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Forum on Robotics & Control Engineering


A Laboratory for Autonomy, Control, Information, and Systems Initiative

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Forum on Robotics & Control Engineering

The mission of the Forum on Robotics & Control Engineering (FoRCE) at the University of South Florida is simple: Provide free, high-quality outreach events and online seminars in order to reach broader robotics and control engineering communities around the globe. To support our mission, we periodically invite distinguished lecturers to the FoRCE to give talks on recent research and/or education results related to robotics and control engineering. As a consequence, the FoRCE aims in connecting academicians and government/industry researchers/practitioners with each other through crosscutting basic and applied research and education discussions.

Each upcoming FoRCE event (see below) is currently
announced through the Guidance, Navigation, and Control Listserv (GNC-L). In order to subscribe to this listserv, simply send an email to listserv@listserv.usf.edu with no text on the subject line but write "subscribe gnc" (without quotation marks) on the body of your email (click here for a sample email); visit GNC-L website for additional details. We also announce the upcoming FoRCE events through the IEEE Control Systems Society E-Letter ahead of time (click here) and the ASME Dynamic Systems and Control Division Listserv (click here).

We cordially hope that you will enjoy the FoRCE events and find them highly-valuable to your own research and education interests!


Upcoming Events

OBSERVER DESIGN FOR NONLINEAR SYSTEMS: A TUTORIAL (Dr. Rajesh Rajamani)

Date (Event Classification): September 26, 2018 - 12:00 PM Eastern Time (Online Seminar)

Abstract:
This tutorial will describe the design of stable observers for nonlinear systems. The design methodology utilizes tools that include Lyapunov analysis, the Circle Criterion and the S-procedure Lemma. The observer stability conditions are typically obtained as linear or bilinear matrix inequalities from which the observer gains can be computed. The tutorial will start with a dynamic system in which the process dynamics has Lipschitz nonlinearities. This will later be generalized to allow for either Lipschitz, bounded Jacobian or sector bounded nonlinearities in both the process dynamics and the measurement equations. Simple programs to solve LMIs in Matlab and obtain the observer gains will also be presented. The lecture will conclude with the application of the developed methodology to automotive slip angle estimation in the presence of nonlinear tire force models.

Biography: Rajesh Rajamani obtained his M.S. and Ph.D. degrees from the University of California at Berkeley in 1991 and 1993 respectively and his B.Tech degree from the Indian Institute of Technology at Madras in 1989. He is currently Professor of Mechanical Engineering at the University of Minnesota. His active research interests include observer design, sensing and control for smart and autonomous systems. Dr. Rajamani has co-authored over 240 refereed papers and is a co-inventor on 13 patent applications. He is the author of the popular book “Vehicle Dynamics and Control” published by Springer Verlag. Dr. Rajamani is a Fellow of ASME and has been a recipient of the CAREER award from the National Science Foundation, the 2001 Outstanding Paper award from the journal IEEE Transactions on Control Systems Technology, the Ralph Teetor Award from SAE, and the 2007 O. Hugo Schuck Award from the American Automatic Control Council. Several inventions from his laboratory have been commercialized through start-up ventures co-founded by industry executives. One of these companies, Innotronics, was recently recognized among the 35 Best University Start-Ups of 2016 in a competition conducted by the US National Council of Entrepreneurial Tech Transfer.

PERSPECTIVES ON THE HISTORY, SOCIOLOGY, AND MATHEMATICS OF INFLUENCE SYSTEMS (Dr. Francesco Bullo)

Date (Event Classification): October 19, 2018 - 12:00 PM Eastern Time (Online Seminar)

Abstract:
This talk will present models for the evolution of opinions, interpersonal influences, and social power in a group of individuals. I will present empirical data and mathematical models for the opinion formation process in deliberative groups, including concepts of self-weight and social power. I will then focus on groups who discuss and form opinions along sequences of judgmental, intellective, and resource allocation issues. I will show how the natural dynamical evolution of interpersonal influence structures is shaped by the psychological phenomenon of reflected appraisal. Multi-agent models and analysis results are grounded in influence networks from mathematical sociology, replicator dynamics from evolutionary games, and transactive memory systems from organization science. (Joint work with: Noah E. Friedkin, Peng Jia, and Ge Chen)

Biography: Francesco Bullo is a Professor with the Mechanical Engineering Department and the Center for Control, Dynamical Systems and Computation at the University of California, Santa Barbara. He was previously associated with the University of Padova (Laurea degree in Electrical Engineering, 1994), the California Institute of Technology (Ph.D. degree in Control and Dynamical Systems, 1999), and the University of Illinois. His research interests focus on network systems and distributed control with application to robotic coordination, power grids and social networks. He is the coauthor of “Geometric Control of Mechanical Systems” (Springer, 2004) and “Distributed Control of Robotic Networks” (Princeton, 2009); his “Lectures on Network Systems” (CreateSpace, 2018) is available on his website. He received best paper awards for his work in IEEE Control Systems, Automatica, SIAM Journal on Control and Optimization, IEEE Transactions on Circuits and Systems, and IEEE Transactions on Control of Network Systems. He is a Fellow of IEEE and IFAC. He has served on the editorial boards of IEEE, SIAM, and ESAIM journals, and is serving as 2018 IEEE CSS President.

NEGATIVE IMAGINARY SYSTEMS THEORY AND APPLICATIONS (Dr. Ian Petersen)

Date (Event Classification): November 9, 2018 - 21:00 PM Eastern Time (Online Seminar)

Abstract:
This seminar presents a survey of some of the main results in the theory of negative imaginary systems. The seminar also presents some applications of negative imaginary systems theory in the design of robust controllers. In particular, the seminar concentrates on the application of negative imaginary systems theory in the area of control of atomic force microscopes.

Biography: Ian R. Petersen was born in Victoria, Australia. He received a Ph.D in Electrical Engineering in 1984 from the University of Rochester. From 1983 to 1985 he was a Postdoctoral Fellow at the Australian National University. From 1985 until 2016 he was with UNSW Canberra where was most recently a Scientia Professor and an Australian Research Council Laureate Fellow in the School of Engineering and Information Technology. He has previously been ARC Executive Director for Mathematics Information and Communications, Acting Deputy Vice-Chancellor Research for UNSW and an Australian Federation Fellow. From 2017 he has been a Professor at the Australian National University. He is currently the Director of the Research School of Engineering at the Australian National University. He has served as an Associate Editor for the IEEE Transactions on Automatic Control, Systems and Control Letters, Automatica, IEEE Transactions on Control Systems Technology and SIAM Journal on Control and Optimization. Currently he is an Editor for Automatica. He is a fellow of IFAC, the IEEE and the Australian Academy of Science. His main research interests are in robust control theory, quantum control theory and stochastic control theory.

DISTRIBUTED PROTOCOLS FOR COOPERATIVE MULTI-ROBOT SYSTEMS (Dr. Jeff Shamma)

Date (Event Classification): November 28, 2018 - 12:00 PM Eastern Time (Online Seminar)

Abstract:
In cooperative multi-robot systems, there is a group of robots that seek to achieve a collective task as a team. Each individual robot makes decisions based on available local information as well as limited communications with neighboring robots. The challenge is to design local protocols that result in desired global outcomes. In contrast to a traditional centralized control paradigm, both measurements and decisions are distributed among multiple actors. This talk surveys various results for cooperative robotics based on methods drawn from game theory and distributed optimization, with applications to area coverage, cooperative pursuit, and self-assembly.

Biography: Jeff S. Shamma is a Professor of Electrical Engineering at the King Abdullah University of Science and Technology (KAUST) and the Director of the Center of Excellence for NEOM Research at KAUST. Shamma received a Ph.D. in systems science and engineering from MIT in 1988. He has held faculty positions at the University of Minnesota, The University of Texas at Austin, and the University of California, Los Angeles, and was the Julian T. Hightower Chair in Systems & Control in the School of Electrical and Computer Engineering at Georgia Tech. Shamma is a Fellow of the IEEE and the IFAC (International Federation of Automatic Control), and a recipient of the NSF Young Investigator Award, American Automatic Control Council Donald P. Eckman Award, and Mohammed Dahleh Award, and he is currently the deputy editor-in-chief for the IEEE Transactions on Control of Network Systems and a Distinguished Lecturer of the IEEE Control Systems Society.


Recorded Past Events

HIGH-GAIN OBSERVERS IN NONLINEAR FEEDBACK CONTROL (Dr. Hassan Khalil)

Link (Event Classification / Date): http://www.youtube.com/watch?v=_an3W_Eacjw (Online Seminar / May 9, 2018)

Abstract:
High-gain observers play an important role in the design of feedback control for nonlinear systems. This lecture overviews the essentials of this technique. A motivating example is used to illustrate the main features of high-gain observers, with emphasis on the peaking phenomenon and the role of control saturation in dealing with it. The use of the observer in feedback control is discussed and a nonlinear separation principle is presented. The use of an extended high-gain observer as a disturbance estimator is covered. Challenges in implementing high-gain observers are discussed, with the effect of measurement noise as the most serious one. Techniques to cope with measurement noise are presented. The lecture ends by listing examples of experimental testing of high-gain observers.

Biography: Hassan K. Khalil received the B.S. and M.S. degrees in electrical engineering from Cairo University, Egypt, in 1973 and 1975, respectively, and the Ph.D. degree from the University of Illinois, Urbana-Champaign, in 1978, all in electrical engineering. Since 1978, he has been with Michigan State University (MSU), where he is currently University Distinguished Professor of Electrical and Computer Engineering. He has consulted for General Motors and Delco Products, and published over 100 papers on singular perturbation methods and nonlinear control. He is the author of High-Gain Observers in Nonlinear Feedback Control (SIAM 2017), Nonlinear Control (Pearson 2015), Nonlinear Systems (Macmillan 1992; Prentice Hall 1996 & 2002) and coauthor of Singular Perturbation Methods in Control: Analysis and Design (Academic Press 1986; SIAM 1999). Dr. Khalil was named IEEE Fellow in 1989 and IFAC Fellow in 2007. He received the 1989 IEEE-CSS George S. Axelby Outstanding Paper Award, the 2000 AACC Ragazzini Education Award, the 2002 IFAC Control Engineering Textbook Prize, the 2004 AACC O. Hugo Schuck Best Paper Award, the 2009 AGEP Faculty Mentor of the Year Award, and the 2015 IEEE-CSS Bode Lecture Prize. At MSU he received the 1983 Teacher Scholar Award, the 1994 Withrow Distinguished Scholar Award, and the 1995 Distinguished Faculty Award. He was named University Distinguished Professor in 2003. He served as Associate Editor of the IEEE Transactions on Automatic Control, Automatica, and Neural Networks, and as Editor of Automatica for nonlinear systems and control. He was Registration Chair of the 1984 CDC, Finance Chair of the 1987 ACC, Program Chair of the 1988 ACC, and General Chair of the 1994 ACC.

REFERENCE GOVERNORS FOR CONTROL OF SYSTEMS WITH CONSTRAINTS (Dr. Ilya Kolmanovsky)

Link (Event Classification / Date): http://www.youtube.com/watch?v=123kKhNp7-0 (Online Seminar / April 6, 2018)

Abstract:
With the increasing trend towards system downsizing and the growing stringency of requirements, constraint handling and limit protection are becoming increasingly important for engineered systems. Constraints can reflect actuator limits, safety requirements (e.g., process temperatures and pressures must not exceed safe values) or obstacle avoidance requirements. Reference governors are control schemes that can be augmented to already existing control systems in order to provide constraint handling/limit protection capabilities. These add-on schemes exploit prediction and optimization or invariance/strong returnability properties to supervise and minimally modify operator (e.g., pilot or driver) commands, or other closed-loop signals, whenever there is a danger of future constraint violations. The presentation will introduce the basic reference governor schemes along with the existing theory. Several recent extensions and new variants of these schemes will be highlighted. Selected aerospace and automotive applications will be described. Opportunities for future research will be mentioned.

Biography: Professor Ilya V. Kolmanovsky has received his Ph.D. degree in Aerospace Engineering in 1995, his M.S. degree in Aerospace Engineering in 1993 and his M.A. degree in Mathematics in 1995, all from the University of Michigan, Ann Arbor. He is presently a full professor with tenure in the Department of Aerospace Engineering at the University of Michigan. Professor Kolmanovsky’s research interests are in control theory for systems with state and control constraints and in control applications to aerospace and automotive systems. Prior to joining the University of Michigan in January 2010, Dr. Kolmanovsky was with Ford Research and Advanced Engineering in Dearborn, Michigan for close to 15 years. He is a Fellow of IEEE, a past recipient of the Donald P. Eckman Award of American Automatic Control Council, of 2002 and 2016 IEEE Transactions on Control Systems Technology Outstanding Paper Awards and of several awards of Ford Research and Advanced Engineering. He is also named as an inventor on 98 United States patents.

NONLINEAR OBSERVERS ROBUST TO MEASUREMENT ERRORS AND THEIR APPLICATIONS IN CONTROL AND SYNCHRONIZATION (Dr. Daniel Liberzon)

Link (Event Classification / Date): http://www.youtube.com/watch?v=3jvWSpHrKUU (Online Seminar / March 23, 2018)

Abstract:
In this talk we address the problem of designing nonlinear observers that possess robustness to output measurement errors. To this end, we introduce a novel concept of quasi-Disturbance-to-Error Stable (qDES) observer. In essence, an observer is qDES if its error dynamics are input-to-state stable (ISS) with respect to the disturbance as long as the plant's input and state remain bounded. We develop Lyapunov-based sufficient conditions for checking the qDES property for both full-order and reduced-order observers. This relates to a novel "asymptotic ratio" characterization of ISS which is of interest in its own right. When combined with a state feedback law robust to state estimation errors in the ISS sense, a qDES observer can be used to achieve output feedback control design with robustness to measurement disturbances. As an application of this idea, we treat a problem of stabilization by quantized output feedback. Applications to synchronization of electric power generators and of chaotic systems in the presence of measurement errors will also be discussed.

Biography: Daniel Liberzon was born in the former Soviet Union in 1973. He did his undergraduate studies in the Department of Mechanics and Mathematics at Moscow State University from 1989 to 1993. In 1993 he moved to the United States to pursue graduate studies in mathematics at Brandeis University, where he received the Ph.D. degree in 1998 (supervised by Prof. Roger W. Brockett of Harvard University). Following a postdoctoral position in the Department of Electrical Engineering at Yale University from 1998 to 2000 (with Prof. A. Stephen Morse), he joined the University of Illinois at Urbana-Champaign, where he is now a professor in the Electrical and Computer Engineering Department and the Coordinated Science Laboratory. His research interests include nonlinear control theory, switched and hybrid dynamical systems, control with limited information, and uncertain and stochastic systems. He is the author of the books "Switching in Systems and Control" (Birkhauser, 2003) and "Calculus of Variations and Optimal Control Theory: A Concise Introduction" (Princeton Univ. Press, 2012). His work has received several recognitions, including the 2002 IFAC Young Author Prize and the 2007 Donald P. Eckman Award. He delivered a plenary lecture at the 2008 American Control Conference. He is a fellow of IEEE and IFAC, and an Editor for Automatica (nonlinear systems and control area).

QUO VADIS MODEL PREDICTIVE CONTROL? FROM STABILIZING TO DISTRIBUTED ECONOMIC MPC (Dr. Frank Allgöwer)

Link (Event Classification / Date): http://www.youtube.com/watch?v=kpkJgXu0CPo (Online Seminar / January 24, 2018)

Abstract: During the past decades model predictive control (MPC) has become a preferred control strategy for the control of a large number of industrial processes. Computational issues, application aspects and systems theoretic properties of MPC (like stability and robustness) are rather well understood by now. For many application disciplines a significant shift in the typical control tasks to be solved can, however, be witnessed at present. This concerns for example robot control, autonomous mobility, or industrial production processes. This will be examplarily discussed with the vision of the smart factory of the future, often termed Industry 4.0, where the involved control tasks, are undergoing a fundamental new orientation. In particular the stabilization of predetermined setpoints does not play the same role as it has in the past. In this talk we will first give an introduction to and an overview over the field of model predictive control. Then new challenges and opportunities for the field of control are discussed with Industry 4.0 as an example. We will in particular investigate the potential impact of Model Predictive Control for the fourth industrial revolution and will argue that some new developments in MPC, especially connected to distributed and economic model predictive control, appear to be ideally suited for addressing some of the new challenges.

Biography: Frank Allgöwer is director of the Institute for Systems Theory and Automatic Control and professor in Mechanical Engineering at the University of Stuttgart in Germany. Frank's main interests in research and teaching are in the area of systems and control with a current emphasis on the development of new methods for optimization-based control, networks of systems and systems biology. Frank received several recognitions for his work including the IFAC Outstanding Service Award, the IEEE CSS Distinguished Member Award, the State Teaching Award of the German state of Baden-Württemberg, and the Leibniz Prize of the Deutsche Forschungsgemeinschaft. Frank served as IEEE CSS Vice-President for Technical Activities over in 2012-2015 and is President of the International Federation of Automatic Control (IFAC) for the years 2017-2020. He was Editor for the journal Automatica from 2001 to 2015 and is editor for the Springer Lecture Notes in Control and Information Science book series. He has published over 500 scientific articles. Since 2012 Frank serves a Vice-President of the German Research Foundation (DFG).

RIGID BODY VEHICLE MODELING USING GEOMETRIC MECHANICS AND MULTI-VEHICLE CONSENSUS CONTROL (Dr. Eric Butcher)

Link (Event Classification / Date): http://www.youtube.com/watch?v=3e_sITS1IuU (Regular Seminar / January 5, 2018)

Abstract:
Geometric mechanics is useful in developing a compact description of the motion of a rigid body in three-dimensional space which is singularity-free, unique, does not limit the motion to small angles, and enables a single control law to be obtained even in the presence of translational/rotational coupling. Such a description, which is based on the Lie group SE(3) and its corresponding "exponential coordinates", is especially useful for spacecraft and other types of autonomous vehicles undergoing fast rotations and tumbling motions. This talk will explore various coordinates for rigid body attitude along with their pros and cons (including the phenomenon of unwinding when using a quaternion attitude description) as well as the use of the SE(3) framework in multi-vehicle consensus control design in which it is desired to achieve leader-follower formations along with attitude synchronization. The case of four formation flying spacecraft in a Molniya orbit will serve as an illustrative example.

Biography:
Eric Butcher is a Professor in the Aerospace and Mechanical Engineering Department at the University of Arizona. He was formerly a faculty member at New Mexico State University and the University of Alaska Fairbanks. He has a M.S. and Ph.D. (in mechanical engineering) from Auburn University and a M.S. (in aerospace engineering sciences) from the University of Colorado. His research interests lie in nonlinear dynamics and control; time-periodic, time-delayed, stochastic, and fractional order systems; chaos and chaos control; decentralized multi-agent consensus control and estimation; nonlinear vibrations; orbital mechanics and spacecraft GNC; spacecraft attitude, relative motion, coupled orbit/attitude dynamics, and geometric mechanics. He is a former associate editor for the Journal of Computational and Nonlinear Dynamics and the International Journal of Dynamics and Control.

MODEL REFERENCE ADAPTIVE CONTROL FUNDAMENTALS (Dr. Tansel Yucelen)

Link (Event Classification / Date): https://youtu.be/c9VwaSEo5t8 (Tutorial Lecture / October 24, 2017)

Abstract:
What is model reference adaptive control? Why does one prefer using a model reference adaptive controller? How can we design and analyze a model reference adaptive controller? In this FoRCE video, we answer these fundamental questions related to model reference adaptive control theory and beyond.

Biography:
Dr. Tansel Yucelen is with the Laboratory for Autonomy, Control, Information, and Systems at the University of South Florida.