|
Topic Name: Adaptive Fuzzy-Artificial Neural Network Based Speed Controller of DC Motor Drive
Category: Electrical
Research persons: Mohammed Golam Sarwer, Md. Abdur Rafiq , B.C. Ghosh
Location: Khulna, Bangladesh
Details
This Research
introduces a DC motor drive system with a fuzzy-artificial neural-network
controller. First, a neural network-based architecture is described for fuzzy
logic control. The characteristic rules and their membership functions of fuzzy
systems are represented as the processing nodes in the neural network structure.
Then, the fuzzy rules and input-output of the system are tuned by the supervised
gradient descent learning algorithm. The performance of the proposed controller
is evaluated under various operating conditions. The controller is shown to be
robust, adaptive and capable of learning.
In the past decade, nonlinear and adaptive control methods have
been used extensively to control DC and brushless dc motor drives . In
thesemethods, the state estimation and parameter identification are based on and
limited to linear models. As the model deviates from the physical system, the
performance of the control degrades.
Furthermore, the methods require the exact equations and precise
numerical values pertinent to the system under study. Li and Lau[1] applied
fuzzy logic to microprocessor-based servomotor controller, assuming a linear
amplifier. They compared the fuzzy controlled systemperformance with PID
controller. Fuzzy logic can be applied in feedback control of dc drive system
which the non-linearity, parameter variation and load disturbance are considered
to be compared with fuzzy logic control. A comparison of drive system
performance withfuzzy logic and PI control is given , that improves the machine
performance by linearizing the motor performance as the load varies.
Unlike classical control strategies, fuzzy logic incorporates an
alternative way of thinking. It allows modeling of complex systems via the use
of a higher level of abstraction originated from accumulated knowledge and
experience. Further,fuzzy logic permits expression of the knowledge bysubjective
concepts, such as very large, moderate,and slightly deviated, which are mapped
onto numeric ranges. A fuzzy logic controller uses fuzzy logic as a design
methodology, which can be applied in developing nonlinear systems for
embedded control. Other researchers have used artificial neural networks (ANN)
to deal with nonlinearities and uncertainties of Brushless DC drives .
ANNs have many advantageous features that include parallel and
distributed processing and efficient nonlinear mapping between inputs and
outputs, without an exact knowledge of the system model.
Additionally, rapidity and robustness are the most profound and
interesting properties of ANNs, in comparison to the classical schemes.
Nonetheless, no underlying knowledge of the system’s dynamics is assumed. Rather
such knowledge is treated as a black-box which, when presented with a given
input, produces a given output. However, one of the drawbacks of using ANNs is
that it is difficult for the user to understand or modify the network
decision-making process. Horikaya S. have proposed Fuzzy Neural Network
principles to Fuzzyreasoning.
Basically, it emulates a fuzzy logic controller. This type of
Fuzzy controller emulation has the advantages that it can automatically identify
fuzzy rules and fuzzy membership function for a problem.
In this paper, an online trained Fuzzy-Artificial Neural-Network
Controller (FANNC) for a DC motor drive system is proposed. The proposed
controller integrates the ideas of the fuzzy logic controller and neural network
structure into an intelligent control system. An ANN-based structure is
introduced for the fuzzy logic control.
The nodes in the hidden layers perform as membership functions
and fuzzy rules. Initially, the proposed controller is constructed from thefuzzy
IF-THEN rules, which is based on the simple engineering knowledge concerning the
controlled DC drive system. A learningmechanism is then used to update the
parameters of the adaptive FANNC. The supervised gradient decent method, which
uses a delta adaptive law is utilized to train the proposed controller online.
The proposed method is tested under normal and with
disturbance addedconditions by simulations.
About The Researchers :
1. Mohammed Golam Sarwer
Assistant Professor,
Electrical & Electronic Engg.,KUET,Bangladesh.
Education :
University of Windsor
City University of Hong Kong
Khulna University of Engineering and Technology (KUET),
Bangladesh
Contact Information of Sarwar:
Email : mdsaku@yahoo.com
2. Dr. Bashudeb Chandra Ghosh
Professor,Department of
Electrical and Electronic Engineering
Khulna
University of Engineering and
Technology,Bangladesh.
Education :
PhD :
IIT
Kharagpur,
India
Electrical
Eng.,1993
M.Sc.Eng.:
BUET,Dhaka ,Bangladesh in 1986
B.Sc.Eng.:
Rajshahi
University,Bangladesh in 1976
Publications in Journals and Conference
Proceedings
a) National and
International Journals :
|
Sl.
No. |
Title of Paper |
Name of Journal with
Vol.No & Page Position. |
Year and Country of Publication |
Author(s) |
|
1. |
Effects of Flux Level on a CSI-fed
Field-Oriented Induction Motor |
IEE Proc. On Electr.
Power
Appl.,
UK,
Vol.144,No5, pp295-300. |
Sep.,1997,
UK |
B.C.Ghosh
and S.N.Bhadra |
|
2. |
On Line Rotor Resistance Identification of a
Vector Controlled Induction Motor Drive |
Journal of IEB(EE),
Vol.EE23, No.I & II, pp.37-49. |
Dec.1995
Bangladesh |
B.C.Ghosh,
M.M.A. Hashem and S.N.
Bhadra. |
|
3. |
Bond Graph Simulation of a Current Source
Inverter Induction Motor(CSI-IM) System. |
Electric Machines and Power System, Vol.21/1,
pp51-67. |
1993
USA. |
B.C.Ghosh
and S.N.Bhadra |
|
4. |
Computer-Aided Design of Non-Segmented
Synchronous Reluctance Motor (SRM) |
Journal of IEB, Vol.15, No.3, pp.27-33. |
1987
Bangladesh. |
B.C.Ghosh
and E.Basher |
|
5. |
Torque Component Current-based Rotor
Resistance Adaptation Scheme of an Induction Motor Drive. |
Journal of IEB (EE), Vol.-24 No. I & II, pp
111-116 |
1996
Bangladesh |
B. C. Ghosh |
|
6. |
Microprocessor based Precision Speed
Measurement. |
Journal of IEB (EE) Vol. 25, No. I & II |
1997
Bangladesh |
B. C. Ghosh and M.M.A.
Hashem |
|
7. |
Nodal Method based Simulation of a Current
Source Inverter Induction Motor (CSI-IM) Drive. |
Journal of IEB (EE) Vol. 25, No. I & II |
1997
Bangladesh |
B. C. Ghosh, N.N. Mollah,
M. A. Rashid and S. N. Bhadra. |
|
8. |
Degradation in Dynamic Performance of a
Vector Controlled
Induction Motor Drive
due to Deviation of Parameters. |
Journal of IEB (EE) Vol. 25, No. I & II |
1997
Bangladesh |
B.C. Ghosh, M. M. Islam and M.A.
Rafiq |
|
9. |
Rotor Flux Observer based Indirect Vector
Controlled Induction Motor Drive. |
Journal of Electric-cal Engineering, IEB Vol.
EE 27, No. I, pp 29-36. |
1999
Bangladesh |
Md.
Abdur Rafiq, B.C. Ghosh,
Md.Monirul Islam andM.M.H.
Rahman.
|
|
10. |
Fuzzy Logic Versus P-I Control of Separately
Excited
DC Motor Drive-A
Comparison. |
Journal of Electric-cal Engineering, IEB Vol.
EE 27, No. I, pp 37-42. |
1999
Bangladesh |
B. C. Ghosh, M. M. Islam, M.M.H.
Rahman, and M.A.S. Kamal |
|
11. |
Fuzzy Logic Enhanced Indirect Vector Control
of Induction Motor Drives. |
Journal of Electrical Engineering, IEB Vol.
EE 27, No. II, pp 35-38. |
1999
Bangladesh |
M.A.S.
Kamal,Md.
Abdur
Rafiq, Md.Monirul
Islam and B.C. Ghosh.
|
|
12. |
Reduced Order observer based Field
Orientation Control and Parameter Adaptation of Induction Motor |
Journal of Electrical Engineering,
IEB vol. 29, No. I, pp 39-45. |
June,2001
Bangladesh |
Md. Abdur
Rafiq and B. C. Ghosh. |
|
13. |
Adaptive Fuzzy-Artificial Neural Network
based speed controller of DC motor |
Journal of Electrical Engineering, IEB, Vol.
EE 31, No. I & II, pp 20-26. |
December, 2004
Bangladesh |
Md.Golam
Sarwer, Md. Abdur
Rafiq and B. C. Ghosh. |
|
14. |
Sliding Mode Speed Controller of a
DC Motor Drive |
Journal of Electrical Engineering, IEB, Vol.
EE 31, No. I & II, pp 45-49 |
December 2004
Bangladesh |
Md.Golam
Sarwer, Md. Abdur
Rafiq and B. C. Ghosh. |
|
15. |
A Zero-Voltage Zero-Current Switching
Controlled Partial Series Resonant AC-to-DC Converter with Improved Power
Factor |
Journal of Electrical Engineering, IEB, Vol.
EE 32, No. I & II, pp 8-12. |
December 2005
Bangladesh |
Md.Nazmul
Hasan, Md.Monirul
Islam, B.C.Ghosh |
|
16. |
PC-based Rotor Resistance Tuning Technique
for the Indirect Field Orientation of an
Induction Motor. |
Journal of Electrical Engineering, IEB, Vol.
EE 32, No. I & II, pp 32-37. |
December 2005
Bangladesh |
Manoj
Datta,
Md.
Abdur Rafiq and Dr.
B.C. Ghosh |
|
17. |
Chattering Free Neuro
Sliding Mode Controller of DC Drives |
Journal of Electrical Engineering, IEB, Vol.
EE 32, No. I & II, pp 25-31. |
December 2005
Bangladesh |
Mohammed Golam
Sarwer, Md. Abdur
Rafiq and Dr. B.C. Ghosh |
|
18. |
Model Reference Control
of Speed-Sensorless Induction Motor Drives
|
Journal of Electrical Engineering, IEB, Vol.
EE 32, No. I & II, pp 56-61. |
December 2005
Bangladesh |
Md. Abdur
Rafiq Mohammed Golam
Sarwer, R.Ahsan and
Dr. B.C. Ghosh |
|
19. |
Fast Speed Response
Field-Oriented control of Induction Motor Drive with Adaptive Neural
Integral |
Journal of Electrical & Electronics
Engineering,
Istambul
University,
Vol.6, No. 2, pp 229-235. |
2006
Istanbul |
Md. Abdur
Rafiq Mohammed Golam
Sarwer and B.C. Ghosh |
|
20. |
High Performance
Decoupling Control of Induction motor with Modified Adaptive Neural
Integration Based Rotor Flux Estimator |
Journal of Electrical Engineering, IEB, Vol.
EE 33, No. I & II, pp 3-8. |
December 2006
Bangladesh |
Manoj
Datta,
Md.
Abdur Rafiq and
B.C. Ghosh |
|
21. |
Fuzzy Logic Enhanced
Fast Speed Response Control of
Interior Permanent Magnet
Synchronous Motor Drive |
IETECH Journal of Electrical Analysis, vol.2,No.4,pp.244-249. |
2008 |
Naruttam
Kumar Roy, Md. Abdur Rafiq,
Rajib Kundu
and B.C. Ghosh |
b) National and
International Conference Proceedings
(Papers Communicated recently are not shown):
|
Sl.No. |
Title of Paper |
Name of Conference, page position, etc. |
Year and Country |
Authors |
|
1. |
DC Link Voltage based Rotor Resistance
Adapta-tion Scheme of a Field Oriented CSI-IM
Drive System. |
Conf. Rec. ELROMA-92,
Bombay,
Vol. IIA, pp 15-19. |
1992
India |
B. C. Ghosh, S. N.
Bhadra |
|
2. |
Controller Design and Robust Stability Study
of a CSI-fed Induction Motor under Field Orientation Control. |
Proc. National Systems Conference NSC-91,
Roorkee,
India,
1992. pp 225-229. |
1992
India |
 
| Tags: |
Adaptive fuzzy - Network Based Speed Controller - DC Motor Drive - |
| Research Documents: |
|
| Related research: |
Full-wave rectifier uses current-feedback amps, Goal of high-yield fusion reactor, Major obstacle from mass production of tiny circuits has removed by researchers., MIT researchers developed Energy-efficient tiny gas sensor that could quickly detect hazardous chemicals, New link of demonstration which relates between cognition and execution, Observability and observer design for kinetic networks, PID Controller, Re-engineered battery material could lead to rapid recharging of many devices : Beltway for electrical energy solves long-standing problem, Researchers say data transmission rate of copper cables be increased, Resolves Einstein’s Twin Paradox : LSU Professor, Scientists have Shown that a Chunk of Hematite Can Conduct Electrons Under Certain Chemical Conditions, The largest fusion experiments in the world : cutting edge of plasma physics.
|
|
|
