Abstract
Performing the optimization requires calculation of the cost function’s derivative(s), and this must be done only with the data collected from the system—there is not an analytical expression of the cost function available. Each particular data-driven “brand” (like IFT, FDT and CbT) is characterized by a particular way of estimating the function’s derivatives from data. This computing aspect, namely the calculation of these quantities, is the subject of Chap. 7. Three different methods are described in some detail and interpreted under the light of the theory presented in the previous chapters: IFT, FDT and CbT.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
That is, the closed-loop system with the controller C(z,ρ 1) is BIBO-stable.
References
F. de Bruyne, L.C. Kammer, Iterative feedback tuning with guaranteed stability, in American Control Conference, vol. 21, San Diego, CA, USA, 1999, pp. 3317–3321
A. Dehghani, A. Lecchini, A. Lanzon, B. Anderson, Validating controllers for internal stability utilizing closed-loop data. IEEE Trans. Autom. Control 59(11), 2719–2725 (2009)
R. Hildebrand, A. Lecchini, G. Solari, M. Gevers, Asymptotic accuracy of iterative feedback tuning. IEEE Trans. Autom. Control 50(8), 1182–1185 (2005)
H. Hjalmarsson, Iterative feedback tuning – An overview. Int. J. Adapt. Control Signal Process. 16(5), 373–395 (2002)
H. Hjalmarsson, M. Gevers, S. Gunnarsson, O. Lequin, Iterative feedback tuning: Theory and applications. IEEE Control Syst. Mag. 18(4), 26–41 (1998)
H. Hjalmarsson, S. Gunnarsson, M. Gevers, A convergent iterative restricted complexity control design scheme, in 33rd IEEE Conference on Decision and Control, Lake Buena Vista, USA, 1994
L.C. Kammer, Stability assessment for cautious iterative controller tuning. Automatica 41, 1829–1834 (2005)
L.C. Kammer, R.R. Bitmead, P.L. Bartlett, Direct iterative tuning via spectral analysis. Automatica 36, 1301–1307 (2000)
A. Karimi, L. Mišković, D. Bonvin, Iterative correlation-based controller tuning: Application to a magnetic suspension system. Control Eng. Pract. 11, 1069–1078 (2003)
A. Karimi, L. Mišković, D. Bonvin, Iterative correlation-based controller tuning. Int. J. Adapt. Control Signal Process. 18, 645–664 (2004)
A. Lecchini, M. Gevers, On iterative feedback tuning for non-minimum phase plants, in 41st IEEE Conference on Decision and Control, 2002, pp. 4658–4663
A. Lecchini, M. Gevers, J. Maciejowski, An iterative feedback tuning procedure for loop transfer recovery, in IFAC Symposium on System Identification, Newcastle, Australia, 2006
L. Ljung, System Identification – Theory for the User, 2nd edn. (Prentice Hall, New York, 1999)
H. Procházka, M. Gevers, B.D.O. Anderson, C. Ferrera, Iterative feedback tuning for robust controller design and optimization, in IEEE Conference on Decision and Control – European Control Conference, Seville, Spain, 2005
G. Solari, M. Gevers, Unbiased estimation of the Hessian for iterative feedback tuning (IFT), in 43th Conference on Decision and Control, Atlantis, Paradise Island, Bahamas, 2004, pp. 1759–1760
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2012 Springer Science+Business Media B.V.
About this chapter
Cite this chapter
Sanfelice Bazanella, A., Campestrini, L., Eckhard, D. (2012). Computations. In: Data-Driven Controller Design. Communications and Control Engineering. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-2300-9_7
Download citation
DOI: https://doi.org/10.1007/978-94-007-2300-9_7
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-2299-6
Online ISBN: 978-94-007-2300-9
eBook Packages: EngineeringEngineering (R0)