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Adaptive neural control for an uncertain fractional-order rotational mechanical system using disturbance observer

机译:基于扰动观测器的不确定分数阶旋转机械系统的自适应神经控制

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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.
机译:在这项研究中,针对存在系统不确定性和外部未知干扰的分数阶旋转机械系统(FORMS),提出了一种鲁棒的自适应神经控制。 FORMS的系统不确定性由神经网络(NN)处理。为了解决未知扰动,针对FORMS探索了非线性分数阶扰动观测器(FODO)。然后,通过将NN与设计的FODO相结合,开发出一种鲁棒的自适应控制方案。最后,数值模拟结果进一步证明了所提出的跟踪控制方案对不确定的FORMS的有效性,该FORMS受到外部未知干扰。

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