Volume 18, Issue 4 (Journal of Control, V.18, N.4 Winter 2025)                   JoC 2025, 18(4): 43-55 | Back to browse issues page

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Abdi S, Zakeri M, Sayyed noorani S M, Beyramzad J. Intelligent control of MEMS gyroscopes using nonsingular fast terminal SMC and fuzzy orthogonal neural networks based adaptive HOSM observer. JoC 2025; 18 (4) :43-55
URL: http://joc.kntu.ac.ir/article-1-1014-en.html
1- University of Tabriz
2- Iran University of Science and Technology
Abstract:   (118 Views)
This paper presents a new control method for MEMS gyroscopes with the aim of achieving high tracking accuracy and fast convergent, eliminating the chattering phenomenon, being robust to the presence of uncertainties and external disturbances, and also not requiring direct measurement of velocity states. In order to avoid increasing the volume of calculations and the complexity of the controller structure, novel fuzzy Chebyshev neural networks based intelligent adaptive high order sliding mode observer have been used to estimate the system states and external disturbances at the same time. Fuzzy Chebyshev neural network have been used, which simultaneously take the advantages of neural network, orthogonal polynomials and fuzzy logics estimation capabilities. The central part of the controller is composed of the nonsingular fast terminal sliding mode control method that ensures finite time stability, fast convergence and high tracking accuracy. In order to eliminate the chattering phenomenon the same fuzzy Chebyshev neural network used to adjust controller gains including sign function. The simulation results have been presented and compared with the results of previous related researches, which indicate the desired performance of the proposed control method in solving the challenges raised. Various control performance evaluation criteria have also been presented to numerically evaluate the quality of the proposed control method in comparison with numerous researches, which shows the very favorable efficiency of the proposed control method and the improvement of the results of the control methods presented in previous similar studies.
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Type of Article: Research paper | Subject: Special
Received: 2024/09/5 | Accepted: 2025/02/18 | ePublished ahead of print: 2025/02/21 | Published: 2025/03/20

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