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- W1497383937 abstract "In this paper, we compare open-loop and closed-loop prediction error identification. In particular, we determine whether open-loop or closed-loop identification is optimal in the least costly identification experiment design framework. The least costly experiment design framework is a new framework for optimal experiment design where the objective is to determine the cheapest identification while ensuring that the accuracy of the identified model is above some nominated threshold. A second contribution of this paper is to develop a control design algorithm which ensures that the designed controller both ensures sufficient closed-loop performance with the true system, but also ensures that a model identified via closed-loop identification on the designed loop has high accuracy." @default.
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- W1497383937 date "2007-07-01" @default.
- W1497383937 modified "2023-10-16" @default.
- W1497383937 title "Open-loop vs. closed-loop identification of Box-Jenkins systems in a least costly identification context" @default.
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- W1497383937 doi "https://doi.org/10.23919/ecc.2007.7068442" @default.
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