System identification of MIMO magnetic bearing via continuous time and frequency response data

Mohd‐Mokhtar, Rosmiwati; Wang, Liuping

doi:10.1109/icmech.2005.1529251

Cited by 12 publications

(6 citation statements)

References 17 publications

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“…Ahn et al also developed 'control relevant identification' which involves iterative design of controller and updating the model parameters. A frequency domain subspace method was developed by Mokhtar et al in [19].…”

Section: Literature Reviewmentioning

confidence: 99%

System identification of Active Magnetic Bearing for commissioning

Khader

Liu²,

Sjöberg

2014

Proceedings of 2014 International Conference on Modelling, Identification &Amp; Control

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Section: Literature Reviewmentioning

confidence: 99%

System identification of Active Magnetic Bearing for commissioning

Khader

Liu²,

Sjöberg

2014

Proceedings of 2014 International Conference on Modelling, Identification &Amp; Control

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“…Because the data naturally contain the effects disregarded in the theoretical modeling, system identification can provide more accurate models. Lots of relevant work on MBs can be found in [9]- [13]. In the literature, integer-order models were commonly adopted to characterize the dynamics of MBs.…”

Section: Introductionmentioning

confidence: 99%

Identification of a solid-core magnetic bearing using incommensurate fractional-order models

Zhong

2013

Proceedings of the 2013 International Conference on Advanced Mechatronic Systems

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Due to the effects of eddy current, solid-core magnetic bearings (MBs) show fractional-order characteristics. In this paper, a practical strategy for incommensurate fractionalorder system identification is adopted to model a solid-core MB. The model structures are firstly determined by selecting the number of terms of the numerator and denominator in sequence, and then the derivative orders are derived based on a passive search within a given range. By using a weighed least squares method, the coefficients of derivative operators are calculated. Besides, a modified error criterion is proposed by combining the mean square error with a maximal phase error. The results show that the new error criterion is better for deriving a model with smaller phase errors, and the identified fractional-order models are more precise and simpler than the integer-order models.

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“…The single-most obstacle for any identification algorithm in a closed-loop setting is that the noise in inputoutput measurements is correlated. Neglecting this correlation, reasonable models for AMBs have been identified using open-loop SIMs in [13] and [14]. In [13], the 4 × 4 MIMO magnetic bearing system is approximated by means of 4 decentralized SISO models.…”

Section: Introductionmentioning

confidence: 99%

“…The well established SIM, N4SID is applied to the input-output measurements for each SISO channel. A SIM for frequency response data of AMB systems is described in [14]. The method relies on the socalled Laguerre network and the 4 × 4 MIMO AMB system is modeled using two 2 × 2 subsystems (by neglecting gyroscopic/electro-magnetic coupling effects).…”

Section: Introductionmentioning

confidence: 99%

Subspace identification and robust control of an AMB system

Balini

Houtzager

Witte

et al. 2010

Proceedings of the 2010 American Control Conference

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Active magnetic bearing (AMB) systems are nonlinear, multi-variable and inherently unstable. Conventionally, LTI models are obtained either from first principles or identification experiments and then used to design/synthesize feedback controllers. In general, identification algorithms are focused on obtaining the current and displacement coefficients for a linearized AMB model, which in-turn is based on first principles modeling. In recent years, it is shown that predictor-based subspace identification algorithms (PBSID) give consistent estimates of the parameters even in the presence of feedback. In view of this, we apply the PBSIDopt method to obtain a linear model of an experimental AMB system. Further, a robust controller against uncertainties in a reduced order model (neglecting flexible dynamics) is synthesized.

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System identification of MIMO magnetic bearing via continuous time and frequency response data

Cited by 12 publications

References 17 publications

System identification of Active Magnetic Bearing for commissioning

System identification of Active Magnetic Bearing for commissioning

Identification of a solid-core magnetic bearing using incommensurate fractional-order models

Subspace identification and robust control of an AMB system

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