Virtual lab for artificial intelligence controllers based speed control for induction motor
Virtual lab for artificial intelligence controllers based speed control for induction motor
Practical implementation has an important role in engineering education. Practical implementations, however, may not be possible insome situations, such as lack of physical possibilities, the presence of situations that may create risks during implementation, or placetimedependence. So, package programs are developed for the virtual practical implementation experience. On the other hand, thesetools may not be flexible and interactive enough for all branches of science. Therefore, in this study a virtual laboratory tool wasdeveloped for the speed control of an induction motor fed by a three-level inverter. The user can select proportional-integral,proportional–integral–derivative, fuzzy logic, artificial neural network, and neuro-fuzzy controllers for the speed controller. Differentworking conditions for the induction motor can be simulated and the outcomes can be observed by the users. The virtual laboratoryhad a flexible interface and it was written on Microsoft Visual Studio 2015 IDE using C# programming language on WindowsPresentation Foundation infrastructure
___
- Deperlioğlu, Ö., Köse, U. 2011. An educational tool for
artificial neural networks. Computers & Electrical
Engineering, 37(3): 392–402, 2011.
DOI:10.1016/j.compeleceng.2011.03.010
- Sevgi, L. 2006. Modeling and simulation concepts in
engineering education: virtual tools. Turkish Journal of
Electrical Engineering & Computer Sciences, 14(1): 113–
127, 2006.
- Öztürk, N., Çelik, E. 2014. An educational tool for the
genetic algorithm-based fuzzy logic controller of a
permanent magnet synchronous motor drive. International
Journal of Electrical Engineering Education, 51(3): 218–231,
2014. DOI:10.7227/ijeee.51.3.4
- Potkonjak V., Gardner, M., Callaghan, V., Mattila, P., Guetl,
C., Petrović, VM., Jovanović, K. 2016. Virtual laboratories
for education in science, technology, and engineering: A
review. Computers & Education, 95: 309–327, 2016.
DOI:10.1016/j.compedu.2016.02.002
- Keyhani, MN., Marwali, LE., Higuera, G., Athalye, G.,
Baum-gartner. 2002. An integrated virtual learning system
for the development of motor drive systems. IEEE Trans.on
Power Systems, 17(1): 1–6, 2002. DOI:10.1109/59.982185
- Köse, U., Deperlioğlu, Ö. 2015. FL-LAB v2: Design and
Development of an Easy-to-Use, Interactive Fuzzy Logic
Control Software System. Applied Mathematics &
Information Sciences, 9(2): 883–897, 2015.
DOI:10.12785/amis/090237
- Avouris, NM., Tselios, N., Tatakis, EC. 2001. Development
and evaluation of a computer-based laboratory teaching tool.
Computer Applications in Engineering Education, 9(1): 8–
19, 2001. DOI:10.1002/cae.1001
- Kayıslı, K., Tuncer, S., Poyraz, M. 2013. An educational tool
for fundamental DC–DC converter circuits and active power
factor correction applications. Computer Applications in
Engineering Education, 21(1): 113-134, 2013.
DOI:10.1002/cae.20455
- Yigit, T., Elmas, Ç. 2008. An educational tool for controlling
SRM. Computer Applications in Engineering Education,
16(4): 268–279, 2008. DOI:10.1002/cae.20148
- Koku, AB., Kaynak, O. 2001. An internet-assisted
experimental environment suitable for the reinforcement on
undergraduate teaching of advanced control techniques,
IEEE Trans. on Education, 44(1): 24–28, 2001. DOI:
10.1109/13.912706
- Altas, IH., Aydar, H. 2008. A real time computer controlled
simulator for control systems. Computer Applications in
Engineering Education, 16(2): 115–126, 2008.
DOI:10.1002/cae.20130
- Gökbulut, M., Bal, C., Dandıl, B. 2006. A virtual electrical
drive control laboratory: neuro–fuzzy control of induction
motors. Computer Applications in Engineering Education,
14(3): 211–221, 2006. DOI:10.1002/cae.20130
- Bingöl, O., Paçacı, S. 2012. A virtual laboratory for neural
network controlled DC motors based on a DC-DC buck
converter. The International Journal of Engineering
Education, 28(3): 713–723, 2012.
- Bingöl, O., Paçacı, S. 2010. A virtual laboratory for fuzzy
logic controlled DC motors. International Journal of Physical
Sciences, 5(16): 2493–2502, 2010.
- Sobczuk, DL. 2007. Internet based teaching of pulse width
modulation for three-level converters. EUROCON The
International Conference on “Computer as a Tool” Warsaw,
September 9-12: 2479–2484, 2007.
DOI:10.1109/eurcon.2007.4400592
- Boldea İ., Nasar, SA. 1992. Vector control of AC drives.
CRC Press, New York.
- Wai RJ., Chang, HH. 2004. Backstepping wavelet neural
network control for indirect field-oriented induction motor
drive. IEEE Trans. on Neural Networks, 15(2): 367–382,
2004. DOI:10.1109/tnn.2004.824411
- Akçayol, MA., Çetin, A., Elmas, Ç. 2002. An educational
tool for fuzzy logic-controlled BDCM. IEEE Trans. on
Education, 45(1): 33–42, 2002. DOI:10.1109/13.983219
- Kaiser, MS., Chowdhury, ZI., Al Mamun, S., Hussain, A.,
Mahmud, M. 2016. A neuro-fuzzy control system based on
feature extraction of surface electromyogram signal for solarpowered
wheelchair. Cognitive Computation, 8(5), 946-954,
2016. DOI:10.1007/s12559-016-9398-4
- Sun, J., Li, Z. 2015. Development and Implementation of a
wheeled inverted pendulum vehicle using adaptive neural
control with extreme learning machines. Cognitive
Computation, 7(6), 740-752, 2015. DOI:10.1007/s12559-
015-9363-7
- Öztürk, N., Çelik, E. 2012. Speed control of permanent
magnet synchronous motors using fuzzy controller based on
genetic algorithms. International Journal of Electrical Power
& Energy Systems, 43(1): 889–898, 2012.
DOI:10.1016/j.ijepes.2012.06.013
- Weerasooriya, S., El-Sharkawi, M. 1991. Identification and
control of a dc motor using back-propagation neural
networks. IEEE Trans. Energy Conversion, 6(4): 663–669,
1991. DOI:10.1109/60.103639
- Narendra, KS., Parthasarathy, K. 1990. Identification and
control of dynamical systems using neural networks. IEEE
Trans. on Neural Networks, 1(1): 1–27, 1990.
DOI:10.1109/72.80202
- Lee YH., Suh, BS., Hyun, DS. 1994. A novel PWM scheme
for a three-level voltage source inverter with GTO thyristors.
IEEE Trans. on Industry Applications, 32(2): 260–268, 1994.
DOI:10.1109/ias.1994.377573
- Lai, JS., Peng, FZ. 1996. Multilevel converters-A new breed
of power converters. IEEE Trans. on Industry Applications,
32(3): 509–517, 1996. DOI:10.1109/ias.1995.530601
- Nabae, A., Takahashi, I., Akagi, H. 1981. A new neutralpoint-clamped
PWM inverter. IEEE Trans. on Industry
Applications, IA-17: 518–523, 1981.
DOI:10.1109/tia.1981.4503992
- Rodriguez, J., Lai, JS., Peng, FZ. 2002. Multilevel
inverters: A survey of topologies, controls, and applications.
IEEE Trans. on Industrial Electronics, 49(4): 724–738, 2002.
DOI:10.1109/tie.2002.801052
- Lin, BR., Lu, HH. 1999. Multilevel AC/DC/AC converter
for AC drives. Electric Power Applications, IEE Proceedings.
146(4): 397–406, 1999. DOI:10.1049/ip-epa:19990253
- VanDer Broeck, HW., Skudelny, HC., Stanke, GV. 1988.
Analysis and realization of a pulse width modulator based on
voltage space vectors. IEEE Trans. on Industry Applications,
24(1): 142–150, 1988. DOI:10.1109/28.87265
- Celanovic, N., Boroyevich, D. 2000. A comprehensive
study of neural-point voltage balancing problem in threelevel
neutral-point-clamped voltage source PWM inverters.
IEEE Trans. on Power Electronics, 15(2): 242–249, 2000.
DOI:10.1109/apec.1999.749733
- Yamanaka, K., Hava, AM., Kirino, H., Tanaka, Y., Koga,
N., Kume, T. 2002. A novel neutral point potentail
stabilization technique using the information of output
current polarities and voltage vector. IEEE Trans. on Industry
Applications, 38(6): 1572–1580, 2002.
DOI:10.1109/ias.2001.955552
- Zadeh, LA. 1965. Fuzzy sets, in Information and Control.
New York: Academic, 8: 338–353, 1965.
DOI:10.1016/s0019-9958(65)90241-x
- Elmas, Ç., Sağıroğlu, Ş., Çolak, İ., Bal, G. 1994. Nonlinear
modelling of a switched reluctance drive based on neural
networks. IEEE Melecon 94, 7th Mediterranean
Electrotechnical Conference, 2: 809–812, 1994.
DOI:10.1109/melcon.1994.380979
- Elmas, Ç. 2011. Artificial Intelligence Applications:
Artificial Neural Networks, Fuzzy Logic and Genetic
Algorithm, Seçkin Press, Ankara, 1–424, 2011.
- Elmas, Ç., Üstün, O., Sayan, HH. 2008. A neuro-fuzzy
controller for speed control of a permanent magnet
synchronous motor drive. Expert Systems with Applications,
34(1): 657–664, 2008. DOI:10.1016/j.eswa.2006.10.002
- Elmas, Ç., Üstün, O. 2008. A hybrid controller for the speed
control of a permanent magnet synchronous motor drive.
Control Engineering Practice, 16(3): 260–270, 2008.
DOI:10.1016/j.conengprac.2007.04.016