IJESC: Vol. 4, No. 1, January-June 2012, pp. 35–42

* Department of Electrical and Electronics, AppoloEngineering College, Anna University, ChennaiE-mail: sowmmeee@gmail.com

Sowmmiya U.*

Abstract : This paper presents an efficient implementation scheme for the ANN based closed-loop speed control of aninduction motor incorporating ‘Space Vector Pulse Width Modulation (SVM)’. The neural network is trained to estimatethe voltage at different conditions. To provide the required data for the training, a simulation program is written. Speedcontrol is required to regulate the speed of the motor by varying the input voltage of the inverter. Space Vector Modulation(SVM) is an algorithm for the control of Pulse Width Modulation (PWM). SVM gives better harmonic response andhigher efficiency compared to pulse width modulation techniques.

Keywords: ANN, Space Vector Modulation, Speed Control, Three Phase Inverter

1. INTRODUCTION

Majority of the industrial drives use electric motors, sincethey are controllable and readily available. In practice,most of these drives are based on AC induction motorbecause these motors are rugged, reliable, and relativelyinexpensive. Three phase induction machine is mostwidely used in industry.

When power is supplied to an induction motor at therecommended specifications, it runs at its rated speed.However, many applications need variable speedoperations. For example, a washing machine may usedifferent speeds for each wash cycle. Historically,mechanical gear systems were used to obtain variablespeed. Recently, electronic power and control systemshave matured to allow these components to be used formotor control in place of mechanical gears. Theseelectronics not only control the motor’s speed, but canimprove the motor’s dynamic and steady statecharacteristics. In addition, electronics can reduce thesystem's average power consumption and noisegeneration of the motor.

Induction motor control is complex due to itsnonlinear characteristics. While there are differentmethods for control, Variable Voltage VariableFrequency (VVVF) or V/f is the most common methodof speed control.

The use of Space Vector Modulation (SVM) invertereliminates the drawback of practical controllers partially.

SVM has the advantage of lower THD in addition to thefeatures of complete digital implementation by a singlechip microprocessor. Thus, SVM is advantageous overphase control and PWM.

Traditionally PI controllers are used in inverters.They suffer from certain disadvantages. Recentdevelopment in artificial neural network (ANN)technology has made it possible to train neural networksfor non linear loads. ANN represent simplified model ofthe human brain. It consists of large number of neuronswhich have weighted interconnections. Since, ANN arehighly parallel and distributed networks, they areextremely fault tolerant and insensitive to noise.

Various formulae involved and the methodology toproduce the gate pulses is explained [1]. The simulationof ANN for the energy saving of a single phase InductionMotor is discussed. In this, various parameters from themotor are taken and are trained to meet the goal [2].

Induction motor model is developed based onKrause's model in a step by step approach. Each block isdeveloped and indirect vector control is implemented. Inthis scheme, Space Vector Modulation is used [3]. TheSVM approach to an Induction Motor is discussed. SpeedControl implementation in Induction Motor was clearlyexplained [4]. An efficient implementation scheme forthe closed loop speed control of an induction motor withconstant v/f control, slip regulation and SVM techniqueis briefly explained [5]. The neural network controlledSpace Vector Modulator with vector control isimplemented and the strategy is explained [6].

The generalized model of the three phase inductionmotor using SIMULINK is discussed [7].Various PWM

36 Sowmmiya U.

techniques that can be used for three phase voltagecontrolled VSI and the three space vector pulse widthmodulation schemes called seven segment SVM, fivesegment SVM, three segment SVM and the basicprinciple of SVPWM are discussed [8,9]. It involves theconventional technique of Space Vector Modulation. Acontrol scheme to implement the energy-savings of three-phase induction motors when they operate under long-term light load or small duty ratio load is explained [10].This scheme is based on the principle of variable voltagecontrol (VVC) at constant speed.

In the above literature, the speed control scheme forthree phase induction motor drive is not implementedusing SVM. In this paper, the SIMULINK model for theANN based speed control scheme of SVM fed inductionmotor is developed and the results are presented.

2. SVM INVERTER FED INDUCTIONMOTOR DRIVE

SVM is quite different from PWM methods. SVM treatsthe inverter as a single unit; the inverter can be driven toeight unique states. The block diagram of ANN basedvoltage control of SVM inverter fed induction motor driveis shown in Figure 1.

3. REALIZATION

Realization of SVM involves

Step 1: Determination of Vd, Vq, Vref and angle ( )

Step 2: Determination of time duration T0, T1 and T2

Step 3: Determination of the switching time of eachtransistor

Three phase to two phase conversion is done withPark’s transformation

Figure 1: Block Diagram of ANN Based Speed Control ofSVM Inverter Fed Induction Motor Drive

The three phase inverter has six power switches S1

to S6. The various parameters {Vab, Vbc, Vca, (rotorspeed), Is(stator current, Ir(Rotor current), conventionalcontroller parameters} are measured and are trained toachieve the goal. The output of the neural network is thegiven to the SVM controller. The control circuit producesthe driving pulses. During each time, the weights andbiases of the NN are updated using the back propagationalgorithm. SVM technique approximates the referencevoltage Vref by a combination of the eight switchingpatterns (V0 to V7).

Figure 2: Voltage Space Vectors and Its Components in(d, q)

From the fig 2,

Vd = Van – Vbn . cos60 – Vcn . cos60 (1)

Vq = 0 + Vbn . cos30 – Vcn . cos30 (2)

The angle between Vd and Vref is calculated as

= tan–1(vq/vd) (3)

Figure 3: Reference Vector as a Combination ofAdjacent Vectors at Sector 1

The switching time duration at any sector can becalculated as

Neural Network Based Speed Control Scheme for Three Phase SVM Inverter FED Induction Motor Drive Systems 37

| |1 3. .

sin coscos sin

3 3

VrefT Tz

n nVdc

| |2 3. .

cos sin( 1)sin cos( 1)

33

VrefT Tz

nn

Vdc

T0 = Tz – (T1 + T2)

(where, n = 1 through 6 (sector 1 to 6))

The switching time calculator block is shown inFigure 4.

The induction motor model consists of the followingblocks

• o-n conversion block

• abc-syn conversion block

• syn-abc conversion block

• Induction machine d-q model block.

According to this model the modeling equations inthe flux linkage form are as follows

dFqs/dt = b[vqs – ( e/ b) * fds + Rs/xls (fmq + fqs)] (7)

dFds/dt = b[vds + ( e/ b) * fqs + Rs/xls (fmd + fds)] (8)

dFqr/dt = b[vqr + ( e – r/ b) * fdr + Rr/xlr (fmq – fqr)](9)

dFdr/dt = b [vdr + ( e – r/ b) * fqr + Rr/xlr(fmd – fdr)](10)

Fmq = xml * [fqs/xls + fqr/xlr] (11)

Fmd = xml * [fds/xls + fdr/xlr] (12)

IqS = 1/xls[fqs – fmq] (13)

IdS = 1/xls[fds – fmd] (14)

Iqr = 1/xlr[fqr – fmq] (15)

Idr = 1/xlr[fqr – fmd] (16)

Te = [3/2] * [P/2] * [1/ b] * [fdsiqs – fqsids](17)

Te – TL = [J] * [2/P] * [d r/dt] (18)

For a squirrel cage induction motor Vdr and Vqr aregenerally set to zero. An induction machine can berepresented with the differential equations as in Equations7-18. To solve these equations, they are rearranged inthe state-space form X = Ax + B where x = [fqs fdr fqr fdrwr]

T is the state vector. State-space form can be achievedby inserting equations 11 and 12 in equations 7-20 andcollecting the similar terms together so that each state

Figure 4: Switching Time Calculator

The switching time is calculated to know the timingof the voltage vector applied to the motor. The block inputis the sector in which the voltage vector lies. The timingsequence obtained is compared with the triangle signaland the gate timing signals to activate the inverter switchesat the proper time are generated.

4. MODELING OF THREE PHASEINDUCTION MOTOR

The induction motor model is designed using Krause’smodel. It is one of the most popular induction motormodels. The inputs of induction machine are three-phasevoltages, their fundamental frequency. The inductionmachine d-q or dynamic equivalent model is shown inFigure 5. From this figure various equations required formodeling the induction motor are derived. The outputson the other hand are the three phase currents and theelectrical torque.

Figure 5: Dynamic or d-q Model of Induction Machine

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derivative is a function of only other state variables andmodel inputs. Then, the modeling equations of squirrelcage induction motor in state-space are given by equations19-23.

dFqs/dt = b[vqs – ( e/ b) * fds + Rs/xls(Xml*/Xlr*fqr

+ (xml */xls – 1) fqs)] (19)

dFds/dt = b [vds – ( e/ b) * fqs + Rs/xls(Xml * /Xlr * fdr

+ (xml*/xls – 1)fds)] (20)

dFqr/dt = b[vqr + ( e – r/ b) * fdr + Rr/xlr

(Xml * /Xlr * fqr + (xml * /xls – 1)fqr)] (21)

dFdr/dt = b[vdr + ( e – r/ b) * fqr + Rr/xlr

(Xml*/Xlr*fqr + (xml*/xls – 1)fqr)] (22)

dwr/dr = (P/2J) (Te – TL) (23)

A. o-n Conversion Block

This block is required for an isolated neutral system,otherwise it can be bypassed. The transformation isimplemented as stated in Equation 24.

2 1 13 3 31 2 13 3 31 1 23 3 3

Van Vao

Vbn Vbo

Vcn Vco (24)

This is implemented using a gain block inSIMULINK, which contains the above transformationin equation 24. The inputs to this block are Vao,Vbo,Vcoand outputs are Van, Vbn, Vcn. Such a block is shown inFigure 6.

1 0 0

1 10

3 3

ansqs

bnsds

cn

vv

vv

v(25)

Vqs = vqss cos e – vds

s sin e (26)

Vds = vqss sin e + vds

s cos e (27)

where, the superscript “s” refers to stationary frame.Equation 25 is implemented using gain block andEquation 26, 27 contains unit vectors thereforeimplemented using sum and product blocks as shown inFigure 7.

Figure 6: o-n Conversion Block Implementation UsingSIMULINK

B. abc-syn Conversion Block

To convert three-phase voltages to voltages in the twophase synchronously rotating frame, they are firstconverted in to in to two-phase stationary frame usingEquation 25. Then they are converted from stationaryframe to the synchronously rotating frame usingEquations 26 and 27.

Figure 7: Implementation of abc-syn Block UsingSIMULINK

C. Induction Motor d-q Model Block

In this block the various equations required for inductionmotor model are implemented in different blocks. Fluxlinkage state equations are required to calculate othervariables. To have access at each point of the model,implementation using discrete models is preferred. Theflux linkages equations are implemented usingSIMULINK as shown in Figure 8.

Figure 8: Implementation of Flux Linkage StateEquations Using SIMULINK

Once the flux linkages are calculated, the rest ofequations can be implemented easily without anydifficulty. After calculating flux linkages stator and rotord and q currents.Then using these currents electrical

Neural Network Based Speed Control Scheme for Three Phase SVM Inverter FED Induction Motor Drive Systems 39

torque and rotor speed are calculated.The entire inductionmotor d-q model block is shown in Figure 9.

In open loop speed control, the load is varied from8Nm to 3 Nm and the output speed is not regulated. Itvaries with the variations in the load and the results areshown in Figure 12. For a 3Nm load torque, the speed is1294rpm and for 8Nm load torque, the speed is 811rpm.The speed can be maintained at the reference valueirrespective of the load torque with closed loop control.

Figure 9: Induction Machine d-q Model BlockImplementation Using SIMULINK

D. Syn-abc Conversion Block

This block is opposite of the abc-syn conversion block.

Iqss = iqscos e + idssin e (28)

Idss = – iqssin e + idscos e (29)

The syn-abc conversion block using simulinkimplements the Equations 28 and 29 is shown inFigure 10.

Figure 10: Implementation of syn-abc Conversion BlockUsing SIMULINK

5. OPEN LOOP SPEED CONTROL OF THREEPHASE INDUCTION MOTOR USING SVM”

The open loop speed control of an induction motor isshown in Figure 11.

Figure 11: Open Loop Speed Control of an InductionMotor

Figure 12: Speed Response of the Open Loop Control ofan Induction Motor

6. NEURAL NETWORK CONTROLLER

Neural networks are simply a class of mathematicalalgorithms, since a network can be regarded as a graphicnotation for a large class of algorithms. The hidden layertransfer function is log-sigmoid or tan-sigmoid and theoutput transfer function is usually linear. Here, the tan-sigmoid is used as the hidden layer transfer functionfollowed by the linear transfer function for the outputlayer. Equations 30 and 31 show these transfer functions.

Y = 1( . )1

(1 )jiV X Be (30)

O = Wkj . Y + B2 (31)

In the above equations, X is the input vector, Y andO are the output vectors of the hidden layer and outputlayer respectively. Vji, Wkj are the weight matrices and B1and B2 are the bias vectors. The neural network systemto estimate the driving pulses of SVM inverter fed threephase Induction Motor is shown in Figure 13.

40 Sowmmiya U.

To provide the required data to train the neuralnetwork, a simulation program is written. Using thisprogram, 1, 00, 000 sets of training pattern are obtained.These patterns are used for training the neural networkusing error back propagation algorithm. After trainingthe neural network successfully, the program is replacedby neural network controller and the simulation isperformed. Output of the neural network controller is usedto generate the driving pulses of the SVM inverter.

7. CLOSED LOOP SPEED CONTROL OF THREEPHASE INDUCTION MOTOR USING SVM

To meet the requirement of constant speed control, neuralnetwork based closed loop operation is performed for thedesired value of the speed. The NN based closed loopspeed control of the induction motor drive system isshown in Figure 14. Here, the speed is compared withthe reference value.

are obtained. These patterns are used for training theneural network, using error back propagation algorithm.

Figure 13: Neural Network System to Estimate theDriving Pulses of SVM Inverter

Figure 14: Closed Loop Speed Control of an InductionMotor

The error from the comparator is given to the PIcontroller. After tuning the parameters of the PI controller,various sets of training pattern for the line voltages, rotorspeed, rotor current, stator current, PI input and PI output

Figure 15: Subsystem of the Closed Loop Scheme

The subsystem of the closed loop scheme and thesubsystem holding the neural controller are shown inFigure 15 and Figure 16 respectively. Various parameters(line voltages, rotor speed, rotor current, stator current,PI input, PI output) are trained and the goal is achieved.After training the neural network successfully, theprogram is replaced by a neural network controller andthe simulation is performed. The internal structure of thetrained neural-network used for the simulation is shownin Figure 17.

Figure 16: Subsystem Showing the Neural Controller

Figure 17: Internal Structure of the Trained NeuralNetwork

Neural Network Based Speed Control Scheme for Three Phase SVM Inverter FED Induction Motor Drive Systems 41

Speed is transformed to voltage by suitabletransformations. By using the voltage and frequency thethree phase voltages are produced. In SVM control, threephase voltages are converted to two phase voltages. Withthe two phase voltages, alpha is determined. With thehelp of switching time calculator, the switching signalsare generated for each switch and the same is shown inFigure 18 and are fed to the inverter switches. Based onthe reference value, the desired speed is obtained. Thus,the speed is regulated. The gate pulses of the upperswitches of the inverter are shown in Figure 18.

From the figure, it is observed that the output speedis closer to the reference value.

Figure 18: Gate Pulses for the Upper Switches

The speed response with PI controller and neuralnetwork controller are shown in Figure 19 and 20respectively. In order to meet the requirement of constantspeed control, closed loop operation is performed for thedesired value of the speed according to the need.

Figure 19: Speed Response of PI Controller

Figure 20: Speed Response of Neural NetworkController

Table 1Comparison of Neural Network and PI Controller based

Induction Motor Drive Systems

Parameters Neural Network PI Controller

Rise Time (sec) 0.22 0.84

Settling Time (sec) 0.27 0.96

Peak Overshoot (%Mp) 1.968 4.093

From the table, it can be seen that the neuralnetwork has lesser peak overshoot, reduced rise timeand settling time.

8. RESULTS AND CONCLUSIONS

From the results, it is observed that SVM has improvedfundamental component and reduced THD. Three phaseInduction Motor is modeled and the same is used for thesimulation.

With the open loop control, the output speed is notregulated and it varies with the fluctuations in the appliedload. By implementing the closed loop control scheme,the output speed is regulated. In order to meet the constantspeed requirement, ANN based closed loop control isproposed. This scheme regulates the output speed.

The comparison is made between PI and NeuralNetwork Controllers and it is observed that, NeuralNetwork Controller gives better results. Thus, with theANN based SVM fed inverter, speed of a three phaseinduction motor is effectively controlled with reducedharmonic content.

REFERENCES

[1] Jin-Woo-Jung, (2005). “Space Vector PWM Inverter’Mechatronics Systems Laboratory”, DECE, The OhioState University.

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[2] Jamuna V. and Rama Reddy S. (2009). “ANNControlled Energy Saver for Induction Motor Drive”,Journal of Electrical Engineering, Romania, 8, Edition4, pp 70-77.

[3] Leon M. Tolbert and Burak Ozpineci (2005). “SimulinkImplementation of Induction Machine Model - AModular Approach”, pp. 728-734.

[4] Linga Swamy R. and Satish Kumar P. (2008). “SpeedControl of Space Vectored Modulated Inverter DrivenInduction Motor”, Proceedings of the International MultiConference of Engineers and Computer Scientist,Volume 2.

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[7] Shi K.L. Chan T.F. Wong Y.K. and Ho S.L. (1999).“Modeling and Simulation of Three Phase InductionMotor Using Simulink”, Int. J. Electrical EngineeringEducation, 36, pp. 163-172.

[8] Trzynadlowski M., (1996). “An Overview of ModernPWM Techniques for Three-phase, Voltage-controlled,Voltage-source Inverters”, in Proc. the IEEEInternational Symposium on Industrial Electronics,Warsaw, Poland, 1996, pp. 25-29.

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[10] Xue X.D. and Cheng K.W.E. (2006). “An Energy-savingScheme of Variable Voltage Control for Three-PhaseInduction Motor Drive Systems”, 2nd InternationalConference on Power Electronics Systems andApplications, pp. 241-243.