New Online Self-Evolving Neuro Fuzzy controller based on the TaSe-NF model

Information Sciences

Volumn 220, Issue , 2013, Pages 226-243

  Cara, A B ^a   Herrera, L J ^a   Pomares, H ^a   Rojas, I ^a  

^a UNIVERSITY OF GRANADA   (Spain)

Author keywords

Evolving fuzzy controller; Evolving fuzzy system; Online control

Indexed keywords

CHANGING ENVIRONMENT; CONTROL PROBLEMS; ERROR SURFACE; EVOLVING FUZZY SYSTEMS; FUZZY CONTROLLERS; INTERPRETABILITY; INTERPRETABLE RULES; NEURO-FUZZY; NEURO-FUZZY CONTROLLER; ON-LINE CONTROLS; ONLINE EVOLUTION; ONLINE LOCAL LEARNING; PRIOR KNOWLEDGE;

DIFFERENTIAL EQUATIONS; FUZZY SYSTEMS;

CONTROLLERS;

EID: 84868488324     PISSN: 00200255     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.ins.2012.02.041     Document Type: Conference Paper

References (44)

1. P. Angelov A fuzzy controller with evolving structure Information Sciences 161 2004 21 35
2. J. de Barros, A. Dexter, Evolving fuzzy model-based adaptive control, in: IEEE International Conference on Fuzzy Systems, 2007. FUZZ-IEEE 2007, pp. 1-5.
3. D. Bellomo, D. Naso, and R. Babuska Adaptive fuzzy control of a non-linear servo-drive: theory and experimental results Engineering Applications of Artificial Intelligence 21 2008 846 857
4. M. Bikdash A highly interpretable form of sugeno inference systems IEEE Transactions on Fuzzy Systems 7 1999 686 696
5. L.G. Bleris, P.D. Vouzis, J.G. Garcia, M.G. Arnold, and M.V. Kothare Pathways for optimization-based drug delivery Control Engineering Practice 15 2007 1280 1291
6. A.B. Cara, Zs. Lendek, R. Babuska, H. Pomares, I. Rojas, Online self-organizing adaptive fuzzy controller: application to a nonlinear servo system, in: Proc. 2010 IEEE World Congress on Computational Intelligence, pp. 2491-2498.
7. A.B. Cara, H. Pomares, and I. Rojas A new methodology for the online adaptation of fuzzy self-structuring controllers IEEE Transactions on Fuzzy Systems 19 2011 449 464
8. A.B. Cara, H. Pomares, I. Rojas, Zs. Lendek, and R. Babuska Online self-evolving fuzzy controller with global learning capabilities Evolving Systems 1 2010 225 239
9. M. Chang An adaptive self-organizing fuzzy sliding mode controller for a 2-DOF rehabilitation robot actuated by pneumatic muscle actuators Control Engineering Practice 18 2010 13 22
10. C.H. Chen, C.J. Lin, and C.T. Lin Nonlinear system control using adaptive neural fuzzy networks based on a modified differential evolution IEEE Transactions on Systems, Man, and Cybernetics - Part C 39 2009 459 473
11. P. Chen, C. Hsu, T. Lee, and C. Wang Fuzzy-identification-based adaptive backstepping control using a self-organizing fuzzy system Soft Computing 13 2008 635 647
12. F. Doctor, H. Hagras, and V. Callaghan A type-2 fuzzy embedded agent to realise ambient intelligence in ubiquitous computing environments Information Sciences 171 2005 309 334
13. Y. Gao, and M.J. Er Online adaptive fuzzy neural identification and control of a class of MIMO nonlinear systems IEEE Transactions on Fuzzy Systems 11 2003 462 477
14. S. Guillaume Designing fuzzy inference systems from data: An interpretability-oriented review IEEE Transactions on Fuzzy Systems 9 2001 426 443
15. H. Hagras, F. Doctor, V. Callaghan, and A. Lopez An incremental adaptive life long learning approach for type-2 fuzzy embedded agents in ambient intelligent environments IEEE Transactions on Fuzzy Systems 15 2007 41 55
16. S. Haykin Neural Networks: A Comprehensive Foundation second ed. 1998 Prentice Hall
17. L.J. Herrera, H. Pomares, I. Rojas, A. Guillen, J. Gonzalez, M. Awad, and A. Herrera Multigrid-based fuzzy systems for time series prediction: CATS competition Neurocomputing 70 2007 2410 2425
18. L.J. Herrera, H. Pomares, I. Rojas, A. Guillen, and O. Valenzuela The TaSe-NF model for function approximation problems: approaching local and global modelling Fuzzy Sets and Systems 171 2011 1 21
19. L.J. Herrera, H. Pomares, I. Rojas, O. Valenzuela, and A. Prieto TaSe, a taylor series-based fuzzy system model that combines interpretability and accuracy Fuzzy Sets and Systems 153 2005 403 427
20. C. Hsu Self-Organizing adaptive fuzzy neural control for a class of nonlinear systems IEEE Transactions on Neural Networks 18 2007 1232 1241
21. C. Hsu, and C. Lin Fuzzy-identification-based adaptive controller design via backstepping approach Fuzzy Sets and Systems 151 2005 43 57
22. J. Jang, and C. Sun Functional equivalence between radial basis function networks and fuzzy inference systems IEEE Transactions on Neural Networks 4 1993 156 159
23. T.A. Johansen, and R. Babuska Multiobjective identification of takagi-sugeno fuzzy models IEEE Transactions on Fuzzy Systems 11 2003 847 860
24. G. Leng, T.M. McGinnity, and G. Prasad Design for self-organizing fuzzy neural networks based on genetic algorithms IEEE Transactions on Fuzzy Systems 14 2006 755 766
25. Y. Liu, and Y. Zheng Adaptive robust fuzzy control for a class of uncertain chaotic systems Nonlinear Dynamics 57 2009 431 439
26. J. MacQueen Some methods for classification and analysis of multivariate observations Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability vol. 1 1967 University of California Press 281 297
27. H. Mingzhi, W. Jinquan, M. Yongwen, W. Yan, L. Weijiang, and S. Xiaofei Control rules of aeration in a submerged biofilm wastewater treatment process using fuzzy neural networks Expert Systems with Applications 36 2009 10428 10437
28. S. Mollov, R. Babuska, J. Abonyi, and H.B. Verbruggen Effective optimization for fuzzy model predictive control IEEE Transactions on Fuzzy Systems 12 2004 661 675
29. J. More The Levenberg-Marquardt algorithm: implementation and theory Lecture Notes in Mathematics 630 1978 105 116
30. M. Mucientes, and J. Casillas Quick design of fuzzy controllers with good interpretability in mobile robotics IEEE Transactions on Fuzzy Systems 15 2007 636 651
31. R.L. Navale, and R.M. Nelson Use of evolutionary strategies to develop an adaptive fuzzy logic controller for a cooling coil Energy and Buildings 42 2010 2213 2218
32. H. Nounou, and K. Passino Stable auto-tuning of adaptive fuzzy/neural controllers for nonlinear discrete-time systems IEEE Transactions on Fuzzy Systems 12 2004 70 83
33. K. Ogata Modern Control Engineering fourth ed. 2001 Prentice Hall
34. J. Park, G. Park, S. Kim, and C. Moon Direct adaptive self-structuring fuzzy controller for nonaffine nonlinear system Fuzzy Sets and Systems 153 2005 429 445
35. P.A. Phan, and T.J. Gale Direct adaptive fuzzy control with a self-structuring algorithm Fuzzy Sets and Systems 159 2008 871 899
36. H. Pomares, I. Rojas, J. Gonzalez, M. Damas, B. Pino, and A. Prieto Online global learning in direct fuzzy controllers IEEE Transactions on Fuzzy Systems 12 2004 218 229
37. H. Pomares, I. Rojas, J. Gonzalez, F. Rojas, M. Damas, and F.J. Fernandez A two-stage approach to self-learning direct fuzzy controllers International Journal of Approximate Reasoning 29 2002 267 289
38. H. Pomares, I. Rojas, J. Ortega, J. Gonzalez, and A. Prieto A systematic approach to a self-generating fuzzy rule-table for function approximation IEEE Transactions on Systems, Man, and Cybernetics - Part B 30 2000 431 447
39. I. Rojas, H. Pomares, J. Gonzalez, L.J. Herrera, A. Guillen, F. Rojas, and O. Valenzuela Adaptive fuzzy controller: application to the control of the temperature of a dynamic room in real time Fuzzy Sets and Systems 157 2006 2241 2258
40. I. Rojas, H. Pomares, J. Ortega, and A. Prieto Self-organized fuzzy system generation from training examples IEEE Transactions on Fuzzy Systems 8 2000 23 36
41. A. Sala, and C. Ario Polynomial fuzzy models for nonlinear control: a Taylor series approach IEEE Transactions on Fuzzy Systems 17 2009 1284 1295
42. J. Spooner, R. Ordonez, K. Passino, Direct adaptive fuzzy control for a class of discrete-time systems, in: Proceedings of the 1997 American Control Conference, vol. 3, pp. 1814-1818.
43. A. Tewari, and M. Macdonald Knowledge-based parameter identification of TSK fuzzy models Applied Soft Computing 10 2010 481 489
44. S. Zhou, J. Gan, Improving the interpretability of Takagi-Sugeno fuzzy model by using linguistic modifiers and a multiple objective learning scheme, in: Proc. 2004 IEEE International Joint Conference on Neural Networks, vol. 3, pp. 2385-2390.