Online adaptive fuzzy neural identification and control of a class of MIMO nonlinear systems

IEEE Transactions on Fuzzy Systems

Volumn 11, Issue 4, 2003, Pages 462-477

  Gao, Yang ^a   Er, Meng Joo ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Fuzzy logic; Lyapunov theorem; Multiple input multiple output (MIMO) nonlinear systems; Neural networks; Robust adaptive control

Indexed keywords

ADAPTIVE CONTROL SYSTEMS; COMPUTER SIMULATION; FUZZY SETS; GENETIC ALGORITHMS; LYAPUNOV METHODS; MANIPULATORS; NEURAL NETWORKS; NONLINEAR SYSTEMS; ROBOT APPLICATIONS; SYSTEM STABILITY;

WAVELETS ALGORITHMS;

FUZZY CONTROL;

EID: 0042880039     PISSN: 10636706     EISSN: None     Source Type: Journal    
DOI: 10.1109/TFUZZ.2003.814833     Document Type: Article

References (32)

1. S. S. Ge, T. H. Lee, and C. J. Harris, Adaptive Neural Network Control of Robotic Manipulators. Singapore: World Scientific, 1998.
2. M. Brown and C. Harris, Neurofuzzy Adaptive Modeling and Control. London, U.K.: Prentice-Hall, 1994.
3. K. J. Hunt, D. Sbarbaro, R. Zbikowski, and P. J. Gawthrop, "Neural networks for control systems - A survey," Automation, vol. 28, no. 6, pp. 1083-1112, 1992.
4. L. X. Wang, A Course in Fuzzy Systems and Control. Upper Saddle River, NJ: Prentice-Hall, 1997.
5. F. J. Lin, W. J. Hwang, and R. J. Wai, "A supervisory fuzzy neural network control system for tracking periodic input," IEEE Trans. Fuzzy Syst., vol. 7, pp. 41-52, Feb. 1999.
6. M. J. Er and S. H. Chin, "Hybrid adaptive fuzzy controllers of robot manipulators with bounds estimation," IEEE Trans. Ind. Electron., vol. 47, pp. 1151-1160, May. 2000.
7. G. Feng, "A new stable tracking control scheme for robotic manipulators," IEEE Trans. Syst., Man, Cybern., vol. 27, pp. 510-516, June 1997.
8. H. Lee and M. Tomizuka, "Robust adaptive control using a universal approximator for SISO nonlinear systems," IEEE Trans. Fuzzy Syst., vol. 8, pp. 95-106, Feb. 2000.
9. H. Han, C. Y. Su, and U. Stepanenko, "Adaptive control of a class of nonlinear systems with nonlinearly parameterized fuzzy approximators," IEEE Trans. Fuzzy Syst., vol. 9, pp. 315-323, Apr. 2001.
10. J. C. Wu and T. S. Liu, "A sliding mode approach to fuzzy control design," IEEE Trans. Control Syst. Technol., vol. 4, pp. 459-468, Mar. 1996.
11. Y. Ohtani and T. Yoshimura, "Fuzzy control of a manipulator using the concept of sliding mode," Int. J. Syst. Sci., vol. 27, pp. 1727-1731, 1996.
12. ∞ approaches," IEEE Trans. Fuzzy Syst., vol. 9, pp. 278-292, Feb. 2001.
13. Y. Pan, G. J. Klir, and B. Yuan, "Bayesian inference based on fuzzy probabilities," in Proc. 5th IEEE Int. Conf. Fuzzy Systems, vol. 3, New Orleans, LA, 1996, pp. 1693-1699.
14. D. J. C. MacKay, "Bayesian neural networks and density networks," Nuclear Instrum. Meth. Phys. Res., vol. 354, no. 1, pp. 73-80, 1995.
15. D. Park, A. Kandel, and G. Langholz, "Genetic-based new fuzzy reasoning models with application to fuzzy control," IEEE Trans. Syst., Man, Cybern., vol. 24, pp. 39-47, Feb. 1994.
16. H. R. Berenji and P. Khedkar, "Learning and tuning fuzzy controllers through reinforcement," IEEE Trans. Neural Networks, vol. 3, pp. 724-739, Oct. 1992.
17. Y. Jin, J. Jiang, and J. Zhu, "Neural network based fuzzy identification with application to modeling and control of complex systems," IEEE Trans. Syst., Man, Cybern., vol. 25, pp. 990-997, June 1995.
18. J. S. R. Jang, C. T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing. Upper Saddle River, NJ: Prentice-Hall, 1997.
19. Y. Jin, "Decentralized adaptive fuzzy control of robot manipulators," IEEE Trans. Syst., Man, Cybern., vol. 28, pp. 47-58, Jan. 1998.
20. 3 fuzzy rule systems from data using evolution strategies," IEEE Trans. Syst., Man, Cybern., vol. 29, pp. 829-845, June 1999.
21. J. Nie and D. Linkens, Fuzzy-Neural Control: Principles, Algorithms and Applications. Upper Saddle River, NJ: Prentice-Hall, 1995.
22. M. R. Cannon and J.-J. E. Slotine, "Space-frequency localized basis function networks for nonlinear system estimation and control," Neurocomputing, vol. 9, 1995.
23. R. M. Sanner and J.-J. E. Slotine, "Structurally dynamic wavelet networks for adaptive control of robotic systems," Int. J. Control, vol. 70, no. 3, pp. 405-421, 1998.
24. S. Q. Wu, M. J. Er, and Y. Gao, "A fast approach for automatic generation of fuzzy rules by generalized dynamic fuzzy neural networks," IEEE Trans. Fuzzy Syst., vol. 9, pp. 578-594, Aug. 2001.
25. Y. Gao, M. J. Er, and S. Yang, "Adaptive fuzzy neural control of robot manipulators," IEEE Trans. Ind. Electron., vol. 48, pp. 1274-1278, Dec. 2001.
26. M. J. Er and Y. Gao, "Robust adaptive control of robot manipulators using generalized fuzzy neural networks," IEEE Trans. Ind. Electron., vol. 50, pp. 620-628, June 2003.
27. J. J. E. Slotine and W. Li, Applied Nonlinear Control. Upper Saddle River, NJ: Prentice-Hall, 1991.
28. K. J. Åström and B. Wittenmark, Adaptive Control. Reading, MA: Addison-Wesley, 1995.
29. W. H. Press, S. A. Teukolsky, W. T. Vetterling, and B. P. Flannery, Numerical Recipes in C: The Art of Scientific Computing. Cambridge, U.K.: Cambridge Univ. Press, 1992.
30. S. Chen, C. F. N. Cowan, and P. M. Grant, "Orthogonal least squares learning algorithm for radial basis function network," IEEE Trans. Neural Networks, vol. 2, pp. 302-309, Apr. 1991.
31. C. M. Bishop, Neural Networks for Pattern Recognition. Oxford, U.K.: Oxford Univ. Press, 1995.
32. F. L. Lewis, C. Y. Abdallah, and D. M. Dawson, Control of Robot Manipulators. New York: Macmillian, 1993.