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izadbakhsh, Alireza. (1402). Bernstein-Schurer-Stancu operator–based adaptive controller design for chaos synchronization in the q-analogue. نشریه مهندسی عمران امیرکبیر, 55(2), 283-298. doi: 10.22060/miscj.2024.22897.5348
Alireza izadbakhsh. "Bernstein-Schurer-Stancu operator–based adaptive controller design for chaos synchronization in the q-analogue". نشریه مهندسی عمران امیرکبیر, 55, 2, 1402, 283-298. doi: 10.22060/miscj.2024.22897.5348
izadbakhsh, Alireza. (1402). 'Bernstein-Schurer-Stancu operator–based adaptive controller design for chaos synchronization in the q-analogue', نشریه مهندسی عمران امیرکبیر, 55(2), pp. 283-298. doi: 10.22060/miscj.2024.22897.5348
izadbakhsh, Alireza. Bernstein-Schurer-Stancu operator–based adaptive controller design for chaos synchronization in the q-analogue. نشریه مهندسی عمران امیرکبیر, 1402; 55(2): 283-298. doi: 10.22060/miscj.2024.22897.5348

Bernstein-Schurer-Stancu operator–based adaptive controller design for chaos synchronization in the q-analogue

AUT Journal of Modeling and Simulation
دوره 55، شماره 2، اسفند 2023، صفحه 283-298    اصل مقاله (4.44 M)
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22060/miscj.2024.22897.5348
نویسنده
Alireza izadbakhsh*
Department of Electrical Engineering, Garmsar Branch, Islamic Azad University, Garmsar, Iran
چکیده
In this paper, a synchronization controller for chaotic master-slave systems is presented based on the q-analogue of the Bernstein-Schurer-Stancu operators. q-analogue of the Bernstein-Schurer-Stancu operators is employed to approximate uncertainties due to their universal approximation property. The coefficients of polynomials are considered free parameters and will be adjusted by the adaptive rules extracted from the stability analysis. Additionally, the controller is designed based on the presumption that the synchronization error rate is unavailable. The controller is applied on a master-slave system using Duffing-Holmes oscillators. The results are compared with the Radial Basis Function Neural Networks (RBFNN). Simulation results and comparisons show that the Bernstein-Schurer-Stancu operator in q-analogue is efficient in uncertainty approximation; needless, the system states for constructing the regressor vector and can be a good alternative for neural networks. 
کلیدواژه‌ها
Adaptive Uncertainty Approximation؛ Neural Network؛ q-Analogue of the Bernstein-Schurer-Stancu Operators؛ Synchronization of Chaos؛ Universal Approximation Theorem
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