references - Shodhganga

advertisement
162
REFERENCES
1.
Al-Olimat, S, Ghandakly, AA & Kamalasadan, SK 2007, ‘Induction
motor speed control via fuzzy logic modification of reference model’,
in Proc IEEE PES, pp. 1-7.
2.
Amiri, M, Feyzi, M & Saberi, H 2013, ‘A Modified Torque Control
Approach For Load Sharing Application Using V/f Induction Motor
Drives’, Power Electronics, Drive Systems and Technologies IEEE
Conference, pp.1-6.
3.
Arab Markadeh, GR, Ehsan Daryabeigi, Caro Lucas &
Azizur Rahman, M 2011, ‘Speed and Flux Control of Induction Motors
Using Emotional Intelligent Controller’, IEEE Transactions on
Industry Applications, vol. 47, no. 3, pp. 1126-1135.
4.
Arulmozhiyal, R & Baskaran, K 2009, ‘Space Vector Pulse Width
Modulation Based Speed Control of Induction Motor using Fuzzy PI
Controller’, International Journal of Computer and Electrical
Engineering, vol. 1, no. 1, pp. 1793-8198.
5.
Arunapriya, P 2012, ‘Implementation of Embedded based Fuzzy
system for Induction motor V/f speed control’, International Journal of
Scientific &Engineering Research’, vol. 3, no. 6,
6.
Bose, BK 1994, ‘Expert system, fuzzy logic, and neural network
applications in power electronics and motion control’, Proc IEEE,
vol. 82, no. 8, pp. 1303-1323.
7.
Bose, BK 2007, ‘Neural network applications in power electronics and
motor drives, An introduction and perspective’, IEEE Trans Ind
Electron, vol. 54, no. 1, pp. 14-33.
8.
Buja, GS & Kazmierkowski, MP 2004, ‘Direct torque control of PWM
inverter-fed AC motors—A survey’, IEEE Trans Ind Electron, vol. 51,
no. 4, pp. 744-757.
163
9.
Casadei, D, Profumo, F, Serra, G, Tani, A, FOC & DTC 2002, ‘Two
viable schemes for induction motors torque control’, IEEE Trans
Power Electron, vol.17, no.5, pp.779–787.
10.
Chen, TC & Sheu, TT 2002, ‘Model referencing neural network
controller for induction motor speed control’, IEEE Trans Energy
Convers, vol. 17, no. 2, pp. 157-163.
11.
Chimurkar, SS & Tarnekar, SG 2011, ‘Torque Control of I. M. using
V/ f Method’, International Journal Of Advances In Engineering
Sciences, vol.1, no.1, pp.44-49.
12.
Datta, Manoj, Rafiq, MD, Abdur & Ghosh, BC 2007, ‘Genetic
Algorithm Based Fast Speed Response Induction Motor Drive without
Speed Encoder’, Proceedings of International Conference on Power
Engineering, Energy and Electrical Drives, pp. 146-151.
13.
De Doncker, R, Profumo, F & Tenconi, A 1993, ‘The universal field
oriented (UFO) controller in the air gap reference frame’, J Inst Elect
Eng, vol. 113, no. 4, pp. 477-486.
14.
Dong, L & Izquierdo, E 2007, ‘A biologically inspired system for
classification of natural images’, IEEE Trans Circuits Syst Video
Technology, vol. 17, no. 5, pp. 590-603.
15.
Dorrah, HT, El-Garhy, AM, El-Shimy, ME 2011, ‘PSO-BELBIC
scheme for two-coupled distillation colum process’, Journal of
Advanced Research, vol. 2, no. 1, pp. 73-83.
16.
Eissa, MM & Virk, GS 2013, ‘Optimum Induction Motor Speed
Control Technique Using Particle Swarm Optimization’, International
Journal of Energy Engineering, vol. 3, no 2, pp. 65-73.
17.
Eissa, MM, Virk, GS, AbdelGhany, A & Ghith, ES 2013, ‘Optimum
Induction Motor Speed Control Technique Using Genetic Algorithm’,
American Journal of Intelligent Systems, vol. 3, no. 1, pp. 1-12,
18.
Emmanuel Delaleau & Jean-Paul Louis_Romeo Ortega 2001,
‘Modeling and Control of Induction Motors’, Int. J. Appl. Math.
Comput. Sci., vol.11, no.1, pp. 105-129.
19.
Guzinski Gdansk, J, Poland & Abu-Rub, H 2013, ‘Speed sensorless
induction motor drive with predictive current controller’, IEEE
transactions on industrial electronics, vol.60, no. 2, pp.699 – 709.
164
20.
Jamali, MR, Arami, A, Dehyadegari, M, Lucas, C & Navabi, Z 2009,
‘Emotion on FPGA: Model driven approach’, International Journal of
expert systems with applications, vol. 36, no. 4, pp.7369-7378.
21.
Jamali, MR, Arami, A, Dehyadegari, M, Lucas, C & Navabi, Z 2010,
‘Real-time embedded emotional controller’ Neural Computing and
Applications , vol.19, no.1, pp.13-19.
22.
Jamali, MR, Arami, A, Hosseini, B, Moshiri, B & Lucas, C 2008,
‘Real time emotional control for anti-swing and positioning control of
SIMO overhead traveling crane’, Int J Innovative Comput Inf Control,
vol. 4, no. 9, pp. 2333-2344.
23.
Jamali, MR, Valadbeigi, M, Dehyadegari, M, Navabi, Z & Lucas, C
2007, ‘Toward embedded emotionally intelligent system’, in Proc
IEEE EWDTS, pp. 51-56.
24.
Jung, JW, Kim, TH & Choi, HH 2010, ‘Speed control of a permanent
magnet synchronous motor with a torque observer: a fuzzy approach’,
IET Control Theory Appl, vol. 4, no. 12, pp. 2971-2981.
25.
Kadri, F, Djarah, D & Drid, S 2010, ‘Neural Network Direct Torque
Control of Induction Motor Fed by Three Phase PWM Inverter’,
Proceeding of International Congress on Models, Optimization and
Security of Systems, pp. 22-28.
26.
Karanayi, B, Rahman, MF & Grantham, C 2007, ‘Online stator and
rotor resistance estimation scheme using artificial neural networks for
vector controlled speed sensorless induction motor drive’, IEEE Trans
Ind Electron, vol. 54, no. 1, pp. 167-176.
27.
Kazmierkowski, MP & Sobczuk, DL 1996, ‘Sliding mode feedback
linearized control of PWM inverter-fed induction motor’, in Proc IEEE
IECON, Taipei, Taiwan, pp. 244–249.
28.
Kennedy, J & Eberhart, RC 1995, ‘Particle swarm optimization’, In,
Proceedings-IEEE International Conference on Neural Networks
(ICNN),Perth, Australia, vol. 4, pp.1942–1948.
29.
Kim, SH, Park, TS, Yoo, JY & Park, GT 2001, ‘Speed sensorless
vector control of an induction motor using neural network speed
estimation’, IEEE Trans Ind Electron vol. 48, no. 3, pp. 609-614.
165
30.
Kumar, Y, Soni & Bhatt, R 2013, ‘Simulated Annealing optimized PID
Controller design using ISE, IAE, IATE and MSE error criteria’,
International Journal of Advanced Research in Computer Engineering
& Technology, vol. 2, no.7, pp. 2337–2340.
31.
Kumar, Y, Soni & Bhatt, R 2013, ‘Simulated Annealing optimized PID
Controller design using ISE, IAE, IATE and MSE error criteria’,
International Journal of Advanced Research in Computer Engineering
& Technology, vol. 2, no. 7, pp. 2337-2340.
32.
Kusagur, L, Kodad, SF & Sankar Ram, BV 2009, ‘Modeling of
induction motor & control of Speed using hybrid controller
technology’, Journal of Theoretical and Applied Information
Technology, vol.10, no.2, pp.117–126.
33.
Kwan CM & Lewis, FL 2000, ‘Robust back stepping control of
induction motors using neural networks’, IEEE Trans Neural Netw,
vol. 11, no.5, pp. 1178–1187.
34.
Lin, FJ, Fung, RF & Wai, RJ 1998, ‘Comparison of slidingmode and
fuzzy neural network control for motor-toggle servomechanism’,
IEEE/ASME Trans Mechatronics, vol. 3, no. 4, pp. 302-318.
35.
Lin, FJ, Huang & PK, 2006, ‘Recurrent Fuzzy Neural Network Using
Genetic Algorithm for Linear Induction Motor Servo Drive’, IEEE
Conference on Industrial Electronics and Applications, pp. 1-6.
36.
Lopez, JC, Romeral, L, Arias, A & Aldabas, E 2006, ‘Novel fuzzy
adaptive sensorless induction motor drive’, IEEE Trans Ind Electron,
vol. 53, no. 4, pp. 1170-1178.
37.
Lucas, C, Mohammadi, R & Araabi, BN 2006, ‘Intelligent modeling
and control of washing machine using LLNF modeling and modified
BELBIC’, Asian Journal of Control, vol. 8, no. 4, pp. 393-400.
38.
Lucas, C, Shahmirzadi, D & Sheikholeslami, N 2004, ‘Introducing
BELBIC: Brain emotional learning based intelligent control’, Int. J.
Intell,Automat, Soft Comput, vol. 10, no. 1, pp. 11-22.
39.
Marcelo Suetake, Ivan, N & Da Silva, 2011, ‘Embedded DSP-Based
Compact Fuzzy System and Its Application for Induction Motor V/f
Speed Control’, IEEE Transactions on Industrial Electronics, vol. 58,
no. 3, pp. 750-760.
166
40.
Marino, R, Peresada, S & Valigi, P 1993, ‘Adaptive input–output
linearizing control of induction motors’, IEEE Trans Autom Control,
vol. 38, no. 2, pp. 208-220.
41.
Mehrabian, AR & Lucas, C 2005, ‘Emotional Learning Based
Intelligent Robust Adaptive Controller for Stable Uncertain Nonlinear
Systems’, International Journal of Intelligent Technology (IJIT), vol. 1
no.4, pp. 34-40.
42.
Mehrabian, AR, Lucas, C & Roshanian, J 2006, ‘Aerospace launch
vehicle control: An intelligent adaptive approach’, Aerospace Science
and Technology, vol. 10, no. 2, pp. 149-155.
43.
Milasi, RM, Jamali, MR & Lucas, C 2007, ‘Intelligent washing
machine A bioinspired and multi-objective approach’, Int J Control
Automat Syst, vol. 5, no. 4, pp. 436-443.
44.
Milasi, RM, Lucas, C & Araabi, BN 2006, ‘Intelligent modeling and
control of washing machine using locally linear neurofuzzy (LLNF)
modeling and modified brain emotional learning based intelligent
controller (BELBIC)’, Asian J Control, vol. 8, no. 4, pp. 393-400.
45.
Mohamadian, M, Nowicki, E, Ashrafzadeh, F, Chu, A, Sachdeva, R &
Evanik 2003, ‘Anovel neural network controller and its efficient DSP
implementation for vector controlled induction motor drives’, IEEE
Trans Ind Appl, vol. 39, no.6, pp. 1622–1629.
46.
Mohammadi, R, Lucas, C & Araabi, BN 2004, ‘A novel controller for
a power system based BELBIC’, Proceedings of World Automation
Congress, vol.18, pp. 409-420.
47.
Moren Emotion & learning, 2002, ‘A computational model of the
Amygdala’, Ph. D. dissertation, Lund Univ., Lund, Sweden,
pp. 1101-8453.
48.
Moren, J & Balkenius, C 2000, ‘A computational model of emotional
learning in the amygdala’, in Proc 6th Int Conf Simul Adapt Behav,
Cambridge, MA, pp. 411-436.
49.
Moren, J & Balkenius, C 2000, ‘Computational model of emotional
learning in the amygdala’, in Proc 6th Int Conf Simul Adapt Behav,
Cambridge, MA, pp. 411-436.
167
50.
Munira Batool & Aftab Ahmad 2013, ‘Mathematical Modeling and
Speed Torque Analysis of Three Phase Squirrel Cage Induction Motor
Using Matlab Simulink for Electrical Machines Laboratory’,
International Electrical Engineering Journal , vol. 4, no. 1, pp. 880-889.
51.
Naouar, MW, Monmasson, E, Naassani, AA, Slama-Belkhodja, I &
Patin, N 2007, ‘FPGA-based current controllers for AC machine
drives-A review’, IEEE Trans Ind Electron, vol. 54, no. 4,
pp. 1907–1925.
52.
Orlowska-Kowalska, T & Szabat, K 2007, ‘Control of the drive system
with stiff and elastic couplings using adaptive neurofuzzy approach’,
IEEE Trans Ind Electron, vol. 54, no. 1, pp. 228-240.
53.
Passino, KM 2002, ‘Biomimicry of bacterial foraging for distributed
optimization and control’, IEEE Control SystMag, vol. 22, no. 3,
pp. 52-67.
54.
Rahman, MA, Milasi, RM, Lucas, C, Arrabi, BN & Radwan, TS 2008,
‘Implementation of emotional controller for interior permanent magnet
synchronous motor drive’, IEEE Trans. Ind. Appl, vol.44, no.5,
pp. 1466–69.
55.
Rahman, MA, Milasi, RM, Lucas, C, Arrabi, BN & Radwan, TS 2008,
‘Implementation of emotional controller for interior permanent magnet
synchronous motor drive’, IEEE Trans Ind Appl, vol. 44, no. 5,
pp. 1466-1476.
56.
Rolls, ET 1999, ‘The Brain and Emotion’, Oxford Univ. Press,
London, UK.
57.
Rouhani, H, Jalili, M, Araabi, BN, Eppler, W & Lucas, C 2007, ‘Brain
emotional learning based intelligent controller applied to neuro-fuzzy
model of micro-heat exchanger’, Expert Systems with Applications,
vol. 32, no. 3, pp. 911-924.
58.
Rouhani, H, Jalili, M, Arabi, B, Eppler, W & Lucas, C 2007, Brain
emotional learning based intelligent controller applied to neuro fuzzy
model of micro-heat exchanger’, Expert Syst Appl, vol. 32, no. 3,
pp. 911-918.
168
59.
Safdar Fasal, TK & Unnikrishnan, L 2013, ‘A Performance Study of PI
controller and Fuzzy logic controller in V/f Control of Three Phase
Induction Motor Using Space Vector Modulation’ ITSI Transactions
on Electrical and Electronics Engineering, vol.1, no. 2, pp.121- 125.
60.
Sangsefidi, Y, Ziaeinejad, S & Shoulaie, A 2012, ‘A simple and lowcost method for three-phase induction motor control in high-speed
applications’, power electronics and drive systems technology IEEE
conference, pp. 212 – 217.
61.
Sheikholeslami, N, Shahmirzadi, D, Semsar, E, Lucas, C &
Yazdanpanah, MJ 2006, ‘Applying brain emotional learning algorithm
for multivariable control of HVAC systems’, J Intell Fuzzy Syst,
vol. 17, no. 1, pp. 35-46.
62.
Shi, TF, Chan, YK, Wong, KL & Ho, SL 2001, ‘Direct self control of
induction motor based on neural network’, IEEE Trans Ind Appl,
vol. 37, no. 5, pp. 1290-1298.
63.
Sifat Shah, A, Rashid, MKL & Bhatti 2012 ‘Direct Quadrate (D- Q)
Modeling of 3-Phase Induction Motor Using MatLab / Simulink’,
Canadian Journal on Electrical and Electronics Engineering, vol. 3,
no. 5, pp. 237-243.
64.
Siva Reddy, YV, Kumar, MV, Reddy, TB & Amarnath, J 2006, ‘Direct
torque control of induction motor based on state feedback and variable
structure fuzzy controllers’, in Proc IEEE Power India Conf, New
Delhi, India, pp. 1-5.
65.
Sujeet Kumar Soni & Anil Gupta, 2013, ‘Analysis of SVPWM Based
Speed Control of Induction Motor Drive with using V/F Control Based
3 Level Inverter’ International Journal of Scientific Engineering and
Technology, vol. 2, no. 9, pp. 932-938.
66.
Takahashi, I & Noguchi, N 1986, ‘A new quick response and high
efficiency control strategy of an induction motor’, IEEE Trans Ind
Appl IA , vol.22, no.5, pp. 820–827.
67.
Talukder, P, Soori, PK, Aranjo, B 2012, ‘Speed control of induction
motor drive using universal controller’, Power engineering and
optimization IEEE conference, Malaysia, pp. 504-514.
169
68.
Tan, WW & Huo, H 2005, ‘A generic neuro fuzzy model-based
approach for detecting faults in induction motors’, IEEE Trans Ind
Electron, vol. 52, no. 5, pp. 1420-1427.
69.
Uddin, MN & Hao Wen, 2007, ‘Development of a Self-Tuned NeuroFuzzy Controller for Induction Motor Drives’ , IEEE Transactions on
Industry Applications, vol. 43, no. 4, pp.1108-1116.
70.
Valizadeh, S, Jamali, MR & Lucas, C 2008, ‘A Particle-Swarm-Based
approach for Optimum Design BELBIC Controller in AVR System’,
International Conference on Control, Automation and Systems,
pp. 2679-2684.
71.
Wlas, M, Krzeminski, Z, Guzinski, J, Abu-Rub, H & Toliyat, HA
2005, ‘Artificial-neural-network-based sensorless nonlinear control of
induction motors’, IEEE Trans Energy Convers, vol. 20, no. 3,
pp. 520-528.
72.
Xiaodong Liang 2011, ‘Induction motor starting in practical industrial
applications’ IEEE Transactions on Industry Applications, vol.47,
no. 1, pp.271 – 280.
73.
Yashasvi, VM & Basawaraj Amarapur 2012, ‘Digital Signal
Processing Based Speed Control of Induction Motor Drive System’,
International Journal on Advanced Electrical and Electronics
Engineering, vol.1, no.1, pp.104-108.
74.
Yuhan Coll, WS, Cho, KM, Kim, S & Kim, HJ 2006, ‘Optimized
neural network speed control of induction motor using genetic
algorithm’, Proceedings of International Conference on Power
Electronics, Electrical Drives, Automation and Motion, pp. 146-151.
75.
Zahra Beheshti & Siti Zaiton Mohd Hashim, 2010, ‘A Review of
Emotional Learning and It’s Utilization in Control Engineering’, Int, J,
Advance, Soft Comput, vol. 2, no. 2, pp. 22.
76.
Zarchi, HA, Daryabeigi, E, Markadeh, GRA & Soltani, J 2011,
‘Emotional controller (BELBIC) based DTC for encoderless
Synchronous Reluctance Motor drives’, Power Electronics, Drive
Systems and Technologies Conference (PEDSTC). Tehran, Iran.
pp. 478-483.
170
77.
Zhao, J & Bose, BK 2004, ‘Neural network based waveform
processing and delayless filtering in power electronics and ac drives’,
IEEE Trans Ind Electron, vol. 51, no. 5, pp. 981-991.
78.
Ziyang, Z, Daobo, W & Zhisheng, W 2007, ‘Flight simulation servo
system based on learning based intelligent controller’, Proceedings of
the Fourth International Conference on Impulse and Hybrid Dynamic
Systems, pp. 1372-1375.
Download