Tom Oomen

## Research on Numerically Reliable Identification of Complex SystemsWe envisage that next-generation motion systems are lightweight. Consequently, these will exhibit dominant lightly damped flexible dynamics. In the future, we will actively compensate these dynamics through many actuators and sensors. In addition, a distinction will be made between measured variables and performance variables, as is explained on the inferential control page. As is argued in Oomen
Identification of models for mechanical systems is often done in the frequency domain, since this enables an efficient data reduction, combination of experiments for multivariable systems, visual inspection of the model fit, and control-relevant modeling. A main challenge lies in the numerically reliable identification of such models. Already for the two input-two output case reported in Oomen Identification for robust control of complex systems: Algorithm and motion application [preprint] Tom Oomen and Maarten Steinbuch In: Marco Lovera, Editor:*Control-oriented modelling and identification: theory and applications*, IET, 2015 Initial work in this direction is reported inRobust-control-relevant coprime factor identification: A numerically reliable frequency domain approach [pdf|link] Tom Oomen and Okko Bosgra In*Proceedings of the 2008 American Control Conference*, 625-631, Seattle, Washington, United States, 2008System identification for robust and inferential control with applications to ILC and precision motion systems [pdf] Tom Oomen Appendix A, Ph.D. Thesis, Eindhoven University of Technology, ISBN: 978-90-386-2189-0, Eindhoven, The Netherlands, 2010
Besides the above developments to enhance numerical conditioning, we have also investigated enhancements of the underlying algorithm. Interestingly, instrumental variable-based algorithms turn out to have significantly better convergence properties compared to the Sanathanan-Koerner iteration that is used in the references above. The main drawback of these instrumental variable-based algorithms is twofold. First, the conditioning is approximately quadratically worse (!) compared to the Sanathanan-Koerner algorithm. Second, the Bi-orthonormal basis functions for improved frequency domain system identification [pdf|link] Robbert van Herpen, Tom Oomen, and Okko Bosgra In*Proceedings of the 51th IEEE Conference on Decision and Control*, 3451-3456, Maui, Hawaii, United States, 2012
In recent years, we have further developed the theory. The underlying fundamental theory is presented in the following two identical documents
Bi-Orthonormal Polynomial Basis Function Framework with Applications in System Identification [preprint] Robbert van Herpen, Okko Bosgra, and Tom Oomen Provisionally accepted for publicationIdentification for Control of Complex Motion Systems: Optimal Numerical Conditioning using Data-Dependent Polynomial Bases [pdf] Robbert van Herpen Chapter 2, Ph.D. Thesis, Eindhoven University of Technology, Eindhoven, The Netherlands, 2014
Application of the developed theory to instrumental variable system identification, requiring a orthonormal vector extension of the fundamental theory mentioned above, and experimental validation is presented in the following two identical documents
Optimally conditioned instrumental variable approach for frequency-domain system identification [preprint|link] Robbert van Herpen, Tom Oomen, and Maarten Steinbuch
*Automatica*, 50(9), 2281-2293, 2014Identification for Control of Complex Motion Systems: Optimal Numerical Conditioning using Data-Dependent Polynomial Bases [pdf] Robbert van Herpen Chapter 3, Ph.D. Thesis, Eindhoven University of Technology, Eindhoven, The Netherlands, 2014
Recently, we have benchmarked the developed approach and compared it to alternative approaches in the literature. In addition, we have made some interesting extensions to pre-existing approaches. The results are documented in On numerically reliable frequency-domain system identification: new connections and a comparison of methods [pdf] Robbert Voorhoeve, Tom Oomen, Robbert van Herpen, and Maarten Steinbuch In*Proceedings of the IFAC 19th Triennial World Congress*, 10018-10023, Cape Town, South Africa, 2014
## AcknowledgementThe success of all the above work is due to the hard and excellent work of many people involved in this research, including Active researchers at TU/e-ME-CST: Robbert Voorhoeve, Maarten Steinbuch Previous reseachers at TU/e-ME-CST: Okko Bosgra, Robbert van Herpen Industrial collaborators from Philips/ASML: Marc van de Wal, Wouter Aangenent and many others
Note that all figures shown on this page can be found in the mentioned papers. Please follow the guidelines regarding copyright and references when citing these. |