Nonlinear system identification by evolutionary computation and recursive estimation method

Proceedings of the American Control Conference

Volumn 7, Issue , 2005, Pages 5073-5078

  Juang, Jih Gau ^a   Lin, Bo Shian ^a  

^a NATIONAL TAIWAN OCEAN UNIVERSITY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; EVOLUTIONARY ALGORITHMS; LEAST SQUARES APPROXIMATIONS; NONLINEAR SYSTEMS; PARAMETER ESTIMATION; RANDOM PROCESSES; RECURSIVE FUNCTIONS;

EXPONENTIAL FORGETTING; NONLINEAR SYSTEM IDENTIFICATION; RECURSIVE ESTIMATION; STOCHASTIC ALGORITHMS;

IDENTIFICATION (CONTROL SYSTEMS);

EID: 23944501744     PISSN: 07431619     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (25)

1. T.C. Hsia, System Identification. D.C. Heath and Co., USA, 1977.
2. L.D. Landau, System Identification and Control Design, Prentice Hall, Englewood Cliffs, N.J., USA, 1990.
3. T. Söderström and P. Stoica, System Identification, Prentice Hall, Cambridge, U.K., 1989.
4. T. Kara and I Eker, "Identification of Nonlinear Systems for Feedback Control", Proceedings of the Forth GAP Engineering Congress, Sanhurfa, Turkey, pp.520-526, June 06-08, 2002.
5. R. Haber and H. Unbehausen, "Structure identification of nonlinear dynamic systems - a survey of input/output approaches," Automatica, vol. 24, pp. 651-677, 1990.
6. J.C. G'ometz and M. Basualdo, "Nonlinear identification of multicomponent batch distillation processes," Proceedings of the IF AC Symposium on Advanced Control of Chemical Processes ADCHEM 2000, pp. 989-994, 2000.
7. J. Sjoberg, Q. Zhang, L. Ljung, A. Benveniste, B. Deylon, P.-Y. Glorennec, H. Hjalmarsson, and J. Juditsky, "Nonlinear black-box modeling in system identification: a unified overview," Automatica, vol. 31, pp. 1691-1724, 1995.
8. L. Benvenuti, A. De Santis, and L. Farina, "On model consistency in compartmental systems identification," Automatica, vol. 38, pp. 1969-1976, 2002.
9. L. Ljung, System Identification: Theory for the User, Prentice Hall, Englewood Cliffs, N.J., USA. 1987.
10. C.L. Lawson and R.J. Hanson, Solving Least Squares Problems, Englewood Cliffs, N.J.: Prentice-Hall, 1974.
11. L. Ljung and T. Soderstrom, Theory and Practice of Recursive Identification, Cambridge, Mass.: MIT Press, 1983.
12. P.E. Wellstead and M.B. Zarrop, Self-tuning Systems: Control and Signal Processing, John Wiley and Sons, U.K., 1991.
13. C.C. Hang, T.H. Lee, and K.H. Weng, Adaptive Control, Instrument Society of America, USA, 1993.
14. B. Huang, "Process identification based on last principal component analysis," Journal of Process Control, vol. 11, pp. 19-33, 2001.
15. D.G. Robertson and J.H. Lee, "On the use of constraints in least squares estimation and control," Automatica, vol. 38, pp. 1113-1123, 2002.
16. L.J. Fogel, A.J. Owens, and M.J. Walsh, "Artificial intelligence through a simulation of evolution," Proc. of the 2nd Cybernetics Science Symp., pp. 131-155, 1965,
17. reprinted in D.B. Fogel (eds.), Evolutionary Computation, The Fossil Record, pp. 230-254, IEEE Press, 1995.
18. D.E. Goldberg, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, 1989.
19. J.H. Holland, Adaptation in Natural and Artificial Systems, MIT Press, 1992.
20. J.R. Koza, Genetic Programming: On the Programming of Computers by Means of Natural Selection, MIT Press, 1992.
21. H.-P. Schwefel, Evolution and Optimum Seeking, J. Wiley, 1995.
22. R.L. Plackett, "Some Theorems in Least Squares," Biometrika, vol. 37, pp. 149-157, 1950.
23. S. Kaczmarz, "Approximate solution of systems of linear equations." Int. J. Control, vol. 57, pp. 1269-1271, 1993.
24. K.F. Man, K.S. Tang, and S. Kwong, Genetic algorithms. London: Springer-Verlag, 1998.
25. C.T. Lin and C.S. Lee, Neural fuzzy systems, Upper Saddle River, NJ: Prentice Hall, 1996.