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TIME BASE FIRING PULSE DELAY CONTROL FOR IMPROVING

SINGLE PHASE INDUCTION MOTOR SPEED PERFORMANCE

USING FUZZY LOGIC CONTROL

Dirman Hanafi1, MohdAzkar Sidik2, Mirza Zoni3, Hidayat4

1,2Advanced Mechatronic Research Group (ADMIRE), Faculty of Electrical and Electronic Engineering,

UniversitiTun Hussein Onn Malaysia, BatuPahat, Johor, Malaysia

3,4Electrical Engineering Department, Faculty of Industrial Technology,

Universitas Bung Hatta, Padang, Indonesia E-Mail: [email protected]

ABSTRACT

This paper focuses on the fuzzy logic controller design for improving the single phase induction motor speed control performance. The controller strategy is done through phase angle control method. The phase angle is controlled by controlling the time base firing pulse angle delay of the triac. Based on experimental results, the fuzzy logic controller is a suitable controller to improve the single phase induction motor speed because it able to reduce the rise time, settling time, peak time and overshoot response to 0.10s, 0.17s, 0.29s and 0.09 % OS respectively. Then compares with the Proportional Integral Derivative (PID) controller responses, the fuzzy logic controller responses are better with the rise time (Tr), the settling time (Ts), the peak time (Tp) and the overshoot (% OS) are 0.08s, 0.08s, 0.05s and 0.004% smaller than PID controller.

Keywords: Single phase induction motor speed control Fuzzy logic controller Time base firing pulse delay

INTRODUCTION

Single phase A.C supply plays important roles in electrical usage because it is commonly used for general electrical purpose in domestic or commercial applications where three phase power supply is not available. Based on this supply, single phase induction motors become one of the most widely used for numerous domestic and industrial applications like home appliances, industrial control system, and automation because of their it offer lower maintenance, reliable and smaller motor size. Single phase induction motor has been covered most servo application in robotics, machine tools and positioning devices.

Normally, it has two winding, main and auxiliary.An auxiliary winding has more turns than main winding (Yo, 2000). Traditional single phase induction motor run directly from AC voltage supply at one speed only. The improvement in ac motor control enable the speed of single phase induction motor to be run on variable speed, which can reduce power consumption, acoustic noise and mechanical vibration. The critical aspect in AC motoris the role of the researcher or engineer to control the speed of an AC motor that being used. Traditionally, the AC motor is controlled by two classical strategies, vector control and torque control. Vector control and direct torque control are the two classical strategies to control synchronization and asynchronous of induction motor (Shenand Dai, 2010).

As mantion previous, the single phase induction motor is widely use in our daily application because of their ability to operate from a single phase power supply.

Since it is impossible to reliably operate at unstable range, simple voltage control (open loop control) is limited to controlling in a narrow range. The speed of the single phase AC induction motor can be adjusted either by applying the proper supply voltage amplitude and frequency (called volts per hertz) or by the changing of supply voltage amplitude with constant frequency (slip control) (Stekl, 2003). To make it is possible to operate reliably even in the unstable range, it is necessary to detect the rotational speed of the motor and use a voltage control mechanism (closed loop control) that reduces the speed error when compared to a set value (Shirataha, 2015).

The speed of induction motor can be control by controlling the voltage applied to the stator voltage. With the enhanced technology in power electronics, a number of semiconductor devices have been introduced in voltage control application. The use of solid state components like the triac for the control of ac drives have been widely used in recent years for several industrial and home applications (Emenike, et. al., 2011). The voltage applied to the stator winding of the single phase induction motor can be control to achieve the desired speed by controlling the firing angle of the triac that are used in this work.

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ISTEM DESI

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change o controlle Reference  Speed + Figu induction B. Desi Base compose Fuzzifica Defuzzif 1.

for this p (ce). The error (e) the refer motor (ω of error by provi single p change o the previ the chang (2) (3) 2. fuzzifica members change o following Linguist Value Negative Negative Medium Negative Small Zero Positive

of error (ce) a er is the time ba

Error (e)

Change of  Error (ce)

ure-4. Block d

n motor speed

ign of Fuzzy L

ed on Figure ed based on

ation, Rule B fication.

Define input a The input var purpose are th e output variab variable is det rence speed (ω ω_act ). The ch

variable contr iding the info phase inductio of error (ce) is m

ious error and ge of error (ce)

Membership F The second st ation process to

ship for linguis The fuzzy se of error and firi

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g table.

Table-1

tic Notati

e Big NB

e NM

e NS

Z PS

and the outpu ase firing pulse

Fuzzy Logic  Controller Triac 

Feedback

diagram overall control using f

Logic Controll

-3, the fuzzy n 4 elemen

ase, Fuzzy In

and output vari riables of the f he error (e) and ble is the firing

termined by th ω_ref )and the ange of error ( ributes to the ormation abou nmotor speed measured by th

the current err ) are given by:

1

Function and L tep in the fuzz o convert crisp stic terms of fu ets and lingui ing angle delay

1. Input variable

ion Range [2000 -1500 -10 [1500 -500] [-1000 -5

[-500 0 5 [0 500 10

ut of the fuzzy e delay (α).

Firing Pulse

Single Phas Induction Motor

l the single pha fuzzy logic con

ler

y logic contro nts which ar nference Syste

ables fuzzy logic co d the change o g pulse delay ( he difference b e actual speed (ce) or the rate inference mec ut the change d. The value he difference b ror. The error

Linguistic Varia zy logic contro p input into de uzzy sets.

stic terms for y are elaborate

e error.

MF

2000

-000] Trap

1000 - Trian

500 0] Trian

500] Trian 000]] Trian y logic se     Motor  Speed  ase ntroller. oller is re the em and ontroller of error (α). The between d of the

change chanism of the of the between (e) and ables ol is the egree of

r error, d in the

pezoidal

ngular

ngular

[image:3.612.311.544.630.745.2]
(4)

Sm Po M Po

L V

N

N M N Sm Ze Po Po M Po

L V

Po Po M Po Sm Ze

N Sm N M N

in ou de

c

N

N

N

Z mall ositive Medium

ositive Big

Table-inguistic Value

Negative Big

Negative Medium Negative

mall ero

ositive Small ositive Medium

ositive Big

Table-3.

inguistic Value

ositive Big ositive Medium ositive mall ero

Negative mall Negative Medium Negative Big

3. Rule B Rule b nference proce utput. The tab evelop in this w

Table-4. Tria

e

ce NB

NB NB

NM NB

NS NM

Z NM

PM [5 15 PB [1 20

-2. Input variab

Notation R

NB [-1 NM

[-3 NS

Z [-PS [0 PM [3 1 PB [7

1

. Output variab

Notation R

PB [0 PM [0 0 PS [0

0 Z [0

0 NS [0

0 NM [0

0 NB [0

0

ase for the fuz based is a set ess to evaluate bulation of the works are as in

angular membe varia

NM NS

NB NM NM NM NM NS NS NS

500 1000 500]

1000 1500 000 2000]

ble change of e

Range

1500 1500 -125 -750] 1125 750 -375]

-750 -375 0]

-375 0 375] 0 375 750]]

375 750 125]

750 1125 500 1500]

ble firing pulse

Range

0 0 0.0015] 0 0.0015

.003]

0.0015 0.003 .0045]

0.003 0.0045 .006]

0.0045 0.006 .0075]

0.006 0.0075 .009]]

0.0075 0.009 .009]

zy logic contro of rules that e the input an

e fuzzy logic n table below.

ership function able

Z PS

NM NS NS NS NS ZE ZE PS

Triangular

Trapezoidal

error.

MF

Trapezoidal

Triangular

Triangular

Triangular Triangular Triangular

Trapezoidal

e delay.

MF

Triangular Triangular

Triangular

Triangular

Triangular

Triangular

Trapezoidal

oller

used in fuzzy nd decide the control rules

n for output

PM PB

NS ZE ZE PS PS PS PS PM

l

l

l

l

y e s

PS N

PM N

PB Z

4.

inference of the w represent

(4)

= valu =

C. Imp

controlle induction of triac is

Figur

1.

the firin When th the triac voltage v angle pu firing pu

time bas voltage i by Figure

NS NS NS ZE

ZE PS

Defuzzificatio The last pro e process outpu well-known met

ted as

ue in universe o degree of mem

plementation o

The Simulink er to control

n motor speed b s illustrated by

re-5. Fuzzy log

Firing pulse su The operation g pulse delay he pulse is ena and the single value is reduce ulse. Figure-6 i lse delay subsy

Figure-6. Tri

The subsystem se pulse angle

nput of the sin e-7.

ZE PS PS PS

PS PM

on Method ocess is fuzz

ut is converted thod is a centr

of discourse mbership relate

of the fuzzy log

k block diagram the speed o by controlling y Figure-5.

gic controller m

ubsystem n of the triac i y that connect abled, the curre

e phase induct ed by increase illustrate the S ystem of this p

iac firing pulse

m model to g e to the triac ngle phase indu

PS PM PM PM

PM PB

ification, whe d again into cris re of area (Co

d with

gic controller

m of the fuzz of the single the firing angl

model in Simul

s basically rel ted to the tria ent will flow t ion motor. Th

the delay of th imulink mode roject.

e subsystem.

generate the r gate to cont uction motor is

PM PB

PB

ere the sp. One oA) and

model

zy logic phase le delay

link.

ated on ac gate. through e stator he triac l of the

(5)

sin

in

A

R

ba Th is fig

Figu

2. Single connec The co ngle phase ind

Figure-8. Sim

The dat n this test are de

Table-5. Sin

Pa

Reference P Voltage

Fre Stator R Stator In

Rotor R Rotor In Main winding Auxiliary win Auxiliary wind

RESULT AND

The tw ased on the sin he speed refer

1500 rpm. Th gure below:

ure-7. Pulse ge

phase inducti ction.

onnection circ duction motor i

mulink model f motor wi

ta of the single escribed in tab

ngle phase indu

arameter

e Speed ( ) Power

Supply ( ) equency Resistance, Rs

nductance, Ls Resistance, Rr

nductance, Lr g mutual induct nding resistance ding inductanc

ANALYSIS

wo controllers ngle phase ind rence for the s he best respons

enerating mode

ion motor and

cuit between s represented b

for single phas th triac.

e phase inducti ble below.

uction motor p

) 1

0

2 7 4

5

tance 0

e, RS 4

ce, LS 8

s are used in duction motor

ingle phase in e from each co

el.

d triac circuit

triac and the by Figure-8.

se induction

ion motor used

arameters.

Value

500 rpm 0.25 HP

240V 50 Hz .02 Ohm 7.4 mH .02 Ohm 5.6 mH 0.1772 H

.12 Ohm 8.5 mH

n experiments data previous. nduction motor ontroller are as t

e

d

s . r s

F

Figur

paramete

Table-Pa

Ri

Settl

Pea

Percen

controlle The fuzz time and

CONCL

controlle controlle time (T_ overshoo respectiv controlle motor.

REFERE Chee-Ho Debnach Fan Mo Internatio

Figure-9. The P

re-10. The fuzz

The compariso ers are elaborat

-6. Comparison Logic Cont

rameter

se Time

ling Time

ak Time

nt Overshoot

Based on data er gives better zy logic contro also lower ove

LUSIONS

From the exp er produced er. The fuzzy _r), settling tim ot (% OS), they vely. Therefo er is a suitable c

ENCE oe, P., Jer-Vui, h, N. (2013). D otor Controller

onal Journal of

PID controller

zy logic contro

on of the two c ted in below.

n between PID trol response pa

PID FL

0.18s 0. 0.25s 0. 0.34s 0.2 0.1% 0.09

a in Table 6 ab r performance oller has faster

ershoot.

eriments show better respon logic controll me (T_s), peak y are 0.08s, 0.0 ore, the pro

controller for s

L., Yea-Dat, C Design of a M r for Smart f Smart Home,

best response.

oller best respo

controllers resp

Control and F arameters.

LC Differ

10s 0.0 17s 0.0 29s 0.0 96 % 0.00

bove, the fuzz than PID con rise time and

w that the fuzz nse than th ler gives shor time (T_p) and 08s, 0.05 and 0 oposed fuzzy

single phase in

C., Yong-Chai, Microcontroller Home Enviro , 7(4). pp.233-2

onse.

ponses

Fuzzy

rences

08s 08s 05 04%

zy logic ntroller. settling

zy logic e PID rter rise

d lower 0.004 % logic duction

(6)

Dongale, T.D., Jadhav, S.R., Kulkarni, S.V., Kulkarni, T.G., Mudholkar, R.R. and Uplane, M.D. (2012). Performance Comparison of PID and Fuzzy Control Technique in Three Phase Induction Motor Control. International Journal on Recent Trend in Engineering and Technology, 7(2). pp.271-275.

Emenike, O.I., C.V, Aravin, C.V. and Gobbi, R. (2011). An Investigation of Closed Loop Control of Single Phase Induction Motors Using Industrial Components. IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (STUDENT). pp.1-6.

Grover, L. and Guy, J. (2005). Closed Loop Control Benefit AC Motor, Aircare Automation, Austin, Texas. Power Electronics Technology. pp.18-22.

Hanafi, D., Mohd-Abueejela, Y. and Zakaria, M.F. (2013). Wall Follower Autonomous Robot Development Applying Fuzzy Incremental Controller, Scientific Research, Intelligent Control and Automation 2013,4(1). pp.18-25.

Hanafi, D. (2010). PID Controller Design for Semi-Active Car Suspension Based on Model from Intelligent System Identification. The 2nd International Conference on Computer Engineering and Application. pp.60-63.

Kose, U. (2012). Fundamental of Fuzzy Logic with and Easy-to-use, Interactive Fuzzy Control Application. International Journal of Modern Enginnering Research (IJMER), 2(3). pp-1198-1203.

Kumar, Y.V.N., HimaBindu, P. H., Sneha, A. D. and Sravani, A. (2013). Novel Implementation of Phase Control Technique for Speed Control Induction Motor using ARDUINO. International Journal of Emerging Technology and Advanced Engineering, 3(4). pp.469-473.

Liu, D.H.F. and Abonyi, J. (2005). Software for Fuzzy Logic Control. Unpublished.

Mallesham, G. (2007). Improvement in Dynamic Response of Electrical Machine with PID and Fuzzy Logic Based Controller. The World Congress on Engineering and Computer Science (WCECS 2007).

Obaid, Z. A., Sulaiman, N. and Hamidon, M.N. (2009). Design of Fuzzy Logic Controller for AC Motor Based on Field Programmable Gate Array. The 2009 IEEE Student Conference on Research and Development (SCOReD 2009). pp. 487-490.

Passino, K. M. and Yurkovich, S. (1998). Fuzzy Control. Addison Wesley.

Rajaji, L. and Kumar. C. (2008). Adaptive Neuron Fuzzy Based Soft Starting of Voltage Control Induction Motor Drive. Southeastcon IEEE. pp. 448-453.

Ramadan, E.A.E.M., El-Bardini, M., El-Rabaie, N.M. and Fkirin, M.A. (2014). Embedded System Based on Real Time Fuzzy Motor Speed Controller. Ain Sham Engineering Journal, 5. pp. 399-409.

Rao, K.S. and Mishra, R. (2014). Comparative Study of P, PI and PID Controller for Speed Control of VSI-Fed Induction Motor, International Journal Engineering Development and Research (IJEDR), 2(2). pp.2740-2744.

Satyanarayana, Y. and Srujana, A. (2012). Speed Control of Induction Motor using Fuzzy PI Controller Based on Space Vector Pulse Width Modulation. International Journal Of Computational Engineering Research, 2(5). pp. 1203-1209.

Shen, J. and Dai, W. (2010). The Research of Closed Loop Control of AC motor based on J-M transformation control. The 3rd International Conference on Advanced Computer Theory and Engineering (ICACTE). pp.256-259.

Shirataha, K. (2015). Speed Control Method of Various types of Speed Control Motor. Oriental Motor.

Stekl, P. (2003). Single Phase AC Induction Motor Control Reference Design. Designer Reference Manual Motorola.

Figure

table action innside control

References

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