Robust hybrid synchronization control of chaotic 3-cell CNN with uncertain parameters using smooth super twisting algorithm

• Autorzy: Siddique Nazam , Rehman Fazal , Raoof Uzair , Iqbal Shahid , Rashad Muhammad

Identyfikatory

DOI

10.24425/bpasts.2023.146474

• Języki publikacji: EN

Abstrakty

EN

This paper presents the control design framework for the hybrid synchronization (HS) and parameter identification of the 3-Cell Cellular Neural Network. The cellular neural network (CNN) of this kind has increasing practical importance but due to its strong chaotic behavior and the presence of uncertain parameters make it difficult to design a smooth control framework. Sliding mode control (SMC) is very helpful for this kind of environment where the systems are nonlinear and have uncertain parameters and bounded disturbances. However, conventional SMC offers a dangerous chattering phenomenon, which is not acceptable in this scenario. To get chattering-free control, smooth higher-order SMC formulated on the smooth super twisting algorithm (SSTA) is proposed in this article. The stability of the sliding surface is ensured by the Lyapunov stability theory. The convergence of the error system to zero yields hybrid synchronization and the unknown parameters are computed adaptively. Finally, the results of the proposed control technique are compared with the adaptive integral sliding mode control (AISMC). Numerical simulation results validate the performance of the proposed algorithm.

Słowa kluczowe

EN

hybrid synchronization; cellular neural network; sliding mode control; smooth super twisting algorithm; Lyapunov stability theory

PL

synchronizacja hybrydowa; sieć neuronowa komórkowa; sterowanie trybem przesuwnym; teoria Lyapunova; stabilność Lyapunova; algorytm super skręcania płynny

• Wydawca: Polska Akademia Nauk, Wydział IV Nauk Technicznych
• Czasopismo: Bulletin of the Polish Academy of Sciences. Technical Sciences
• Rocznik: 2023
• Tom: Vol. 71, nr 5
• Strony: art. no. e146474
• Opis fizyczny: Bibliogr. 27 poz., rys.

Twórcy

autor

Siddique Nazam

• University of Gujrat, Gujrat, Pakistan

• https://orcid.org/0000-0003-4592-8104

autor

Rehman Fazal

• Capital University of Science and Technology, Islamabad, Pakistan

autor

Raoof Uzair

• University of Lahore, Lahore, Pakistan

autor

Iqbal Shahid

• University of Gujrat, Gujrat, Pakistan

autor

Rashad Muhammad

• University of Lahore, Lahore, Pakistan

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).