IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 53, NO. 4, AUGUST 2006 1027

New Maximum Power Point Tracker UsingSliding-Mode Observer for Estimation of Solar Array

Current in the Grid-Connected Photovoltaic SystemIl-Song Kim, Member, IEEE, Myung-Bok Kim, Member, IEEE, and Myung-Joong Youn, Senior Member, IEEE

AbstractA new maximum power point tracker (MPPT) for agrid-connected photovoltaic system without solar array currentsensor is proposed. The solar array current information is ob-tained from the sliding-mode observer and fed into the MPPTto generate the reference voltage. The parameter values suchas capacitances can be changed up to 50% from their nominalvalues, and the linear observer cannot estimate the correct statevalues under the parameter variations and noisy environments.The structure of a sliding-mode observer is simple, but it showsthe robust tracking property against modeling uncertainties andparameter variations. In this paper, the sliding-mode observerfor the solar array current has been proposed to compensate forthe parameter variations. The mathematical modeling and theexperimental results verify the validity of the proposed method.

Index TermsMaximum power point tracker (MPPT), photo-voltaic (PV) power systems, sliding-mode observer.

I. INTRODUCTION

THE photovoltaic (PV) energy as an alternative energysource has been widely used because it is pollution free,abundant, and broadly available. The PV energy applicationscan be divided into two categories, namely: 1) a stand-alonesystem and 2) a grid-connected system. A stand-alone systemrequires the battery bank to store the PV energy and is suitablefor a low-power system. On the other hand, a grid-connectedsystem does not require the battery bank and has become theprimary method for high-power applications.

A typical single-stage grid-connected PV system consistsof solar array, input capacitor C, single-phase inverter, filterinductor L, and grid voltage es(t), as shown in Fig. 1 [1]. Thesolar cells are connected in a seriesparallel configuration tomatch the required solar voltage and power rating. The inputcapacitor supports the solar array voltage for the voltage sourceinverter. The full-bridge inverter with filter inductor convertsa dc input voltage into an ac sinusoidal voltage by means ofappropriate switch signals to make the output current in phasewith the utility voltage and obtain a unity power factor.

The output power of PV array is dependent on environmen-tal factors such as illumination level and temperature. Since

Manuscript received November 21, 2004; revised June 27, 2005. Abstractpublished on the Internet May 18, 2006.

The authors are with the Department of Electrical Engineering and Com-puter Science, Korea Advanced Institute of Science and Technology, Dae-jeon 305-701, Korea (e-mail: iskim@powerlab.kaist.ac.kr; joyful@kaist.ac.kr;mmyoun@ee.kaist.ac.kr).

Digital Object Identifier 10.1109/TIE.2006.878331

Fig. 1. Typical configuration of a single-stage grid-connected PV system.

the characteristic curve of a solar cell exhibits a nonlinearvoltagecurrent relationship, a controller named the maximumpower point tracker (MPPT) is required to match the solar cellpower to the environmental changes. Many algorithms havebeen developed for tracking maximum power point of a solarcell [2][5]. Among them, the most commonly used methodsare the perturb and observe (P&O) algorithm and the incre-mental conductance algorithm. The P&O algorithm measuresthe derivative of power p and the derivative of voltage vto determine the movement of the operating point. If the signof p/v is positive, the reference voltage is increased, andvice versa. The advantage of this method is the easiness ofimplementation due to the simple control structure.

The other method, i.e., the incremental conductance algo-rithm, can track the maximum power point voltage accuratelythan the P&O algorithm by comparing the incremental con-ductance with an instantaneous conductance of a PV array toavoid the problem of oscillation because it stops perturbingthe operating point when the reference voltage reaches themaximum power point voltage.

All of these algorithms are required to measure the solararray current and voltage to acquire the information on the solararray power and conductance. The additional information suchas the measurements of the grid voltage and inductor current isalso required for the grid-connected PV system to synchronizethe phase of the inductor current to the grid voltage.

Since the solar array current has a close relation with theinductor current, it is possible to estimate the solar array currentthrough the state observer. As the state observer requires theexact information on the circuit parameters, such as capacitanceand inductance, it is absolutely required to know the exactparameter value. However, in a grid-connected PV invertersystem, the electrolytic capacitor is used for the input capacitor,and it is known that its actual capacitance value has 50%

0278-0046/$20.00 2006 IEEE

1028 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 53, NO. 4, AUGUST 2006

Fig. 2. Solar cell/array electrically equivalent circuit. (a) Single-cell circuit. (b) Solar array circuit (Ns, series; Np, parallel).

tolerance from its nominal value and deteriorates year by year[6]. If the capacitance information is not exact, the performanceof the state observer is degraded and, thus, the MPPT cannotoperate at the optimum point. The inductance also has thevariation from its nominal value. All of these uncertaintiesmake it difficult to use the linear-state observer. Linear ob-servers like Luenberger observer are known not to performwell under the presence of disturbance and unknown param-eter variations.

Although the variable structure controller has been known tohave the robustness under the presence of parameter variationsand disturbance, the sliding-mode observers are also knownto have similar robustness properties [7][10]. Thus, it wouldappear appropriate to adopt sliding-mode observer for the es-timation of the solar array current under the environment ofparameter uncertainties.

In this paper, a new MPPT without solar array currentmeasurement has been proposed. The current information isobtained from the sliding-mode observer and fed into thecontroller to generate the maximum power point referencevoltage. The sliding-mode observer has been constructed fromthe system dynamic equation. Due to the finite sampling time,there has been a chattering phenomenon in the estimated value,and it makes hard to acquire the steady-state value. To obtainthe steady-state value regardless of these chattering phenomena,the measured solar array voltage and estimated solar arraycurrent are averaged over a half cycle of the ac utility gridfrequency. As the reference voltage of the MPPT controller isupdated at every zero-crossing point of the grid voltage, theaverage solar array power during the half cycle of the gridfrequency is obtained from the average solar array voltageand the average estimated array current. To verify the trackingperformance against rapidly changing illumination level, thesolar array current has been changed from the upper limit to thelower limit, and vice versa. In addition, the capacitance valuehas been changed to 100% from the nominal value to verifythe robust tracking property of the sliding-mode observer. Thesimulation and experimental results show the validity of theproposed method.

II. SOLAR CELL/ARRAY MODELING

The voltagecurrent characteristic equation of a solar cell iscomposed of the light-generated current source, diode, seriesresistance, and parallel resistance as can be seen in Fig. 2(a).

The terminal equation for the current and voltage of the solarcell is given as follows [1]:

I = Iph Isat{exp

(V + IRs

ko

) 1

} V + IRs

Rsh(1)

whereko AKT/q;I , V cell output current and voltage;Iph light-generated current;Isat cell reverse saturation current;A ideality factor (= 1);K Boltzmanns constant (= 1.3805 1023 N m/K);T cell temperature (in kelvin);q electronic charge (= 1.6 1019 C);Rs series resistance;Rsh shunt resistance.The equivalent circuit for the solar cells arranged in Np

(parallel) and Ns (series) is shown in Fig. 2(b), and themathematical equation for the array current and array voltagebecomes as follows:

Isa = NpIph NpIsat{exp

(VsaNsko

+IsaRsNpko

) 1

}

1Rsh

(VsaNs

+IsaRsNp

)(2)

where Np represents the number of parallel modules. Notethat each module is composed of Ns cells connected in series.NpIph corresponds to the short-circuit current of the solar array.The characteristic curves of the solar array at two differentvalues of Iph are shown in Fig. 7. These curves show a highlynonlinear characteristic around the maximum power point.

III. SLIDING-MODE OBSERVER FOR THEGRID-CONNECTED PV SYSTEM

The dynamic model of a grid-connected single-stage PVsystem shown in Fig. 1 can be obtained by applying nodeequation. The state averaging equation is described as follows:

vsa =1C

(iL u+ isa) + f1

iL =1L

(vsa u es(t)) (3)

where vsa and iL are the capacitor voltage and inductor cur-rent, respectively, and es(t) is the grid voltage. The circuit

KIM et al.: NEW MPPT FOR ESTIMATION OF SOLAR ARRAY CURRENT IN THE GRID-CONNECTED PV SYSTEM 1029

parameters C and L correspond to their nominal values, whichare exactly known. The uncertainty f1 represents modelinguncertainties and measurement errors caused by the capacitanceand inductance deviations from the nominal values and isbounded by the known value 1.

The control input u is the average control input that can takethe continuous value from 1 to 1, and the value is determinedfrom the output of the current controller and is given as follows:

u =vINVvtri

(4)

where vtri is the peak amplitude of the triangular carrier signal,and vINV is the control signal of the current controller to controlthe amplitude of the current and also to adjust the solar arrayvoltage for tracking the maximum power point.

The solar array current isa is a function of the solar arrayvoltage, temperature, and light-generated current and can bedescribed as another state variable. The measurements of solararray voltage vsa and current isa are necessary to generate thereference voltage to track the maximum power point of thesolar array. The measurements of the grid voltage es(t) andinductor current iL are also required to synchronize their phaseand transfer solar array current into the grid with unity powerfactor. Among these measurements, the solar array current isa function of capacitor voltage and inductor current as can beseen in (3). Therefore, solar array current isa can be estimatedthrough the state observer from the measurable state vsa and iL.

The solar array voltage and current have ripple componentsin accordance with the grid voltage, and their ripple frequencyis twice the grid frequency (120 Hz) in a single-stage PVsystem. The solar array power that is the product of voltageand current also has ripple component. Because of this, theMPPT controller uses the average values to update the referencevoltage rather than the instantaneous value. In most cases, theMPPT reference voltage is updated at every zero-crossing pointof grid voltage using the average values during the half cycle ofthe grid frequency. Therefore, the required estimated current isan average current rather than an instantaneous value. Based onthis average concept, it is possible to assume that the derivativeof the solar array current isa is zero, although it has ripplecomponents, if the sampling frequency is fast compared withthe dynamics of the solar array current. Then the new stateequation for vsa and isa is given as follows:

vsa =1C

(iL u+ isa) + f1isa =0y = vsa. (5)

The corresponding sliding-mode observer for the above equa-tion is given by [7]

vsa =1C

(iL u+ isa) + L1sgn(ey)isa =L2 (L1sgn(ey))ey

= y y = vsa sasgn(ey) =

{+1, ey > 01, ey < 0 (6)

where (vsa, isa) are the estimates for (vsa, isa), and L1, L2are constant positive observer gains. Define current error ei

=isa isa, then the error system is obtained as follows:

ey =eiC

+ f1 L1sgn(ey) (7)ei = L2 (L1sgn(ey)) . (8)

With a sufficiently large L1, ey and ey are guaranteed to havedifferent signs, so that the sliding mode takes places on themanifold of the output error states in (7) and the convergenceto the equilibrium state is guaranteed. The range of L1 and L2determine the magnitude of the chattering and stability of theobserver.

Although it is usually claimed that the sliding mode generallyyields robustness against disturbance, it should be noted thatthere is a restriction on this property. As to the sliding-modeobserver, the structure of observer is determined by the systemequation, where the switching gain L1, L2 can be arbitrarilyassigned to attain robustness against disturbances. However, therestriction on the assignment of the switching gain comes fromthe condition that the observer is stable. The practical system isimplemented with digital system that has a finite sampling time,and it gives rise to the chattering phenomena. The magnitude ofchattering is highly dependent on the observer gain. If the gainis too big, a large amount of ripples may result, causing theestimation errors. Therefore, a tradeoff should be made betweenthe robustness and stability [11].

The range of L1 is dependent upon the maximum value ofsolar array current and amount of uncertainties. The parameteruncertainty f1 is bounded to 1, and the solar array currentestimation error ei is also bounded to NpIph and correspondsto the solar array short-circuit current. This short-circuit currentis a function of the temperature and illumination level. If theboundaries of the temperature and illumination level are known,the maximum value of the solar array current can be determinedas NpIph. The range of observer switching gain L1 is given as

L1 > max(eiC

+ f1)=eiC

+|f1| = NpIphC

+ 1. (9)

For a given L1, the following equation holds for the errorsystem in (7):

ey > 0 : ey =eiC

+ f1 L1 ey < 0

ey < 0 : ey =eiC

+ f1 + L1 ey > 0. (10)

From (10), the following inequality is satisfied:

ey ey < 0. (11)

Therefore, the voltage error ey reduces to zero.According to the equivalent control method, the system in

sliding mode behaves as if L1sgn(ey) were replaced by itsequivalent value (L1sgn(ey))eq, which can be calculated from(7) assuming ey = 0 when the sliding trajectory is restrictedon the sliding manifold ey = 0. Once the sliding surface isreached, then from the equivalent control concept, ey and ey

1030 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 53, NO. 4, AUGUST 2006

Fig. 3. Overall controller configuration of the proposed system.

Fig. 4. Simulation waveform of the solar array voltage, current, and estimated states.

TABLE IPARAMETERS FOR SIMULATION AND EXPERIMENT

reduced to zero and the uncertainties vanish, and then theresulting equation from (7) can be written as follows:

L1sgn(ey)eq =eiC. (12)

Substituting (12) into (8), then we obtain the following result:

ei = L2 eiC. (13)

Then from (13), the following inequality always holds:

ei ei = L2C e2i < 0. (14)

Therefore, the convergence condition for the current error ei isalways satisfied if the observer gain L2 is positive.

However, as previously mentioned, the solar array current os-cillates at a frequency of 120 Hz due to the sinusoidal inductorcurrent. The assumption has been made at (5) that the derivativeof the solar array current is zero. Therefore, the current error eihas ripple component that oscillates at a frequency of 120 Hz.This error ripple component can be eliminated by the averageof current error over the half cycle of the grid frequency. Thiscan be expressed as follows:

1T/2

T/20

ei dt =0 (15)

1T/2

T/20

(isa isa)dt =0

1T/2

T/20

isa dt = 1T/2

T/20

isa dt (16)

where T = 1/f (f is the grid frequency = 60 Hz).Therefore, the following relation is satisfied:

isa_avg = isa_avg (17)

KIM et al.: NEW MPPT FOR ESTIMATION OF SOLAR ARRAY CURRENT IN THE GRID-CONNECTED PV SYSTEM 1031

Fig. 5. Simulation waveforms of current, average current, and estimated states. (a) Iph changes from 1 to 2 A. (b) Iph changes from 2 to 1 A.

Fig. 6. Hardware experimental setup configuration.

where

isa_avg=

1T/2

T/20

isadt

isa_avg=

1T/2

T/20

isadt. (18)

The estimated average current has the same value as theaverage current. This estimated average current is fed intothe MPPT controller instead of the average current. As theMPPT controller updates the reference voltage at every zero-crossing point of the grid voltage using the average array volt-age and average estimated current to get the solar array power,the average estimated solar array current is necessary ratherthan the instantaneous estimated array current as previouslymentioned.

1032 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 53, NO. 4, AUGUST 2006

Fig. 7. Voltagecurrent characteristics of SAS. (a) Iph = 2 A. (b) Iph = 1 A.

The average solar array voltage during the half cycle of thegrid frequency is given as follows:

vsa_avg=

1T/2

T/20

vsadt. (19)

Then, the solar array power Psa_avg is given as the product ofvsa_avg and isa_avg. This value is used to determine the powerslope and update the reference voltage using the P&O algorithmas follows [2]:

Vref(k + 1)=Vref(k) +M

sgn(Psa_avg(k) Psa_avg(k 1)vsa_avg(k) vsa_avg(k 1)

)(20)

where M means the shift step from the previous value, andthe parenthesis of equation means the power slope over voltageslope.

Fig. 3 shows the overall controller configuration. It consistsof the sliding-mode observer, MPPT controller, voltage con-troller for the solar array voltage control, and current controllerfor the inductor current control. The MPPT controller detectsa power slope from the array average voltage and averageestimated current information, and generates the reference volt-age. The voltage controller controls the solar array voltageto follow the reference using the proportionalintegral (PI)controller. The output of the voltage controller becomes the dccurrent reference, and the inductor current reference Iref is ob-tained by multiplying the phase information of the grid voltageas follows:

Ii =Kp(Vsa V ref) +KI

(Vsa V ref)dt

Iref =2 Ii sin(st) (21)

Fig. 8. Experimental waveform of voltage, current, and estimated states.

where Kp is the proportional gain, and KI is the integral gainof the error system. The current controller controls the inductorcurrent to follow current command Iref . The predictive currentcontroller has the good control property and fixed switchingfrequency. The inverter voltage command of the predictivecurrent controller is given as follows:

V INV(i+ 1) = es(i) +L

Ts(Iref(i) iL(i)) . (22)

This inverter voltage command is compared with thepulsewidth-modulated (PWM) ramp voltage and generates theappropriate switching pattern of the inverter.

IV. SIMULATION RESULT

Fig. 4 shows the simulation waveform of the solar arrayvoltage, current, estimated voltage, estimated current, and

KIM et al.: NEW MPPT FOR ESTIMATION OF SOLAR ARRAY CURRENT IN THE GRID-CONNECTED PV SYSTEM 1033

Fig. 9. Experimental waveforms of current, average current, and estimated values. (a) Iph changes from 1 to 2 A. (b) Iph changes from 2 to 1 A.

Fig. 10. Waveform against parameter variation when Iph changes 1 to 2 A. (a) C = 2000 F. (b) C = 500 F.

current error using the parameters shown in Table I. The peakmagnitude of the grid voltage is 25 V, and the frequency is60 Hz. The reference voltage of the MPPT controller is set to40 V for simulation. As can be seen in Fig. 4, the solar arrayvoltage and current are oscillated at a frequency of 120 Hz,which is twice of the grid frequency es(t). The estimated solararray voltage vsa exactly follows the solar array voltage vsa withthe bounded switching ripple error. The estimated solar arraycurrent isa follows the solar array current isa with the delayedchattering value that overlapped on the equivalent value. Thecurrent error has also 120-Hz ripple that is symmetrical overzero at a frequency of 120 Hz. Although isa does not coincidewith isa, the current error over the half cycle of the gridfrequency is zero as can be seen in Fig. 4.

To verify the tracking performance of the sliding-mode ob-server, Iph is changed from 1 to 2 A, and vice versa. Fig. 5shows the waveform of isa, isa, isa_avg, and isa_avg for thechange of Iph. As can be seen in this figure, the average valueof the estimated current exactly coincides with the real averagecurrent regardless of the abrupt change of Iph. Therefore, it

can be concluded that the solar array current estimation usingthe sliding mode can be applied to a real situation without themeasurement of the solar array current.

V. EXPERIMENTAL RESULT

To verify the performance of the proposed sliding-modeobserver in the grid-connected PV system, an experimentalconfiguration has been setup as shown in Fig. 6. The solararray simulator (SAS) has been used for simulating the PVarray following the mathematical expression of (2). It consistsof adjustable current sources and a series-connected diodestring. The SAS can simulate the change of voltagecurrentcharacteristics according to the temperature and illuminationlevel variations by switching the value of current source andthe number of series cells in a diode string. The measuredvoltagecurrent characteristics of the SAS for Iph = 2 and 1 Aare shown in Fig. 7. This curve data are plotted from theAutomated Test Equipment (ATE), which is connected to theSAS by varying the resistance of the ATE. The maximum power

1034 IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 53, NO. 4, AUGUST 2006

Fig. 11. Grid voltage and inductor current waveforms. (a) Iph changes from 1 to 2 A. (b) Iph changes from 2 to 1 A.

Fig. 12. MPPT tracking performance. (a) Iph changes from 1 to 2 A. (b) Iph changes from 2 to 1 A.

is 75 W, and the maximum power point resides in 38 V as canbe seen in Fig. 7(a). As the maximum output voltage of the SASis limited only to 50 V, which is lower than the grid voltage, theoutput of the inverter is connected to the grid voltage through astep-up transformer in the experiment.

The digital signal processor (DSP), type TMS320C31, isused to control the sliding-mode observer and MPPT includ-ing the predictive current controller. The array current isa istentatively measured by dc current sensor in the experimentalsystem. This sensor information is used to calculate the realaverage value of the current. The analog-to-digital (A/D) con-verters are used to convert the sensor information to digital val-ues. The digital-to-analog (D/A) converters are used to displaythe observer outputs and their average values. The software isexecuted at the interrupt routine that is called at every 0.1 ms.Whenever the grid voltage crosses the zero-cross point, theaverage value of estimated current is updated using the half-cycle data, and the reference voltage of the MPPT controller isalso updated.

Fig. 8 shows the experimental waveform of the solar arrayvoltage, current, estimated voltage, and estimated current. Theestimated voltage and current waveforms exactly follow theoriginal values. Fig. 9 shows the experimental waveforms ofisa, isa, isa_avg, and isa_avg for the change of Iph from 1 to2 A, and vice versa. The average estimated current isa_avgexactly coincides with the real average current isa_avg exceptfor the transition period. During the transition period, a reach-ing phase happened, and an estimation error can be seen. Itshows the same result as the simulation waveform. To showthe robust control property against the parameter variationsand uncertainties, the value of capacitance C is changed from1000 to 2000 and 500 F. The resultant waveform is shown inFig. 10. The capacitance value determines the amount of theripple in the solar array current. The higher capacitance showsthe lower current ripple. Although the magnitude of ripple inthe estimated current becomes large when the capacitance isdeviated from its nominal value, the average values of themeasured and estimated current are the same. It also shows the

KIM et al.: NEW MPPT FOR ESTIMATION OF SOLAR ARRAY CURRENT IN THE GRID-CONNECTED PV SYSTEM 1035

exact coincidence between the average measured and estimatedcurrent. From these figures, it comes to a conclusion that thesliding-mode observer has the robust tracking property againstparameter variations.

Fig. 11 shows the utility voltage es(t) and inductor currentiL(t) waveforms when Iph changes from 1 to 2 A, and viceversa. It can be seen that the inductor current is in phase withthe utility voltage, and the power factor is 1 even if Iph suddenlychanges.

Using the average estimated current, the MPPT trackingperformance for the change of Iph is shown in Fig. 12. Thewaveforms of vsa, vsa_ref , and Psa_avg are shown for the Iphchange. It can be said that the MPPT can track the exact maxi-mum power 37 W 75 W 37 W using the estimated currentwithout measurement of solar array current. The proposedsliding-mode observer system does not require the additionalhardware in the implementation. The addition of few lines ofsoftware code to the previous system is enough, and it has themerit of cost reduction.

VI. CONCLUSION

The sliding-mode observer for the estimation of solar arraycurrent in the grid-connected PV system has been proposed.The sliding-mode observer is constructed from the state equa-tion of the system, and the convergence of the error systemis proved using equivalent control concept. Although the es-timated current has some chattering ripples, the average esti-mated value for the half cycle of the grid frequency exactlycoincides with the real average current value. Using the pro-posed sliding-mode observer, the robust tracking performanceagainst parameter variations and uncertainties has been verifiedby simulation and experimental results. The proposed systemis possible to reduce the expensive current sensor and showssuperior performance than the conventional system.

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[2] E. Koutroulis, K. Kalaitzakis et al., Development of a microcontroller-based, photovoltaic maximum power point tracking control system,IEEE Trans. Power Electron., vol. 16, no. 1, pp. 4654, Jan. 2001.

[3] F. Valenciaga, P. F. Puleston, and P. E. Battiaiotto, Power control of a pho-tovoltaic array in a hybrid electric generation system using sliding modetechniques, Proc. Inst. Electr. Eng.Control Theory Appl., vol. 148,no. 6, pp. 448455, Nov. 2001.

[4] T. Noguchi, S. Togashi, and R. Nakamoto, Short-current pulse-basedmaximum power point tracking method for multiple photovoltaic andconverter module system, IEEE Trans. Ind. Electron., vol. 49, no. 1,pp. 217223, Feb. 2002.

[5] D. P. Hohm and M. E. Ropp, Comparative study of maximum powerpoint tracking algorithm using an experimental, programmable, maximumpower point tracking test bed, in Proc. IEEE PESC, 2000, pp. 16991702.

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Il-Song Kim (M04) was born in Korea in 1968. Hereceived the B.S. degree in electronics engineeringfrom Yonsei University, Seoul, Korea, in 1991, andthe M.S. and Ph.D. degrees in electrical engineer-ing from the Korea Advanced Institute of Scienceand Technology, Daejeon, Korea, in 1994 and 2005,respectively.

Since 1994, he has been with the Satellite BusinessDivision, Hyundai Electronics, Korea. Since 1999,he has been a Power Team Leader with the KITSAT-4 satellite project in the Satellite Research Center

(SATREC). His research interests include photovoltaic system, satellite powerand system engineering, aerospace electronic equipment, and control systems.

Dr. Kim is a member of the Korean Institute of Power Electronics.

Myung-Bok Kim (M04) was born in Gyeong-Buk,Korea, on October 23, 1973. He received the B.S.degree in electronics engineering from KyungpookNational University, Daegu, Korea, in 1996, andthe M.S. degree in electrical engineering from theKorea Advance Institute of Science and Technology(KAIST), Daejeon, Korea, in 1998. He is currentlyworking toward the Ph.D. degree at KAIST.

Mr. Kim is a member of the Korean Institute ofPower Electronics.

Myung-Joong Youn (S74M78SM89) was bornin Seoul, Korea, on November 26, 1946. He receivedthe B.S. degree from Seoul National University,Seoul, Korea, in 1970, and the M.S. and Ph.D. de-grees in electrical engineering from the University ofMissouri, Columbia, in 1974 and 1978, respectively.

In 1978, he joined the Air-Craft Equipment Divi-sion, General Electric Company, Erie, PA, where hewas an Individual Contributor on Aerospace Elec-trical System Engineering. Since 1983, he has beena Professor with the Korea Advanced Institute of

Science and Technology, Daejeon, Korea. His research activities are in theareas of power electronics and control, which include drive systems, rotatingelectrical machine design, and high-performance switching regulators.

Prof. Youn is a member of the Institution of Electrical Engineers, U.K.,the Korean Institute of Power Electronics, the Korean Institute of ElectricalEngineers, and the Korean Institute of Telematics and Electronics.