Improving Robustness of the MRAS-based Speed Estimator to Variability of Induction Motor Electromagnetic Parameters Resulting from the Rotor Deep Bar Effect

Rolek, Jarosław; Utrata, Grzegorz; Kaplon, Andrzej

doi:10.1109/wzee.2018.8749014

Cited by 3 publications

(5 citation statements)

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“…The correct operation and reliability of the IM depend on the fault-free operation of the speed sensor [37]. Consequently, the optimum manner to reduce the space, cost and to improve the performance of the control is to eliminate the sensors and replace them with observers.…”

Section: Sosm Observermentioning

confidence: 99%

Archives of Electrical Engineering

Farhi,

Sakri,

Golèa

2022

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This paper proposes two high-order sliding mode algorithms to achieve highperformance control of induction motor drive. In the first approach, the super-twisting algorithm (STA) is used to reduce the chattering effect and to improve control accuracy. The second approach combines the super-twisting algorithm with a quasi-barrier function technique. While the super-twisting algorithm (STA) aims at the chattering reduction, the Barrier super-twisting algorithm (BSTA) aims to eliminate this phenomenon by providing continuous output control signals. The BSTA is designed to prevent the STA gain from being over-estimated by making these gains to decrease and increase according to system's uncertainties. Stability and finite-time convergence are guaranteed using Lyapunov's theory. In addition, the two controlled variables, rotor speed, and rotor flux modulus are estimated based on the second-order sliding mode (SOSM) observer. Finally, simulations are carried out to compare the performance and robustness of two control algorithms without adding the equivalent control. Tests are achieved under external load torque, varying reference speed, and parameter variations.

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Section: Sosm Observermentioning

confidence: 99%

Archives of Electrical Engineering

Farhi,

Sakri,

Golèa

2022

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“…This fact makes the rotor flux voltage-current model a prospective candidate to the role of the adjustable model of the MRAS-based speed estimator which is intended for speed-sensorless IM drive applications. When assuming the conformity of the estimated stator current (12) with the actual one, the state error equation of the modified MRAS-based speed estimator can be expressed in analogous form as in [6]. Thus, the adaptation mechanism derived in [6] remains adequate to the modified MRAS-based speed estimator.…”

Section: Modified Mras-based Speed Estimatormentioning

confidence: 99%

“…The second group includes estimation schemes which are formulated on the basis of IM mathematical models. In this case, the IM speed is usually estimated simultaneously with the rotor flux space vector by means of the Model Reference Adaptive System (MRAS) based estimator [6][7][8][9][10][11][12][13][14][15], an extended observer [16][17][18] or an extended Kalman filter [19,20].…”

Section: Introductionmentioning

confidence: 99%

“…The issue of robustness enhancement of the MRAS-based speed estimator to IM electromagnetic parameter variability constituted the trigger to extensive investigations for many research centres worldwide. In consequence, various modifications of the MRAS-based speed estimator were developed [7][8][9][10][11][12][13][14]. Some schemes were extended by algorithms enabling tracking variability of IM electromagnetic parameters as in [15].…”

Section: Introductionmentioning

confidence: 99%

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Archives of Electrical Engineering

Rolek,

Utrata,

Kaplon

2020

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Accurate information on Induction Motor (IM) speed is essential for robust operation of vector controlled IM drives. Simultaneous estimation of speed provides redundancy in motor drives and enables their operation in case of a speed sensor failure. Furthermore, speed estimation can replace its direct measurement for low-cost IM drives or drives operated in difficult environmental conditions. During torque transients when slip frequency is not controlled within the set range of values, the rotor electromagnetic time constant varies due to the rotor deep-bar effect. The model-based schemes for IM speed estimation are inherently more or less sensitive to variability of IM electromagnetic parameters. This paper presents the study on robustness improvement of the Model Reference Adaptive System (MRAS) based speed estimator to variability of IM electromagnetic parameters resulting from the rotor deep-bar effect. The proposed modification of the MRAS-based speed estimator builds on the use of the rotor flux voltage-current model as the adjustable model. The verification of the analyzed configurations of the MRAS-based speed estimator was performed in the slip frequency range corresponding to the IM load adjustment range up to 1.30 of the stator rated current. This was done for a rigorous and reliable assessment of estimators' robustness to rotor electromagnetic parameter variability resulting from the rotor deep-bar effect. The theoretical reasoning is supported by the results of experimental tests which confirm the improved operation accuracy and reliability of the proposed speed estimator configuration under the considered working conditions in comparison to the classical MRAS-based speed estimator.

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“…At present, to address the problem of degraded MPC strategic performance arising from a model mismatch, many scholars have proposed a number of countermeasures. In [10], authors used identified motor parameters to correct parameters of the predictive model in real time. This measure introduces ordinary least squares (OLS) to identify the motor parameters, but OLS computation is very time consuming, which makes it unsuitable for real-time identification [11,12].…”

Section: Introductionmentioning

confidence: 99%

Archives of Electrical Engineering

Tang,

Wang,

Luo

2022

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The model predictive current control (MPCC) of the permanent magnet synchronous motor (PMSM) is highly dependent on motor parameters, and a parameter mismatch will cause the system performance degradation. Therefore, a strategy based on an internal model control (IMC) observer is proposed to correct the mismatch parameters. Firstly, based on the MPCC strategy of the PMSM, according to the dynamic model of the PMSM in a rotating orthogonal coordinate system, 𝑑-axis and 𝑞-axis current IMC observers are designed, and the stability derivation is carried out. It is proved that the observer can estimate 𝑑-axis and 𝑞-axis disturbance components caused by a parameter mismatch without static error. Then, the estimated disturbance component is compensated for by the reference voltage prediction expression. Finally, the effectiveness of the proposed strategy is verified in two different conditions. The experimental results show that the proposed control strategy can effectively compensate for the parameter mismatch disturbance in MPCC for PMSM, improve the dynamic and static performance of the system, and improve the robustness of the system.

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Improving Robustness of the MRAS-based Speed Estimator to Variability of Induction Motor Electromagnetic Parameters Resulting from the Rotor Deep Bar Effect

Cited by 3 publications

References 1 publication

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