On the stability of current based MRAS

Vonkomer, Jakub; Zalman, Milan

doi:10.1109/iecon.2013.6699611

Cited by 17 publications

(9 citation statements)

References 18 publications

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“…Previous research showed that almost all known MRAS-type speed estimators are unstable in a certain range of regenerating mode (Bensiali et al 2015;Korzonek and Orłowska-Kowalska 2016;Pal et al in press;Purti et al 2015;Rashed et al 2003;Stoicuta and Pana 2016;Verma and Chakraborty 2014;Vonkomer and Zalman 2013). In addition, AFO with matrix G=0 has some unstable operating points in this mode (Chen et al 2014;Etien et al 2010;Harnefors and Hinkkanen 2008;Hinkkanen and Luomi 2004;Kubota et al 2002;Sunwankawin and Sangwongwanich 2006;Zaky 2011).…”

Section: General Remarksmentioning

confidence: 96%

“…However, the first method is more difficult in practical implementation due to the fact that it requires calculation of at least four g ij parameters, while in the second method it is enough to calculate one parameter φ (Etien et al 2010;Harnefors and Hinkkanen 2008;Hinkkanen and Luomi 2004;Korzonek and Orłowska-Kowalska 2016;Vonkomer and Zalman 2013). Thus, in this paper, only the second method of estimator stabilisation is analysed.…”

Section: General Remarksmentioning

confidence: 99%

See 1 more Smart Citation

Comparative Stability Analysis of Stator Current Error-based Estimators of Induction Motor Speed

Korzonek

Orłowska-Kowalska

2018

Power Electronics and Drives

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This paper deals with the stability problem of three stator current error-based estimators of induction motor speed, especially in the regenerating operation mode. The stability of the adaptive full-order observer (AFO) and two model reference adaptive systems (MRASs) based on a stator current error (MRASCCand MRASCV) is briefly analysed, and the stability borders are determined and compared. It is shown that MRASCVspeed estimator is stable in the whole operation range including the regenerating mode without any modifications. The stability enhancement method for AFO and MRASCCestimators is described, and the solution for their stability improvement is proposed. Torque-speed characteristics of the analysed MRAStype estimators in a wide range of drive speed and load torque changes are given, as well as the behaviour of estimators during transients is compared. The theoretical analysis and simulation test results are validated by experimental tests.

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Section: General Remarksmentioning

confidence: 96%

Section: General Remarksmentioning

confidence: 99%

Comparative Stability Analysis of Stator Current Error-based Estimators of Induction Motor Speed

Korzonek

Orłowska-Kowalska

2018

Power Electronics and Drives

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“…The estimator stability to the changes of the motor and PI controller parameters is confirmed using small‐signal‐perturbation analysis. Paper [117] presents two stabilisation methods – pole placement of stator current model and adaptation law modification for stator current‐based MRAS for sensorless vector control IM drive. The proposed stabilisation methods make the speed adaptation algorithm stable in a wide speed range, in both motoring and regenerating mode of operation.…”

Section: Stability and Dynamics Of Mras Control Schemesmentioning

confidence: 99%

Review on model reference adaptive system for sensorless vector control of induction motor drives

Kumar

Das

Syam

et al. 2015

IET Electric Power Applications

190

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The most frequently used electrical machine in various modern high-performance drive applications is the induction motor (IM), especially its squirrel cage type rotor counterpart. The high-precision, efficient control of sensorless IM drives throughout its operating range demands an exact knowledge of a few of the IM parameters. The stator resistance, rotor resistances are such important IM parameters whose variations may lead to improper estimation of speed over the whole operating range in sensorless drives. Numerous methods for the estimation of speed of high-performance sensorless IM drives taking into account the effect of parameter variations have been developed. This paper aims at providing a review of the major model reference adaptive system (MRAS) based techniques applied for the estimation of speed of such sensorless drives. This paper is illustrated throughout with relevant mathematical equations, experimental and simulation results, associated to different MRAS-based sensorless vector control of the IM drive.Nomenclature v s stator voltage vector i s stator current vector i m = i s + (L r /L m )i r ,î m magnetising and estimated current vector e m back EMF vector (V) v ds , v qs d-axis and q-axis components of stator voltage (V) i ds , i qs d-axis and q-axis components of stator current (A) c dr , c qr d-axis and q-axis components of rotor flux (Wb) c dr ,ĉ qr estimated d-axis and q-axis components of rotor flux (Wb) c r ,ĉ r rotor flux (Wb), estimated rotor flux (Wb) K p , K i proportional, integral gain constants ε r , ε rotor-flux-error signal (Wb), error signal R r R s rotor, stator resistance referred to stator (Ω) L r , L s , L m rotor self-, stator self-, mutual inductance referred to stator (H) X r , X s , X m rotor self-, stator self-, mutual reactance referred to stator (Ω) L ′ m = L 2 m /L r equivalent mutual inductance (H) T r = L r /R r rotor time constant (s) s = 1 − L 2 m /(L s L r ) total machine leakage factor v r , ω r , v * r estimated, actual and reference rotor speed (rad/s) Δe s error in estimated back EMF (V) p derivative operator k ωr speed gain q m ,q m instantaneous and estimated reactive power volt-ampere reactive (VAR) ω e , Δω e speed and speed-deviation of rotating reference frame (rad/s) e ds, qs = i ds, qs −î ds, qs error between measured and estimated stator currents (A) e c control signal based on combined stator current error and rotor flux

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“…Therefore, a number of attempts were made to modify their mathematical models in order to obtain stable operation in the entire range of the speed and load torque changes. In the case of the AFO estimator, originally proposed in [27], these issues were raised in [28][29][30][31][32][33], while for the MRAS CC estimator in [32][33][34][35][36], but most of these solutions have only been tested in the continuous-time domain in the regenerating mode. Only in the case of the MRAS CC estimator, originally developed in [37], the authors of the conference paper [38] analyzed the impact of two discretization methods (forward and modified Euler) on the stability of one of its modified versions, namely MRAS CC+ϕ .…”

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Speed-Sensorless Induction Motor Drive Using Discrete Current-Error Based MRAS Estimators

Orłowska-Kowalska

Korzonek²,

Tarchała

2020

Energies

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In the literature on sensorless control of induction motors, many algorithms have been presented for rotor flux and speed estimation. However, all these algorithms have been developed in the continuous–time domain. The digital realization of the control systems, requires the implementation of those estimation methods in a discrete–time domain. The main goal of this article is comparison of the impact of different numerical integration methods, used in analogue emulation under the digital implementation of the control systems, to the operation of classical Model Reference Adaptive System; CC-based on two current models (MRASCC) speed estimator and its three modified versions developed for the extension of the estimator stability region. In this paper the generalized mathematical model of MRASCC estimator is proposed, which takes into account all known methods for the extension of the stability region of classical speed estimator of this type. After the short discussion of the discretization methods used for the microprocessor implementation of control algorithms the impact of different numerical integration methods on the stable operation range of the classical and modified MRASCC estimators is analyzed and validated in simulation and experimental tests. It is proved that Modified Euler discretization method is much more accurate than forward and backward Euler methods and gives almost as accurate results as Tustin method, however is much less complicated in practical realization.

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On the stability of current based MRAS

Cited by 17 publications

References 18 publications

Comparative Stability Analysis of Stator Current Error-based Estimators of Induction Motor Speed

Comparative Stability Analysis of Stator Current Error-based Estimators of Induction Motor Speed

Review on model reference adaptive system for sensorless vector control of induction motor drives

Performance Analysis of Speed-Sensorless Induction Motor Drive Using Discrete Current-Error Based MRAS Estimators

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