Open AccessAdaptive neural control for an uncertain fractional‐order rotational mechanical system using disturbance observer
Author(s) -
Shao Shuyi,
Chen Mou,
Chen Shaodong,
Wu Qingxian
Publication year - 2016
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2015.1054
Subject(s) - control theory (sociology) , artificial neural network , adaptive control , robust control , observer (physics) , computer science , control system , control (management) , control engineering , engineering , artificial intelligence , physics , quantum mechanics , electrical engineering
In this study, a robust adaptive neural control is proposed for a fractional‐order rotational mechanical system (FORMS) in the presence of system uncertainties and external unknown disturbances. System uncertainties of the FORMS are handled by the neural network (NN). To tackle unknown disturbances, a non‐linear fractional‐order disturbance observer (FODO) is explored for the FORMS. A robust adaptive control scheme is then developed by combining the NN with the designed FODO. Finally, numerical simulation results further demonstrate the effectiveness of the proposed tracking control scheme for the uncertain FORMS subject to external unknown disturbances.