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Stability analysis of adaptive control using fuzzy adapting rate neural emulator: Experimental validation on a thermal process

Abstract : In this study, an adaptive control based on fuzzy adapting rate for neural emulator of nonlinear systems having unknown dynamics is proposed. The indirect adaptive control scheme is composed by the neural emulator and the neural controller which are connected by an autonomous algorithm inspired from the real-time recurrent learning. In order to ensure stability and faster convergence, a neural controller adapting rate is established in the sense of the continuous Lyapunov stability method. Numerical simulations are included to illustrate the effectiveness of the proposed method. The performance of the proposed control strategy is also demonstrated through an experimental simulation.
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https://hal-normandie-univ.archives-ouvertes.fr/hal-03685141
Contributor : Dimitri Lefebvre Connect in order to contact the contributor
Submitted on : Wednesday, June 1, 2022 - 10:38:19 PM
Last modification on : Thursday, June 2, 2022 - 3:32:18 AM

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Fatma Ezzahra Rhili, Asma Atig, Ridha Ben Abdennour, Fabrice Druaux, Dimitri Lefebvre. Stability analysis of adaptive control using fuzzy adapting rate neural emulator: Experimental validation on a thermal process. Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering, 2021, 235 (8), pp.1403-1416. ⟨10.1177/0959651820988189⟩. ⟨hal-03685141⟩

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