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Identification of nonlinear dynamic models of electrostatically actuated MEMS

机译:静电驱动MEMS非线性动力学模型的识别

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This paper focuses on the identification of nonlinear dynamic models for physical systems such as electrostatically actuated micro-electro-mechanical systems (MEMS). The proposed approach consists in transforming, by means of suitable global operations, the input-output differential model in such a way that the new equivalent formulation is well adapted to the identification problem, thanks to the following properties: first, the linearity with respect to the parameters to be identified is preserved, second, the continuous dependence on noise measurements is restored. Consequently, a simple least-square resolution can be used, in such a way that some of the difficulties classically encountered with identification methods are by-passed. The method is implemented on real measurement data from a physical system.
机译:本文着重于识别物理系统的非线性动力学模型,例如静电驱动微机电系统(MEMS)。所提出的方法包括通过适当的全局运算来转换输入-输出差分模型,使得新的等效公式由于以下特性而非常适合于识别问题:首先,相对于线性保留要识别的参数,其次,恢复对噪声测量的连续依赖性。因此,可以使用简单的最小二乘分辨率,从而可以绕过识别方法通常遇到的一些困难。该方法在来自物理系统的真实测量数据上实现。

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