OPTIMAL TORQUE RIPPLE CONTROL OF ASYNCHRONOUS DRIVE USING INTELLIGENT CONTROLLERS

Electrical and Electronics Engineering: An International Journal (ELELIJ) Vol 5, No 3, August 2016
DOI : 10.14810/elelij.2016.5321 1
OPTIMAL TORQUE RIPPLE CONTROL OF
ASYNCHRONOUS DRIVE USING INTELLIGENT
CONTROLLERS
J.N.Chandra Sekhar 1 and Dr.G.V Marutheswar 2
1
Department of EEE, Assistant Professor, S V University College of Engineering,
Tirupati-517502
2
Department of EEE, Professor, S V University College of Engineering, Tirupati-517502
ABSTRACT
The dynamic performance of an asynchronous machine when operated with cascaded Voltage Source
Inverter using Space Vector Modulation (SVM) technique is presented in this paper. A classical model of
Induction Motor Drive based on Direct Torque Control (DTC) method is considered which displays
appreciable run-time operation with very simple hysteresis control scheme. Direct control of the torque and
flux variables is achieved by choosing suitable inverter voltage space vector from a lookup table. Under
varying torque conditions the performance of the drive system is verified using MATLAB/Simulink
software tool. The ripple content in the torque parameter is significant when traditional PI controller and
Fuzzy approach are configured in the proposed system. Finally, by replacing the PI-Fuzzy controller with
Hybrid Controller the torque ripple minimization can be achieved during no-load and loaded conditions.
KEYWORDS
Direct torque control (DTC), Induction Motor (IM), Cascaded Voltage Source Inverter (VSI), Space vector
modulation (SVM), PI controller, Fuzzy logic controller (FLC), Hybrid controller.
1. INTRODUCTION
In conventional electrical drive systems which are employed for variable speed applications, the
utilization of dc motor is mostly preferred. A typical Motor-Generator arrangement is used to
serve the need of wide range speed control systems. However the present electrical drive models
are mostly configured with ac motor due to its appreciable operational features which outraced
the dc motors in industrial applications [1].
Multilevel inverters with their working effectiveness are more prefered for the next generation
medium voltage and high power applications. One popular arrangement such as a three-level
Cascaded inverter also called as H –Bridge inverter is used in the present paper. The output
voltage waveforms in these inverters can be generated at low switching frequencies with high
efficiency and minimum distortion. In the recent years, multilevel inverters employing various
pulse width modulation (PWM) techniques have been developed. Among these techniques
Space Vector Modulation (SVM) technique is considered as the best method because of its
effective utilization of dc link voltage, reduced current ripple and easy implementation. This
technique results in higher magnitude of fundamental output voltage as compared to Sinusoidal

2
PWM. Also, in SVM method the degree of complexity increases with the increase in the level of
inverters since many inverter switching states have to be handled [12].
Induction motor is an asynchronous variable speed ac motor well suited for medium and high
power applications. The low cost and most widely used induction motor type is the squirrel cage
motor [2]. Basically, the control design and estimation of ac drives is significantly complex than
that of dc drives, and complexity increases highly if better performances are demanded. So,
Induction motors have been widely used more in the industrial field for variable speed drive
systems. Though the vector control strategy served for industrial demand, due to its significant
demerits, the Direct Torque Control method is being implemented effectively.
The control and estimation of ac drives is considerably complex than those of dc drives.
Conventional approaches like PI controller have been inefficient for various constraints such as
unsuitable converter power supplies, non linearity of the machine model and motor parameter
variations and frequency variations. Further an advanced control technique like fuzzy Logic
Controller (FLC) can be used for the optimal control of the drive. Fuzzy logic systems have
shown a simple approach in solving numerous non-linear problems and generated quite interest in
certain applications. A fuzzy control model is based on a set of fuzzy rules which are linguistic if-
then statements and hence bypass the requirement of relying on mathematical approach [3]. The
combinational feature of PI and FLC is a possible solution in dealing with the effects produced by
the subsequent load variations.
2. MATHEMATICAL MODEL OF THE INDUCTION MOTOR
Equations describing the Stator model of the Motor:
d s
d s s d s q s
d
V R i
d t
λ
ω λ= + +
---- (1)
q s
q s s q s d s
d
V R i
d t
λ
ω λ= + +
---- (2)
Equations describing the Rotor model of the Motor:
( )dr
dr r dr r qr
d
V R i
dt
λ
ω ω λ= + − −
---- (3)
( )
qr
rqr r qr dr
d
V R i
dt
λ
ω ω λ= + + −
---- (4)

3
Fig 1: Dynamic de
-qe
equivalent circuits of Machine (a) d e
-axis and (b) q e
– axis.
The electromagnetic torque developed by the interaction of air gap rotating flux and rotor mmf is
represented with regard to the d-q axis model as
( )3
2 2
e qr dds rqsT i i
p
λ λ=
 
− 
 
---- (5)
3. PROPOSED SYSTEM
Direct Torque Control (DTC) is a good speed control scheme with simple structure used
commonly in Induction Motor drive system. In such method the suitable selection of the inverter
switching states supports the enhaced performance feature of the system [12]. Inverter switching
vectors are selected from look up table from the torque and flux errors which are passed through
by the hysteresis band limits
Proposed by Takahashi in the mid 1980’s, the Direct Torque Control (DTC) provides good
dynamic reponse and has spread its presence effectively in the field of industrial and automobile
applications. The unoptimized effects of flux and torque amplitudes subjected to the hysteresis
band controllers along with high ripples attracts the interests of research community. In Fig.2,
conventional DTC control is shown.

4
Fig 2: Block Diagram of Conventional Direct Torque Control.
3.1 Three Level Cascaded Multilevel Inverter
A Voltage Source Inverter (VSI) is a power electronic circuit which converts a stiff dc voltage to
a 3-ᴓ ac voltage with variable frequency and amplitude [10]. Basically a two-level VSI consists of
6 groups of fast acting semiconductor switches and in contrast a three-level inverter consists of 12
groups of such switches. Depending on the direct current (DC) operating voltage of the inverter,
each switch group consists of two or more IGBT or GCT or any switching devices connected in
series. In this paper three level VSI are used in SVM DTC technique. The three level inverter
configuration using cascaded two two-level inverters is shown in Fig. 3.
Fig 3: Three level inverter configuration

5
3.2 Space Vector Modulation (SVM):
Space Vector Pulse width Modulation (SVPWM) is an advanced method with intensive
computational feature and is best suited for variable speed drive applications. This method
considers a sinusoidal voltage as a phasor which rotates with fixed angular frequency (ω). The
output voltage of a 3-ᴓ VSI is produced by the vector sum of three modulating voltage signals
which is given by the following equation [7].
( )22
3
ref a b cV V aV a V= + + --- (6)
Fig 4: Sectors and their regions for Three-level Inverter
4. CONFİGURABLE CONTROLLERS
4.1. PI Controller:
A PI controller is a typical traditional controller which is generally intended to minimize the
steady state error with increased type and order of the system.The output quantity of PI controller
has two parts, one part is proportional to the input quantity and the other is proportional to the
integral of the input quantity.
( ) ( )
0
T
i pq K e t dt K e t= +∫ ---- (7)
4.2 Fuzzy-Controller:
A fuzzy logic system describes the control algorithm which derives a fuzzy relation between
input information to the expertise control action based on human experience [8]. In the proposed
model, the fuzzy system has two inputs E (n) and dE (n) each defined with seven fuzzy sets. The

6
output of the system is represented as V (n) defined with nine fuzzy sets. Generally a fuzzy set
comprises a universe of discourse and a membership function(triangular function) that maps each
element holding a membership value ranging from 0 to 1. Fuzzification referes to a mathematical
procedure which convertsan element in the universe of discourse into the membership value of
the fuzzy set. Mamdani minimum inference method is considered for this system and finally to
convert the fuzzy set to a real number, Centroid method of defuzzification is used.
T able 1: Rule Base for Fuzzy Logic Controller
E
dE
NB NM NS ZE PS PM PB
NB NB NB NB NM NS NVS ZE
NM NB NB NM NS NVS ZE PVS
NS NB NM NS NVS ZE PVS PS
ZE NM NS NVS ZE PVS PS PM
PS NS NVS ZE PVS PS PM PB
PM NVS ZE PVS PS PM PB PB
PB ZE PVS PS PM PB PB PB
4.2.1 Fuzzy Control Action
For the control signals involved in the fuzzy system namely error signal (E), the change in error
signal (dE) and the control input error dC, the following equation describes the defined
procedure: C(k)=C(k-l)+dC(k) where k represents the sampling instant.
4.3. Hybrid Controller:
The hybrid controller comprises of PI-controller and Fuzzy Logic Controller connected in
parallel. Such an arrangement has the advantages of both PI and Fuzzy Logic controller. Fuzzy
logic assists the actual speed to get close to the reference speed, which compensate the reference
speed given to PI controller with reference to rotor speed [5].

7
Fig 5: Block Diagram of Hybrid Controller.
5. SIMULATION RESULTS AND DISCUSSION
Using MATLAB/Simulink tool SVM based DTC of 3-ᴓ induction machine has been simulated
with no-load and loaded torque cases. The simulation results display the operation of the variable
speed drive in motoring mode and braking mode.
Fig 6: Simulink block diagram for the proposed method (SVM-DTC using Hybrid-Fuzzy plus PI
controller).

8
Fig 7: No load response for PI controller based SVM DTC at fixed speed 150 rad/sec.
Fig 8: No load response for FLC based SVM DTC at fixed speed 150 rad/sec.
Fig 9: No load response for Hybrid Controller based SVM DTC at fixed speed 150 rad/sec.

9
Fig 10: Load torque response of 15 N-m at 0.5 sec for PI controller based SVM DTC at fixed speed 150
rad/sec.
Fig 11: Load torque response of 15 N-m at 0.5 sec for Fuzzy Logic Controller based SVM DTC at fixed
speed 150 rad/sec.
Fig 12: Load torque response of 15 N-m at 0.5 sec for Hybrid controller based SVM DTC at fixed speed
150 rad/sec.

10
Fig 13: Load torque response of -10 N-m at 0.5 sec for PI controller based SVM DTC at fixed speed 150
rad/sec.
Fig 14: Load torque response of -10 N-m at 0.5 sec for Fuzzy logic controller based SVM DTC at fixed
speed 150 rad/sec.
Fig 15: Load torque response of -10 N-m at 0.5 sec for Hybrid Controller based SVM-DTC at fixed speed
150 rad/sec.

11
The variations with regard to the motor torque from fig.7 to fig.15 using different control
techniques from no-load to nearly 3/4th
load were obtained. Fig.7, fig.8 and fig.9 exhibit no-load
torque response using PI, Fuzzy and Hybrid controllers whereas fig.10, fig.11 and fig.12 explain
the torque behaviour when a load torque of 15 N-m is applied at 0.5 sec. Further a passive load
torque of -10 N-m is added to the system at 0.5 sec to depict the operation of the motor during
transient mode. From all the simulated results listed above, the optimized torque waveform with
reduced ripple is obtained by using Hybrid controllers.
6. CONCLUSIONS
Under various operating conditions, the improved performance of Space Vector Modulation
based DTC three level VSI fed Induction Motor with Hybrid Controller has been simulated and
studied. The proposed method (Hybrid Controller) results are compared with Fuzzy Logic
controller and PI controller. Significant torque and flux ripple optimization has been achieved
using Hybrid Controller. Therefore, SVM-DTC method can be a better solution for general
purpose IM drives in the wide power range applications. It may be inferred that such method will
continue to play a very important role in the development of high performance induction motor
drives.
APPENDIX – A
List of Principal Symbols
e e
d q− Synchronously rotating reference frame direct and quadrature axes
dsV d-axis stator voltage
qsV q-axis stator voltage
drV d-axis rotor voltage
qrV q-axis rotor voltage
dsi d-axis stator current
qsi q-axis stator current
dri d-axis rotor current
qri q-axis rotor current
sR Stator resistance

12
dsλ d-axis stator flux linkage
qsλ q-axis stator flux linkage
drλ d-axis rotor flux linkage
qrλ q-axis rotor flux linkage
ω stator angular frequency
rω rotor electrical speed
REFERENCES
[1] Takahashi, I. and Noguchi, T. "A new quick-response and high efficiency control Strategy of an
induction motor." IEEE Transactions on Industry Applications, vol.22, No. 5, pp. 820-827, 1986.
[2] Bose, B. K.; "Power Electronics and AC Drives". Prentice-Hall. 1986.
[3] MATLAB Fuzzy logic toolbox user guide. The Math Works, Inc, 1999.
[4] S.W. Lee,S.Kim & Y.Park,(1998) ,“Fuzzy Pre-Compensated PI Controller For A Variable Capacity
Heat Pump”, In proceedings of the IEEE Conference on control Applications, pp953-957.
[5] M. N. Uddin and H. Wen, “Development of a self-tuned neuro- fuzzy controller for induction motor
drives,” IEEE Trans. Industry Applications, Vol.43, No. 4, July/Aug. 2007.
[6] I. Miki, et al. “Vector control of induction motor with fuzzy PI controller,” IEEE Conf., IASAnnu.
Meeting 1991, Vol. 1, pp.341-346.
[7] K. V. Naresh, Investigation of SVM-PWM based Induction Motor Drives, M Tech Dissertation,
Indian Institute of Technology Roorkee, 2007.
[8] V.Chitra, R.S.Prabhakar, Induction Motor Speed Control using Fuzzy Logic Controller, World
Academy of Science, Engineering and Technology 23, 2006.
[9] Dumitru D., Chemin B.,“A PI-Fuzzy Controller Designated For Industrial Motor Control
Application”. AIAA, 1990, pp.949-954.
[10] R.Toufouti, S.Meziane, H. Benalla, “Direct Torque control for induction motor using intelligent
techniques”, Journal of Theoretical and Applied Information Technology, vol. 3, no. 3, pp. 35–44,
2007.
[11] Y. S. Lai and J. H. Chen, “A new approach to direct torque control of induction motor drives for
constant inverter switching frequency and torque ripple reduction,” IEEE Trans. Energy Conv., vol.
16, pp. 220–227, Sept. 2001.
[12] Hui-Hui Xiao, Shan Li, Pei-lin Wan and ming-Fu Zhao, “Study on Fuzzy Direct torque Control
System ”, Proceedings of the Fourth International Conference on Machine Learning and Cybernetics,
Vol. 3, pp. 1537-1540, 2002. J. Clerk Maxwell, A Treatise on Electricity and Magnetism, 3rd ed., vol.
2. Oxford: Clarendon Press, 1892, pp.68-73. (Book)

OPTIMAL TORQUE RIPPLE CONTROL OF ASYNCHRONOUS DRIVE USING INTELLIGENT CONTROLLERS

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