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CONTINUOUS NONLINEAR SISO SYSTEM IDENTIFICATION USING PARAMETERIZED LINEARIZATION FAMILIES

机译:基于参数化线性化函数的连续非线性SISO系统识别

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This paper presents a new approach to the modeling and identification of continuous nonlinear dynamic systems in terms of linear local models. In this approach, each local model is associated with a member of the linearization family of the original nonlinear system. Based on this family, a nonlinear model can be constructed, constituting an approximation of the nonlinear system around the entire equilibrium manifold. As a result, empirical model interpolation procedures are not necessary. It is also shown how this method can be used for plant identification. A numerical example demonstrates the efficiency of the method.
机译:本文提出了一种基于线性局部模型的连续非线性动力系统建模与辨识的新方法。在这种方法中,每个局部模型都与原始非线性系统的线性化族的成员相关联。基于这个族,可以构建一个非线性模型,构成围绕整个平衡流形的非线性系统的近似值。结果,不需要经验模型内插程序。还显示了如何将该方法用于植物鉴定。数值算例说明了该方法的有效性。

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