Direct Torque Control of Sensorless Induction Motor ... - IEEE Xplore

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, VOL. 40, NO. 2, MARCH/APRIL 2004

Direct Torque Control of Sensorless Induction Motor Drives: A Sliding-Mode Approach Cristian Lascu, Ion Boldea, Fellow, IEEE, and Frede Blaabjerg, Fellow, IEEE

Abstract—Direct torque control (DTC) is known to produce fast response and robust control in ac adjustable-speed drives. However, in the steady-state operation, notable torque, flux, and current pulsations occur. A new, direct torque and flux control strategy based on variable-structure control and space-vector pulsewidth modulation is proposed for induction motor sensorless drives. The DTC transient merits and robustness are preserved and the steadystate behavior is improved by reducing the torque and flux pulsations. A sliding-mode observer using a dual reference frame motor model is introduced and tested. Simulations and comparative experimental results with the proposed control scheme, versus classic DTC, are presented. Very-low-speed sensorless operation (3 r/min) is demonstrated. Index Terms—Induction motor drives, sliding-mode observers, variable-speed drives, variable-structure systems.

I. INTRODUCTION

T

HE adjustable-speed drives (ASDs) with induction motors (IMs) have been making significant inroads in industry in the last decade. While ASDs in industry are quite numerous, the next frontiers to be conquered are the very challenging domestic and automotive applications. The well-known direct torque control (DTC) strategy [1] for ac motors control seems to be particularly useful for these ASDs, due to its robustness and functional simplicity. Despite its simplicity, DTC is able to produce very fast torque and flux control and is robust with respect to motor parameters changes and to perturbations. However, in the steady-state operation, notable torque, flux, and current pulsations, and acoustical noise occur. Using the space-vector modulation (SVM) [2], instead of the DTC switching logic, provides higher control resolution and helps improving the drive’s behavior. Drives with SVM display excellent performance in terms of low torque ripple and quiet operation. The switching frequency results constant and the switching pattern can be further optimized [3]. Attempts to combine the DTC with SVM have led to new schemes. A predictive, deadbeat direct torque control solution is proposed in [4]. Moderate torque ripple reduction is reported in [5], by using discrete SVM with predefined time intervals

and extended switching tables. Linear proportional–integral (PI) torque and flux control using SVM is investigated in [6]; smooth operation was obtained in the steady state, but the robustness is low due to the linear control. Variable-structure control (VSC) or sliding-mode control is a nonlinear, high-speed switching, feedback control strategy that provides an effective and robust approach for controlling nonlinear multivariable plants [7]. Since power converters for ac drives are, by their nature, switching devices, it is worth considering VSC as a solution for generating discontinuous control laws. In fact, the classical DTC is a VSC scheme, excellently designed to match the eight-state, discrete nature of the Voltage Source Inverter (VSI). Recently, several solutions that integrate the VSC and DTC principles within high performance drives have been proposed [7]–[12]. Sensorless control of ASD is achieved by extensive use of state observation techniques. Among other solutions, the sliding-mode observer (SMO) is an attractive choice for induction motor state estimation, due to its fast dynamics and strong robustness in face of disturbances, parameter deviations and noise [8], [9]. Usually, the SMO for induction motor drives is realized as a speed adaptive observer, with discontinuous correction terms based on the current estimation error [13]–[16]. However, errors in the estimated speed affect the flux estimation and degrade the estimation accuracy. A current model based sliding observer, proposed in [17], avoids the speed adaptation and the problems related to it. Recognizing the VSC merits and the advantages of using the SVM, this paper presents a VSC-DTC solution for sensorless induction motor drives. Direct torque and flux control is achieved by means of VSC. The DTC transient merits and its robustness are preserved and the steady-state behavior is much improved. The proposed sliding observer uses a modified motor model that does not require the speed information, that is, an inherently sensorless observer. To achieve adequate sensorless operation at very low speeds, a novel stator resistance adaptation is proposed and tested. II. DIRECT TORQUE CONTROL PRINCIPLES

Paper IPCSD 03-120, presented at OPTIM 2002, Bras¸ov, Romania, May 16–17, and approved for publication in the IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS by the Industrial Drives Committee of the IEEE Industry Applications Society. Manuscript submitted for review November 29, 2002 and released for publication December 23, 2003. C. Lascu and I. Boldea are with the Faculty of Electrical Engineering, University Politehnica of Timis¸oara, RO-1900 Timis¸oara, Romania (e-mail: [email protected]; [email protected]). F. Blaabjerg is with the Institute of Energy Technology, Aalborg University, DK-9220 Aalborg East, Denmark (email: [email protected]). Digital Object Identifier 10.1109/TIA.2004.824441

The DTC for ac drives is a strategy exclusively based on stator voltage control. The consecutive voltage vectors applied to the motor are directly selected on the basis of torque and flux errors. In this way, fast response and robust torque and flux control are obtained, without intermediate current control. The classic DTC uses bang-bang torque and flux controllers, without decoupling [1]. A simple switching logic (switching table) employs the output signals of these controllers to select the most

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LASCU et al.: DIRECT TORQUE CONTROL OF SENSORLESS INDUCTION MOTOR DRIVES

appropriate voltage vector, i.e., the one which rapidly reduces the torque and flux errors. Due to the fact that the voltage vector is maintained for the whole duration of the control period, the classic approach causes large torque, flux and current ripple, accompanied by acoustical noise. The switching frequency of the power devices is variable and uncontrollable. One way to decrease the ripple is to significantly shorten the duration of the control period. This requires powerful/expensive digital signal processors (DSPs), and the switching frequency remains variable. Another approach is to increase the control resolution. The torque ripple was reduced, in [5], when the control period was divided into three subintervals and a sequence of three voltage vectors was applied in this time. This refinement can be further continued, the control resolution will continue to increase and the ripple will decrease. At the limit, a linear space results. Asymptotical, ripple-free behavior was realized with linear torque and flux controllers and SVM, in [6]. Torque generation in induction motors is governed by

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Fig. 1.

Block diagram of the VSC-DTC sensorless drive.

Fig. 2.

Variable-structure direct torque and flux controller.

(1) is the developed torque, and are the stator and where rotor flux magnitudes, is the angle between the stator and and , is the number of pole pairs, rotor flux vectors , and , , and are the stator, rotor, and magnetizing inductances, respectively. As long as the flux magnitude is constant, changing the angle will control the torque. Accelerating the stator flux vector, with respect to the rotor flux, will increase the torque, and decelerating the same vector will decrease the torque. Stator flux and torque control can be achieved by taking into account the IM stator equation in stator flux reference frame (2) and are the stator voltage and current, is the where is the stator flux angular speed. stator resistance, and The direct and quadrature components of (2) are (3) (4) Equation (3) indicates that the direct component of the stator , can be employed for flux control. voltage, Under the assumed orientation, the developed torque is (5) Taking into account (4), the torque becomes (6) This last equation indicates that the quadrature component of , can be employed for torque control. the voltage,

III. VARIABLE-STRUCTURE CONTROL Block diagram of the variable-structure direct torque controlled drive (VSC-DTC) under consideration is shown in Fig. 1. The drive operates with constant rotor flux and the control quantities are the stator flux magnitude , the motor torque , and the rotor speed . It is possible to open the speed control loop and to operate the drive with torque and flux control only. The speed controller is of the PI type. The main task of the variable structure controller, shown in Fig. 2, is to achieve fast and reliable torque and flux control. For this purpose, two sliding-mode-plus-PI controllers in estimated stator flux reference frame have been designed. A refer, is obtained at the output ence stator voltage, of the VSC, where is generated by the flux control law and by the torque control law. The control law is of the “Relays with constant gains” type, (7) (8) , is the signum function, , , , where are the PI controller gains, is the sliding and surface, and superscript “ ” stands for estimated quantities. In order to accelerate the voltage response during speed transients, the torque control law contains a feedforward compensation for the dynamic electromotive force (EMF). The PI con-

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trollers help to reduce the chattering associated with VSC and define the system’s behavior when it is not in the sliding mode (during the reaching phase). The sliding surface is designed so as to enforce sliding-mode operation with first-order dynamics,

The torque reference, , is produced by the speed controller, or can be independently set. The stator flux reference, , is calculated from the rotor flux reference, , and the torque reference, as

(9) (13) and are the flux and where , are design constants. torque control errors, and In the sliding mode, the control law (7) and (8) restrict the system state onto the surface , and its behavior is exclusively governed by [8]. First-order linear torque and flux error dynamics result from (9) as (10) , and are selected so as to impose Design constants the desired dynamics on the control errors (10). When the system is not in the sliding mode, assuming accu, the torque rate state estimation and ideal inverter behavior results from (6) and (8) as

All control quantities are estimated by the sliding observer. IV. SLIDING-MODE OBSERVER A. Flux Observer Accurate estimation of IM variables that are not directly measured is crucial for good operation of a sensorless drive. Usually, full-order observers employ the linear, time-variable state-space model of the motor. The motor model in arbitrary reference frame, which rotates with the speed , with the stator flux and the stator current as state variables, is

(11) and is the integral of the discontinwhere . uous control Hence, the torque has two components: a discontinuous one , and a linear slow motion controlled by . controlled by value accelerates the torque response during tranA large sients, but increases the chattering in the steady state. A large makes the quasi-linear behavior dominant. Adequate balance between quasi-linear, PI specific behavior, and switching, DTC specific behavior has to be found by proper gain selection. In this way, the torque ripple can be significantly reduced, while the transient operation and the robustness are not much compromised. The flux dynamic behavior is obtained from (3) and (7), by neglecting the resistive voltage drop, as (12) is the integral of . As for the torque control, where controls the discontinuous component and controls the slow motion component of the flux dynamics. The adequate equilibrium between fast response and low ripple behavior can be obtained by finding the proper balance of these gains. An important aspect is the robustness with respect to parameter deviations and perturbations. The sliding-mode design procedure [7] requires the VSC gains to be large enough to compensate for model uncertainties, perturbations, and to assure the stability. It can be proved that large enough values for the pro, and , satisfy the stability condition portional gains . Also, the proportional gains have to be able to compnesate for the lack of decoupling in the torque and flux control laws. A symmetrical space-vector modulator [2], which generates the inverter switching signals , , and , is the output stage. This helps increasing the resolution of control.

(14) (15) where

,

, ,

, is the rotor resistance. An SMO for (14) is [8]

,

, ,

, , , and

(16) where the gain is selected so as the observer is stable. Other dynamic models of the motor can be used instead of (14) and (15). Various reference frames can be selected, but always only one reference frame was utilized for the SMO realization. Whatever that frame is, at least one element of the matrix contains the rotor speed, and the observer has to be speed adaptive. Usually, the flux is estimated first, while speed estimation is the last step. Consequently, the estimated speed is affected by cumulative noise and delays. This estimate is fed back to the flux observer in the same, or subsequent sampling cycles. In this way, the accuracy of state estimation may progressively deteriorate. The speed-adaptive observer has been proven stable [15], but undesirable effects, such as limit cycles, sensitivity to noise, or phase shifting tend to occur. An inherently sensorless SMO, shown in Fig. 3, has been developed. It is input–output equivalent to (16), and using two reference frames allows eliminating the speed adaptation. This feature is significant in drives that do not need the speed estimation for control (torque-controlled drives) and it is expected to produce better results than (16). The induction motor stator current is (17)


Fig. 3.

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Inherently sensorless sliding-mode observer.

Replacing (17) in the second equation of (16), the SMO is (18)

(19) (20) Since only algebraic manipulations were involved, the sliding observers (16) and (18)–(20) are equivalent. In order to eliminate the rotor speed adaptation, the stator equation (18) is implemented in stator reference frame, and the rotor equation (19) is implemented in rotor flux frame (superscript “ ”), which rotates with rotor flux speed, (21)

Fig. 4. Stator and error—simulation.

rotor

flux

magnitude

for

050% R

It can be shown that the observer is stable if its gains and are large enough, i.e. if the gains dominate the measurement errors and the model parameter uncertainties. The following speed-dependent gains have been implemented: (26)

(22) Taking into account that the rotor flux is aligned with the reference frame, the rotor model (22) turns out to be simple

errors

where speed one.

, , , and are constants. Since the reference is noiseless, it was preferred instead of the estimated

B. Stator Resistance Adaptation (23) (24) The estimated position of the rotor flux frame is obtained as , where another estimate of the rotor flux, in the stator frame, has been calculated as (25) The SMO implements (20)–(25), and in the sliding mode it is equivalent to a linear asymptotic observer. However, if the plant and the observed signals are affected by noise, the nonlinear observer turns out to be preferable due to its filtering proprieties, which coincide to those of a Kalman filter [7].

Computer simulations have been performed to determine the observer sensitivity to motor parameters changes. The drive was subjected to the following speed and torque profiles: rad/s for s, and • reference speed: rad/s for s; N m for s, and • load torque: N m (full load) for s. Wb. The The rotor flux reference was constant, s. The same motor used for motor is supplied and starts at experiments was simulated. The SMO is almost insensitive to rotor resistance changes, as shown in Fig. 4, which gives the stator and rotor flux magnitude , ) for 50% error errors ( within the observer. Similar behavior was obtained for positive

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Fig. 5. Stator and rotor flux magnitude errors for

025% R

error—simulation.

errors. Insignificant estimation errors appear only during flux transients (the first 0.05 s). The SMO is sensitive to stator resistance changes, as shown error. The in Fig. 5, which gives the same errors for 25% high-speed operation is slightly affected, but the low-speed operation is ruined. Higher error magnitudes cause instability. As expected, increasing the SMO gains significantly reduces that sensitivity, but causes undesired increase of the chattering.

Fig. 6. Stator resistance adaptation and flux magnitude errors for R = 1:5R .

In order to deal with this contradictory situation, an online sliding-mode adaptation for the stator resistance was designed using the same sliding surface (9) as for the flux observer

where gain.

is the initial estimate of

and

(27) is a constant

The adaptation error has been selected similar to the torque estimation error because the resistance error affects the active power balance and, therefore, the torque estimation. The evolution of estimated resistance, and the stator and rotor flux magnitude estimation errors, for 50% initial error , are shown in Fig. 6. The same quantities, for 50% initial error , are shown in Fig. 7. In both cases, ms. Noticeably, the resistance estimation was started at the rate of convergence at high speeds is comparable to the one at low speeds and depends much on the torque level. The estimation is not possible at no load. The simulation has been per, in order to achieve fast formed with a high gain, response under this extreme condition. Lower values, around one, give good results in a real drive. It was determined that the SMO suffers from the highest sensitivity to stator resistance changes, and its adaptation is desirable at low speeds. The magnetizing inductance detuning causes smaller errors, which can be eliminated to some extent by increasing the SMO gains. Interestingly, overestimation of the magnetizing inductance causes low sensitivity at all speeds, and, whenever its value is uncertain, it is preferable in place of underestimation, which causes much higher errors.

Fig. 7. Stator resistance adaptation and flux magnitude errors for = 0 :5 R . R

V. SPEED AND TORQUE ESTIMATOR The rotor speed estimate is needed for the speed control only. It was calculated as the difference between the rotor flux speed and the slip speed, (28) where is the duration of the sampling period and subscripts and indicate two consecutive sampling periods. is estimated as The developed torque (29) Although this speed estimator is simple, it produces fast and accurate results, but it is rather sensitive to noise.


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Fig. 8. Experimental setup of the VSC-DTC drive.

The slip speed is sensitive to rotor resistance changes, and adaptation is required for low speed sensorless operation. Taking into account similar stator and rotor resistance changes due to temperature, an approximation of the rotor resistance is (30) is the initial estimate of and is constant. where The stator flux speed is estimated in the same way as the rotor flux speed was [i.e., the first term in (28)].

Fig. 9. (a) Estimated motor torque transients and (b) estimated stator and rotor flux magnitudes, at zero speed, for the VSC-DTC drive.

VI. EXPERIMENTAL RESULTS Experimental investigation was focused on the torque and flux controller behavior and on very-low-speed sensorless operation. The experimental setup for the VSC-DTC drive is shown in Fig. 8. It uses a dual processor system based on the ADMCF 328 Motor Controller DSP and the ADSP-21 062 DSP, both from Analog Devices. The inverter is a commercial, 4.3-kVA unit from Danfoss Drives. kW, The IM nameplate data and parameters are: V, A, Hz, , N m, , , H, H. The IM was mechanically connected to a and dc machine with rather high inertia rotor. In order to build up torque at low speeds, the dc machine was supplied from a dc power source. The control system parameters are: , , • VSC-DTC gains: , , , , and switching frequency kHz. , , • SMO gains: , , , , and kHz. sampling frequency Comparative experimental results of the VSC-DTC drive versus a classic DTC drive are shown in Figs. 9 and 10. In both cases, the drive was operated with torque and flux control only. At the instant of 10 ms, while at zero speed, each drive was subjected to 12-N m torque step reference, while the flux reference was maintained constant. Fig. 9 shows the estimated torque transients, and the stator and rotor flux magnitudes for the VSC-DTC drive. The same quantities are shown in Fig. 10 for the DTC drive.

Fig. 10. (a) Estimated motor torque transients and (b) estimated stator and rotor flux magnitudes, at zero speed, for the DTC drive.

The torque ripple has been significantly reduced for the VSC-DTC, with respect to the DTC, but the torque increases accelerates the torque reslower. Increasing the gain sponse, but increases the torque ripple. In order to accelerate

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Fig. 11. Estimated speed and measured speed at 3-r/min full-load sensorless operation with the VSC-DTC drive.

Fig. 12. (a) Estimated motor torque and (b) estimated stator and rotor flux magnitudes at 3-r/min sensorless operation with the VSC-DTC drive.

the response and to maintain low ripple, the sliding surface gains and are very small. Flux ripple in the VSC-DTC drive is much smaller than that of the DTC drive, and the flux controller maintains very well the set point, showing excellent robustness with respect to torque transients and to the lack of decoupling between the torque and flux controllers. Very-low-speed sensorless operation of the VSC-DTC drive, at 3 and 6 r/min, is demonstrated by the next experiment. Fig. 11 shows the estimated speed and the measured speed, and Fig. 12 shows the estimated motor torque and the estimated stator and rotor flux magnitudes, all during steady-state sensorless operation at 3 r/min (0.1 Hz), full load (7 N m). Although some torque and speed ripple are present, mainly due to the dc machine parasitic torques, the drive control in terms of flux, torque, and speed is of good quality.

Fig. 13. Estimated speed and measured speed at 6-r/min full-load sensorless reversal with the VSC-DTC drive.

Fig. 14. (a) Estimated motor torque and (b) current magnitude estimation error at 6-r/min full-load sensorless reversal with the VSC-DTC drive.

Motoring and regenerative sensorless operation at 6 r/min ( 0.2 Hz), full load, is demonstrated in Fig. 13 which shows the estimated and measured speed, and in Fig. 14 which gives the estimated motor torque and the current magnitude estimation within the SMO. error All low-speed results prove the good performance of the speed estimator. In effect, this was possible due to the accuracy and robustness of the sliding-mode flux observer and to the fact that it is inherently sensorless. The current error in Fig. 14 proves the robustness of the SMO with respect to torque and speed transients. Although not shown, the resistance estimator produces correct results. The startup-on-the-fly of the sensorless VSC-DTC drive is s, the IM was not demonstrated in Figs. 15 and 16. Before supplied. Initial conditions for all estimated and control quantities were zero. The dc machine was supplied and it was ro-


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the dc machine and, in less than 200 ms, stationary operation at reference speed, full load, is achieved. VII. CONCLUSION A complete variable-structure solution (sliding-mode controller and observer) for sensorless induction machine drives was proposed and tested. The control strategy combines VSC and DTC principles within a simple and robust high performance drive. In the steady state, the new drive operates with low torque, flux, and current ripple. During transient operation it displays good dynamic response and strong robustness with respect to speed and torque transients. A new sliding-mode flux observer that does not require the speed adaptation was realized. It employs a novel sliding-modebased stator resistance adaptation, and yields accurate and robust flux estimation in a wide speed range. Very-low-speed sensorless operation at 3 and 6 r/min was demonstrated. This performance was obtained without using high-frequency signal injection or saliency effects for the flux and speed estimation. Excepting for the structural changes induced by the VSC, the drive topology remains the same when the operation changes from low to high speeds. Fig. 15. (a) Estimated speed and (b) measured speed at 30-r/min sensorless startup on-the-fly of the VSC-DTC drive.

Fig. 16. (a) Estimated motor torque and (b) estimated stator and rotor flux magnitudes at 30-r/min sensorless startup on-the-fly of the VSC drive.

tating at about 145 r/min, in motoring mode. At s, the VSC-DTC drive is started with rated rotor flux reference and s, after the flux has increased, zero torque reference. At the speed reference was set at 30 r/min (1 Hz). The IM takes over

REFERENCES [1] I. Takahashi and T. Noguchi, “A new quick response and high efficiency control strategy of an induction motor,” IEEE Trans. Ind. Applicat., vol. 22, pp. 820–827, Sept./Oct. 1986. [2] J.-O. Krah and J. Holtz, “High performance current regulation and efficient PWM implementation for low-inductance servo motors,” IEEE Trans. Ind. Applicat., vol. 35, pp. 1039–1049, Sept./Oct. 1999. [3] A. M. Trzynadlowski and S. Legowski, “Minimum-loss vector PWM strategy for three phase inverters,” IEEE Trans. Power Electron., vol. 9, pp. 26–34, Jan. 1994. [4] T. G. Habetler, F. Profumo, M. Pastorelli, and L. M. Tolbert, “Direct torque control of induction machines using space vector modulation,” IEEE Trans. Ind. Applicat., vol. 28, pp. 1045–1053, Sept./Oct. 1992. [5] D. Casadei, G. Serra, and A. Tani, “Implementation of a direct torque control algorithm for induction motors based on discrete space vector modulation,” IEEE Trans. Power Electron., vol. 15, pp. 769–777, July 2000. [6] C. Lascu, I. Boldea, and F. Blaabjerg, “A modified direct torque control for induction motor sensorless drive,” IEEE Trans. Ind. Applicat., vol. 36, pp. 122–130, Jan./Feb. 2000. [7] V. I. Utkin, “Sliding mode control design principles and applications to electric drives,” IEEE Trans. Ind. Electron., vol. 40, pp. 23–36, Feb. 1993. [8] V. Utkin, J. Guldner, and J. Shi, Sliding Mode Control in Electromechanical Systems. New York: Taylor & Francis, 1999. [9] Z. Yan, C. Jin, and V. I. Utkin, “Sensorless sliding-mode control of induction motors,” IEEE Trans. Ind. Electron., vol. 47, pp. 1286–1297, Dec. 2000. [10] I. Boldea and A. Trica, “Torque vector control (TVC) voltage fed induction motor drives-very low speed performance via sliding mode,” in Conf. Rec. ICEM’90, vol. 3, 1990, pp. 1212–1217. [11] H.-J. Shieh and K.-K. Shyu, “Nonlinear sliding-mode torque control with adaptive backstepping approach for induction motor drive,” IEEE Trans. Ind. Electron., vol. 46, pp. 380–389, Apr. 1999. [12] F. S. Neves, T. G. Habetler, B. R. Menezes, R. P. Landim, and S. R. Silva, “Induction motor DTC strategy using discrete-time sliding mode control,” in Conf. Rec. IEEE-IAS Annu. Meeting, vol. 1, 1999, pp. 79–85. ˇ ´ , “Speed sensorless sliding [13] M. Rodiˇc, K. Jezernik, and A. Sabanovic mode torque control of induction motor,” in Conf. Rec. IEEE-IAS Annu. Meeting, vol. 3, 2000, pp. 1820–1827. [14] M. Tursini, R. Petrella, and F. Parasiliti, “Adaptive sliding mode observer for speed sensorless control of induction motors,” IEEE Trans. Ind. Applicat., vol. 36, pp. 1380–1387, Sept./Oct. 2000.

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[15] S. Doki, S. Sangwongwanich, and S. Okuma, “Implementation of speed-sensor-less field-oriented vector control using adaptive sliding observer,” in Conf. Rec. IEEE IECON’92, vol. 1, 1992, pp. 453–458. [16] F. Chen and M. W. Dunnigan, “Comparative study of a sliding-mode observer and Kalman filters for full state estimation in an induction machine,” Proc. IEE—Elect. Power Applicat., vol. 149, no. 1, pp. 53–64, Jan. 2002. [17] H. Rehman, A. Derdiyok, M. K. Güven, and L. Xu, “A new current model flux observer for wide speed range sensorless control of an induction machine,” IEEE Trans. Power Electron., vol. 17, pp. 1041–1048, Nov. 2002.

Cristian Lascu graduated in 1994 and received the M.S. and Ph.D. degrees in electrical engineering in 1995 and 2002, respectively, from the University Politehnica of Timis¸oara, Timis¸oara, Romania. In 1995, he joined the Department of Electrical Engineering, University Politehnica of Timis¸oara, where his research focused on power electronics and high-performance electrical drives. He was a Visiting Researcher at the Institute of Energy Technology, Aalborg University, Denmark, in 1997, and in the Department of Electrical Engineering, University of Nevada, Reno, in 1999 and 2000. Currently, he is working on advanced power electronics and drives for electrical vehicles under a European Marie Curie fellowship, Dr. Lascu was the recipient of an IEEE Industry Applications Society Prize Paper Award in 1998.

Ion Boldea (M’77–SM’81–F’96) received the M.S. and Ph.D. degrees in electrical engineering from the University Politehnica of Timisoara, Timisoara, Romania, in 1967 and 1973, respectively. He is currently a full Professor at the University Politehnica of Timisoara. He has visited universities in the U.S. and the U.K. repeatedly and has published extensively on linear and rotary electric machines, drives and power electronics. His latest books (with S.A. Nasar) are Induction Machine Handbook (Boca Raton, FL: CRC Press, 2001) and Linear Motion Electromagnetic Devices (London, U.K.: Taylor & Francis, 2001). He is an Associate Editor of Electric Power Components and Systems and Director of the Internet-only Journal of Electric Engineering (www.jee.ro). He has presented keynote addresses and intensive courses and works as a Consultancy in the U.S., Europe, and Asia. Prof. Boldea is a member of the Industrial Drives and the Electric Machines Committees of the IEEE Industry Applications Society (IAS) and was Co-Chairman of the OPTIM International Conferences (IAS sponsored) in 1996, 1998, 2000, and 2002.

Frede Blaabjerg (S’86–M’88–SM’97–F’03) was born in Erslev, Denmark, in 1963. He received the M.Sc.EE. from Aalborg University, Aalborg East, Denmark, in 1987, and the PhD. degree from the Institute of Energy Technology, Aalborg University, in 1995. He was with ABB-Scandia, Randers, Denmark, from 1987 to 1988. He became an Assistant Professor in 1992, an Associate Professor in 1996, and a Full Professor of power electronics and drives in 1998 at Aalborg University. In 2000, he was a Visiting Professor at the University of Padova, Italy, as well as a part-time programme research leader at the Research Center Risoe, working with wind turbines. In 2002, he was a Visiting Professor at Curtin University of Technology, Perth, Australia. His research areas are power electronics, static power converters, ac drives, switched reluctance drives, modeling, characterization of power semiconductor devices and simulation, wind turbines, and green power inverters. He is involved in more than ten research projects with industry. Among them is the “Danfoss Professor Programme in Power Electronics and Drives.” He is the author or coauthor of more than 250 publications in his research fields, including the book Control in Power Electronics (New York: Academic, 2002). Dr. Blaabjerg is a member of the European Power Electronics and Drives Association. He is also a member of the Industrial Power Converter, Power Electronics Devices and Components, and Industrial Drives Committees of the IEEE Industry Applications Society. He is an Associate Editor of the IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS, IEEE TRANSACTIONS ON POWER ELECTRONICS, Journal of Power Electronics, and the Danish journal Elteknik. He served as a Member of the Danish Technical Research Council during 1997–2003, and from 2001 to 2003, he was its Chairman. He has also been Chairman of the Danish Small Satellite Programme and the Center Contract Committee which supports collaboration between universities and industry. He became a member of the Danish Academy of Technical Science in 2001. During 2002–2003, he was a Member of the Board of the Danish Research Councils. He received the 1995 Angelos Award for his contribution to modulation technique and control of electric drives and an Annual Teacher Prize from Aalborg University, also 1995. In 1998, he received the Outstanding Young Power Electronics Engineer Award from the IEEE Power Electronics Society. He has received four IEEE Prize Paper Awards during the last five years. In 2002, he received the C.Y. O’Connor Fellowship from Perth, Australia, and in 2003, the Statoil Prize for his contributions to power electronics.