An Observer and Observer Based Modeling Lateral Dynamics For Moving Steel Strip

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The steel strip processing systems rely on accurate lateral positioning to achieve high processing speeds and improved product quality. In real steel strip process systems are not just nonlinear and time-varying but also highly uncertain. This research focuses on the disturbance estimation approach to modeling unknown dynamics of physical plant. The Euler’s beam theory with boundary condition is considered to derive the equation of the moving steel strip. To consider unknown dynamics in the real steel strip, a nonlinear state space equation is employed to describe unknown dynamics of the moving steel strip. The nonlinear part of this system is proposed as an unknown disturbance input to this system. The neural-based observer (NNO) is designed to estimate nonlinear unknown dynamics. The online weight-updating mechanism is a modified version of the backpropagation algorithm with a simple structure together with an error-modification term added to guarantee the robustness of the observer. The measure of sensor and estimation of observer pair of input and output is used to train the weight of NN. The simulation and measure result shown that the NNO can track the un-modeling dynamic of nonlinear systems.

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286-295

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December 2011

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© 2012 Trans Tech Publications Ltd. All Rights Reserved

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