A reproducing Kernel Hilbert Space approach for the online update of Radial Bases in neuro-adaptive control

Proceedings of the IEEE Conference on Decision and Control

Volumn , Issue , 2011, Pages 1796-1802

  Kingravi, Hassan A ^a   Chowdhary, Girish ^b   Vela, Patricio A ^a   Johnson, Eric N ^b  

^a GEORGIA INSTITUTE OF TECHNOLOGY   (United States)

^b Georgia Institute of Technology   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONTROLLERS; DYNAMICAL SYSTEMS; HILBERT SPACES; IMAGE SEGMENTATION; NONLINEAR DYNAMICAL SYSTEMS; RADIAL BASIS FUNCTION NETWORKS; VECTOR SPACES;

ADAPTIVE CONTROLLERS; DOMAIN KNOWLEDGE; NEURO-ADAPTIVE CONTROL; NEURO-ADAPTIVE CONTROLLERS; ON-LINE ALGORITHMS; PERSISTENTLY EXCITING; RADIAL BASIS FUNCTION NEURAL NETWORKS; REPRODUCING KERNEL HILBERT SPACES;

MODEL REFERENCE ADAPTIVE CONTROL;

EID: 84860699436     PISSN: 07431546     EISSN: 25762370     Source Type: Conference Proceeding    
DOI: 10.1109/CDC.2011.6160765     Document Type: Conference Paper

References (23)

1. K. J. Astrom and B. Wittenmark. Adaptive Control. Addison-Weseley, Readings, 2nd edition, 1995.
2. S. Boyd and S. Sastry. Necessary and sufficient conditions for parameter convergence in adaptive control. Automatica, 22(6):629-639, 1986.
3. c. Burges. A tutorial on support vector machines for pattern recognition. Data Mining and Knowledge Discovery, 2:121-167, 1998.
4. Anthony J. Calise, Manu Sharma, and Seungjae Lee. Adaptive autopilot design for guided munitions. AIAA Journal of Guidance, Control, and Dynamics, 23(5), 2000.
5. G. Chowdhary. Concurrent Learning for Convergence in Adaptive Control Without Persistency of Excitation. PhD thesis, Georgia Institute of Technology, Atlanta, GA, 2010.
6. Girish Chowdhary and Eric N. Johnson. Concurrent learning for convergence in adaptive control without persistency of excitation. In 49th IEEE Conference on Decision and Control, 2010.
7. N. Cristianini and J. Shawe-Taylor. Kernel Methods for Pattern Analysis. Cambridge University Press, 2004.
8. P. A. Ioannou and J. Sun. Robust Adaptive Control. Prentice-Hall, Upper Saddle River, 1996.
9. Petros A. Ioannou and Peter V. Kokotovic. Adaptive Systems with Reduced Models. Springer Verlag, Secaucus, NJ, 1983.
10. E. N. Johnson. Limited Authority Adaptive Flight Control. PhD thesis, Georgia Institute of Technology, Atlanta GA, 2000.
11. Eric N. Johnson and Anthony J. Calise. Limited authority adaptive flight control for reusable launch vehicles. Journal of Guidance, Control and Dynamics, 2001.
12. S. Kannan. Adaptive Control of Systems in Cascade with Saturation. PhD thesis, Georgia Institute of Technology, Atlanta GA, 2005.
13. N. Kim. Improved Methods in Neural Network Based Adaptive Output Feedback Control, with Applications to Flight Control. PhD thesis, Georgia Institute of Technology, Atlanta GA, 2003.
14. N. Nardi. Neural Network based Adaptive Algorithms for Nonlinear Control. PhD thesis, Georgia Institute of Technology, School of Aerospace Engineering, Atlanta, GA 30332, nov 2000.
15. K. Narendra and A. Annaswamy. A new adaptive law for robust adaptation without persistent excitation. IEEE Transactions on Automatic Control, 32(2): 134-145, February 1987.
16. K. S. Narendra and A. M. Annaswamy. Stable Adaptive Systems. Prentice-Hall, Englewood Cliffs, 1989.
17. D. Nguyen-Tuong, B. SchOlkopf, and J. Peters. Sparse online model learning for robot control with support vector regression. In IEEEIRSJ International Conference on Intelligent Robots and Systems, 2009.
18. J. Park and I.W. Sandberg. Universal approximation using radial-basis-function networks. Neural Computation, 3:246-257, 1991.
19. I. Steinwart, D. Hush, and C. Scovel. An explicit description of the reproducing kernel Hilbert spaces of Gaussian RBF kernels. IEEE Transactions on Information Theory, 52(10), 2006.
20. N. Sundararajan, P. Saratchandran, and L. Yan. Fully Tuned Radial Basis Function Neural Networks for Flight Control. Springer, 2002.
21. J.A.K. Suykens, J.P.L. Vandewalle, and B.L.R. De Moor. Artificial Neural Networks for Modeling and Control of Non-Linear Systems. Kluwer, Norwell, 1996.
22. G. Tao. Adaptive Control Design and Analysis. Wiley, New York, 2003.
23. Kostyantyn Y. Volyanskyy, Wassim M. Haddad, and Anthony J. Calise. A new neuroadaptive control a-chitecture for nonlinear uncertain dynamical systems: Beyond a and e-modifications. IEEE Transactions on Neural Networks, 20(11): 1707-1723, Nov 2009.