Adaptive neural control for an uncertain fractional-order rotational mechanical system using disturbance observer - Shao, Shuyi; Chen, Mou; Chen, Shaodong; Wu, Qingxian (IET control theory & applications, 2016)
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.