Representations of multi-model based controllers by using artificial intelligence tools

Informatica

Volumn 15, Issue 3, 2004, Pages 337-362

  Ibeas, Asier ^a   De La Sen, Manuel ^a  

^a UNIVERSITY OF THE BASQUE COUNTRY UPV EHU   (Spain)

Author keywords

Artificial intelligence; Fuzzy logic; Genetic algorithms; Multimodel control; Neural networks; Switching

Indexed keywords

EID: 4344716963     PISSN: 08684952     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (26)

1. Alonso-Quesada, S., M. de la Sen, A. Bilbao-Guillerna and A. Ibeas (2004). A semiempirical identification method by using a multiestimation technique via reduced-order nominal models. In Proceedings of the ACC'04 (in press).
2. Beyers, H.G. (1998). The Theory of Evolution Strategies. Springer-Verlag, 1998.
3. Chang, M.H., and E.J. Davison (1999). Adaptive switching control of LTI MIMO systems using a family of controllers approach. Automatica, 35, 453-465.
4. Da Ruan (Ed.) (1997). Intelligent Hybrid Systems, Fuzzy Logic, Neural Networks and Genetic Algorithms. Kluwer.
5. Etxebarria, V. (1994). Adaptive control of discrete systems using neural networks. IEE Proc. Contr. Theory and Appl, Part D, 141(4), 209-215.
6. Etxebarria, V., M. de la Sen (1996). An approach to adaptive neural control of robot manipulators. International Journal of System Science, 27(11), 1143-1152.
7. Fausett, L.V. (1998). Fundamentals of Neural Networks. Prentice Hall.
8. Feng, G. (2004). Stability analysis of discrete-time fuzzy dynamic systems based on piecewise lyapunov functions. IEEE Transactions on Fuzzy Systems, 12(1), 22-28.
9. Gregorcic, G., A. Mullane and G. Lightbody (2001). Simulink implementation of adaptive control and multiple model network control. In Proc. of the Nordic Matlab Conf. pp. 167-173.
10. Hocherman-Frommer, J., S.R. Kulkami and P.J. Ramadge (1998). Controller switching based on output prediction errors. IEEE Transactions on Automatic Control, 43(5), 596-607.
11. Ibeas, A., M. de la Sen and S. Alonso-Quesada (2003). Adaptive stabilization of discrete linear systems via a multiestimation scheme. Inter. Math. J., 3(4), 381-407.
12. Ibeas, A., and M. de la Sen (2004). Intelligent control of robotic manipulators based on a multiestimation scheme. In Proc.of the IASTED Int. Conf. Artificial Intelligence and Applications, pp. 694-699.
13. Ibeas, A., M. de la Sen and S. Alonso-Quesada (2004). Intelligent control of discrete linear systems based on a supervised adaptive multiestimation scheme. Journal of Intelligent and Robotic Systems (in press).
14. Liutkevicius, R. (2003). Coupled adaptive fuzzy control of nonlinear, time-varying plant. Informatica, 14(3), 323-336.
15. Melin, P., and O. Castillo (2003). Adaptive intelligent control of aircraft systems with a hybrid approach combining neural networks, fuzzy logic and fractal theory. Applied Soft Computing, 3(4), 353-362.
16. Mosca, E., and T. Agnoloni (2001). Inference of candidate loop perfomance and data filtering for switching supervisory control. Automatica, 37, 527-534.
17. Mwembeshi, M.M., C.A. Kent and S. Salhi (2004). A genetic algorithm based approach to intelligent modelling and control of pH in reactors. Computers & Chemical Engineering, 28(9), 1743-1757.
18. Narendra, K.S., and J. Balakrishnan (1994). Improving transient response of adaptive control systems using multiple models and switching. IEEE Transactions on Automatic Control, 39(9), 1861-1866.
19. Narendra, K.S., and J. Balakrishnan (1997). Adaptive control using multiple models. IEEE Transactions on Automatic Control, 42(2), 171-187.
20. de la Sen, M., and A. Almansa (2002). Adaptive stable control of manipulators with improved adaptation transients by using on-line supervision of the free parameters of the adaptation algorithm and sampling rate. Informatica, 13(3), 345-368.
21. de la Sen, M., S. Alonso-Quesada, A. Bilbao-Guillerna and A.J. Garrido (2003). A supervised multiestimation scheme for discrete adaptive control which guarantees robust closed-loop stability. Inter. Math. J., 3(9), 907-937.
22. de la Sen, M., J.J. Miñambres, A.J. Garrido, A. Almansa and J.C. Soto (2004). Basic theoretical results for expert systems. Application to the supervision of adaptation transients in planar robots. Artificial Intelligence, 152(2), 173-211.
23. Tilli, T. (1992). Fuzzy Logic. Franzis-Verlag.
24. VanDoren, V. (Ed.) (2003). Techniques for Adaptive Control. Elsevier Science.
25. Wang, J., and M. Qing (2004). An output tracking control strategy for unknown nonlinear systems. Applied Artificial Intelligence, 18(1), 1-16.
26. Wetter, M., and J. Wright (2004). A comparison of deterministic and probabilistic optimization algorithms for nonsmooth simulation-based optimization. Building and Environment, 39(8), 989-999.