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Content/Contributors/Date&Location/Program/Registration/Questions?

1-day pre-congress workshop
at the 45th IEEE Conference on Decision and Control, San Diego, CA, USA


Model predictive control for fast nonlinear systems:
existing approaches, challenges, and applications

December 12th, 2006
prior to the  45th IEEE Conference on Decision and Control


Content and objective:

Model predictive control (MPC), also referred to as moving or receding horizon control, is a control strategy in which the applied input is determined on-line at the recalculation instant by solving an open-loop optimal control problem over a fixed prediction horizon into the future. The first part of the obtained open-loop input signal is implemented until new measurements become available. Based on the new information the open-loop optimal control problem is solved again and the whole procedure is repeated.

Over the past decade significant theoretical as well as implementational advances in the area of nonlinear model predictive control (NMPC) have been achieved. By now many issues related to stability and robustness of NMPC are well understood and NMPC has been successfully applied in practice to relatively slow processes, mainly in the process industry.

One of the main remaining questions is how NMPC can be applied to relatively fast systems such as robotic systems, aerospace systems, electrical systems, or automotive systems, since the appearing optimal control problem must be solved in real-time. Over the recent years significant progress with respect to the application of NMPC to fast systems has been made. The progress is carried by special NMPC formulations that allow a fast (approximate) solution of the appearing optimal control problem, as well as recent advances in the area of real-time solutions of optimal control problems.

The purpose of this workshop is twofold. The main objective is to provide an in depth review of the existing solution approaches for the application of NMPC to fast systems by some of the key researches in the field. The second objective is to underline these approaches considering practically relevant control examples from various areas such as the control of automotive systems, aerospace systems, or fast chemical processes.

The workshop starts with an elementary level before moving to the more advanced topics. It is accompanied by copies of the slides and suplementary material provided by the lecturers. It is of interest to graduate students, engineers, mathematicians and researchers, who are interested in becoming familiar with the application of nonlinear model predictive control to fast systems.

Contributors:

  • Mazen Alamir, Laboratoire d'Automatique de Grenoble, France
  •  Francesco Borrelli, Control Department of the Università del Sannio, Benevento, Italy
  • Moritz Diehl (Optimization in Engineering Center (OPTEC), K.U.Leuven, Belgium)
  •  Martin Guay, Department of Chemical Engineering, Queen’s University, Canda
  • Rolf Findeisen, organizer (IST, University of Stuttgart, Germany)
  • Toshiyuki Ohtsuka, Department of Mechanical Engineering, Graduate School of Engineering, Osaka University
Details about the lecturers can be found following the links.

Date and location:

The one day workshop/mini course will be held prior to the 45th IEEE Conference on Decision and Control. Details can be found on the conference web page or the registration form.

Tentative program:

Time Lecture Content
Presenter/Lecturer
08:40-08:45 Welcome + overview Rolf Findeisen
08:45-09:30 Introduction and overview to NMPC for fast nonlinear systems Rolf Findeisen
09:30-10:30 Efficient numerical solution methods for fast NMPC
Moritz Diehl
10:30-11:00 Coffee break
11:00-11:45 Real-time NMPC  using the continuation method and GMRES including mechatronic examples Toshiyuki Ohtsuka
11:45-12:30 A new real-time framework for NMPC of continuous-time systems with applications to chemical processes and manufacturing systems Martin Guay
12:30-13:45 Lunch break
13:45-14:45 The parameterized approach for fast NMPC Mazen Alamir
14:45-15:30 Nonlinear MPC applied to vehicle dynamics control Francesco Borrelli
15:30-16:00 Coffee breake
16:00-16:45 NMPC subject to communication delays and NMPC for automotive applications Rolf Findeisen
16:45-17:00 Wrap up, summary and outlook

Provided material:

Copies of the slides and supplementary material will be provided to the registered participants.

Course Web Page:

http://www.ist.uni-stuttgart.de/~findeise/fastnmpccdc06

Registration:

Please refer to the conference web page for registration.

Questions:

In case of additional questions or requests please feel free to contact:

Rolf Findeisen
Institute for Systems Theory and Automatic Control
University of Stuttgart
Pfaffenwaldring 9
70550 Stuttgart, Germany
Tel. +49-711-685-7748
Fax. +49-711-685-7735
findeise@ist.uni-stuttgart.de

Details about the lecturers

  • Mazen Alamir, Laboratoire d'Automatique de Grenoble, France:
    Mazen Alamir Mazen Alamir is researcher at the French National Research Center. He coordinates the Nonlinear Research Group of the Grenoble's Control Laboratory (LAG). His main research areas are nonlinear model predictive control, nonlinear receding horizon observers, nonlinear systems diagnosis with application in Mechatronics, process control, micro-systems and aerospace. He is Guest Editor of the Special Issue "NMPC for fast systems" in the International Journal of Robust and Nonlinear Control and organizer of the "IFAC 2006 Workshop on NMPC for Fast Systems". 

    Selected publications relevant to the workshop:
    • Alamir, M.: Stabilization of Nonlinear Systems Using Receding-Horizon Control Schemes: A Parameterized Approach for Fast Systems. Lecture Notes in Control and Information Sciences, Springer, London, ISBN 1-84628-470-8 (2006)
    • Alamir, M.: New path-generation based receding-horizon formulation for constrained   stabilization of nonlinear systems Automatica 40, No.4, 647-652 (2004).
    • Alamir, M. and Marchand, N. Constrained minimum-time-oriented feedback control for the stabilization of nonholonomic systems in chained form J. Optimization Theory Appl. 118, No.2,  229-244 (2003).

  •  Francesco Borrelli, Control Department of the Università del Sannio, Benevento, Italy:
    Francesco Borrelli Francesco Borrelli was born in Milano, Italy in 1974. He received the "Laurea" degree in computer science engineering in 1998 from the University of Naples "Federico II", Italy. In 2002 he received the Ph.D. from the Automatic Control Laboratory at ETH Zurich, Switzerland, advised by Prof. Manfred Morari. In 2003 he received the ETH Medal for the best Ph.D. dissertation. He has been a research assistant at the Automatic Control Laboratory of the ETH Zurich and a contract assistant professor at the Aerospace and Mechanics Department at the University of Minnesota, USA. Currently he is an assistant professor at the "Universita' del Sannio", Benevento, Italy. Francesco Borrelli is a consultant for Ford Research Laboratories (Dearborn, USA) and for Honeywell Laboratories (Minneapolis,USA). He is author of the book "Constrained Optimal Control of Linear and Hybrid Systems" published by Springer Verlag. He is the winner of the Innovation Prize from the ElectroSwiss Foundation. His research interests include constrained optimal control, model predictive control, robust control, parametric programming, singularly perturbed systems and automotive applications of automatic control.
    Selected publications relevant to the workshop:
    • Borrelli, F., Falcone, P. Keviczky, T., Asgari, J. and Hrovat, D.: MPC-based approach to active steering for autonomous vehicle systems. International Journal on Vehicle Autonomous Systems , vol. 3 , no. 2/3/4 , November 2005 , p. 265-291.
    • Borrelli, F. and Bemporad, A. and Fodor, M. and Hrovat, D.: A Hybrid Approach to Traction Control. Accepted for publication on the IEEE Transaction on Control System Technology, 2005.
    • Bemporad A., F. Borrelli and M. Morari, Min-max Control of Constrained Uncertain Discrete-Time Linear Systems, IEEE Transaction on Automatic Control, Vol. 48, No. 9, September 2003.


  • Moritz Diehl (Optimization in Engineering Center (OPTEC), K.U.Leuven, Belgium):
    Moritz Diehl is professor for optimization in engineering at the newly founded center for optimization in engineering (OPTEC) at K.U. Leuven. His main research interests are: algorithms for dynamic optimization, nonlinear model predictive control, parameter- and state estimation; applications e.g. in chemical engineering, medicine, robotics, power engineering. He serves as reviewer for "Automatica", "Automatisierungstechnik", "Computational Optimization and Applications", "Computers and Chemical Engineering", "Optimization and Engineering", "Journal of Process Control". moritz diehl

    Selected publications relevant to the workshop:
    • M. Diehl, R. Findeisen, H.G. Bock, J.P. Schlöder, and F. Allgöwer. Nominal stability of the real-time iteration scheme for nonlinear model predictive control. IEE Control Theory Appl., 152(3):296-308, 2005.
    • M. Diehl, H.G. Bock, and J.P. Schlöder:  A Real-Time Iteration Scheme for Nonlinear Optimization in Optimal Feedback Control.  SIAM Journal on Control and Optimization, Vol 43, No 5, pp. 1714-1736, 2005.
    • M. Diehl, R. Findeisen, S. Schwarzkopf, Ilknur Uslu, F. Allgöwer, H.G. Bock, E. D. Gilles, J.P. Schröder: An Efficient Algorithm for Optimization in Nonlinear Model Predictive Control of Large-Scale Systems. Automatisierungstechnik 12/2002 and 1/2003.
    • M. Diehl, I. Uslu, S. Schwarzkopf, F. Allgöwer, H.G. Bock, R. Findeisen, E.D. Gilles, A. Kienle, J.P. Schlöder, and E. Stein: Real-Time Optimization for Large Scale Processes: Nonlinear Model Predictive Control of a High Purity Distillation Column In Groetschel, Krumke, Rambau (eds.): Online Optimization of Large Scale Systems: State of the Art, Springer, 2001.

  • Martin Guay, Department of Chemical Engineering, Queen’s University, Canada:
    Martin Guay Martin Guay received his Ph.D. in Chemical Engineering at Queen’s University in 1996. From 1995 to 1997, he was a research scientist in Research and Development Center at Dupont Canada Inc. In 1997, he joined the Department of Chemical and Materials Engineering at the University of Alberta where he was Assistant Professor until 1999. He then joined the Department of Chemical Engineering at Queen’s University where he is Associate Professor. He is currently on leave at CESAME at l’Université Catholique de Louvain in Louvain-la-Neuve, Belgium. In 2004, he received the Premier Research Excellence Award from the Government of Ontario. His research interests are in the area nonlinear control theory, process control, bioprocess control and manufacturing systems control.
    Selected publications relevant to the workshop:
    • D. DeHaan, M. Guay: A new real-time method for nonlinear model predictive control, in Assessment and Future Directions of Nonlinear Model Predictive Control, Lecture Notes in Control and Information Sciences, R. Findeisen, R. Allgöwer, L. Biegler, ed(s)., Springer, 2006.
    • D. DeHaan, M. Guay: A Real-time Framework for Model Predictive Control of Continuous-Time Nonlinear Systems, Decision and Control, 2005 and 2005 European Control Conference. CDC-ECC '05. 2005, pp 957 – 962.
    • Adetola, V. and M. Guay: Nonlinear Receding Horizon Output-Feedback Control of Sampled-Data Systems, J. Proc. Control 15, 4, 469-480, 2005.
       
  • Rolf Findeisen (IST, University of Stuttgart, Germany):
    Rolf Findeisen is Habilitand (equivalent to assistant professor) and lecturer at the Institute for Systems Theory in Engineering at the University of Stuttgart. His main research areas are: nonlinear model predictive control, output feedback control, optimization based control and state estimation, differential algebraic systems, nonlinear control, system theoretical methods in biomedical engineering and biological systems; and the application of these methods in  chemical, biological and mechanical systems. He serves as reviewer for various journals and conferences including Automatica, IEEE Transaction on Automatic Control, SIAM Journal on Control and Optimization, Computers and Chemical Engineering, System and Control Letters, Journal of Process Control. Rolf Findeisen

    Selected publications relevant to the workshop:
    • R. Findeisen, L.B. Biegler, and F. Allgöwer, editors. Assessment and Future Directions of Nonlinear Model Predictive Control. Lecture Notes in Control and Information Sciences. Springer-Verlag, Berlin, 2006.
    • D. Mayne, S.V. Rakovi, R. Findeisen, and F. Allgöwer. Robust output feedback model predictive control of constrained linear systems. Automatica, 1217-1222(42):7, 2006.
    • M. Diehl, R. Findeisen, H.G. Bock, J.P. Schlöder, and F. Allgöwer. Nominal stability of the real-time iteration scheme for nonlinear model predictive control. IEE Control Theory Appl., 152(3):296-308, 2005.
    • R. Findeisen, L. Imsland, F. Allgöwer, and B.A. Foss. Output feedback stabilization for constrained systems with nonlinear model predictive control. Int. J. of Robust and Nonlinear Control, 13(3-4):211-227, 2003.

  • Toshiyuki Ohtsuka (Department of Mechanical Engineering, Graduate School of Engineering, Osaka University):
    Ohtsuka
    Toshiyuki Ohtsuka was born in Tokyo, Japan, in 1967. He received his doctoral degree in aerospace engineering from the Tokyo Metropolitan Institute of Technology, Tokyo, Japan, in 1995. During 1995–1999, he was an Assistant Professor at the University of Tsukuba, Ibaraki, Japan. Since 1999, he has been with the Department of Computer-Controlled Mechanical Systems at the Graduate School of Engineering, Osaka University, Osaka, Japan, where he is currently an Associate Professor. His research interests include nonlinear control theory with applications to aerospace engineering and mechanical engineering.

    Selected publications relevant to the workshop:
    • Ohtsuka, T. A Continuation/GMRES Method for Fast Computation of Nonlinear Receding Horizon Control. Automatica, Vol. 40, No. 4, Apr. 2004, pp. 563-574.
    • Seguchi, H., and Ohtsuka, T.: Nonlinear Receding Horizon Control of an Underactuated Hovercraft. International Journal of Robust and Nonlinear Control, Vol. 13, Nos. 3-4, Mar.-Apr. 2003, pp. 381-398.
    • Ohtsuka, T., and Fujii, H.A.: Real-Time Optimization Algorithm for Nonlinear Receding-Horizon Control.  Automatica, Vol. 33, No. 6, June 1997, pp. 1147-1154.

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