two parameters: t-norm (T) and fuzzy implication (I). Because of the singleton representation of crisp inputs in fuzzy controllers, the t-norm is no longer considered in the CRI, which gives results based only on the fuzzy implication. In this study, we use non-singleton representation of the inputs, and we apply several implications in a fuzzy PID controller combined with the product t-norm. We study the behaviour of the fuzzy PID controller according to each combination (T,I) to evaluate its efficiency in term of quality and time of convergence. We finally compare the obtained results with the theoretical inference results and we find that they are consistent.
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Zerarka, N., Bel Hadj Kacem, S., Tagina, M. (2021). The Behaviour of the Product T-Norm in Combination with Several Implications in Fuzzy PID Controller. In: Fujita, H., Selamat, A., Lin, J.CW., Ali, M. (eds) Advances and Trends in Artificial Intelligence. Artificial Intelligence Practices. IEA/AIE 2021. Lecture Notes in Computer Science(), vol 12798. Springer, Cham. https://doi.org/10.1007/978-3-030-79457-6_50
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