Adaptive fuzzy CMAC-based nonlinear control with dynamic memory architecture

Journal of the Franklin Institute

Volumn 348, Issue 9, 2011, Pages 2480-2502

  Cheng, Kuo Hsiang ^a  

^a INDUSTRIAL TECHNOLOGY RESEARCH INSTITUTE   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

ADAPTIVE CONTROL; ADAPTIVE FUZZY; APPROXIMATION ERRORS; APPROXIMATION PERFORMANCE; ARCHITECTURE LEARNING; ASSOCIATIVE MEMORIES; CEREBELLAR MODEL ARTICULATION; COMPUTATION CONTROLLERS; CONTROLLER PARAMETER; DYNAMIC ARCHITECTURE; DYNAMIC CONTROLS; DYNAMIC MEMORY; FUZZY-CMAC; LYAPUNOV STABILITY THEOREM; MEMORY CELL; NON LINEAR CONTROL; SUPERVISORY CONTROLLERS;

ARCHITECTURE; ASSOCIATIVE PROCESSING; ASSOCIATIVE STORAGE; MEMORY ARCHITECTURE; NETWORK ARCHITECTURE; REINFORCEMENT;

CONTROLLERS;

EID: 81155160922     PISSN: 00160032     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.jfranklin.2011.07.011     Document Type: Article

References (30)

1. J.E. Slotine, and W. Li Applied Nonlinear Control 1991 Prentice-Hall Englewood Cliffs, New Jersey
2. D. Yu, and Z. Xu Nonlinear coordinated control of drum boiler power unit based on feedback linearization IEEE Trans. Energy Convers. 20 2007 204 210
3. B. Mirkin, P.-O. Gutman, and Y. Shtessel Robust adaptive tracking with an additional plant identifier for a class of nonlinear systems J. Franklin Inst. 347 2010 974 987
4. H.K. Khalil Nonlinear Systems 1996 Prentice Hall Englwood Cliffs, NJ
5. M. Raoof, and A.A. Suratgar Adaptive control of PLL using neural network J. Franklin Inst. 346 2009 81 93
6. C.F. Hsu, C.M. Lin, and T.Y. Chen Neural-network-identification-based adaptive control of wing rock motions IEE Proc.-Control Theory Appl. 152 2005 65 71
7. F.O. Tellez, A.G. Loukianv, E.N. Sanchez, and E.J.B. Corrochano Decentralized neural identification and control for uncertain nonlinear systems: application to planar robot J. Franklin Inst. 347 2010 1015 1034
8. S.-K. Oh, and W. Pedrycz Multi-layer self-organizing polynomial neural networks and their development with the use of genetic algorithms J. Franklin Inst. 343 2006 125 136 (Pubitemid 43190060)
9. D. Hanbay, I. Turkoglu, and Y. Demir Modeling switched circuits based on wavelet decomposition and neural networks J. Franklin Inst. 347 2010 607 617
10. S.S. Ge, C.C. Hang, and T. Zhang Adaptive neural network control of nonlinear systems by state and output feedback IEEE Trans. Syst. Man Cybern. Part B: Cybern. 29 1999 818 828 (Pubitemid 32211618)
11. F. Abdollahi, H.A. Talebi, and R.V. Patel A stable neural network-based observer with application to flexible-joint manipulators IEEE Trans. Neural Networks 17 2006 118 129 (Pubitemid 43263945)
12. J.S. Albus A new approach to manipulator control: the cerebellar model articulation controller Trans. ASME, J. Dyn. Syst., Meas. Control 1975 220 227
13. J.S. Albus Data storage in the cerebellar model articulation controller Trans. ASME, J. Dyn. Syst., Meas. Control 1975 228 233
14. H.-C. Lu, J.-C. Chang, and M.-F. Yeh Design and analysis of direct-action CMAC PID controller Neurocom 70 2007 2615 2625 (Pubitemid 47308613)
15. Z.J. Geng, and C.L. Mccullough Missile control using fuzzy CMAC neural networks AIAA J. Guid., Control, Dyn. 20 1997 557 565
16. C.-M. Lin, and Y.-F. Peng Adaptive CMAC-based supervisory control for uncertain nonlinear systems IEEE Trans. Syst. Man Cybern. Part B: Cybern. 34 2004 1248 1260
17. Z. Shen, C. Guo, and H. Li General fuzzified CMAC based model reference adaptive control for ship steering Proc. IEEE Int. Symp. Intell. Control 2005 1257 1262
18. S.D. Teddy, C. Quek, and E.M.-K. Lai PSECMAC: a novel self-organizing multiresolution associative memory architecture IEEE Trans. Neural Networks 19 2008 689 712 (Pubitemid 351583583)
19. L. Li, C. Hou, The study of application of FCMAC neural network in the industrial process on-line identification and optimization, in: Proceedings of the International Conference on Neural Information Processing (ICONIP 02), vol. 4, 2002, pp. 17341738.
20. P.E.M. Almeida, and M.G. Simoes Parametric CMAC networks: fundamentals and applications of a fast convergence neural structure IEEE Trans. Ind. Appl. 39 2003 1551 1557
21. C.-J. Lin, and C.-Y. Lee A self-organizing recurrent fuzzy CMAC model for dynamic system identification, Int. J Intell. Syst. 2008 384 396 (Pubitemid 351322245)
22. C.-Y. Lee, C.-J. Lin, and H.-J. Chen A self-constructing fuzzy CMAC model and its applications Inf. Sci. 2007 264 280 (Pubitemid 44556687)
23. M.N. Nguyen, D. Shi, and C. Quek FCMAC-BYY: fuzzy CMAC using bayesian yingyang learning IEEE Trans. Syst. Man Cybern. Part B: Cybern. 36 2006 1180 1190 (Pubitemid 44500786)
24. C.-F. Hsu, and K.-H. Cheng Recurrent fuzzy-neural approach for nonlinear control using dynamic structure learning scheme Neurocom 71 2008 3447 3459
25. L. Gang, T.M. McGinnity, and G. Prasad An approach for on-line extraction of fuzzy rules using a self-organising fuzzy neural network Fuzzy Sets Syst. 150 2005 211 243 (Pubitemid 40056019)
26. C.-C. Wen, and C.-C. Cheng Design of sliding surface for mismatched uncertain systems to achieve asymptotical stability J. Franklin Inst. 345 2008 926 941
27. K.S. Narendra, and A.M. Annaswamy Stable Adpative Systems 1989 Prentice-Hall Englewood Cliffs, NJ
28. G. Chen, and X. Dong On feedback control of chaotic continuous-time systems IEEE Trans. Circuits Syst. 40 Part I 1993 591 601
29. H. Nijmeijer, and H. Berghuis On Lyapunov control of the Duffing equation IEEE Trans. Circuits Syst. 42 Part I 1995 473 477
30. K.Y. Lian, P. Liu, T.S. Chiang, and C.S. Chiu Adaptive synchronization design for chaotic systems via a scalar driving signal IEEE Trans. Circuits Syst. 49 Part I 2002 17 27 (Pubitemid 34228683)