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CLOSED-LOOP ISSUES IN SYSTEM IDENTIFICATION

机译:系统识别中的闭环问题

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摘要

The identification of dynamical systems on the basis of data, measured under closed-loop experimental conditions, is a problem which is highly relevant in many (industrial) applications. Initiated by an emerging interest in the area called 'identification for control', classical prediction error identification methods have been extended to also handle the problem of identifying approximate models from closed-loop observations. In this paper the several procedures that have resulted from this research are reviewed and their characteristic properties are compared. Additionally it is discussed which role closed-loop identification can play in the identification of (optimal) models for (robust) control design.
机译:在闭环实验条件下测得的基于数据的动力系统识别是一个在许多(工业)应用中高度相关的问题。由于在“控制识别”领域中出现了新的兴趣,经典的预测误差识别方法已经扩展到可以处理从闭环观测中识别近似模型的问题。在本文中,对本研究产生的几种方法进行了综述,并对它们的特性进行了比较。此外,还讨论了闭环识别在(鲁棒)控制设计的(最佳)模型识别中可以发挥的作用。

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