INFORMATION FOR REGISTERED ATTENDEES
- The workshop ran on July 11, 2020. It consisted of a Zoom session conducted by IFAC, where the recorded presentations were streamed, followed by another Zoom session conducted by the organizers for questions and discussions. If you were unable to make these, the recorded presentations are available for streaming until August 31, 2020 for registered participants. Details should have been emailed to you by IFAC.
- The workshop slides are available for the participants at the bottom of this page. The password was announced during the Zoom sessions on July 11, 2020. If you were not able to attend this session (for example, because you were planning to watch the recordings at another time), please contact the organizers for the password to the slides.
- The workshop has a dedicated discussion forum (Piazza website) for participants to post their questions/comments. Please fill this form if you want to be added to the forum. You will be registered to the website with your email address, and an automated invite link will be sent to you. The organizers and speakers will continue to monitor the forum and answer questions as time allows.
For any other questions, please contact the organizers.
Berlin, Germany (Virtual Workshop)
July 11, 2020
Dr. Berk Altın1 (organizer and presenter)
Prof. Ricardo G. Sanfelice1 (organizer and presenter)
Prof. Francesco Ferrante2 (presenter)
Dr. Mohamed A. Maghenem1 (presenter)
Hybrid systems model the behavior of dynamical systems where the states can evolve continuously as well as instantaneously. Such systems arise when hybrid control algorithms — algorithms which involve logic, timers, clocks, and other digital devices — are applied to continuous-time systems, or due to the intrinsic dynamics (e.g., mechanical systems with impacts and switching electrical circuits). Hybrid control may be used for improved performance and robustness properties compared to conventional control, and hybrid dynamics may be unavoidable due to the interplay between digital and analog components of a system. This full day workshop is a brief but complete course on the analysis and design of model predictive control (MPC) algorithms for hybrid dynamical systems.
The workshop has two main parts. The first part presents an overview of the literature and state-of-the-art on hybrid MPC, and provides a short tutorial on a powerful hybrid modeling framework that encapsulates switched systems, hybrid automata, impulsive systems, and many other class of systems; see Goebel et al., 2009. Key analysis tools corresponding to this framework, along with several advantages over other hybrid frameworks are demonstrated. This necessary background is then used to lay the theoretical foundations of a general MPC framework for hybrid dynamical systems, with guaranteed stability and feasibility. The ideas are illustrated in several applications, including networked systems, mechanical systems with impacts, power systems, and autonomous vehicles.
The second part presents several synthesis and analysis tools arising in the aforementioned hybrid systems framework, as they pertain to the MPC problem. It also presents a computationally tractable counterpart of the MPC framework in the first part. This particular MPC scheme relies on the time-discretization of the underlying continuous-time dynamics. Feasibility and stability properties of the nondiscretized hybrid MPC algorithm presented in the first part are extended to the discretized case. Computational methods to solve the optimal control problem, such as mixed integer nonlinear programming, are presented. As the discretization of hybrid dynamical systems is a nontrivial problem, appropriate discretization techniques are demonstrated. Applications are revisited. The workshop concludes with an in-depth discussion on open problems.
A particular goal of the workshop is to reveal the key steps in carrying over MPC methodologies to the hybrid dynamics setting. Each proposed module/lecture is designed to present key theoretical concepts as well as applications of current relevance.
The workshop is based in part on the recent articles by the organizers. Preprints of these articles are available at https://hybrid.soe.ucsc.edu/biblio.
The workshop targets a broad audience in academia and industry, including graduate students, looking for an introduction to a new and active area of research and to some modern mathematical analysis tools; control practitioners interested in novel design techniques; researchers in dynamical systems in pursuit of relevant applications; and researchers in industry and labs applying hybrid predictive control methods to engineering systems. The required background is basic familiarity with continuous-time and discrete-time linear and nonlinear systems. The lectures are closely related to each other and not meant to be independent research presentations.
Times indicated are local time in Berlin.
- [10:00-10:05] Welcome Remarks (Berk Altın)
- [10:05-11:40] Introduction to Hybrid Dynamical Systems: Modeling, Examples, Asymptotic Stability (Francesco Ferrante)
- [11:40-12:30] Background on Hybrid Model Predictive Control: Models, Methods, and Open Questions (Ricardo G. Sanfelice)
- Further Reading: Tuna et al., 2007; Sanfelice, 2018; Altın et al., 2018; Altın and Sanfelice, 2019
- See Also:
- F. Borrelli, A. Bemporad, and M. Morari. Predictive control for linear and hybrid systems. Cambridge University Press, 2017.
- P. Sopasakis, P. Patrinos, H. Sarimveis, and A. Bemporad. Model predictive control for linear impulsive systems. IEEE Transactions on Automatic Control, 60(8):2277–2282, 2015.
- D. Q. Mayne, "Model predictive control: Recent developments and future promise", Automatica, 12/2014.
- M. Lazar, W.M.P.H. Heemels, and A. Bemporad. Stabilizing model predictive control of hybrid systems. IEEE Transactions on Automatic Control, 51(11):1813–1818, 2006.
- A. Bemporad, F. Borrelli, and M. Morari. Piecewise linear optimal controllers for hybrid systems. In Proceedings of the 2000 American Control Conference, volume 2, pages 1190–1194. IEEE, 2000.
- [12:30-12:45] Overview of Model Predictive Control for Hybrid Dynamical Systems (Berk Altın)
--- Lunch ---
- [13:30-13:50] Model Predictive Control for Hybrid Dynamical Systems: Feasibility, Value Function Properties, Lyapunov Stability Analysis (Berk Altın)
- Further Reading: Altın and Sanfelice, 2019
- See also: B. Altın, and R. G. Sanfelice "Model Predictive Control for Hybrid Dynamical Systems: Suffcient Conditions for Asymptotic Stability with Persistent Flows or Jumps", American Control Conference, 2020.
- [13:50-14:25] Control Lyapunov Functions for Hybrid MPC (Ricardo G. Sanfelice)
- Further Reading: Sanfelice, 2013
- [14:25-15:15] Forward Invariance Tools for Hybrid MPC (Mohamed Maghenem)
- Further Reading: Maghenem and Sanfelice, 2018; Chai and Sanfelice, 2019; Maghenem and Sanfelice, 2019a; Maghenem and Sanfelice, 2019b
- See Also: M. Maghenem and R. G. Sanfelice, "Sufficient conditions for forward invariance and contractivity in hybrid inclusions using barrier functions", arXiv preprint:1908.03980, 2019.
- [15:15-15:50] Evaluating the Cost of Hybrid MPC without Computing (Francesco Ferrante)
--- Coffee Break ---
- [16:05-16:25] Discretizing Hybrid Dynamical Systems to Solve the Hybrid MPC Problem (Berk Altın)
- [16:25-16:50] Hybrid MPC Applications (Ricardo G. Sanfelice, Mohamed Maghenem, Francesco Ferrante)
- [16:50-17:00] Open Problems and Concluding Remarks (Ricardo G. Sanfelice) (conducted live, no recordings)
- Further Reading: Sanfelice and Teel, 2010
- [17:00-18:30] Live Session (Berk Altın, Ricardo G. Sanfelice, Francesco Ferrante, Mohamed Maghenem)
Berk Altın received his B.S. in Mechatronics from Sabancı University in 2011, Istanbul, Turkey in 2011. From 2011 to 2016, he attended the University of Michigan, Ann Arbor, as a Fulbright fellow, where he received the M.S. and Ph.D. degrees in Electrical Engineering: Systems, and the M.S. degree in Mathematics, in 2013, 2016 and 2016, respectively. He is currently employed as a postdoctoral researcher at the University of California, Santa Cruz, with the Hybrid Systems Laboratory. His primary research interests include hybrid systems, model predictive control, iterative learning control, repetitive processes, and multidimensional systems, with applications in cyber-physical systems, power systems, robotics, and additive manufacturing.
Ricardo G. Sanfelice received the B.S. degree in Electronics Engineering from the Universidad de Mar del Plata, Buenos Aires, Argentina, in 2001, and the M.S. and Ph.D. degrees in Electrical and Computer Engineering from the University of California, Santa Barbara, CA, USA, in 2004 and 2007, respectively. In 2007 and 2008, he held postdoctoral positions at the Laboratory for Information and Decision Systems at the Massachusetts Institute of Technology and at the Centre Automatique et Systemes at the Ecole de Mines de Paris. In 2009, he joined the faculty of the Department of Aerospace and Mechanical Engineering at the University of Arizona, Tucson, AZ, USA, where he was an Assistant Professor. In 2014, he joined the faculty of the Computer Engineering Department, University of California, Santa Cruz, CA, USA, where he is currently an Associate Professor. Prof. Sanfelice is the recipient of the 2013 SIAM Control and Systems Theory Prize, the National Science Foundation CAREER award, the Air Force Young Investigator Research Award, and the 2010 IEEE Control Systems Magazine Outstanding Paper Award. He is Associate Editor for Automatica and serves as Chair of the Hybrid Systems Technical Committee from the IEEE Control Systems Society. His research interests are in modeling, stability, robust control, observer design, and simulation of nonlinear and hybrid systems with applications to power systems, aerospace, and biology.
Francesco Ferrante received the B.Sc. (Laurea) degree in control engineering from the Sapienza Università di Roma, Italy, in 2010, the M.Sc. (Laurea Magistrale) degree in control engineering from the Università degli Studi di Roma Tor Vergata, Italy in 2012, and the Ph.D. degree in control theory from the Institut supérieur de l’aéronautique et de l’espace (SUPAERO) Toulouse, France, in 2015. In 2014, he held a Visiting Scholar position at the Department of Computer Engineering, University of California Santa Cruz. From November 2015 to August 2016, he was a Post-DoctoralFellow at the Department of Electrical and Computer Engineering, Clemson University, Clemson, SC, USA. From August 2015 to September 2016, he held a position as a Post-Doctoral Scientist at the Hybrid Systems Laboratory, University of California at Santa Cruz. He is currently an Assistant Professor with the Faculty of Sciences, Université Grenoble Alpes, France. He also holds an Adjunct Assistant Professor position at the Department of Automotive Engineering, Clemson University. He currently serves as an Associate Editor for the European Journal of Control, the IMA journal of Journal of Mathematical Control and Information, and the conference editorial boards of the IEEE Control Systems Society and the European Control Association.
Mohamed Adlene Maghenem received his Control-Engineering Degree from the Polytechnical School of Algiers, Algeria, in 2013. He received his M.S. and Ph.D. degrees in Control from the University of Paris-Saclay, France, in 2014 and 2017, respectively. He is currently a Postdoctoral Fellow at the Electrical and Computer Engineering Department at the University of California, Santa Cruz. His research interests include: distributed coordination of multiagent systems with application to synchronization of oscillators and formation control of mechanical systems, control of nonholonomic and underactuated systems, singular perturbations, and safety verification in hybrid dynamical systems.
If you are interested in attending, please register until July 8, 2020.
Participation in the workshop does not require participation in IFAC WC. The registration fee is €40-70. Further details are available at https://www.ifac2020.org/program/workshops.html
For further information, contact Berk Altın (email@example.com) or Ricardo G. Sanfelice (firstname.lastname@example.org).
- "Hybrid MPC: Open-minded but not Easily Swayed", Assessment and Future Directions of Nonlinear Model Predictive Control, vol. Lecture Notes in Control and Information Sciences 358: Springer Berlin / Heidelberg, pp. 17–34, 2007.
- R. Goebel, R. G. Sanfelice, and A.R. Teel "Hybrid dynamical systems", IEEE Control Systems Magazine, vol. 29, no. 2, pp. 28-93, April, 2009.
- R. G. Sanfelice, and A. R. Teel "Dynamical Properties of Hybrid Systems Simulators", Automatica, vol. 46, no. 2, pp. 239–248, 2010.
- R. Goebel, R. G. Sanfelice, and A. R. Teel Hybrid Dynamical Systems: Modeling, Stability, and Robustness , New Jersey, Princeton University Press, 2012.
- R. G. Sanfelice, D. A. Copp, and P. Nanez "A Toolbox for Simulation of Hybrid Systems in Matlab/Simulink: Hybrid Equations (HyEQ) Toolbox", Proceedings of Hybrid Systems: Computation and Control Conference, pp. 101–106, 2013.
- R. G. Sanfelice "On the existence of control Lyapunov functions and state-feedback laws for hybrid systems", IEEE Transactions on Automatic Control, vol. 58, no. 12, pp. 3242–3248, December, 2013.
- T. A. F. Theunisse, J. Chai, R. G. Sanfelice, and W.P.M.H. Heemels "Hybrid Control of the Boost Converter: Robust Global Stabilization", Proceedings of the IEEE Conference on Decision and Control, pp. 3635–3640, 2013.
- R. G. Sanfelice "Hybrid Model Predictive Control", Handbook of Model Predictive Control, Edition 1, Basel, Birkhäuser , pp. pp. 199-220, 09/2018.
- L. Torquati, R. G. Sanfelice, and L. Zaccarian "A Hybrid Predictive Control Algorithm for Tracking in a Single-Phase DC/AC Inverter", Proceedings of the IEEE Conference on Control Technology and Applications, no. 904--909, 2017.
- B. Short, and R. G. Sanfelice "A Hybrid Predictive Control Approach to Trajectory Tracking for a Fully Actuated Biped", Proceedings of the American Control Conference, pp. 3526-3531, 08/2018.
- B. Altin, P. Ojaghi, and R. G. Sanfelice "A Model Predictive Control Framework for Hybrid Systems", NMPC, vol. 51, pp. 128-133, August, 2018.
- F. Ferrante, and R. G. Sanfelice "Cost Evaluation for Hybrid Inclusions: A Lyapunov Approach", Proceedings of the 2018 IEEE Conference on Decision and Control, pp. 855-860, December, 2018.
- J. Chai, and R. G. Sanfelice "Forward Invariance of Sets for Hybrid Dynamical Systems (Part I)", IEEE Transactions on Automatic Control, vol. 64, pp. 2426-2441, 06/2019.
- "Robust Distributed Synchronization of Networked Linear Systems with Intermittent Information", Automatica, vol. 105, pp. 323-333, 07/2019.
- B. Altin, and R. G. Sanfelice "Asymptotically Stabilizing Model Predictive Control for Hybrid Dynamical Systems", Proceedings of the American Control Conference, July, 2019.
- M. Maghenem, and R. G. Sanfelice "Characterizations of safety and conditional invariance in dynamical systems", Proceedings of the American Control Conference, pp. 5039-5044, July, 2019.
- M. Maghenem, and R. G. Sanfelice "Characterizations of Safety in Hybrid Inclusions via Barrier Functions", Proceedings of the Hybrid Systems: Computation and Control, July, 2019.
- P. Ojaghi, B. Altin, and R.G. Sanfelice "A Model Predictive Control Framework for Asymptotic Stabilization of Discretized Hybrid Dynamical Systems", Proceedings of the 2019 IEEE Conference on Decision and Control, December, 2019.
- F. Ferrante, and R. G. Sanfelice "Certifying Optimality in Hybrid Control Systems via Lyapunov-like Conditions", 11th IFAC Symposium on Nonlinear Control Systems (NOLCOS 2019), 2019.