Model Reduction of Linear Systems by Using Improved Mihailov Stability Criterion

A. Prajapati, R. Prasad
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引用次数: 4

Abstract

In this paper, a new model reduction method is proposed for the simplification of the complexity of large scale models. The proposed technique is based on the Mihailov stability criterion and it assured the stability of the reduced system, if the higher order model is stable. In this method, the denominator polynomial of the reduced model is determined by Mihailov stability criterion and the numerator polynomial is obtained by using a simple mathematical algorithm discussed in the literature. The superiority of the proposed technique is judged by comparing the time responses of original and reduced systems. The performance of the proposed method is measured in terms of various error indices such as integral square error (ISE), relative integral square error (RISE), integral absolute error (IAE) and integral time absolute error (ITAE). It is seen that the results of the standard numerical example are quite competitive as compared to the standard model order reduction methods.
基于改进Mihailov稳定性准则的线性系统模型约简
本文提出了一种新的模型约简方法来简化大尺度模型的复杂性。该方法基于Mihailov稳定性判据,在高阶模型稳定的情况下,保证了系统的稳定性。该方法采用Mihailov稳定性判据确定简化模型的分母多项式,利用文献中讨论的一种简单的数学算法得到分子多项式。通过比较原始系统和简化系统的时间响应,判断了该方法的优越性。用积分平方误差(ISE)、相对积分平方误差(RISE)、积分绝对误差(IAE)和积分时间绝对误差(ITAE)等误差指标对该方法的性能进行了测量。与标准模型降阶方法相比,标准数值算例的结果具有很强的竞争力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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