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Use of the Modified EPSILON Decomposition for the LTI Models Reduction

机译:使用改进的epsilon分解进行LTI模型减少

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For the purposes of representing the characteristics of physical systems, the LTI (Linear Time Invariant) models are often used. Even in the case where the physical system is described by a set of nonlinear differential equations, the linearization process is able to determine a set of linear differential equations e.g. at the working point. The main problem that arises when designing the system model is the order of the resulting matrices. The model order reduction of the LTI models is a common operation which led to obtain a model of smaller size. The large system size issue often make impossible to perform real-time simulation or designate the control system - for example, determining the LQG control system is possible only for relatively small models. In order to achieve high accuracy of the reduced model with the original model, it is necessary to perform a reduction in the specified range of frequency. The problem arises when the resulting model has to match both - low and high frequencies. In addition, models that describe the slow and fast phenomenon are difficult to numerical analyze. The authors propose the use of a methodology, which bases on separating the model into two parts - the fast part and the slow part. The modified Epsilon decomposition is proposed do achieve this goal. The obtained results confirm that the presented methodology is correct.
机译:出于代表物理系统的特征的目的,通常使用LTI(线性时间不变)模型。即使在由一组非线性微分方程描述物理系统的情况下,线性化过程也能够确定一组线性微分方程。在工作点。设计系统模型时出现的主要问题是所得到的矩阵的顺序。 LTI模型的模型顺序减少是导致获得较小尺寸型号的常用操作。大型系统规模问题通常不可能执行实时仿真或指定控制系统 - 例如,仅针对相对较小的模型确定LQG控制系统。为了利用原始模型实现降低模型的高精度,有必要在指定的频率范围内执行减少。当所得模型必须匹配 - 低频率和高频时出现问题。此外,描述了描述缓慢和快速现象的模型难以数值分析。作者提出了使用方法,该方法基于将模型分成两部分 - 快速部件和慢一部分。建议改进的epsilon分解确实达到了这一目标。获得的结果证实,所提出的方法是正确的。

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