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Bode Lecture: Richard M. Murray
California Institute of Technology, USA
Future Directions in Control: A Look Backwards and Forwards
Time: 8:30-9:30 a.m, Wednesday, December 14, 2016
Location: Room Ironwood 4
Abstract:The field of control provides the principles and methods used to design physical, biological and information systems that maintain desirable performance by sensing and automatically adapting to changes in the environment. The opportunities to apply control principles and methods are exploding. In this talk I will briefly review some of the past predictions for future directions in control (including some of my own) and provide some thoughts on how well the field is doing in terms of living up to its past promises of future success. The ultimate goal of the talk is to help inspire the next generation of controls researchers, balance theory with application, provide a view into the possible futures of control, give credit where it is due, and let the guard down and talk about personal stuff a bit.
Biography: Richard M. Murray received the B.S. degree in Electrical Engineering from California Institute of Technology in 1985 and the M.S. and Ph.D. degrees in Electrical Engineering and Computer Sciences from the University of California, Berkeley, in 1988 and 1991, respectively. He is currently the Thomas E. and Doris Everhart Professor of Control & Dynamical Systems and Bioengineering at Caltech. Murray's research is in the application of feedback and control to networked systems, with applications in biology and autonomy. Current projects include analysis and design biomolecular feedback circuits, synthesis of discrete decision-making protocols for reactive systems, and design of highly resilient architectures for autonomous systems.
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Andrew G. Alleyne
University of Illinois at Urbana-Champaign, USA
Modeling and Control of Power Flow for Transient Thermal Systems
Time: 8:30-9:30 a.m, Monday, December 12, 2016
Location: Room Juniper 4
Abstract: This talk examines the transient modeling of power flow for transient thermal systems. The focus is on dynamic phenomena starting with a basic thermodynamic cycle and building up to more complex systems. The overall goal of the modeling process is to develop systems-level models that are sufficiently flexible to be used on a variety of different applications. These models balance complexity with accuracy to obtain models that are sufficient for dynamic optimization and design as well as control algorithms
In addition to the modeling approach we present control strategies aimed at managing the flow of thermal power. We present a particular hierarchical approach to power flow that accommodates multiple power modes. The hierarchy allows for systems operating on different time scales to be coordinated. It also allows for different control tools to be used at different levels of the hierarchy based on the needs of the physical systems under control. Stability results exploit the system structure to provide guarantees. Recent results will be presented representing both interconnected complex systems with specific examples from industrial partners.
Biography: Professor Alleyne received a B.S. Degree from Princeton in 1989 and his M.S. and Ph.D. degrees in 1992 and 1994, respectively, from U.C. Berkeley. He joined the University of Illinois, Urbana-Champaign in 1994 where he holds the Ralph & Catherine Fisher Professorship and is the Director of the NSF ERC on Power Optimization for Electro Thermal Systems (POETS). He is appointed in Mechanical Science & Engineering, Electrical & Computer Engineering as well as the Coordinated Science Laboratory. A Fulbright fellow, he has held visiting appointments at TU Delft, University of Colorado, Johannes Kepler University, and ETHZ. He is a recipient of the Gustus Larson Award and Henry Paynter Award from ASME. His research interests are a mix of theory and implementation with a broad application focus. Further information may be found at: http://arg.mechse.illinois.edu/
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Christos G. Cassandras
Boston University, USA
Smart Cities as Cyber-Social-Physical Systems
Time: 8:30-9:30 a.m, Tuesday, December 13, 2016
Location: Room Ironwood 5
Abstract: Smart Cities are an example of Cyber-Physical Systems whose goals include improvements in transportation, energy distribution, emergency response, and infrastructure maintenance, to name a few. One of the key elements of a Smart City is the ability to monitor and dynamically allocate its resources. The availability of large amounts of data, ubiquitous wireless connectivity, and the critical need for scalability open the door for new control and optimization methods which are both data-driven and event-driven. The talk will present such an optimization framework and its properties. It will then describe several applications that arise in Smart Cities, some of which have been tested in the City of Boston: a “Smart Parking” system which dynamically assigns and reserves an optimal parking space for a user (driver); the “Street Bump” system which uses standard smartphone capabilities to collect roadway obstacle data and identify and classify them for efficient maintenance and repair; adaptive traffic light control; optimal control of connected autonomous vehicles. Lastly, to address the “social’’ dimension, the talk will describe how a large traffic data set from the Massachusetts road network was analyzed to estimate the Price of Anarchy in comparing “selfish” user-centric behavior to “social” system-centric optimal traffic routing solutions.
Biography: Christos G. Cassandras is Distinguished Professor of Engineering at Boston University, Head of the Division of Systems Engineering, Professor of Electrical and Computer Engineering, and co-founder of the Center for Information and Systems Engineering. He received degrees from Yale University, Stanford University, and Harvard University. In 1982-84 he was with ITP Boston, Inc. and in 1984-1996 he was with the Department of Electrical and Computer Engineering, University of Massachusetts/Amherst. He specializes in the areas of discrete event and hybrid systems, cooperative control, stochastic optimization, and computer simulation, with applications to computer and sensor networks, manufacturing systems, and transportation systems. He has published over 350 refereed papers in these areas, and five books. He has collaborated with The MathWorks, Inc. in the development of the discrete event and hybrid system simulator SimEvents. Dr. Cassandras was Editor-in-Chief of the IEEE Transactions on Automatic Control (1998-2009) and the 2012 President of the IEEE Control Systems Society. He is the recipient of several awards, including the 2011 IEEE Control Systems Technology Award, the Distinguished Member Award of the IEEE Control Systems Society (2006), IFAC’s 1999 Harold Chestnut Prize, 2011 and 2014 prizes for the IBM/IEEE Smarter Planet Challenge competition, the 2014 Engineering Distinguished Scholar Award at Boston University, several honorary professorships, a 1991 Lilly Fellowship and a 2012 Kern Fellowship. He is also a Fellow of the IEEE and a Fellow of the IFAC.
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Angelia Nedich
Arizona State University, USA
Distributed Large-Scale Optimization
Time: 8:30-9:30 a.m, Tuesday, December 13, 2016
Location: Room Juniper 4
Abstract: Distributed and large-scale optimization problems have gained a significant attention in the context of cyber-physical, peer-to-peer, and ad-hoc networked systems. The large-scale property is reflected in the number of decision variables, the number of constraints, or both, while the distributed nature of the problems is inherent due to partial (local) knowledge of the problem data (e.g., a portion of the cost function or a subset of the constraints is known to different entities in the system). The talk will focus on some recent developments on optimization models and algorithmic approaches for solving such problems with applications in domains ranging from control to machine learning.
Biography: Angelia Nedich has a Ph.D. from Moscow State University, Moscow, Russia, in Computational Mathematics and Mathematical Physics (1994), and a Ph.D. from Massachusetts Institute of Technology, Cambridge, USA in Electrical and Computer Science Engineering (2002). She has worked as a senior engineer in BAE Systems North America, Advanced Information Technology Division at Burlington, MA. Currently, she is a professor at the School of Electrical, Computer and Energy Engineering, at Arizona State University. Prior to joining Arizona State University, she has been a Willard Scholar faculty member at the University of Illinois at Urbana-Champaign. She has been a recipient of NSF CAREER Award 2007 in Operations Research for her work in distributed multi-agent optimization. She is a recipient (jointly with her co-authors) of the Best Paper Award at the Winter Simulation Conference 2013 and the Best Paper Award at the International Symposium on Modeling and Optimization in Mobile, Ad Hoc and Wireless Networks (WiOpt) 2015. Her interest is in large scale complex systems dynamics and optimization.
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Pierre Rouchon
MINES ParisTech, France
On the first experimental realization of a quantum state feedback
Time: 8:30-9:30 a.m, Monday, December 12, 2016
Location: Room Ironwood 5
Abstract: At the quantum level, feedback loops have to take into account measurement back-action. The goal of this talk is to explain, in a tutorial way and on the first experimental realization of a quantum-state feedback, how such purely quantum effect can be exploited in models and stabilization control schemes. This closed-loop experiment was conducted in 2011 by the group of Serge Haroche (Physics Nobel Prize 2012). The control goal was to stabilize a small number of micro-wave photons trapped between two super-conducting mirrors and subject to quantum non-demolition measurement via probe off-resonant Rydberg atoms. The implemented control scheme was decomposed into two parts. The first part estimates in real-time the quantum state of the trapped photons via a discrete-time Belavkin quantum filter. The second part is a nonlinear quantum-state feedback based on control Lyapunov functions. It stabilizes via suitable coherent displacements the number of photon(s) towards its set-point, namely an integer less than 5 in the experiment. This control scheme relies on a hidden control Markov model whose structure combines three quantum rules: unitary deterministic Schrödinger evolution; stochastic collapse of the wave packet induced by the measurement; tensor product for the composite systems. These basic quantum rules characterize the structure of all Markovian models describing open-quantum systems. These rules explain also the existence to two kinds of feedback schemes currently developed for quantum error correction: measurement-based feedback where an open quantum system is stabilized by a classical controller; coherent or autonomous feedback (reservoir engineering) where an open quantum system is passively stabilized through its coupling with another highly dissipative quantum system, namely the quantum controller.
Biography: Pierre Rouchon is professor with the Centre Automatique et Systemes (CAS) at Mines-ParisTech. He graduated from Ecole Polytechnique in 1983, has obtained a PhD in Chemical Engineering in 1990. In 2000, he obtained an ``habilitation à diriger des recherches'' in mathematics at University Paris-Sud Orsay. From 1993 to 2005, he was associated professor at Ecole Polytechnique in applied mathematics. From 1998 to 2002, he was the head of the Centre Automatique et Systèmes of Mines ParisTech. Since 2007, he is serving as chair of the department "Mathématiques et Systèmes" at Mines-ParisTech. Since 2015, he is a member of the Quantic Research team between Inria, Mines ParisTech, Ecole normale supérieure de Paris, Université Pierre et Marie Curie (Paris 6) and CNRS. His fields of interest include nonlinear control and system theory with applications to physical systems. His contributions include differential flatness and its extension to infinite dimensional systems, nonlinear observers and symmetries, quantum filtering and quantum feedback control.
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Key dates (2016)
| Submission Site Open: | January 4 |
Invited Session
Proposals Due: |
March 7 |
Initial Submissions Due: |
March 15 |
Workshop Proposals Due: | May 2 |
| Decision Notification: | End-July |
| Registration Opens: | August 1 |
Final Submissions: | September 23 |
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