摘要
In this paper, the modeling and prescribed performance control(PPC) problem is investigated for cold rolling mill system. First, considering the measurement delay and disturbances in practical process, a mathematical model is established for the cold rolling mill hydraulic automatic gauge control(HAGC) system. Then, based on a state transformation with the performance index function, a predefined performance control scheme is proposed to guarantee both transient-state and steadystate performances. In addition, adaptive neural networks approach is employed to approximate the uncertainties in the controller design procedure. It is proved that the proposed controller can guarantee the stability of the closed-loop system in the sense of uniformly ultimately boundedness. Finally, simulation results illustrate the effectiveness of the proposed method.
In this paper, the modeling and prescribed performance control(PPC) problem is investigated for cold rolling mill system. First, considering the measurement delay and disturbances in practical process, a mathematical model is established for the cold rolling mill hydraulic automatic gauge control(HAGC) system. Then, based on a state transformation with the performance index function, a predefined performance control scheme is proposed to guarantee both transient-state and steadystate performances. In addition, adaptive neural networks approach is employed to approximate the uncertainties in the controller design procedure. It is proved that the proposed controller can guarantee the stability of the closed-loop system in the sense of uniformly ultimately boundedness. Finally, simulation results illustrate the effectiveness of the proposed method.
引文
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