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An intelligent passivity‐based backstepping approach for optimal control for grid‐connecting permanent magnet synchronous generator‐based tidal conversion system
Author(s) -
Belkhier Youcef,
Achour Abdelyazid
Publication year - 2020
Publication title -
international journal of energy research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.808
H-Index - 95
eISSN - 1099-114X
pISSN - 0363-907X
DOI - 10.1002/er.6171
Subject(s) - control theory (sociology) , permanent magnet synchronous generator , robustness (evolution) , passivity , backstepping , electric power system , matlab , maximum power principle , tidal power , control engineering , computer science , engineering , turbine , voltage , power (physics) , adaptive control , control (management) , physics , quantum mechanics , artificial intelligence , electrical engineering , mechanical engineering , biochemistry , chemistry , marine engineering , gene , operating system
Summary Tidal turbine systems‐based permanent magnet synchronous generator (PMSG) has been largely investigated due to their higher efficiency, predictability, and high‐power density. However, parameter uncertainties and external disturbances make the controller design a challenging work. This study suggests a new adaptive fuzzy linear feedback passivity‐based backstepping control to solve the robustness problems faced by the conventional proportional‐integral (PI) controls in the machine‐side converter (MSC). The proposed controller design uses an energy‐based approach; therefore, its dependence on the system parameters is extremely reduced and avoids the cancellation of nonlinearities of the system. Then, the dynamic response is fast and efficient, and the asymptotic stability and the robustness of the conversion system are improved. The main objectives are the extraction of the maximum tidal power, feeding the electrical grid with only the active power, and regulating the DC voltage and the reactive power toward their references, whatever the disturbances caused by the PMSG behavior. The control strategy is tested under parameter variations, and the performances are compared to the conventional PI strategy. Numerical investigation under MATLAB/Simulink environment demonstrates that the proposed control solution provides a higher efficiency and robustness under parameter variations over conventional PI approach.