Model Reduction by New Clustering Method and Frequency Response Matching

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• 作者：Sharad Kumar Tiwari…
• 关键词：Order reduction ; Clustering ; Lehmer measure ; Frequency response matching ; Stability ; Integral square error
• 刊名：Journal of Control, Automation and Electrical Systems
• 出版年：2017
• 出版时间：February 2017
• 年：2017
• 卷：28
• 期：1
• 页码：78-85
• 全文大小：
• 刊物主题：Electrical Engineering; Control, Robotics, Mechatronics; Control; Robotics and Automation;
• 出版者：Springer US
• ISSN：2195-3899
• 卷排序：28

文摘

In this paper, mixed method of linear, time-invariant system model reduction method is suggested. A novel clustering algorithm based on Lehmer measure is utilized in the proposed method to obtain the reduced-order denominator polynomial. The selection of poles to form cluster center is based on the viewpoint of important poles contributing to the system is preserved by dominant pole algorithm. Having obtained the denominator polynomial of the reduced model, the coefficient of the numerator is found using the frequency response matching method. The reduction algorithm is fully computer oriented. The reduced model is stable if the original model is stable. Moreover, this method gives a good quality approximation in both the transient and the steady-state responses of the original system.