Recurrent fuzzy neural network by using feedback error learning approaches for LFC in interconnected power system

Energy Conversion and Management

Volumn 50, Issue 4, 2009, Pages 938-946

  Sabahi, Kamel ^a   Teshnehlab, Mohammad ^a   shoorhedeli, Mahdi Aliyari ^a  

^a K N TOOSI UNIVERSITY OF TECHNOLOGY   (Iran)

Author keywords

Feedback error learning; Load frequency control; Recurrent fuzzy neural network; Supervised controller

Indexed keywords

ASYMPTOTIC STABILITY; CONTROLLERS; EDUCATION; ELECTRIC CONTROL EQUIPMENT; ELECTRIC FREQUENCY CONTROL; ELECTRIC LOAD MANAGEMENT; ELECTRIC POWER TRANSMISSION NETWORKS; FEEDBACK; FREE ELECTRON LASERS; FUZZY NEURAL NETWORKS; NONLINEAR CONTROL SYSTEMS; POWER TRANSMISSION; PRESS LOAD CONTROL; PROPORTIONAL CONTROL SYSTEMS; SYSTEM STABILITY; TABLE LOOKUP;

ABRUPT CHANGES; ADAPTIVE CONTROLLERS; CONTROL PERFORMANCE; CONTROLLED SYSTEMS; CONVENTIONAL CONTROLLERS; FEED-FORWARD CONTROLLERS; FEEDBACK CONTROLLERS; FEEDBACK ERROR LEARNING; FEEDBACK PATHS; FEEDFORWARD; GLOBAL ASYMPTOTIC STABILITIES; GLOBAL STABILITIES; INTERCONNECTED POWER SYSTEMS; LOAD FREQUENCY CONTROL; LOOK-UP TABLES; OPERATING CONDITIONS; PERFORMANCE INDEXES; PID CONTROLLERS; PID PARAMETERS; POWER SYSTEMS; PROPORTIONAL , INTEGRAL AND DERIVATIVE CONTROLLERS; RECURRENT FUZZY NEURAL NETWORK; REFERENCE SIGNALS; SUPERVISED CONTROLLER;

FUZZY CONTROL;

EID: 61449155324     PISSN: 01968904     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.enconman.2008.12.028     Document Type: Article

References (33)

1. Saadat H. Power system analysis (2002), McGraw-Hill
2. Kundur P. Power system stability and control (1994), McGraw-Hill, New York
3. Aldeen M., and Trinh H. Load-frequency control of interconnected powersystems via constrained feedback control schemes. Comput Electr Eng 20 1 (1994) 71-88
4. Vajk I., et al. Adaptive load-frequency control of the Hungarian power system. Automatica 21 2 (1985) 129-137
5. Yamashita K, Miyagi H. Multivariable self tuning regulator for load frequency control system with interaction of voltage on load demand, IEEE Proceedings-D, vol. 138, no. 2, March 1991.
6. Pan C.T., and Liaw C.M. An adaptive controller for power systemload-frequency control. IEEE Trans Power Syst 4 1 (1989) 122-128
7. Zribi M., Al-Rashed M., and Alrifai M. Adaptive decentralized load frequency control of multi-area power systems. Electr Power Energy Syst 27 (2005) 575-583
8. Zeynelgil H.L., Demiroren A., and Sengor N.S. The Application of ANN technique to automatic generation control for multi-area power system. Electr Power Energy Syst 24 (2002) 354-545
9. Shayeghi H., Shayanfar H.A., and Malik O.P. Application of ANN technique based on μ-synthesis to load frequency control of interconnected power system. Electr Power Energy Syst 28 7 (2006) 503-511
10. Ashraf Mohamed H. Wavelet neural network load frequency controller. Energy Convers Manage 46 9-10 (2005) 1613-1630
11. Chaturvedi D.K., Satsangi P.S., and Kalra P.K. Load frequency control: a generalised neural network approach. Int J Electr Power Energy Syst 21 6 (1999) 405-415
12. Cam E., and Kocaarslan I. A fuzzy gain scheduling PI controller application for an interconnected electrical power system. Electr Power Syst Res 73 3 (2005) 267-274
13. Chang C.S., and Fu W. Area load frequency control using fuzzy gain scheduling of PI controllers. Electr Power Syst Res 42 2 (1997) 145-152
14. Ertugrul C., and İlhan K. Load frequency control in two area power systems using fuzzy logic controller. Energy Convers Manage 46 2 (2005) 233-243
15. Talaq J., and Al-Basri F. Adaptive fuzzy gain scheduling for load-frequency control. IEEE Trans Power Syst 14 1 (1999) 145-150
16. Adel A. Adaptive optimal gain scheduling for theload frequency control problem. Electr Power Compos Syst 30 (2002) 45-56
17. Ghoshal S.P. Optimizations of PID gains by particle swarm optimizations in fuzzy based automatic generation control. Electr Power Syst Res 72 3 (2004) 203-212
18. Jun N., and Stefan S. Feedback error learning and nonlinear adaptive control. Neural Networks 17 10 (2004) 1453-1465
19. Yesil E., Gouzelkaya M., and Eksin I. Self tuning fuzzy PID type load and frequency controller. Energy Convers Manage 45 3 (2004) 377-390
20. Kawato M. A hierarchical neural-network model for control and learning of voluntary movement. Biol Cybern 57 (1987) 169-185
21. Aiko M., and Hidenori K. Stability of feedback error learning scheme. Syst Control Lett 45 4 (2002) 303-316
22. Aiko Miyamura I. Stability of feedback error learning method with time delay. Neurocomputing 69 13-15 (2006) 1645-1654
23. Sabahi K, Nekoui MA, Teshnehlab M, Aliyari M, Mansouri M. Load frequency control in interconnectedpower system using modified dynamicneural networks. In: 15th Meditaranaen conference on control & automation, July 27-29, Athena, Greece; 2007.
24. Luo ZW, Fujii S, Saitoh Y, Muramatsu E, Watanabe K. Feedback-error learning for explicit force control of a robot manipulator interacting with unknown dynamic environment. In: Proceedings of the IEEE international conference on robotics and biomimetics, vol. 2; 2004. p. 262-7.
25. Ruan X., Ding M., Gong D., and Qiao J. On-line adaptive control for inverted pendulum balancing based on feedback-error-learning. Neurocomputing 70 4-6 (2007) 770-776
26. Wang L.X. A course in fuzzy systems and control (1997), Prentice-Hall, Upper Saddle River (NJ)
27. Narendra K.S., and Parthasarathy K. Identification and control of dynamical systems using neural networks. IEEE Trans Neural Network 1 1 (1990) 4-27
28. Lin F.-J., Wai R.-J., and Chen H.-P. A PM synchronous servo motor drive with an on-line trained fuzzy neural network controller. IEEE Trans Energy Convers 13 4 (1998)
29. Leu Y.G., Lee T.T., and Wang W.Y. On-line turning of fuzzy-neural network for adaptive control of non-linear dynamical systems. IEEE Trans SMC 27 6 (1997) 1034-1043
30. Wai R.J., and Lin F.J. Fuzzy-neural network sliding-mode position controller for induction servo motor drive. IEE Proc Electr Power Appl 146 3 (1999) 297-308
31. Lin F.-J., Wang D.-H., and Huang P.-K. RFNN controlled sensorless induction spindle motor drive. Electr Power Syst Res 70 (2004) 211-222
32. Zhanga Q.-Z., Ganb W.-S., and Zhoua Y.-l. Adaptive recurrent fuzzy neural networks for active noise control. J Sound Vibration 296 (2006) 935-948
33. Lee C.-H., and Teng C.-C. Identification and control of dynamic systems using recurrent fuzzy neural networks. IEEE Trans Fuzzy syst 8 4 (2000)