On the equivalence of least costly and traditional experiment design for control

Automatica

Volumn 44, Issue 11, 2008, Pages 2706-2715

  Rojas, Cristian R ^a   Agüero, Juan C ^a   Welsh, James S ^a   Goodwin, Graham C ^a  

^a UNIVERSITY OF NEWCASTLE   (Australia)

Author keywords

Experiment design; Identification for control; Optimal input design

Indexed keywords

CLOSED LOOP CONTROL SYSTEMS; CLOSED LOOP SYSTEMS; EXPERIMENTS;

CLOSED LOOPS; EXPERIMENT DESIGN; EXPERIMENT DESIGNS; FINITE ORDERS; HIGH ORDERS; IDENTIFICATION FOR CONTROL; NOISE MODELS; OPEN LOOPS; OPTIMAL INPUT DESIGN; PERFORMANCE SPECIFICATIONS;

DESIGN;

EID: 55049140484     PISSN: 00051098     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.automatica.2008.03.023     Document Type: Article

References (31)

1. Bernstein D.S. Matrix mathematics (2005), Princeton University Press, Princeton, New Yersey
2. Bombois X., Gevers M., Scorletti G., and Anderson B. Robustness analysis tools for an uncertainty set obtained by prediction error identification. Automatica 37 10 (2001) 1629-1636
3. Bombois, X., & Gilson, M. (2006). Cheapest identification experiment with guaranteed accuracy in the presence of undermodeling. In Proceedings of the 14th IFAC symposium on system identification (pp. 505-510)
4. Bombois, X., Scorletti, G., Gevers, M., Hildebrand, R., & Van den Hof, P. (2004). Cheapest open-loop identification for control. In Proceedings of the 43rd IEEE conference on decision and control (pp. 382-387)
5. Bombois X., Scorletti G., Gevers M., Van den Hof P., and Hildebrand R. Least costly identification experiment for control. Automatica 42 10 (2006) 1651-1662
6. Bombois, X., Scorletti, G., & Van den Hof, P. (2005). Least disturbing closed-loop identification experiment for control. In Proceedings of the 16th IFAC world congress (pp. 505-510)
7. Bombois, X., Scorletti, G., Van den Hof, P., & Gevers, M. (2004). Least costly identification experiment for control: A solution based on a high-order model approximation. In Proceedings of the American control conference(pp. 2818-2823)
8. Boyd S., El Ghaoui L., Feron E., and Balakrishnan V. Linear matrix inequalities in system and control theory (1994), SIAM, Philadelphia, USA
9. Fedorov V.V. Theory of optimal experiments (1972), Academic Press, New York, London
10. Gevers M. Identification for control: From the early achievements to the revival of experiment design. European Journal of Control 11 (2005) 1-18
11. Gevers, M., & Bombois, X. (2006). Input design: From open-loop to control-oriented design. In 14th IFAC symposium on system identification (pp. 1329-1334)
12. Goodwin G.C., and Payne R.L. Dynamic system identification: Experiment design and data analysis (1977), Academic Press, New York
13. Hildebrand R., and Gevers M. Identification for control: Optimal input design with respect to a worst-case ν-gap cost function. SIAM Jurnal on Control Optimization 41 5 (2003) 1586-1608
14. Hjalmarsson H. From experiment design to closed-loop control. Automatica 41 3 (2005) 393-438
15. Jansson, H. (2004). Experiment design with applications in identification for control. Ph.D. thesis. Royal Institute of Technology (KTH), tRITA-S3-REG-0404
16. Jansson H., and Hjalmarsson H. Input design via lmis admitting frequency-wise model specifications in confidence regions. IEEE Transactions on Automatic Control AC-50 10 (2005) 1534-1549
17. Jansson, H., & Hjalmarsson, H. (2005b). Optimal experiment design in closed loop. In 16th IFAC world congress on automatic control
18. Lasserre J.B., and Hiriart-Urruty J.B. Mathematical properties of optimization problems defined by positively homogeneous functions. Journal of Optimization Theory and Applications 112 1 (2002) 31-52
19. Levadi V.S. Design of input signals for parameter estimation. IEEE Transactions on Automatic Control AC-11 2 (1966) 205-211
20. Lighthill M.J. Introduction to fourier analysis and generalised functions (1959), Cambridge University Press, London
21. Ljung L. System identification: Theory for the user. 2nd edition (1999), Prentice Hall, Upper Saddle River, New Jersey
22. Mehra R.K. Optimal inputs for system identification. IEEE Transactions on Automatic Control AC-19 (1974) 192-200
23. Priestley M.B. Spectral analysis and time series (1981), Academic Press, New York
24. Rockafellar R.T. Convex analysis (1970), Princeton University Press, Princeton, New Jersey
25. Rojas, C.R., Barenthin, M., Welsh, J.S., & Hjalmarsson, H. (2008). The cost of complexity in identification of FIR systems. In Proceedings of the 17th IFAC World Congress (pp. 11451-11456)
26. Rojas C.R., Welsh J.S., Goodwin G.C., and Feuer A. Robust optimal experiment design for system identification. Automatica 43 6 (2007) 993-1008
27. Söderström T., and Stoica P. System identification (1989), Prentice Hall, Hertfordshire, United Kingdom
28. Whittle P. Some general points in the theory of optimal experimental design. Journal of the Royal Statistical Society 35 1 (1973) 123-130
29. Yuan Z., and Ljung L. Black-box identification of multivariable transfer functions-asymptotic properties and optimal input design. International Journal of Control 40 2 (1984) 233-256
30. Zarrop M. Optimal experiment design for dynamic system identification. Lecture notes in control and information Vol. 21 (1979), Springer, Berlin, New York
31. Zhou K., Doyle J.C., and Glover K. Robust and optimal control (1996), Prentice Hall, Englewood Cliffs, New Jersey