Robust control of dynamical systems using neural networks with input-output feedback linearization

International Journal of Control

Volumn 76, Issue 18, 2003, Pages 1783-1789

  Van Den Boom, Ton ^a   Botto, Miguel Ayala ^b   Sá Da Costa, José ^b  

^a DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

^b INSTITUTO SUPERIOR TÉCNICO   (Portugal)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; FEEDBACK CONTROL; LINEARIZATION; LYAPUNOV METHODS; MATHEMATICAL MODELS; NEURAL NETWORKS; NONLINEAR CONTROL SYSTEMS; OPTIMIZATION; ROBUSTNESS (CONTROL SYSTEMS); STATE FEEDBACK; STATE SPACE METHODS; SYSTEM STABILITY;

INPUT-OUTPUT FEEDBACK LINEARIZATION; NEURAL NETWORK MODELS; STATE SPACE MATRICES;

CONTROL SYSTEM SYNTHESIS;

EID: 0346504011     PISSN: 00207179     EISSN: None     Source Type: Journal    
DOI: 10.1080/00207170310001633295     Document Type: Article

References (23)

1. Aoyama, A., Doyle III, F. J., and Venkatasubramanian, V., 1996, Control-affine neural network approach for non-minimum-phase nonlinear process control. Journal of Process Control, 6, 17-26.
2. Ayala Botto, M., van den Boom, T., Krijgsman, A., and Sá Da Costa, J., 1999, Predictive control based on neural network models with I/O feedback linearization. International Journal of Control, 72, 1538-1554.
3. Ayala Botto, M., Wams, B., Van Den Boom, T., and Sá Da Costa, J., 2000, Robust stability of feedback linearised systems modelled with neural networks: dealing with uncertainty. Engineering Applications of Artificial Intelligence, 13, 659-670.
4. Baron, A., 1993, Universal approximation bounds for superpositions of a sigmoidal function. IEEE Transactions on Information Theory, 39, 930-945.
5. Billings, S., and Voon, W., 1986, Circulation based model validity test for non-linear models. International Journal of Control, 4, 235-244.
6. Chao, A. I., 1995, Stability robustness to unstructured uncertainty for nonlinear systems under feedback linearization. PhD thesis, Massachusetts Institute of Technology, USA.
7. Chen, F.-C., and Khalil, K., 1995, Adaptive control of a class of nonlinear discrete-time systems using neural networks. IEEE Transactions on Automatic Control, 40, 791-801.
8. Cybenko, G., 1989, Approximation by superpositions of a sigmoidal function. Mathematics of Control Signals and Systems, 2, 303-314.
9. Fang, Y., and Kincaid, T. G., 1996, Stability analysis of dynamical neural networks. IEEE Transactions on Neural Networks, 7, 996-1005.
10. Funahashi, K., 1989, On the approximate realization of continuous mappings by neural networks. Neural Networks, 2, 183-192.
11. Haykin, S., 1994, Neural Networks: a Comprehensive Foundation (New York: Macmillan College Publishing).
12. Hunt, K., Sbarbaro, D., Zbikowski, R., and Gawthrop, P., 1992, Neural networks for control systems - a survey. Automatica, 28, 1083-1112.
13. Isidori, A., 1989, Nonlinear Control Systems: An Introduction, Communications and Control Engineering Series (Berlin: Springer-Verlag).
14. Kothare, M., Balakrishnan, V., and Morari, M., 1996, Robust contrained predictive control using linear matrix inequalities. Automatica, 32, 1361-1379.
15. Levin, A. U., and Narendra, K. S., 1993, Control a nonlinear dynamical systems using neural networks: Controllability and stabilization. IEEE Transactions on Neural Networks, 41, 192-206.
16. Lewis, F. L., Yesildirek, A., and Kai, L., 1996, Multilayer neural-net robot controller with guaranteed tracking performance. IEEE Transactions on Neural Networks, 7, 388-399.
17. Narendra, K. S., and Mukhopadhyay, S., 1994, Adaptive control of nonlinear multivariable systems using neural networks. Nerual Networks, 7, 737-752.
18. Narendra, K. S., and Parthasarathy, K., 1990, Identification and control of dynamical systems using neural networks. IEEE Transactions on Neural Networks, 1, 4-27.
19. Seber, G., and Wild, C., 1989, Nonlinear Regression (New York: Wiley).
20. Sjöberg, J., 1995, Nonlinear black-box modeling in system identification: a unified overview. Automatica, 31, 1691-1724.
21. Suykens, J., Vandewalle, J, and De Moor, B., 1996, Artificial Neural Networks for Modelling and Control of Non-linear Systems (Boston, MA: Kluwer Academic Publishers).
22. Tanaka, K., 1996, An approach to stability criteria of neural-network control systems. IEEE Transactions on Neural Networks, 7, 629-642.
23. van den Boom, T., 2000, Algorithm for low-order polytope approximations. Internal report TvdB:005, System and Control, Faculty ITS, TU Delft.