模型约简的最优投影方法及其与Wilson和Moore方法的关系

The 23rd IEEE Conference on Decision and Control Pub Date : 1984-12-01 DOI:10.1109/CDC.1984.272285

D. Hyland, D. Bernstein

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引用次数: 14

摘要

本文以确定最优降阶模型的斜投影耦合的一对修正Lyapunov方程的形式，导出了线性定常系统最优降阶建模的一阶必要条件。这种形式的必要条件大大简化了先前的Wilson([1])的结果，并清楚地揭示了Moore([2])平衡方法的次优性。

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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The optimal projection approach to model reduction and the relationship between the methods of Wilson and Moore

First-order necessary conditions for optimal reduced-order modelling of linear time-invariant systems are derived in the form of a pair of modified Lyapunov equations coupled by an oblique projection that determines the optimal reduced-order model. This form of the necessary conditions considerably simplifies previous results of Wilson ([1]) and clearly reveals the suboptimality of the balancing method of Moore ([2]).

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The 23rd IEEE Conference on Decision and Control

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