Page 1 of 10
European Journal of Business &
Social Sciences
Available at https://ejbss.org/
ISSN: 2235-767X
Volume 07 Issue 04
April 2019
ARTIFICIAL INTELLIGENCE BASED REAL TIME CONTROL OF INDUCTION MOTOR
DRIVES
JESU ANTONY SAHAYA NIXON .N
PG Student
PRIST Deemed to be University, Thanjavur
Page 2 of 10
European Journal of Business &
Social Sciences
Available at https://ejbss.org/
ISSN: 2235-767X
Volume 07 Issue 04
April 2019
ABSTRACT
This paper presents design and implementation of Real
time MATLAB Interface for speed control of induction
motor drive using dsPIC 30F4011. In recent years, the field
oriented control of induction motor drive is widely used in
high performance drive system. It is due to its unique
characteristics like high efficiency, good power factor and
extremely rugged .This scheme leads to be able to adjust
the speed of the motor by control the frequency and
amplitude of the stator voltage, the ratio of stator voltage to
frequency should be kept constant
Keywords: Fuzzy logic control (FLC), Membership
Function, PIC digital signal microcontroller Induction
motor, Intelligent Power Module.
1. INTRODUCTION
In recent years, speed control of induction motor drive is
widely used in high performance drive system ,because of
its advantages like high efficiency, very simple , extremely
rugged, good power factor and it does not require starting
motor. Induction motors are used in many applications such
as HVAC, Industrial drives control, automotive control,
etc... In recent years there has been a great demand in
industry for adjustable speed drives [1].
Recently, Fuzzy logic control has found many applications
in the past decade. Fuzzy Logic, deals with problems that
have vagueness, uncertainty and use membership functions
with values varying between 0 and 1[2]. This means that if
the a reliable expert knowledge is not available or if the
controlled system is too complex to derive the required
decision rules, development of a fuzzy logic controller
become time consuming and tedious or sometimes
impossible. In the case that the expert knowledge is
available, fine-tuning of the controller might be time
consuming as well [3, 4]. Real time implementation of
MATLAB Interface for speed control of induction motor
drive using dsPIC 30F4011 as quite new. [5- 7]. The aim of
this paper is that it shows the dynamics response of speed
with design the fuzzy logic controller to control a speed of
Induction motor. This paper presents design and real time
implementation of MATLAB Interface for speed control of
induction motor drive using dsPIC 30F4011.
2. PROPOSED SPEED CONTROL
SYSTEM
Figure-1 shows the block diagram the proposed system.
From the induction motor sense the speed using Quadature
Encoder pulse (QEP) sensor , then Speed is given back to
the Intelligent power Module(IPM) , From the IPM , speed
converted into the voltage in analog form. Through the PIC
controller analog form of the voltage converted in digital
form. Digital form input to the MATLab Work. In the
MATLab work we design the fuzzy
logic control, from that we obtain the controlled output
given to the dsPIC controller. Depends upon the
controlled output, the controller produce the SVPWM
signals, that signals feed back into the gate drive of the
IGBT of Intelligent Power Module. Inverter output
from the intelligent power module is given to the input
of the induction motor.
Figure-1 Block diagram for the proposed
system
Figure-2 show the MATLAB work, where Query
instrument is Digital signal PIC controller (dsPIC 30F
4011).The speed error e and the change of speed error
ce are processed inputs through the fuzzy logic
controller whose output is the controlled voltage to
dsPIC controller. The controlled output voltage from
the fuzzy logic controller is processed by PIC
controller to produce a control frequency and
Amplitude. This control frequency adjusts the V/f of
SVPWM such that the desired speed of the motor can
be obtained[8-11].
Figure-2 MATLAB work
3. FUZZY LOGIC CONTROL
The process of fuzzy logic controller design includes
the following steps. (i)Fuzzification: process of
representing the inputs as suitable linguistic variable.
(ii) decision Making: appropriate control action to
carried out. It is based on the knowledge base and rule
base. Knowledge base and rule base are the details
about the linguistic variables and control rules
(iii) Defuzzification: Process of converting fuzzified
output into crisp value. The inputs to the FLC are
error (e) and change in error (ce). The output is the
Page 3 of 10
European Journal of Business &
Social Sciences
Available at https://ejbss.org/
ISSN: 2235-767X
Volume 07 Issue 04
April 2019
voltage of the switching signal.
The universe of discourse of all the variables, covering
the whole region, is expressed in per unit values. All the
MFs are asymmetrical because near the origin, the signals
require more precision. There are seven MFs for e and ce
signal, whereas there are seven MFs for the output. All
the MFs are symmetrical for positive and negative values
of the variables. Table 1 shows the corresponding rule
table for the speed controller. The top row and left
column of the matrix indicate the fuzzy sets of the
variables e and ce, respectively, and the MFs of the
output variable du are shown in the body of the matrix.
There may be 7*7 = 49 possible rules in the matrix.
Mamdani type controller is chosen for this application
and the basic rule of this type of controller is
IF ce is PS AND e is NM THEN du is NS.
Membership functions are associated with each lable as
shown in Figure. 3(a)-(c)
(a) MF for speed error
(b) MF for change in speed error
(c) MF for voltage
(d) Figure 3- Membership functions for input and output
variables Table 1. Rule base Speed control
e nl nm ns z ps pm pl
ce u
nl nl nl nl nl nm ns z
nm nl nl nl nm ns z ps
ns nl nl nm ns z ps pm
z nl nm ns z ps pm pl
ps nm ns z ps pm pl pl
pm ns z ps pm pl pl pl
pl z ps pm pl pl pl pl
4. SPACE VECTOR PULSE WIDTH
MODULATION
The basic power circuit topology of a three-phase voltage
source inverter supplying a star connected three-phase
load is given in Figure 4. The power circuit contains in
general six semiconductor switches such as MOSFETs,
IGBTs, BJTs etc with antiparallel diodes for protection.
The two power switch of one leg is complimentary in
operation with a small dead band between the switching
of two devices. Switching operation of the inverter yield
in total 8 output vectors with 6 being active or non zero
and two zero vectors. The six active vectors are labeled
as V1, V2, V3, V4, V5,V6 and the two zero vectors are
labeled as Vo and V7.
V
Figure 4 Power Circuit topology of a three-phase
VSI.
If these 8 voltage vectors are converted to 2 axis, it can
be plotted as shown in Figure 5. The tips of the 6 non
zero vectors, when cornered form a regular hexagon with
the two zero vectors lying at the origin.
The Vref in α-β plane rotates circularly, so that the output
voltage will be sinusoidal. Since the voltage source
inverter can have 8 states, Vref can only be synthesized
by using 8 voltage vectors. There can be infinite ways to
PWM 1 S1 PWM 3 S3 PWM 5 S5
a
+
dc
- N
b c
PWM 4 S4 PWM 6 S6 PWM 2 S2
