LOLIMOT - local linear model trees for nonlinear dynamic system Identification;LOLIMOT - Lokale, lineare modelle zur identifikation nichtlinearer, dynamischer systeme

At-Automatisierungstechnik

Volumn 45, Issue 4, 1997, Pages 163-174

  Nelles, Oliver ^a  

^a DARMSTADT UNIVERSITY OF TECHNOLOGY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85041042798     PISSN: 01782312     EISSN: None     Source Type: Journal    
DOI: 10.1524/auto.1997.45.4.163     Document Type: Article

References (27)

1. Nelles, O., Emst, S. und Isermann, R.: Neural Networks for Identification of Nonlinear Dynamic Systems-An Overview. European Congress on Intelligent Techniques and Soft Computing (EIMT), Aachen, 1996.
2. Nelles, O. und Isermann, R.: A New Technique for Determination of Hidden Layer Parameters in RBF Networks. IFAC World Congress, San Francisco, 1996.
3. Chen, S, Cowan, C. F. N. und Grant, P. M.: Orthogonal Least-Squares Leaming Algorithm for Radial Basis Function Networks. IEEE Transactions on Neural Networks, Vol. 2, No. 2, March 1991.
4. Hwang, J-N, Lay, S-R., Maechler, M., Martin, D. M. und Schimert, J.: Regression Modelling in Back-Propagation and Projection Pursuit Leaming. IEEE Transactions on Neural Networks, Vol. 5, No. 3, May 1994.
5. Leontaritis, L J. und Billings, S. A.: Input-Output Parametric Models for Nonlinear Systems, Part 1: Deterministic Nonlinear Systems. International Journal of Control 41.
6. He, X. und Asada, H.: A New Method for Identifying Orders of Input-Output Models for Nonlinear Dynamic Systems. American Control Conference (ACC), 1993.
7. Nelles, O.: Nonlinear Dynamic System Identification-From Classical Methods to Neural Networks. Technischer Bericht, TH Darmstadt, Institut für Regelungstechnik, Fachgebiet Regelsystemtechnik und Prozeßautomatisierung, 1996.
8. Nelles, O. und Isermann, R.: Identification of Nonlinear Dynamic Systems-Classical Methods versus Radial Basis Function Networks. American Control Conference (ACC), 1995.
9. Isermann, R.: Identifikation dynamischer Systeme. Band 1, Springer, 1992.
10. Narendra, K. S. und Parthasarathy, K.: Identification and Control of Dynamical Systems Using Neural Networks. IEEE Transactions on Neural Networks, Vol. 1, No. 1, March 1990.
11. Ljung, L: System Identification-Theory for the User. Prentice-Hall, Englewood Cliffs, N.J., 1987.
12. Nelles, O.: On the Identification with Neural Networks as Series-Parallel and Parallel Models. International Conference on Artificial Neural Networks (ICANN), Paris, October 1995.
13. Takagi, T. und Sugeno, M.: Fuzzy Identification of Systems and its Application to Modelling and Control. IEEE Transactions on Systems, Man and Cybemetics Vol. 15, No. 1, 1985.
14. Murray-Smith, R.: A Local Model Network Approach to Nonlinear Modelling. Ph.D. Thesis, University of Strathclyde, UK, 1994.
15. Johansen, T. A. und Foss, B. A.: Constructing NARMAX Models Using ARMAX Models. International Journal of Control, Vol. 58, No. 5, 1993.
16. Geman, S., Bienenstock, E. und Doursat, R.: Neural Networks and the Bias/Variance Dilemma. Neural Computation 4, 1992.
17. Breinum, L, Friedman, J., Olshen, R. und Stone, C. J.: Classification and Regression Trees. Wadsworth Belmont, CA, 1984.
18. Sanger, T. D.: Basis-Function Trees for Approximation in High-Dimensional Spaces. Proceedings of the 1990 Connectionist Models Summer School, Morgan Kaufmann, San Mateo, CA, 1990.
19. Friedman, J. H.: Multivariate Adaptive Regression Splines (with discussion). Annais of Statistics, March, 1991.
20. Bellman, R.: Adaptive Control Processes. Princeton University Press, Princeton, NJ., 1961.
21. Scales, L E.: Introduction to Nonlinear Optimization. Macmillan Computer Science Series, 1985.
22. Nelles, O.: Local Linear Model Tree for On-Line Identification of Time-Variant Nonlinear Dynamic Systems. International Conference on Artificial Neural Networks (ICANN), Bochum, 1996.
23. Nelles, O., Isermann, R. und Sinsel, S.: Local Basis Function Networks for Identification of a Turbocharger. UKACC lEE International Conference on Control, Exeter, 1996.
24. Nelles, O. und Fischer, M.: Local Linear Model Trees (LOLIMOT) for Nonlinear System Identification of a Cooling Blast. European Congress on Intelligent Techniques and Soft Computing (EUFIT), Aachen, 1996.
25. Fischer, M., Nelles, O. und Füssel, D.: Pole Placement Design of PID-Controllers Based on Local Linear Model Trees (LOLIMOT). European Congress on Intelligent Techniques and Soft Computing (EUFIT), Aachen, 1996.
26. Hecker, O., Nelles, O. und Moseler, O.: Nonlinear System Identification and Predictive Control of a Heat Exchanger Based on Local Linear Fuzzy Models (eingereicht). American Control Conference (ACC), Albuquerque, 1997.
27. Isermann, R., Lachmann, K-H. und Matko, D.: Adaptive Control Systems. Prentice Hall, 1992.