Adaptive Nonlinear Direct Torque Control of Sensorless IM Drives With Efficiency Optimization

Hajian, M.; Soltani, Jafar; Markadeh, Gholamreza Arab; HosseinNia, S. Hassan

doi:10.1109/tie.2009.2029592

Cited by 97 publications

(45 citation statements)

References 18 publications

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“…For the solution of the problems associated with the speed-sensorless control of IMs, a variety of estimation methods [4][5][6][7][8], which use deterministic IM models, have been very recently introduced in the literature; however, * Correspondence: mbarut@nigde.edu.tr they are especially sensitive to variations in R s and/or R r , together with variations in L m . In addition to those, studies like those in [9][10][11][12] undertake performing both R s and R r estimations without L m estimation.…”

Section: Introductionmentioning

confidence: 99%

Bi input-extended Kalman filter-based speed-sensorless control of an induction machine~capable of working in the field-weakening region

İnan¹,

Barut²

2014

Turk J Elec Eng & Comp Sci

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This study introduces a novel bi input-extended Kalman filter (BI-EKF)-based speed-sensorless direct vector control (DVC) of an induction motor (IM). The proposed BI-EKF-based estimator includes online estimations of the stator stationary axis components of the stator currents, isα and i sβ ; stator stationary axis components of the rotor flux, φrα and φ rβ ; rotor angular velocity, ωm ; stator resistance, Rs ; rotor resistance, Rr ; and load torque tL , as well as the magnetizing inductance, Lm , by only supposing that the stator phase currents and voltages are measured. Thus, the speed-sensorless DVC of the IM with the inclusion of the proposed estimator is able to be perfectly operated at a wide speed range, varying from zero speed to beyond the rated/based speed under the extreme variations in Rs , Rr , tL , and Lm . The simulations confirm the effectiveness of the proposed BI-EKF-based estimator and, consequently, the speed-sensorless DVC of the IM.

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Section: Introductionmentioning

confidence: 99%

Bi input-extended Kalman filter-based speed-sensorless control of an induction machine~capable of working in the field-weakening region

İnan¹,

Barut²

2014

Turk J Elec Eng & Comp Sci

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“…For example, the rotor speed and position can be estimated based on the stator voltage equation of the AC motor [3], reference model of the AC motor [4], state observer [5], back EMF [6], the Kalman filtering [7], nonlinear control [8], signal injection [9] and fuzzy control [10].…”

Section: Introductionmentioning

confidence: 99%

Sensorless Vector Control of Induction Motors for Wind Energy Applications Using MRAS and ASO

Jeong¹,

Choi²,

Park³

2014

Journal of Electrical Engineering and Technology

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-Speed sensorless modes of operation are becoming standard solution in the area of electric drives. This paper presents flux estimator and speed estimator for the speed sensorless vector control of induction motors. The proposed sensorless methods are based on the model reference adaptive system (MRAS) observer and adaptive speed observer (ASO). The proposed speed estimation algorithm can be employed in the power control of grid connected induction generator for wind power applications. Two proposed schemes are verified through computer simulation PSIM and compared their simulation results.

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“…A significant improvement in the steady state performance was reported. Some of the different solutions proposed include DTC with SVM, different power converter topologies, such as multi-level inverters [10], [11], a matrix converter [12], sensor-less methods [13], [14], optimum stator flux estimators for high speed operation [15], [16], and artificial intelligence techniques, such as fuzzy logic and neuro-controllers [17]. Direct torque control consists of a pair of hysteresis comparators, torque and flux calculators, a lookup table, and a voltage-source inverter (VSI) [18].…”

Section: Introductionmentioning

confidence: 99%

Modified Direct Torque Control using Algorithm Control of Stator Flux Estimation and Space Vector Modulation Based on Fuzzy Logic Control for Achieving High Performance from Induction Motors

Rashag¹,

Koh²,

Abdalla³

et al. 2013

Journal of Power Electronics

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Direct torque control based on space vector modulation (SVM-DTC) protects the DTC transient merits. Furthermore, it creates better quality steady-state performance in a wide speed range. The modified method of DTC using SVM improves the electrical magnitudes of asynchronous machines, such as minimizing the stator current distortions, the stator flux with electromagnetic torque without ripple, the fast response of the rotor speed, and the constant switching frequency. In this paper, the proposed method is based on two new control strategies for direct torque control with space vector modulation. First, fuzzy logic control is used instead of the PI torque and a PI flux controller to minimizing the torque error and to achieve a constant switching frequency. The voltages in the direct and quadratic reference frameare achieved by fuzzy logic control. In this scheme, the switching capability of the inverter is fully utilized, which improves the system performance. Second, the close loop of stator flux estimation based on the voltage model and a low pass filter is used to counteract the drawbacks in the open loop of the stator flux such as the problems saturation and dc drift. The response of this new control strategy is compared with DTC-SVM. The experimental and simulation results demonstrate that the proposed control topology outperforms the conventional DTC-SVM in terms of system robustness and eliminating the bad outcome of dc-offset.

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Adaptive Nonlinear Direct Torque Control of Sensorless IM Drives With Efficiency Optimization

Cited by 97 publications

References 18 publications

Bi input-extended Kalman filter-based speed-sensorless control of an induction machine~capable of working in the field-weakening region

Bi input-extended Kalman filter-based speed-sensorless control of an induction machine~capable of working in the field-weakening region

Sensorless Vector Control of Induction Motors for Wind Energy Applications Using MRAS and ASO

Modified Direct Torque Control using Algorithm Control of Stator Flux Estimation and Space Vector Modulation Based on Fuzzy Logic Control for Achieving High Performance from Induction Motors

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