Online Parameter Estimation and Adaptive Control of Permanent-Magnet Synchronous Machines

Underwood, S.; Husain, Iqbal

doi:10.1109/tie.2009.2036029

Cited by 426 publications

(200 citation statements)

References 17 publications

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“…In (5), there are many pairs of d-axis and q-axis reference currents that generate the same torque. When the reference current is given as the stator current, the torque can be derived as (6). In such a case, the reference d-and q-axis currents are generated by the angle of the stator current.…”

Section: Torque Characteristic and Mtpa Controlmentioning

confidence: 99%

“…Several on-line parameter estimations such as the extended Kalman filter (EKF), recursive least square (RLS), and model reference adaptive system (MRAS) have been proposed [5][6][7][8][9][10]. Among them, the extended Kalman filter is the most effective estimator in terms of the leastsquare for estimating the states of nonlinear systems, which is very appropriate for implementation in systems with sensors affected by noise.…”

Section: Introductionmentioning

confidence: 99%

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On-line Parameter Estimation of Interior Permanent Magnet Synchronous Motor using an Extended Kalman Filter

Sim¹,

Lee²,

Lee³

2014

Journal of Electrical Engineering and Technology

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-This paper presents estimation of d-axis and q-axis inductance of an interior permanent magnet synchronous motor (IPMSM) by using an extended Kalman filter (EKF). The EKF is widely used for control applications including the motor sensorless control and parameter estimation. The motor parameters can be changed by temperature and air-gap flux. In particular, the variation of the inductance affects torque characteristics like the maximum torque per ampere (MTPA) control. Therefore, by estimating the parameters, it is possible to improve the torque characteristics of the motor. The performance of the proposed estimator is verified by simulations and experimental results based on an 11kW PMSM drive system.

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Section: Torque Characteristic and Mtpa Controlmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

On-line Parameter Estimation of Interior Permanent Magnet Synchronous Motor using an Extended Kalman Filter

Sim¹,

Lee²,

Lee³

2014

Journal of Electrical Engineering and Technology

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“…The vector control system of PMSM can achieve high accuracy, robust dynamic performance, and wide range of speed and position control [1]. In d-q coordinate system, the vector control method is easier to be realized in PMSM drive systems.…”

Section: Introductionmentioning

confidence: 99%

An improved Synchronous Control Strategy based on Fuzzy controller for PMSM

Shao¹,

Tan²,

et al. 2014

ElAEE

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Abstract-In industry, rail gnawing phenomenon often appears in the synchronous operation of crane. An improved synchronous control strategy for a dual permanent magnet synchronous motor (PMSM) servo system is proposed in this paper. To achieve a synchronous performance with robustness, a cross-coupled synchronous system based on the virtual electronic shaft which both torque and speed are used as feedback signals is developed. Two fuzzy PID compensators with accurate approximation capability based on programmable logic controller (PLC) is implemented to estimate the lumped uncertainty. In the computer simulation, the improved synchronous control strategy is proved to have strong ability to adjust for the external disturbance, and have both smaller convergence time and tracking error. Some experimental results are illustrated to depict the validity of the proposed control approach, which can effectively inhibited wheel's rail gnawing phenomenon in crane.

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“…To take into account nonlinearities of the PMSM, different approaches have been adopted such as nonlinear control [6] and sliding mode control [7]. Feedback linearization [8], [9] and adaptive control [10], [11] have been successfully applied for PMSM control. The controller proposed in [8] gives good performance, but its implementation requires precise knowledge of the load torque.…”

mentioning

confidence: 99%

“…In [9], the control is achieved through nonlinear quadratic optimal control, and extended Kalman filter is used for parametric estimation. In [10], the benefits of adaptive control are demonstrated and a two-time scale recursive least square algorithm is used for parametric estimation. An adaptive control scheme with online identification of the load inertia is proposed in [11].…”

mentioning

confidence: 99%

Robust cascaded nonlinear predictive control of a permanent magnet synchronous motor

Errouissi¹,

Ouhrouche²

2009

2009 IEEE International Conference on Industrial Technology

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Abstract-A nonlinear predictive control (NPC) scheme in a cascaded structure for a permanent magnet synchronous motor drive is proposed. Taylor series expansion is used to predict the system response over a finite horizon. As NPC cannot remove completely the steady-state error in the presence of mismatched parameters and external perturbation, a disturbance observer is used to estimate the offset caused by parametric uncertainties and the load torque variation. In addition, input constraints (restrictions on the magnitude) are considered in the synthesis of the disturbance observer, resulting in an equivalent cascaded proportional integral action with an antiwindup compensator. The validity of the proposed controller was tested via simulation and experiment. Excellent results were obtained with respect to the speed trajectory tracking, stability, and disturbance rejection.Index Terms-Antiwindup compensator, cascaded control, disturbance observer, nonlinear predictive control (NPC), permanent magnet synchronous motor (PMSM), robustness.

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Online Parameter Estimation and Adaptive Control of Permanent-Magnet Synchronous Machines

Cited by 426 publications

References 17 publications

On-line Parameter Estimation of Interior Permanent Magnet Synchronous Motor using an Extended Kalman Filter

On-line Parameter Estimation of Interior Permanent Magnet Synchronous Motor using an Extended Kalman Filter

An improved Synchronous Control Strategy based on Fuzzy controller for PMSM

Robust cascaded nonlinear predictive control of a permanent magnet synchronous motor

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