Tom Oomen

## Research on Advanced and Iterative Feedforward ControlFrom our prespective, traditional feedforward control design techniques involve a trade-off between performance and flexibility. Flexibility is here meant as performance robustness with respect to e.g. setpoint changes. Our vision is that new research is necessary to obtain a breakthrough that does not suffer from this trade-off. This is summarized in the following figure and in the publication: Intelligente regeltechniek voor nieuwe generatie mechatronica [pdf] Joost Bolder, Frank Boeren, and Tom Oomen
*Aandrijftechniek*, 10:22-24 (In Dutch), 2014
We investigate two aspects: ILC for ultra-high performance: see our dedicated Iterative Learning Control page advanced feedforward control by combining high flexibility of traditional controllers with high performance obtained through iterative learning control
As a continuation of the pioneering work of Jeroen van de Wijdeven and Stan van der Meulen in the early 2000s in the CST group, we have made significant progress in developing a framework for advanced feedforward control. We are developing the following two alternative approaches: on based on Iterative Learning Control (ILC) and one based on System Identification. Both approaches are outlined below. Their differences are also clearly illustrated in the following movie: ## ILC with basis functionsOn the one hand, a research line based on ILC is pursued. The basic idea is to introduce basis functions in ILC to parameterize the feedforward signal. Initial steps using polynomial basis functions are presented in Using iterative learning control with basis functions to compensate medium deformation in a wide-format inkjet printer [preprint|link] Joost Bolder, Tom Oomen, Sjirk Koekebakker, and Maarten Steinbuch
*IFAC Mechatronics*, Invited paper, 24(8): 944-953, 2014Iterative learning control with basis functions for media positioning in scanning inkjet printers [pdf|link] Joost Bolder, Sjirk Koekebakker, Bas Lemmen, Tom Oomen, Okko Bosgra, and Maarten Steinbuch In*2012 IEEE Multi-conference on Systems and Control*, invited paper, 1255-1260, Dubrovnik, Croatia, 2012
All of the above results have been developed in the so-called lifted ILC framework with typically a quadratic criterion. To facilitate the implementation in various industries, we have also developed an approach based on frequency domain ILC design principles. The results are documented in Frequency-domain ILC approach for repeating and varying tasks: With application to semiconductor bonding equipment [preprint] Frank Boeren, Abhishek Bareja, Tom Kok, and Tom Oomen
*IEEE/ASME Transactions on Mechatronics*, To appear
Unified ILC Framework for Repeating and Varying Tasks: A Frequency Domain Approach with Application to Semiconductor Bonding Equipment Frank Boeren, Abhishek Bareja, Tom Kok, and Tom Oomen In*54th IEEE Conference on Decision and Control*, Invited paper, Osaka, Japan, 2015
Interesting applications of these ILC-based approaches are reported in various places, including
Using iterative learning control with basis functions to compensate medium deformation in a wide-format inkjet printer [preprint|link] Joost Bolder, Tom Oomen, Sjirk Koekebakker, and Maarten Steinbuch
*IFAC Mechatronics*, Invited paper, 24(8): 944-953, 2014Rational basis functions and Norm Optimal ILC: Application to industrial setups B. Moris M.Sc. Thesis, Eindhoven University of Technology, Eindhoven, The Netherlands, 2013Unified ILC Design Framework for Repeating and Almost Repeating Tasks Abhishek Bareja M.Sc. Thesis, Eindhoven University of Technology, Eindhoven, The Netherlands, 2014Iterative Learning Control with a Rational Feedforward Basis: a new Solution Algorithm Jurgen van Zundert M.Sc. Thesis, Eindhoven University of Technology, Eindhoven, The Netherlands, 2014
## System identification based approach: instrumental variablesOn the other hand, we have been developing an approach based on Instrumental Variable System Identification. Initial steps towards this approach have been taken already in 2008, after we realised that pre-existing data-based feedforward tuning approaches suffered from a closed-loop identification problem. Initial steps towards IV-based feedforward tuning are reported in Iterative motion feedforward tuning: A data-driven approach based on instrumental variable identification [pdf|link] Frank Boeren, Tom Oomen, Maarten Steinbuch
*Control Engineering Practice*, 37, 11-19, 2015Iterative feedforward control: A closed-loop identification problem and a solution [pdf] Frank Boeren and Tom Oomen In*Proceedings of the 51th IEEE Conference on Decision and Control*, 6694-6699, Florence, Italy, 2013Optimal iterative feedforward control for High-precision motion systems using Closed-loop identification methods Robin de Rozario B.Sc. Thesis, Eindhoven University of Technology, Eindhoven, The Netherlands, 2013
Soon after developing these techniques, we realised that we had indeed solved the bias problems due to closed-loop operation, but the accuracy of our approach in terms of variance had not yet been investigated. In fact, initial applications suffered from a very poor performance due to a large variance error. This lead to the development of optimal instumental variable based methods, which are reported in Accuracy aspects in motion feedforward tuning [pdf] Frank Boeren, Tom Oomen, and Maarten Steinbuch In*Proceedings of the 2014 American Control Conference*, 2178-2183, Portland, Oregon, United States, 2014Enhanced motion feedforward tuning exploiting IV-identification: with extension to input shaping Leon van Breugel M.Sc. Thesis, Eindhoven University of Technology, Eindhoven, The Netherlands, 2013 Further extensions towards input shaping are reported inJoint input shaping and feedforward for point-to-point motion: Automated tuning for an industrial nanopositioning system [preprint|link|errata] Frank Boeren, Dennis Bruijnen, Niels van Dijk, and Tom Oomen
*IFAC Mechatronics*, Invited paper, 24(6): 572-581, 2014 Whereas extensions to rational feedforward compensators are reported inRational feedforward tuning: Approaches, stable inversion, and experimental Comparison [pdf] Lennart Blanken, Frank Boeren, Dennis Bruijnen, and Tom Oomen In*2016 IEEE American Control Conference*, Invited paper, Boston, Massachusetts, United States, 2016
Several successful applications of the Instrumental Variable approach have been obtained and are reported in, e.g.,
Iterative feedforward tuning approach and experimental verification for nano-precision motion systems [pdf] Frank Boeren, Dennis Bruijnen, Tom Oomen In*ASME 2014 Dynamic Systems and Control*, San Antonio, Texas, 2014Enhanced motion feedforward tuning exploiting IV-identification: with extension to input shaping Leon van Breugel M.Sc. Thesis, Eindhoven University of Technology, Eindhoven, The Netherlands, 2013Rational Feedforward: Optimal IV Approach and Experimental Comparison on a Wafer Stage Lennart Blanken M.Sc. Thesis, Eindhoven University of Technology, Eindhoven, The Netherlands, 2015Rational feedforward tuning: Approaches, stable inversion, and experimental Comparison [pdf] Lennart Blanken, Frank Boeren, Dennis Bruijnen, and Tom Oomen In*2016 IEEE American Control Conference*, Invited paper, Boston, Massachusetts, United States, 2016
## Rational basis functions: tuning and non-causalityAs an extension of polynomial basis functions, we have been extensively investigating the use of rational basis functions in feedforward and learning control. In particular, the use of rational learning filters is quite common in ILC (think about In this respect, the steps one has to take with rational feedforward are very similar to an ILC design. Especially in the first iteration, this is basically just inverting the system, either being open-loop or closed-loop, but this does not lead to a fundamental difference.
The inverse of a system can be directly computed
where the key observation is that the inverse has a certain system matrix that depends on all matrices of the original state-space realization. As a result, stability is not straightforward, and in the LTI case this requires non-minimum phase behavior of the original system. See, e.g., Jurgen van Zundert, Joost Bolder, Sjirk Koekebakker, and Tom Oomen Manuscript under review, 2016
The main idea behind implementing these ZPETC and stable inversion algorithms is to try to invert a nonminimum-phase system. Of course, these inverses are unstable if one uses the standard unilateral Laplace or z-transform. By using the bilateral Laplace or z-transform, a bounded yet noncausal inverse can be obtained, which is Lennart Blanken, Frank Boeren, Dennis Bruijnen, Tom Oomen Submitted for publication, 2015Rational feedforward tuning: Approaches, stable inversion, and experimental Comparison [pdf] Lennart Blanken, Frank Boeren, Dennis Bruijnen, and Tom Oomen In*2016 IEEE American Control Conference*, Invited paper, Boston, Massachusetts, United States, 2016
Further developments of rational basis functions in ILC are presented in Rational basis functions in iterative learning control - With experimental verification on a motion system [preprint|link] Joost Bolder and Tom Oomen
*IEEE Transactions on Control Systems Technology*, 23(2), 722-729, 2015Optimality and flexibility in iterative learning control for varying tasks [preprint|link] Jurgen van Zundert, Joost Bolder, and Tom Oomen
*Automatica*, 67, 295-302, 2016
Similarly, the use of rational basis functions in instrumental variable-based feedforward tuning are presented in Rational Iterative Feedforward Control: Optimal Instrumental Variable Approach for Enhanced Performance Frank Boeren, Lennart Blanken, Dennis Bruijnen, and Tom Oomen In*54th IEEE Conference on Decision and Control*, Invited paper, Osaka, Japan, 2015
State-space computations for stable inversion are described in Appendix A of Iterative motion feedforward tuning: A data-driven approach based on instrumental variable identification [pdf|link|matlab] Frank Boeren, Tom Oomen, Maarten Steinbuch
*Control Engineering Practice*, 37, 11-19, 2015Jurgen van Zundert, Joost Bolder, Sjirk Koekebakker, and Tom Oomen Manuscript under review, 2016
## Extensions: beyond SISO LTIThe results described above involve the basic steps we have taken in recent years. At present, the research on these topics gained quite some momentum, at present (2016) four Ph.D. projects are working on this in our team. Some recent extensions include the following.
Jurgen van Zundert, Joost Bolder, Sjirk Koekebakker, and Tom Oomen Manuscript under review, 2016
some details may be found in Jurgen van Zundert, Joost Bolder, Sjirk Koekebakker, and Tom Oomen Manuscript under review, 2016
as well as a rational feedforward tuning approach, e.g., initial results are documented in P. Smits M.Sc. Thesis, Eindhoven University of Technology, Eindhoven, The Netherlands, 2016 (to appear)
non-equidistant sampling may enhance reliable and fast (on average) sampling frequencies. Some initial results are described in On the potential of lifted domain feedforward controllers with a periodic sampling sequence [pdf] Jurgen van Zundert, Tom Oomen, Dip Goswami, and Maurice Heemels In*2016 IEEE American Control Conference*, Invited paper, Boston, Massachusetts, United States, 2016
sampling frequencies may be significantly increased in control loops that are critical for high performance. To avoid excessive hardware cost, we believe it may be attractive to implement other loops at a low sampling frequency. Therefore, we are developing a multirate feedforward approach to deal with this scenario. The results are in line with the sampled-data/multirate ILC approaches in the research page on iterative learning control but then using basis functions as explained above and multirate controllers. The results are documented in Feedforward for multi-rate motion control: Enhanced performance and cost-effectiveness [pdf] J.C.D. van Zundert, J.L.C. Verhaegh, W.H.T.M. Aangenent, T. Oomen, D. Antunes, and W.P.M.H. Heemels In*Proceedings of the 2015 American Control Conference*, 2831-2836, Invited paper, Chicago, Illinois, United States, 2015
*Extension to multivariable systems*. If the system is multivariable, additional complications may be encountered. Small parts of the interesting research that is done here are described inDesign techniques for multivariable ILC: Application to an industrial flatbed printer Lennart Blanken, Jeroen Willems, Sjirk Koekebakker, and Tom Oomen In*7th IFAC Symposium on Mechatronic Systems & 15th Mechatronics Forum International Conference*, Loughborough, UK, 2016
*Further extensions*. The above list is just a glimpse on what is being developed at the moment. Please check again soon, as we will gradually expand this page (usually with some delay, unfortunately, so don't forget to check the publications page, which is usually a bit more up to date.
## Learn more?If you want to learn how to improve the performance of your system, check out the teaching page for information on M.Sc., Ph.D., and post-academic/industrial courses! ## 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: Frank Boeren, Jurgen van Zundert, Lennart Blanken, Robin de Rozario, Maarten Steinbuch, Maurice Heemels Previous reseachers at TU/e-ME-CST: Joost Bolder, Okko Bosgra, Bart Moris, Leon van Breugel, Abhishek Bareja, Robin de Rozario, Janno Lunenburg, Jan Verhaegh, Jeroen van de Wijdeven, Stan van der Meulen, Pepijn Smits, Duarte Antunes Industrial collaborators from NXP, Oce, Philips: Sjirk Koekebakker, Dennis Bruijnen, Tom Kok, Niels van Dijk, 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. |