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Wyświetlanie 1-2 z 2
Tytuł:
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
Powiązania:
https://bibliotekanauki.pl/articles/27311427.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
hybrid synchronization
cellular neural network
sliding mode control
smooth super twisting algorithm
Lyapunov stability theory
synchronizacja hybrydowa
sieć neuronowa komórkowa
sterowanie trybem przesuwnym
teoria Lyapunova
stabilność Lyapunova
algorytm super skręcania płynny
Opis:
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.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 5; art. no. e146474
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Robust estimation based nonlinear higher order sliding mode control strategies for PMSG-WECS
Autorzy:
Nazir, Awais
Khan, Safdar Abbas
Khan, Malak Adnan
Alam, Zaheer
Khan, Imran
Irfan, Muhammad
Rehman, Saifur
Nowakowski, Grzegorz
Powiązania:
https://bibliotekanauki.pl/articles/27311430.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
wind energy conversion systems
WECS
robust control
maximum power point tracking
MPPT
sliding mode control
SMC
super-twisting algorithm
STA
high gain observer
artificial neural network
ANN
function fitting
backstepping
śledzenie maksymalnego punktu mocy
obserwator o dużym wzmocnieniu
sztuczna sieć neuronowa
dopasowanie funkcji
system konwersji energii wiatrowej
sterowanie odporne
sterowanie ślizgowe
algorytm super skręcania
Opis:
The wind energy conversion systems (WECS) suffer from an intermittent nature of source (wind) and the resulting disparity between power generation and electricity demand. Thus, WECS are required to be operated at maximum power point (MPP). This research paper addresses a sophisticated MPP tracking (MPPT) strategy to ensure optimum (maximum) power out of the WECS despite environmental (wind) variations. This study considers a WECS (fixed pitch, 3KW, variable speed) coupled with a permanent magnet synchronous generator (PMSG) and proposes three sliding mode control (SMC) based MPPT schemes, a conventional first order SMC (FOSMC), an integral back-stepping-based SMC (IBSMC) and a super-twisting reachability-based SMC, for maximizing the power output. However, the efficacy of MPPT/control schemes rely on availability of system parameters especially, uncertain/nonlinear dynamics and aerodynamic terms, which are not commonly accessible in practice. As a remedy, an off-line artificial function-fitting neural network (ANN) based on Levenberg-Marquardt algorithm is employed to enhance the performance and robustness of MPPT/control scheme by effectively imitating the uncertain/nonlinear drift terms in the control input pathways. Furthermore, the speed and missing derivative of a generator shaft are determined using a high-gain observer (HGO). Finally, a comparison is made among the stated strategies subjected to stochastic and deterministic wind speed profiles. Extensive MATLAB/Simulink simulations assess the effectiveness of the suggested approaches.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 5; art. no. e147063
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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