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Control and Intelligent Processing
Center of Excellence
Design, Control and Fault
Diagnosis of Industrial Drives
Department of
Electrical and Computer Engineering
University of Tehran
August 25, 2004
Introduction
 Motivation and Scope: Embedded intelligent
derives has been emerged as a pivotal part of
modern industrial networks, where different parts
of the system, including motor, driver, and
controller are designed in a coherent unified
design process, making them an integrated part of
a large distributed industrial network.
 Objectives: To develop intelligent methods in
design and implementation of industrial drive
systems including motor, driver, and controller,
with fault diagnosis capability
August 25, 2004
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Sub-projects and Research Directions
 Sub-project 1: Design, development, and
implementation of SR motor.
 Sub-project 2: Design, development, and
implementation of SR motor drive.
 Sub-project 3: Design, development, and
implementation of PMS motor drive, using
SV-PWM, and FPGA technologies, for an
industrial robot controller.
 Sub-project 4: Design and development of
Emotional controller for SR motor.
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Sub-projects and Research Directions
 Sub-project 5: Design and development of
Predictive controller for SR motor.
 Sub-project 6: Fault diagnosis in induction motors
using intelligent methods.
 Sub-project 7: Detection an suppression of audible
noise in electrical motors using the idea of
biological immune systems
 Sub-project 8: Implementation of classical and
intelligent controllers on DSP and microcontroller
based systems
August 25, 2004
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Main Achievements & Contributions
 A complete SR motor drive system including
motor, driver, and controller is designed,
developed and implemented. (In cooperation with
Motogen Co.)
 A PSM motor drive system including driver and
PC-based controller is designed, developed and
implemented, as a part of an industrial six degree
of freedom robot controller project.
 Numerous journal and conference publications,
describing or developed methods, algorithms, and
applications in the general area of motor droves.
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Publications
 Number of Journals Publications:
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6 published, ISI
3 published, non-ISI and national
2 submitted
 Number of Conferences Publications:
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14 international conferences
17 national conferences
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Selected Publications
 J.E. B. Mirzaeian, M. Moallem, V. Tahani, and C. Lucas, “Multiobjective
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Optimization Method Based on a Genetic Algorithm for Switched
Reluctance Motor Design”. IEEE Transaction on Magnetics 38 (2), March
2002, 1- 4.
J.E. C. Lucas, D. Shahmirzadi, H. Ghafoorifard, “Eliminating Stator
Oscillations through Pin Placement”. Journal of Engineering Simulation 3
(1), March 2002, 3- 7.
J.E. M. Nourani, A. Attarha, and C. Lucas, “Application of Fuzzy Logic in
Resistive Fault Modeling and Simulation”. IEEE Transaction on Fuzzy
Systems 10 (4), August 2002, 461- 472.
C. Lucas, D. Shahmirzadi, M. Nikkhah Bahrami, and M. H. Gaforifard, “A
FEM based quasi-static neuro model for acoustic noise in switch reluctance
motors, to appear in Int’l J. of Computational Acoustics, 2003.
M. R. Rafimanzelat and B. N. Araabi, “Induction Machine Broken Bar
Detection Using Rough Sets Based Classification,” Lecture Notes in
Artificial Intelligence, vol. 3070, pp. 532-537, Springer Verlag, 2004.
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People in the R&D Group
 Faculty Members
 Dr. Babak N. Araabi
 Prof. Caro Lucas
 Dr. Majid Nili Ahmadabadi
 Students (Current)
 Mohsen Farshad
 Arash Sadeghzadeh
 Mohammad Reza Rafimanzelat
 Mahmoud Hatami
 Ali Eskandari
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Test-beds and Approaches
 Test-beds
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SR motor drive test-bed (UT, ECE, Control Lab.)
PMS motor drive test-bed (UT, ECE, Robotics Lab.)
 Approaches
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Emotional control
Predictive control
Neuro-fuzzy modeling and control
Pattern recognition techniques for fault diagnosis
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Future Projects and Directions
 Increase our international cooperation through
joint R&D projects with other international center
of excellences.
 Increase our cooperation with industries through
mutual R&D projects.
 Optimize our designed and developed SR and
PMS drive systems and examine our previously
proposed intelligent motor control algorithms on
developed test-beds.
 Adding linear motor drives to our research agenda.
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