1. direct torque control of induction motor with fuzzy controller a review

Siva Ganesh Malla and Jagan Mohana Rao Malla 1

International Journal of Emerging Trends in Electrical and Electronics (IJETEE ISSN: 2320-9569) Vol. 10, Issue. 3, April-2014.

Direct Torque Control of Induction Motor withFuzzy Controller: A Review

Siva Ganesh Malla and Jagan Mohana Rao Malla

Abstract:At present, induction motors are the dominant drivesin various industries. It is quite cumbersome to control aninduction motor (IM) because of its poor dynamic response incomparison to the DC motor drives. The central theme ofVector Control (VC) is to decouple the stator current of the IMinto two orthogonal components and is to control these twocomponents individually so as to achieve an independentcontrol of flux and torque of the IM. VC is still very complexto implement. Direct Torque Control (DTC) is an improvisedVC method. With the DTC scheme employing a Voltage SourceInverter, it is possible to control directly the stator flux linkageand the electromagnetic torque by the optimum selection ofinverter switching vectors. The modeling of an IM driveemploying DTC with application of fuzzy is performed in thisarticle, it is better to understand the DTC and its difficulties.The reference voltage vector is then realized using a voltagevector modulator. Several variations of DTC-SVM have beenproposed and discussed in the literature. The work of thisreview paper is to study, evaluate and compare the varioustechniques of the DTC-SVM applied to the Induction Motor.Keywords: Induction Motor Drive, Modeling of InductionMotor, Vector Control, Field Orient Control, Direct TorqueControl, and Fuzzy Applications.

1. INTRODUCTIONThe history of electrical motors goes back as far as

1820, when Hans Christian Oersted discovered the magneticeffect of an electric current. One year later, Michael Faradaydiscovered the electromagnetic rotation and built the firstprimitive D.C. motor. Faraday went on to discoverelectromagnetic induction in 1831, but it was not until 1883that Tesla invented the A.C. asynchronous motor [1].Currently, the main types of electric motors are still thesame, DC, AC asynchronous and synchronous, all based onOested, Faraday and Teslas theories developed anddiscovered more than a hundred years ago.

An IM is a type of asynchronous AC motor wherepower is supplied to the rotating device by means ofelectromagnetic induction [2-5]. Induction motors arewidely used, especially polyphase induction motors, whichare frequently used in industrial drives. These facts are dueto the induction motors advantages over the rest of themotors. Most of the industrial motor applications use ACinduction motors. The reasons for this include highrobustness, reliability, low price and high efficiency [2-8].2. PRINCIPLE OF OPERATION AND COMPARISON TO

SYNCHRONOUS MOTORSA 3-phase power supply provides a rotating

magnetic field in an IM. The basic difference between anIM and a synchronous AC motor is that in the latter acurrent is supplied onto the rotor. This then creates amagnetic field which, through magnetic interaction, links to

the rotating magnetic field in the stator which in turn causesthe rotor to turn. It is called synchronous because at steadystate the speed of the rotor is the same as the speed of therotating magnetic field in the stator. By way of contrast, theIM does not have any direct supply onto the rotor; instead, asecondary current is induced in the rotor [2, 9]. Thischanging magnetic field pattern can induce currents in therotor conductors. These currents interact with the rotatingmagnetic field created by the stator and the rotor will turn[10].

This difference between the speed of the rotor andspeed of the rotating magnetic field in the stator is calledslip. The three phase AC IM and is the most widely usedmachine. Because it is having the characteristic featuresSimple and rugged construction, Low cost and minimummaintenance, High reliability and sufficiently highefficiency, Needs no extra starting motor and need not besynchronized, and an IM has basically two parts: Stator andRotor [10].

2.1. APPLICATIONSA wide variety of induction motors are available

and are currently in use throughout a range of industrialapplications. Single phase induction motors are widely used,due to their simplicity, strength and high performance. Theyare used in household appliances, such as refrigerators, airconditioners, hermetic compressors, washing machines,pumps, fans, as well as in some industrial applications.Before the days of power electronics, a limited speed controlof IM was achieved by switching the three-stator windingsfrom delta connection to star connection, allowing thevoltage at the motor windings to be reduced [1-20].

2.2. VARIABLE-FREQUENCY DRIVES (VFD)A VFD can easily start a motor at a lower frequency

than the AC line, as well as a lower voltage, so that themotor starts with full rated torque and with no inrush ofcurrent. The rotor circuit's impedance increases with slipfrequency, which is equal to supply frequency for astationary rotor, so running at a lower frequency actuallyincreases torque [21-23]. Industries have many applications,where variable operating speed is a prime requirement.Principal benefits of variable speed drives in industrialapplications are that they allow the drive speed and torque tobe adjusted to suit the process requirements. In manyapplications, operating the plant at a reduced speed whenfull output is not needed produces a further importantbenefit: energy savings and reduced cost [21]. Whereasinfinitely variable speed drives with good performances forDC motors already existed. These drives not only permittedthe operation in four quadrants but also covered a widepower range. Moreover, they had a good efficiency, and



with a suitable control even a good dynamic response. Itsmain drawback was the compulsory requirement of brushes[10].

The various methods of speed control of squirrelcage IM through semiconductor devices are given in [2, 9-20] as under: Scalar control, Vector control (Field-OrientedControl, FOC), Direct Torque Control (DTC) and DTC withSVM & Fuzzy based control. These controllers are dependson how inverters can be controlled, mostly multilevelinverters are using in industries due to their advantages [21-45].

Scalar controllers: Despite the fact that Voltage-Frequency (V/F) is the simplest controller, it is the mostwidespread, being in the majority of the industrialapplications [2]. It is known as a scalar control and acts byimposing a constant relation between voltage and frequency,so as to give nearly constant flux over wide range of speedvariation [9]. More over Constant voltage/hertz controlkeeps the stator flux linkage constant in steady state withoutmaintaining decoupling between the flux and torque [2].However, this controller does not achieve a good accuracyin both speed and torque responses, mainly due to the factthat the stator flux and torque are not directly controlled.Even though, as long as the parameters are identified, theaccuracy in the speed can be 2% (expect in a very lowspeed), and the dynamic response can be approximatelyaround 50ms [2, 9].

Vector controllers: In 1971, Blaschke propose ascheme which aims as the control of an IM like a separatelyexcited dc motor, called field oriented control, VC, or Transvector control [46-48]. In this scheme the IM analyzed froma synchronously rotating reference frame where allfundamental variables appears to be dc ones. The torque andflux component of currents are identified and controlledindependently to achieve good dynamic response [46, 47].The most widespread controllers of this type are the onesthat use vector transform such as either Park or Ku.However there is a necessity of transforming the variables inthe synchronously rotating reference frame to statorreference frame to affect the control of actualcurrents/voltages [47]. Additionally the transformation alsoneeds the approximate flux vector angle, where is eithercalculated slip angle or measured rotor angle as indirect VCor by estimating the flux angle directly by employing a fluxobserver as in direct VC [47]. Its accuracy can reach valuessuch as 0.5% regarding the speed and 2% regarding thetorque, even when at standstill. The main disadvantages arethe huge computational capability required and thecompulsory good identification of the motor parameters.

Recently advanced control strategies for PWMinverter fed IM drives have been developed based on thespace vector approach, where the IM can be directly andindependently controlled without any co-ordinationtransformation [48]. One of the emerging methods in thisperspective is the direct torque and flux control (DTFC). InDTFC, the motor torque and the flux are calculated from theprimary variables, and they are controlled directly andindependently by selecting optimum inverter switch modes[2-52]. This control results in quick torque response in thetransient operation and improvement in the steady stateefficiency [14]. Its main characteristic is the goodperformance, obtaining results as good as the classical

vector control but with several advantages based on itssimpler structure and control diagram.

DTC is said to be one of the future ways ofcontrolling the IM in four quadrants. In DTC it is possible tocontrol directly the stator flux and the torque by selectingthe appropriate inverter state [46, 54]. DTC main featuresare direct control of flux and torque, indirect control ofstator currents and voltages, approximately sinusoidal statorfluxes and stator currents, and High dynamic performanceeven at stand still [53, 54]. DTC have several advantageslike, Decoupled control of torque and flux, Absence of co-ordinate transforms, Absence of voltage modular block,Absence of mechanical transducers, Current regulator,PWM pulse generation, PI control of flux and torque andco-ordinate transformation is not required, Very simplecontrol scheme and low computational time, and Reducedparameter sensitivity and Very good dynamic properties aswell as other controllers such as PID for motor flux andtorque, and Minimal torque response time even better thanthe VCs [53, 54]. However, some disadvantages are alsopresent such as: Possible problems during starting,Requirement of torque and flux estimators, implying theconsequent parameters identification, and Inherent torqueand stator flux ripple [53-54]. Although, somedisadvantages are: High torque ripples and currentdistortions, Low switching frequency of transistors withrelation to computation time, Constant error betweenreference and real torque [3].

After this, comparison of variable speed drives isgiven. The aim being to find even simpler methods of speedcontrol for induction machines one method, which ispopular at the moment, is DTC.

Initially the theory of induction machine model isgiven. The understanding of this model is mandatory tounderstand both the control strategies (i.e. FOC and DTC).DTC drives utilizing hysteresis comparators suffer fromhigh torque ripple and variable switching frequency.Straightly speaking, Major drawback of Classical DTC ishigh torque & flux ripples. The most common solution tothis problem is to use fuzzy applications with Space VectorModulation (SVM) or using multilevel inverter [2, 3]. Inthis Paper the author briefly explained about two-fuzzycontroller along with the SVM technique is applied to twolevel inverter. Before going to DTC, first we study about themathematical background of DTC.3. INDUCTION MOTOR MATHEMATICAL MODEL

The steady-state model and equivalent circuit areuseful for studying the performance of machine in steadystate. This implies that all electrical transients are neglectedduring load changes and stator frequency variations. Thedynamic model of IM is derived by using a two-phase motorin direct and quadrature axes [55]. This approach isdesirable because of the conceptual simplicity obtained withthe two sets of the windings, one on the stator and the otheron the rotor.

The equivalence between the three-phase and two-phase machine models is derived from the simpleobservation. The concept of power invariance is introduced[2, 3, 8]. The reference frames are chosen to arbitrary andparticular cases such as stationary, rotor, and synchronousreference frames, are simple instances of the general case.



The space-phasor model is derived from the dynamic modelin direct and quadrature axes [55].

3.1 DYNAMIC d-q MODELThe assumptions are made to derive the dynamic

model as uniform air gap, balanced rotor and statorwindings, with sinusoidal distributed mmf, inductance vs.rotor position in sinusoidal, and Saturation and parameterchanges are neglected.

The dynamic performance of an AC machine issomewhat complex because the three-phase rotor windings

move with respect to the three-phase stator windings asshown in Fig 1(a). Basically, it can be looked on as atransformer with a moving secondary, where the couplingcoefficients between the stator and rotor phases changecontinuously with the change of rotor positioncorrespond to rotor direct and quadrature axes [2-4, 7, 8].Note that a three-phase machine can be represented by anequivalent two-phase machine as shown in Fig 1(b), whereds ~ qs correspond to stator direct and quadrature axes, and dr ~q r is corresponding to rotor.

Fig 1: (a) Coupling effect in three-phase stator and rotor windings of motor; (b) Equivalent two-phase machine.Although it is somewhat simple, the problem of time-

varying parameters still remains. R.H. Park, in the 1920s,proposed a new theory of electric machine analysis to solvethis problem. Essentially, he transformed or referred, thestator variables to a synchronously rotating reference framefixed in the rotor [56]. With such a transformation (calledParks transformation), he showed that all the time-varyinginductances that occur due to an electric circuit in relativemotion and electric circuits with varying magneticreluctances can be eliminated [3,7]. Later, in the 1930s, H.C. Stanley showed that time- varying inductances in thevoltage equations of an induction machine due to electriccircuits in relative motion can be eliminated bytransforming the rotor variables to variables associatedwith fictitious stationary windings. Later, G. Kron proposeda transformation of both stator and rotor variables to asynchronously rotating reference frame that moves with therotating magnetic field. D. S. Brereton proposed atransformation of stator variables to a rotating referenceframe that is fixed on the rotor. In fact, it was shown later byKrause and Thomas that time-varying inductances can beeliminated by referring the stator and rotor variables to acommon reference frame which may rotate at any speed.

3.2. AXES TRANSFORMATION

Fig 2. Stationary frame a~b~c to ds~qs axes transformation.Consider a symmetrical three-phase induction

machine with stationary as-bs-cs axes at 2/3-angle apart, asshown in Fig 2. Our goal is to transform the three-phasestationary reference frame (as-bs -cs) variables into two-phase stationary reference frame (ds~qs) variables and thentransform these to synchronously rotating reference frame(de ~ qe), and vice-versa [3, 56]. Assume that the de qe.Axesare oriented at angle, as shown in Fig 2. The voltages

r



and can be resolved into as-bs-cs componentsand can be represented in the matrix form as

=

(1)The corresponding inverse relation is.

=

(2)

Where is added as the zero sequence component,which may or may not be present. The current and fluxlinkages can be transformed by similar equations. It isconvenient to set = 0, so that the qs axis is aligned withthe as-axis, the transformation relations can be simplified byignoring zero sequence. Fig 3 shows the synchronouslyrotating de- q e, which rotates at synchronous speed withrespect to the ds-qs axes and the angle the two-phase de- qs windings are transformed into the hypotheticalwindings mounted on the de-qe axes [3]. The voltages on theds-qs axes can be converted (or resolved) into the de-qe frameas follows:

(3)(4)

For convenience, the superscript e has beendropped from now on from the synchronously rotatingframe parameters. Again, resolving the rotating frameparameters into a stationary frame, the relations are.

(5)(6)

The qe -de components can also be combined into avector form:

(7)Or inversely

(8)Note that the vector magnitudes in stationary and

rotating frames are equal, that is,(9)

In Equation (7), eje is defined as the inversevector rotator that converts ds -qs variables into de - qe

variables. The vector V and its components projected onrotating and stationary axes are shown in Fig 3. The as-bs-csvariables can also be expressed in vector form. And also:

(10)Where a=e j 2 / 3. The parameters a and a2 can be

interpreted as unit vectors. Similar transformations can bemade for rotor circuit variables also [3, 8, 17].

3.3. SYNCHRONOUSLY ROTATING REFERENCEFRAME - DYNAMIC MODEL.

Fig.3: (a) Stationary frame ds - qs to rotating frame de - qe ;(b) Flux and current vectors de - qe.

For the two-phase machine shown in Fig 3, we needto represent both ds -qs and dr qr circuits and their variables

sdsV sqsV

cs

bs

as

VVV

1)120sin()120cos(1)120sin()120cos(1sincos

00

00

sos

sds

sqs

VVV

sos

sds

sqs

VVV

32

5.05.05.0)120sin()120sin(sin)120cos()120cos(cos

00

00

cs

bs

as

VVV

sosV

e.tee

esdse

sqsqs VVV sincos

esdse

sqsds VVV cossin

edseqssqs VVV sincos

edseqssds VVV cossin

ee jjsdssqs

esdse

sqse

sdse

sqsdsqs

eqds

eVejVVVVjVVjVVV

)()cossin()sincos(

ejdsqssds

sqs ejVVjVVV )(

22 dsqsm VVVV

csbsascsbscsbsas

sds

sqs

VaaVV

VVjVVVjVVV

232

31

31

31

31

32



in a synchronously rotating de -qe frame. We can write thefollowing stator circuit equations:

(11)

sds

sdss

sds dt

dIRV (12)Where and are q- axis and d-axis stator flux

linkages, respectively. When these equations are convertedto de -qe frame, the following equations can be written:

(13)

qsedsdssds dtdIRV (14)

If the rotor is not moving, that is, , the rotorequations for a doubly fed wound-rotor machine will besimilar to Equations (13) - (14):

(15)

qredrdrrdr dtdiRV (16)

The rotor actually moves at speed r , the d - q axesfixed on the rotor move at a speed e - r relative to thesynchronously rotating frame. Therefore, rotor equationsshould be modified as.

(17)

(18)The de -qe dynamic model equivalent circuits that

satisfy Equations (13), (14) and (17), (18). A specialadvantage of the de -qe dynamic model of the machine is thatall the sinusoidal variables in stationary frame appear as dcquantities in synchronous frame. The flux linkageexpressions in terms of the currents can be written from Fig3(b) as follows:

(19))( qrqsmqrlrqr iiLiL (20)

)( qrqsmqm iiL (21))( drdsmdslsds iiLiL (22))( drdsmdrlrdr iiLiL (23)

)( drdsmdm iiL (24)Combining the above expressions with Equations

(13), (14), (17) and (18), the electrical transient model interms of voltages and currents can be given in matrix formas

(25).Where S is Laplace operator. For a cage motor,

Vrq=Vdr= 0. If the speed is considered constant. Then,knowing the inputs Vsq, Vsd and , the currents iqs, ids, iqrand idr can be solved from Equation (25). If the machine isfed by current source, iqs, ids and are independent. Thenthe dependent variables Vsq,Vsd, iqr and idr can be solvedfrom Equation (25). The speed in Equation (25) cannotnormally be treated as a constant. It can be related to thetorques as

(26)

Where TL = load torque, J = rotor inertia, and =mechanical speed. Often, for compact representation, themachine model and equivalent circuits are expressed incomplex form [3]. Multiplying Equation (14) by j andadding with Equation (13) gives.

(27)Or

(28)Similarly, the rotor equations (17)-(18) can be combined torepresent

qdrreqdrqdrrqdr jdtdiRV )( (29)

Where Vqdr=0. Therefore, the steady-state equationscan be derived as(30)

(31)If the parameter Rm is neglected. We know that

sin223

rme IPT

(32)From Equation (32), the torque can be generally

expressed in the vector form as(33)

drqmqrdme IiPT

223 (34)Some other torque expressions can be derived easily

as follows:

sqs

sqss

sqs dt

dIRV

sqs sds

dseqsqssqs dtdIRV

0r

dreqrqrrqr dtdiRV

drreqrqrrqr dtdiRV )(

qrredrdrrdr dtdiRV )(

)( qrqsmqslsqs iiLiL

dr

qr

ds

qs

rrrremmre

rrerrmrem

mmessse

memsess

dr

qr

ds

qs

iiii

SLRLSLLLSLRLSL

SLLSLRLLSLLSLR

VVVV

)()()()(

re

e

r

dtdJPTdt

dJTT rLmLe 2m

)()()( dsqsedsqsdsqssdsqs jjjdtdjiiRjVV

qdsreqdsqdssqds jdtdiRV )(

sesss jIRV rer

r jISR 0

rme IxPT

223



dsqmqsdme IiPT

223 (35)

dsqsqsdse IiPT

223 (36)

)(223

qrdsdrqsme iiiiLPT

(37)

)(223

drqrqrdre IiPT

(38)Equations (25), (26), and (37) give the complete

model of the electro-mechanical dynamics of an IM insynchronous frame. Fig 4 shows the block diagram of themachine model along with input voltage & output currenttransformation [2, 8] and resolving variables into dqecomponents. Renewable energy based water supply systemis one of the application [57-74]. In irrigation and drinkingwater supply, mostly we are using induction motors; hencestudy of control of induction motor is necessary.

4. CONTROL METHODSStator flux linkage is estimated by integrating the

stator voltages. Torque is estimated as a cross product ofestimated stator flux linkage vector and measured motorcurrent vector [75, 76]. The estimated flux magnitude andtorque are then compared with their reference values. If

either the estimated flux or torque deviates from thereference more than allowed tolerance, the GTO of thevariable frequency drive are turned off and on in such a waythat the flux and torque will return in their tolerance bandsas fast as possible. Thus DTC is one form of the hysteresisor bang-bang control. This control method implies theproperties of the control: Torque and flux can be changedvery fast by changing the references, The step response hasno overshoot, No coordinate transforms are needed, allcalculations are done in stationary coordinate system, Noseparate modulator is needed, the hysteresis control definesthe switch control signals directly [3, 75, 76], and There areno PI current controllers. Thus no tuning of the PI isrequired.

However, by controlling the width of the tolerancebands the average switching frequency can be kept roughlyat its reference value [2, 3]. This also keeps the current andtorque ripple small. Thus the torque and current ripple are ofthe same magnitude than with vector controlled drives withthe same switching frequency. Due to the hysteresis controlthe switching process is random by nature. Synchronizationto rotating machine is straightforward due to the fastcontrol; just make the torque reference zero and start theinverter [2, 3, 75, 76]. The flux will be identified by the firstcurrent pulse. Typically the control algorithm has to beperformed with 10 - 30 microseconds or shorter intervalsbecause of the simplicity of the algorithm.

Fig 4. Synchronously rotating frame machine models with input voltage and output current transformations.



Fig 5: Block diagram of the induction motor drive system based on DTC scheme.The DTC method performs very well even without

speed sensors [3]. However, the flux estimation is usuallybased on the integration of the motor phase voltages [75,76]. Due to the inevitable errors in the voltage measurementand stator resistance estimate the integrals tend to becomeerroneous at low speed. Thus it is not possible to control themotor if the output frequency of the variable frequencydrive is zero. However, by careful design of the controlsystem it is possible to have the minimum frequency in therange 0.5 Hz to 1 Hz that is enough to make possible to startan IM with full torque from a standstill situation. A reversalof the rotation direction is possible too if the speed ispassing through the zero range rapidly enough to preventexcessive flux estimate deviation [77, 78]. If continuousoperation at low speeds including zero frequency operationis required, a position sensor can be added to the DTCsystem [77-79].

4.1. VIEW OF DIRECT TORQUE CONTROLIn principle the DTC method selects one of the six

nonzero and two zero voltage vectors of the inverter on thebasis of the instantaneous errors in torque and stator fluxmagnitude [13, 76]. In spite of its simplicity, DTC allowsgood torque control in both steady and transient state. Itsmain characteristic is the good performance, obtainingresults as good as the classical vector control. Fig 5. Showsthe Block diagram of the IM drive system based on DTCscheme [3, 75, 76]. DTC method still required furtherresearch in order to improve the motors performance, aswell as achieve a better behavior regarding environmentcompatibility (Electro Magnetic Interference and Energy),that is desired nowadays for all industrial applications.

4.2 CLASSICAL DIRECT TORQUE CONTROLClassic DTC makes use of hysteresis comparators

with torque and stator flux magnitude errors as inputs todecide which stator voltage vector is applied to motorterminals. The complex plane is divided in six sectors, and aswitching table is designed to obtain the required vectorbased on the hysteresis comparators outputs [3, 4]. Due tofast time constants of stator dynamics it is very difficult tokeep machine torque between the hysteresis bands. This cando either by increasing the sampling frequency as in, thusincreasing switching frequency, commutation losses andcomputation requirements, or using multilevel converters.The use of hysteresis comparators in classic DTCimplementations give rise to variable switching frequency(VSF), which depends on rotor speed, load, sample

frequency, etc. VSF may excite resonant dynamics in theload and hence constitute a serious drawback of DTC.

Generally there are two methods to reduce the torqueand flux ripple for the DTC drives. One is multi levelinverter; the other is space vector modulation (SVM) [77,78]. In the first method, the cost and the complexity will beincreased, in the second method, the torque ripple and fluxripple can be reduced, however the switch frequency stillchanges. In the next section a fuzzy approach is given toreduce torque ripple [8]. This goal is achieved by the fuzzycontroller which determinates the desired amplitude oftorque hysteresis band.

4.3 TORQUE EXPRESSIONS WITH STATOR ANDROTOR FLUXES

The torque expression for induction machine can beexpressed in vector form as,

223

sse IPT

(39)Where sdssqss j and sdssqss jiiI .

In this equation, sI is to be replaced by rotor flux r . Inthe complex form, s and r can be expressed asfunction of currents as,

rmsss ILIL (40)smrrr ILIL (41)

From equations 39, 40 and 41:

srsr

me LL

LPT '223

(42)

That is, the magnitude torque is

sin223

' srsr

me LL

LPT

(43)Where is the angle between the fluxes, indicating

the vectors s , r , and sI for positive developedtorque. If the rotor flux remains constant and stator flux ischanged incrementally by stator voltage sV as shown and



the corresponding change of angle is , the incrementaltorque eT expression is given as sin22

3'

ssr

srm

e LLLPT (44)

4.4 CONTROL STRATEGY OF DTC

Fig 6: In principle the DTC method selects one of the six nonzero and two zero voltage

Fig 7: Inverter voltage vectors and corresponding stator flux variation in time t.

Table1: Switching table of inverter voltage vectors.H HTe S(1) S(2) S(3) S(4) S(5) S(6)

11 V2 V3 V4 V5 V6 V10 V0 V7 V0 V7 V0 V7-1 V6 V1 V2 V3 V4 V5

-11 V3 V4 V5 V6 V1 V20 V7 V0 V7 V0 V7 V0-1 V5 V6 V1 V2 V3 V4

Table2: Flux and Torque variations due to applied voltagevector in.

Voltagevector

V1 V2 V3 V4 V5 V6 V0 or V7s 0Te

Block diagram of the IM drive system based on DTCscheme is shown in Fig 6. The speed control loop and theflux program as a function of speed are shown as usual andwill not be discussed. The command stator flux * s and



torque *eT magnitudes are compared with the respectiveestimated values and the errors are processed throughhysteresis-band controllers, as shown [2]. The flux loopcontroller has two levels of digital output according to thefollowing relations:

for1 HBEH (45) HBEH for1 (46)

Where HB2 = total hysteresis-band widthcontroller. The circular trajectory of the command fluxvector * s with the hysteresis band rotates in an anti-clockwise direction as shown in Fig 7. The actual stator flux

s is constrained within the hysteresis band and it tracksthe command flux in a zigzag path. The torque control loophas three levels of digital output, which have the followingrelations [2]:

TeTeTe HBEH for1 (47)TeTeTe HBEH for1 (48)

for0 TeTeTeTe HBEHBH (49)The feedback flux and torque are calculated from the

machine terminal voltages and currents. The signalcomputation block also calculates the sector number S(k) inwhich the flux vector s lies. There are six sectors (each /3angle wide), as in Fig 7(a). The voltage vector table block inFig 8 receives the input signals ,, TeHH and S(k)andgenerates the appropriate control voltage vector (switchingstates) for the inverter by lookup table, which is shown intable 1 (the vector sign is deleted) [2, 3]. The invertervoltage vector and a typical s are shown in Fig 7(b).Neglecting the stator resistance of the machine, we canwrite.

)( ss dtdV (50)Or

. tVss (51)Which means that s can be changed incrementally

by applying stator voltage sV for time increment t. Theflux increment vector corresponding to each of six invertervoltage vectors is shown in Fig 7. The flux in machine isinitially established to at zero frequency (dc) along thetrajectory OA shown in Figure 7. With the rated flux, thecommand torque is applied and the *s vector startsrotating [2, 3].

Table 1 applies the selected voltage vector, whichessentially affects both the torque and flux simultaneously[2, 3]. The flux trajectory segments AB, BC, CD and DE bythe respective voltage vectors 4343 and,,, VVVV areshown in Figure 7(a). The total and incremental torque dueto s are explained in Fig 7(b). Note that the stator fluxvector changes quickly by, but the r change is verysluggish due to large time constant Tr. Since r is morefiltered, it moves uniformly at frequency e, whereas smovement is jerky. The average speed of both, however,remains the same in the steady-state condition. Table2summarizes the flux and torque change (magnitude anddirection) for applying the voltage vectors for the location of

s shown in Fig 7(b) [2, 3]. The flux can be increased bythe 621 and,, VVV vectors, whereas it can be decreasedby the 543 and,, VVV vectors [2]. Similarly, torque isincreased by the 432 and,, VVV Vectors, but decreasedby the 651 and,, VVV vectors. The zero vectors (V0 orV7) short-circuit the machine terminals and keep the fluxand torque unaltered. Due to finite resistance (Rs) drop, thetorque and flux will slightly decrease during the short-circuitcondition.

Consider for example, an operation in sector S(2)as shown in Fig 7(a), where at point B, the flux is too highand the torque is too low; that is, 1H and

1TeH . From table 1, voltage V4 is applied to theinverter, which will generate the trajectory BC. At point C,

1H and 1TeH and this will generate theV3 vector from the table. The drive can easily operate in thefour quadrants, and speed loop and field-weakening controlcan be added, if desired [80]. The torque response of thedrive is claimed to be comparable with that of a vector-controlled drive [2].

5. FUZZY APPLICATIONSoft computing techniques can apply for nonlinear

system [80-83]. A fuzzy controller is introduced to allow theperformance of DTC scheme in terms of flux and torqueripple to be improved [84-87]. The speed regulators areconventional PI controllers (CPIC), which requires precisemath model of the system and appropriate value of PIconstants to achieve high performance drive. Therefore,unexpected change in load conditions or environmentalfactors would produce overshoot, oscillation of the motorspeed, oscillation of the torque, long settling time andcauses deterioration of drive performance [84-87].



Figure 8: Direct torque and flux control block diagram.

Fig: 9. Two fuzzy based DTC-SVM modelThe selected voltage vector is applied for the entire

switching period, and thus allows electromagnetic torqueand stator flux to vary for the whole switching period. Thiscauses high torque and flux ripples. To overcome theseproblems in DTC, two fuzzy controllers are widely analyzedin literature [2, 3]. Those are:

1. Fuzzy PI Controller (FPIC) to achieve precisionspeed control.2. Fuzzy Logic Duty Ratio Control (FLDRC) tominimize torque & flux ripple.When Fuzzy Logic is used for the on-line tuning of

the PI controller, it receives scaled values of the speed errorand change of speed error. Its output is updating in the PIcontroller gains based on a set of rules to maintain excellentcontrol performance even in the presence of parametervariation and drive non-linearity [87]. Block diagram of themethod with close-loop torque and flux control in stator fluxcoordinate system is presented in Fig 9. The output of the PI

flux and torque controllers can be interpreted as thereference stator voltage components Vsx, Vsy are the statorflux oriented coordinates (x y). Design of Fuzzy LogicController is depend on Selection of input variables,Selection of output variable, Number of fuzzy controllers,Selection of Membership functions and Selection ofdefuzzification. Here, we had taken two fuzzy controllersfor torque and flux, triangular membership and centroiddefuzzification.

FPIC does dynamically adjusts the gains kP and kI toensure the stability of system over wide torque-speed range,Swift speed response, Less overshoot and, Extremely smallsteady state errors.

FLDRC does Minimizes torque & flux rippleseffectively, increased efficiency, Low acoustic noise,Operates at a lower switching frequency compared to theexisting methods, and Reduces computation burden.



By using these two fuzzy controllers we achievegood speed and torque responses. After outputs of thesefuzzy controllers (after defuzzification) we generate Vsx andVsy, again converted this X-Y coordinate components to -components. By using this values generate 6 pulses with thehelp of Space Vector Modulation.).

CONCLUSIONThe paper has presented a DTC drive with fuzzy

controller. This controller determinates the desiredamplitude of torque hysteresis band. The main advantage isthe improvement of torque and flux ripple characteristics atany speed region; this provides an opportunity for motoroperation under minimum switching loss and noise.

The two-fuzzy based DTC-SVM-IMD system,thereby dramatically reducing the torque ripple. A fuzzycontroller seems to be a reasonable choice to evaluate theamplitude of torque hysteresis band according to the torqueripple level. Fuzzy-PI Controller to achieve precision speedcontrol and Fuzzy Logic Duty Ratio Control is used tominimize torque & flux ripple. When Fuzzy Logic is usedfor the on-line tuning of the PI controller, it receives scaledvalues of the speed error and change of speed error.

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1. direct torque control of induction motor with fuzzy controller a review

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