induction motor drive using fuzzy...

Induction Motor Drive Using Fuzzy Logic

SHAHRAM JAVADI

Islamic Azad University –Central Tehran Branch

Electrical Engineering Department

Moshanir Power Electric Company

Thermal Power Plant Division

IRAN

Email: [email protected]

Abstract: Variable speed drives are growing and varying. Drives expanse depend on progress in different part of science

like power system, microelectronic, control methods, and so on. Artificial intelligent contains hard computation

and soft computation. Artificial intelligent has found high application in most nonlinear systems same as

motors drive. Because artificial intelligent techniques can use as controller for any system without requirement

to system mathematical model, it has been used in electrical drive control. With this manner, efficiency and

reliability of drives increase and volume, weight and cost of them decrease. Due to the improved operating

characteristics they give to the equipment control, electronic motor soft starters are increasingly widely applied.

Escalators, pumps, elevators and conveyor belts all operate more effectively if they are soft started. However, it

is not simply the ergonomics of an airport, process plant or shopping mall that are improved by soft starters.

A major factor in the growth in popularity of soft starters is the reduced wear and tear that they place on motors

and their associated drive systems.

In turn, this reduces maintenance, conserves energy and plays a significant part in improving plant performance

and operating costs.

Keywords: Power Plant, Fuzzy Logic, Induction Motor, Soft starter

I. INTRODUCTION An important factor in industrial progress during

the past five decades has been the increasing

sophistication of factory automation which has

improved productivity manifold. Manufacturing

lines typically involve a variety of variable speed

motor drives which serve to power conveyor

belts, black start of power plants, robot arms,

overhead cranes, steel process lines, paper mills,

and plastic and fiber processing lines to name

only a few. Prior to the 1950s all such

applications required the use of a DC motor drive

since AC motors were not capable of smoothly

varying speed since they inherently operated

synchronously or nearly synchronously with the

frequency of electrical input. To a large extent,

these applications are now serviced by what can

be called general-purpose AC drives. In general,

such AC drives often feature a cost advantage

over their DC counterparts and, in addition, offer

lower maintenance, smaller motor size, and

improved reliability. However, the control

flexibility available with these drives is limited

and their application is, in the main, restricted

to fan, pump, and compressor types of

applications where the speed need be regulated

only roughly and where transient response and

low-speed performance are not critical. More

demanding drives used in machine tools,

spindles, high-speed elevators, dynamometers,

mine winders, rolling mills, glass float lines,

and the like have much more sophisticated

requirements and must afford the flexibility to

allow for regulation of a number of variables,

such as speed, position, acceleration, and

torque. Such high-performance applications

typically require a high speed holding accuracy

and fast transient response. Until recently, such

drives were almost exclusively the domain of

DC motors combined with various

Proceedings of the 7th WSEAS International Conference on Systems Theory and Scientific Computation, Athens, Greece, August 24-26, 2007 264

configurations of AC-to-DC converters

depending upon the application. With suitable

control, however, induction motors have been

shown to be more than a match for DC drives in

high-performance applications. While control of

the induction machine is considerably more

complicated than its DC motor counterpart, with

continual advancement of microelectronics, these

control complexities have essentially been

overcome. Such that power electronic equipment

which is used widely in motor drives is IGBTs

which is shown in figure 1.

Figure1. IGBT power electronic element

Although induction motors drives have already

overtaken DC drives during the next decade it is

still too early to determine if DC drives will

eventually be relegated to the history book.

However, the future decade will surely witness a

continued increase in the use of AC motor drives

for all variable speed applications.

II. Speed Control AC motor drives can be broadly categorized into

two types, thyristor based and transistor based

drives. Thyristor posses the capability of self

turn-on by means of an associated gate signal but

must rely upon circuit conditions to turn off

whereas transistor devices are capable of both

turn-on and turn-off. Because of their turn-off

limitations, thyristor based drives must utilize an

alternating EMF to provide switching of the

devices (commutation) which requires reactive

volt-amperes from the EMF source to

accomplish.

Induction motors are practically fixed speed

devices. There are practically only two methods

to change the rotation speed of AC induction

motor: use frequency converter or use motor with

separate winding for different speeds. In some

applications motors with dual speed winging are

used. The applications where accurate speed

control is needed, you need a frequency

converter. A frequency converter can run a

three phase AC motor at very wide speed range

quite well (the performance of motor is usually

reduced outside its optimal operation speed).

There are variable frequency drives that allow

induction motors to run on different speeds. But

on those applications mechanical load and the

speed range must be considered, because on

those applications motors can get very hot very

fast. The problem is that a 60 Hz (or 50 Hz)

motor does not have enough iron in it to allow

efficient 25 Hz operation. The motor will run

hot due to not having enough inductive

reactance at the reduced frequency. Dropping

down to 10 Hz would make it even worse. A

motor designed for variable frequency drive has

more iron. Also, it might use a different

iron/steel alloy to allow efficient operation at

higher frequencies (say 400 Hz). With a light

mechanical load and a good motor combined

with a good variable frequency drive controller,

it's sometimes possible to get a reasonable

speed range using a variable frequency inverter.

A good variable frequency drive device controls

both frequency and voltage. The better ones

even take into account that at very low speeds

the resistance of the coils cannot be neglected.

In VFD (variable frequency drive) system the

incoming single phase power is rectified and

filtered, and three-phase power is generated

from the DC rail using three half-bridges. You

get to set the frequency over a range so you can

vary the speed of your motor, plus a nice digital

display etc. It's a bit harder on the motor

insulation than just running it from the line, but

well-designed motors should be okay. The

reason why VFD is harder for motor insulation

is that the inductance in the wiring to the motor

allows spikes and ringing at the motor itself.

The waveforms that go from VFD to motor are

typically quite far from ideal sine wave.

Frequency converter does not work with AC

induction motors that are run from single phase

power source, because the operation of the

needed motor phase conversion capacitor is

very frequency sensitive (works as expected

only at normal mains frequency).

There are variable frequency drive devices that

take in single phase power but can output three-


phase power to the three phases motor. The

problem in this kind of single phase to three

phases VFD is that single phase high power to dc

conversion is much more expensive than three

phase high power to dc conversion. Filter

capacitors have to be much larger with lower

ESR. Also, you will need at least three times the

current on a single phase line (3 phase power of

same amps per line carries about 1.73 times of

power of the same amps on single phase line).

The momentary power requirements when motor

spins up are much larger.

A brief list of the available drive types is given in

Figure2. The drives are categorized according to

switching nature (natural or force commutated),

converter type and motor type. Naturally

commutated devices require external voltage

across the power terminals (anode-cathode) to

accomplish turn-off of the switch whereas a force

commutated device uses a low power gate or

base voltage signal which initiates a turn-off

mechanism in the switch itself. In this figure the

category of transistor based drives is intended to

also include other hard switched turn-off devices

such as GTOs, MCTs and IGCTs which are, in

reality, avalanche turn-on (four-layer) devices.

The numerous drive types associated with each

category is clearly extensive and cannot be

treated in complete detail here. However, the

speed control of the four major drive types

having differing control principles will be

considered namely

1) Voltage controlled induction motor drives

2) Load commutated synchronous motor drives

3) Volts per hertz and vector controlled induction

motor drives

4) Vector controlled permanent magnet motor

drives.

Figure2. Various Motor Drive Types

A Schematic block diagram of a transistor

based controller of an induction motor is shown

in figure3.

Figure3. A transistor based induction motor drive

III. Soft Starting In today’s market motors or used across a wide

section of the commercial sector. It could be

from standard squirrel cage motors in a typical

boiler room situation or alternatively it could be

a variable speed motor requiring the use of an

inverter to ramp the run cycle up and down.

Similarly soft starts are becoming more

apparent throughout the industry. The current

drawn by a three-phase motor at start up is

several times more than its rated operating

current. This can vary from 3 to 15 times

depending on the characteristics of the motor

and is typically at least a factor of 7 more than

the operating current. In addition, problems

associated with torque surge are encountered

when a motor is started direct. Extra stress on

the gearbox, couplings, belt drives and other

parts can soon lead to wear and even failure.

To overcome the problems associated with

current and torque surges, designers have

developed different systems over the years.

These can be categorized as follows: Direct-on-

line starting; Star delta starting; Frequency

conversion; and Solid state, stepless control, or

soft starting.

Direct-on-line starting is common up to 7.5kW.

However for higher currents, some form of

start-up reduction is required.

Traditionally, the star delta method of reducing

the start-up voltage electro-mechanically has

proved popular. The technique, so called

because the motor windings are switched from a

star connection to a delta connection, reduces

both start-up current and torque by about two

thirds. However, at the point where switching

occurs there is still a current surge that can be

as high as those experienced in DOL starting.


The alternative method of frequency conversion

takes the AC voltage, converts it to DC and then

to a start-up voltage of any desired frequency.

However this can be both complicated and

expensive.

Soft start systems however, offer an excellent

alternative at low cost and complexity. Soft start

devices provide stepless motor control, allowing

both the start-up torque and current to be adjusted

in small increments. Not only can these

parameters be controlled; soft starters can also

vary the time taken to run the motor up to its

normal operating speed. The devices operate by

gradually increasing the voltage to the motor

during the run-up period, this being done by

phase control of the input AC voltage. The

starting current is reduced in proportion to the

reduction in voltage, the starting torque by the

square of the reduction. Soft starting is now

finding application in control situations as

diverse as water treatment plants and crisp

factories.

The benefits of longer motor life, reduced

maintenance and improved torque control mean

that this type of starter is now being used in many

areas where inverters would have previously

been considered the only option.

IV. Control Principle AC motors, particularly the squirrel-cage

induction motor (SCIM), enjoy several inherent

advantages like simplicity, reliability, low cost

and virtually maintenance-free electrical drives.

However, for high dynamic performance

industrial applications, their control remains a

challenging problem because they exhibit

significant non-linearity and many of the

parameters, mainly the rotor resistance, vary with

the operating conditions. Field orientation control

(FOC) or vector control (Vas, 1990) of an

induction machine achieves decoupled torque

and flux dynamics leading to independent control

of the torque and flux as for a separately excited

DC motor. FOC methods are attractive but suffer

from one major disadvantage: they are sensitive

to motor parameter variations such as the rotor

time constant and an incorrect flux measurement

or estimation at low speeds (Trzynadlowski,

1994). Consequently, performance deteriorates

and a conventional controller such as a PID is

unable to maintain satisfactory performance

under these conditions. Recently, there has been

observed an increasing interest in combining

artificial intelligent control tools with classical

control techniques. The principal motivations

for such a hybrid implementation is that with

fuzzy logic and/or neural networks issues such

as uncertainty or unknown variations in plant

parameters and structure can be dealt with more

effectively, hence improving the robustness of

the control system. Conventional controls have

on their side well-established theoretical

backgrounds on stability and allow different

design objectives such as steady state and

transient characteristics of the closed loop

system to be specified. Several works

contributed to the design of such hybrid control

schemes (Cao et al., 1996; Chen and Chang,

1998; Shaw and Doyle, 1997).

In this paper both control methods (Classical

PID controller and Fuzzy Control base) are

introduced and applied to an indirect field-

oriented induction motor.

In the first design approach a classical PID

controller is introduced to apply to an induction

motor in order to control its speed and also

starting situation is investigated. See figure 4 in

bellow.

Figure 4. PID Controller

In the second design approach the basic fuzzy

logic controller (FLC), regarded as a kind of

variable structure controller (VSC) for which

stability and robustness are well established is

developed. This follows the interpretation of


linguistic IF–THEN rules as a set of controller

structures that are switched according to the

process states. Figure 5 shows a typical FLC.

Figure 5. Fuzzy Logic Controller

The mathematical technique called fuzzy logic

offers a new approach to improving ASD

voltage/frequency/current control. Fuzzy logic

has evolved from an esoteric branch of

mathematics into a useful engineering tool. By

virtue of its adaptability, it can be applied to

problems whose nonlinearity and dynamic nature

makes them intractable to solution via classical

control methods. Motor control has all of the

attributes of this class of problems. Fuzzy logic

has been implemented in this development of

improved motor control because:

1) Fuzzy logic overcomes the mathematical

difficulties of modeling highly non-linear

systems.

2) Fuzzy logic responds in a more stable fashion

to imprecise readings of feedback control

parameters, such as the dc link current and

voltage.

3) Fuzzy logic control mathematics and

software are simple to develop and flexible for

each modification.

V. Vector Control Drive: Although the large majority of variable speed

applications require only speed control in which

the torque response is only of secondary

interest, more challenging applications such a

traction applications, servomotors and the like

depend critically upon the ability of the drive to

provide a prescribed torque whereupon the

speed becomes the variable of secondary

interest. The method of torque control in ac

machines is called either vector control or,

alternatively field orientation. Vector control

refers to the manipulation of terminal currents,

flux linkages and voltages to affect the motor

torque while field orientation refers to the

manipulation of the field quantities within the

motor itself. Since it is common for machine

designers to visualize motor torque production

in terms of the air gap flux densities and MMFs

instead of currents and fluxes which relate to

terminal quantities, it is useful to begin first

with a discussion of the relationship between

the two viewpoints. A complete vector

controlled induction motor signal diagram is

shown in figure 6. The feedback speed control

loop generates the active or torque current

command iqs*’. The vector rotator receives the

torque and excitation current commands Iqs*

and ids* from one of the two positions of a

switch: the transient position (1) or the steady-

state position (2). The fuzzy controller becomes

effective at Steady state condition; i.e., when

the speed loop error, dωr approaches zero.

Figure 6. PI Vector Control Induction motor diagram


A feed-forward pulsating torque compensator has

been developed to prevent speed ripple and

mechanical resonance during transient operation.

As the excitation current is reduced in adaptive

steps by the fuzzy controller, the rotor flux

decreases exponentially. The decrease of flux

causes loss of torque, which normally is

compensated for slowly by the speed control

loop. Efficiency optimization control is effective

only at steady-state conditions. A disadvantage of

this control mode is that the transient response

becomes sluggish. For any change in load torque

or speed command, fast transient response

capability of the drive can be restored by

establishing the rated flux.

VI. Fuzzy Logic: Three interactive efficiency-optimizing (input

power minimizing) controllers have been

developed for Type 1 ASDs. These controllers

are 1) voltage perturbation for input power

minimization, 2) speed correction, and 3) slip

compensation.

The voltage perturbation controller is based on

changes in input power and stator voltage. Fuzzy

logic control has been emphasized for voltage

perturbation. The fuzzy logic membership

functions for both inputs and the output are

partitioned using seven MF for inputs and nine

MF for output fuzzy sets and are shown in figure

7. The input variables are:

S

r

T

CE

t

E

dt

dE

E

=∆

∆=

−= ωω*

The output variable is:

CEKEKTDU e 21

*+=∆=

Triangular fuzzy sets are used for both inputs and

outputs, with a restriction that the output fuzzy

sets must be isosceles to simplify defuzzification.

Input and output values are represented

linguistically (i.e., NM=negative medium,

NS=negative small, ZE=zero, PS=positive small,

and PM=positive medium). As it is shown in

figure7, both inputs and output are normalized

between -1 and 1. So it is necessary to define

proper gains for all parameters, i.e. ke , kde and

kdu in order to change parameters in per unit.

Selecting these gains is one of challenging part of

fuzzy logic controller and if it is selected

improper, it may be we don't get optimum result

or even it leads to instability.

Figure 7. Fuzzy Membership functions for

2 inputs (e & de) and output (du)

The rule base table can be read according to the

following example:

IF ERROR (E) is ZERO (Z) AND CHANGE

IN ERROR (CE) is NEGATIVE SMALL (NS),

THEN OUTPUT (DU) is NEGATIVE SMALL

(NS).

FAM table of such rules is brought in table 1:

Table1: FAM Table for Fuzzy Speed Controller

e

ce NB NM NS Z PS PM PB

NB NB NB NB NM NS NVS Z

NM NB NB NM NS NVS Z PVS

NS NB NM NS NVS Z PVS PS

Z NM NS NVS Z PVS PS PM

PS NS NVS Z PVS PS PM PB

PM NVS Z PVS PS PM PB PB

PB Z PVS PS PM PB PB PB


Speed correction control is needed because the

perturbation approach alters motor speed and

output power. The motor's output rotor speed

should be maintained as constant as possible.

The input/output mapping of the FLC is shown in

figure 8.

Figure 8. Crisp input/output map

VII. Simulation In this paper two case studies have been studied.

In Both simulations, it is used simulink and

powersym toolboxes of MATLAB software.

In the first case study, a 50 HP induction motor is

started and controlled by a PID controller. 3

phase voltages and currents are measured and

plotted in the first 3 seconds of its action. Also

acceleration curve and output torque are

investigated. All graphs are shown in figure 9.

In the second case, the same motor is started and

controlled by a Fuzzy Logic Based controller.

The results are shown in figure 10. As it is shown

the outputs are improved regarding to magnitude

of starting currents and also time response of

acceleration. For example amplitude of current

with a classic PID controller is about 500 A

during startup while with fuzzy logic controller

this value reduced to 200 A.

Figure 9. Output Variable of a classic controlled

induction Motor from Top to Bottom:

Voltage, Current, Rotor Speed, Output Torque

Figure 10. Output Variable of a Fuzzy Logic Controlled

induction Motor from Top to Bottom:

Voltage, Current, Rotor Speed, Output Torque


VIII. Conclusion An AC induction motor can consume more

energy than it actually needs to perform its work,

particularly when operated at less than full load

conditions. This excess energy is given off by the

motor in the form of heat. Idling, cyclic, lightly

loaded or oversized motors consume more power

than required even when they are not working.

With a fuzzy logic controller we can control the

amplitude of starting current and also save more

energy during this time. In addition the cost and

complexity of controller is reduced when it is

designed by fuzzy method, because it does not

need the exact model of system. The complete

schematic of controller is shown in figure 11.

Figure 11. Top: Complete system

Bottom: Fuzzy Logic Controller

IX. Acknowledgment The author thanks MOSHANIR, the most important

consultant company in electrical engineering in

IRAN for using real data of one of its projects and

also Islamic AZAD University for whole helps.

References

[1] Bimal Bose, Power Electronics and Motor Drives,

Elsevier, Academic Press, 2006

[2] M. AZZEDINE DENAI, S. "AHMED ATTIA, FUZZY

AND NEURAL CONTROL OF AN INDUCTION MOTOR"

Int. J. Appl. Math. Computer. Sci., 2002, Vol.12.

[3] John G. Cleland and M. Wayne Turner, "Fuzzy Logic

Control of Electric Motors and Motor Drives Feasibility

Study", United States Air and Energy Engineering

Environmental Protection Research Laboratory

Agency Research Triangle Park,

[4] J. X. Shen, Z. Q. Zhu, and D. Howe, "Hybrid PI and

Fuzzy Logic Speed Control of PM Brushless AC Drives",

EPE 2001 – Graz

[5] Andreas Dannenberg, "Fuzzy Logic Motor Control

with MSP430x14x", Texas Instruments, Application

Report, SLAA235–February 2005.

[6] Y. Miloud, A. Draou, "Performance Analysis of a

Fuzzy Logic Based Rotor Resistance Estimator of an

Indirect Vector Controlled Induction Motor Drive", Turk

J Elce Engine, VL 13, NO. 2, 2005


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