An instrumental variable method for closed-loop identification of coreless linear motors

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This paper presents an instrumental variable (IV) method dedicated to identification of coreless linear motors (CLMs) operating in closed-loop. The dynamics of a CLM can be described as a linear dynamical system preceded by a static input gain that is nonlinearly dependent on the output. The nonlinear dependency on the output makes it challenging to find an appropriate predictor for identification. In this paper, we introduce a linear-in-the-parameter predictor for the CLM dynamics, which is a modification of the nonlinear autoregressive exogenous (NARX) model. It is proven that the IV method using the introduced predictor results in a consistent estimate. In addition, we show that in many applications, the simple NARX predictor, which does not require knowledge of the statistical properties of the output measurement noise, can provide an estimate that is very close to the true parameter. A numerical example is shown for demonstration.

Original languageEnglish
Title of host publication2018 Annual American Control Conference, ACC 2018
PublisherInstitute of Electrical and Electronics Engineers
Number of pages6
ISBN (Print)9781538654286
Publication statusPublished - 9 Aug 2018
Event2018 Annual American Control Conference, (ACC2018) - Milwauke, United States
Duration: 27 Jun 201829 Jun 2018


Conference2018 Annual American Control Conference, (ACC2018)
Abbreviated titleACC2018
CountryUnited States
Internet address

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