Workshop for Middle and High School Students and Teachers:
What are Feedback Systems and How are They Critical to Our Increasingly Automated World

Sponsor:           AACC Technical Committee on Control Education, in Cooperation with the IFAC and IEEE CSS TCs on Control Education

Time:                 1:00 PM – 4:15 PM (US Central Time) Wednesday, May 26, 2021

Location:           Virtual

Organizers:      Dr. Daniel Abramovitch, Agilent Technologies and Dr. Bozenna Pasik-Duncan, University of Kansas

The control research community understands that control and system theory are vital to the world at large and to the soon to be ubiquitous technologies of automated devices, vehicles, instruments, appliances, and our future robotic helpers.  Sadly, this importance is hidden from the general public.  While the public is becoming aware of the buzz and hype about Machine Learning (ML) and Artificial Intelligence (AI), understanding of how intelligent machines interact with the environment, each other, and humans is lacking.  At the core of this is a need for the public to understand the concepts of feedback and system theory. Our community has a lot of catching up to do so that the engineers and scientists who will be building devices that depend on feedback, those folks who are and will be “practicing control without a license” learn enough to do so safely.

This outreach event is designed to introduce the principles and structure of feedback and control to a new generation of middle and high school age students and their teachers.  Our focus will be on the students, not the controls researchers, but teachers and parents are welcome in the session.

The workshop itself will consist of a combination of live and recorded presentations from controls researchers from around the world who have shown an enthusiasm for system theory to students that have not yet had calculus.  There will be introductory material provided online in advance so that students come into the workshop with a basic idea of what they will learn and why it is important. Following this, there will be a series of talks on different aspects and applications of control systems.

Presentations in our workshop:

What Is a Control System and Why Should I Care?

Dr. Daniel Abramovitch, Agilent Technologies

This is the introduction to the entire workshop where we try to literally tell students and teachers what we mean when we say “control system” and why they might find it useful to know about topic.  In order to save time in the live portion of the workshop, only a summary of this talk will be presented in the live session. However, since the full talk can help students and teachers feel more comfortable with the material and set up the talks of the other speakers, we have split this talk into two videos that can be streamed individually, in class, or via remote learning. These are a bit more relaxed than the frenetic pace of trying to get them into one hour, and give teachers and students a chance to become familiar with the fundamentals before attending the workshop.

· Video Part 1: Introduces the basic concepts of feedback with lots of visual examples (38 minutes)

· Video Part 2: Gives a glimpse of some of the methods and math that allow us to understand these systems (34 minutes)

Abstract: After years of teaching coaching little league trying to explain control systems to biologist and computer scientist friends, I will try the ultimate test of explaining the topic to a group of bright and easily bored high school kids. We will go through examples of feedback in everyday life, and then tease out what is common to all these examples. We will talk about how the "control" is computed, even when we don't have a computer. And we will talk about the dreaded math of control systems and explain why we use it and what it tells us. The talk will finish with some general lessons about science and engineering, and why anyone might want to learn these intense subjects.

Feedback in the Squishy Stuff

Dr. Babatunde Ogunnaike, University of Delaware

Abstract: Feedback doesn’t just happen in robots and self-driving cars, but in the regulation of our very bodies and in the ways in which we transform raw ingredients into materials we can use, be they for Silicon chips, disease fighting monoclonal antibodies and vaccines, or even dinner.  All of these processes – from regulating our blood sugar to making a stew – involve similar principles of feedback.  The processes, although complicated in the details, can often be understood using some fairly simple and yet powerful models.  We will talk about some of these.

Efficient Wind Energy Systems—How Control Methods Can Enable a Clean Energy Future

Dr. Lucy Pao, University of Colorado Boulder

Abstract: Wind energy is recognized worldwide as cost-effective and environmentally friendly and is among the fastest-growing sources of electrical energy. We will provide an overview of wind energy systems, discuss some of the challenges in the design and operation of wind turbines and wind farms, and highlight how control methods have improved the performance of these systems. We shall close by discussing continuing challenges and on-going and future research that can further facilitate the growth of wind energy.

How to Design a Self-Driving Car

Dr. Richard M. Murray, California Institute of Technology

Abstract: Building robots that can do things as well as humans has been the goal of scientists and engineers for decades. Despite what we see in the movies and on TV, getting a real robot to perform as well as a human can is still a challenge goal. Approximately 15 years ago, the US has sponsored a competition to spur advances in robotics, called the DARPA Grand Challenge. This competition paved the way for the advances that we see today in the development of autonomous cars. In this talk I will explain how these cars work and some of the engineering challenges that remain.

Resonance in Nature and Bioinspired Squid Robots

Dr. Nicole Xu, US Naval Research Lab

Abstract: Bioinspired robots combine the best of both biology and engineering. Using tools learned from nature, we can build squid-like and other squishy robots to improve current capabilities in robotics, such as speed and energy efficiency. As one example, jellyfish and squids use the concept of resonance to swim more efficiently. Resonance is defined as a mechanical property, in which a system performs better when driven at or near its natural frequency. We will discuss the concept of resonance and how both animals, and now squid-like robots, use this concept to their advantage.

Coopetitive Learning

Dr. Hamidou Tembine, Learning & Game Theory Laboratory, NYU

Abstract: We have much to learn from Nature, Ecology, Biology, and the Living Systems around us. By experience-by-experience, one can gather data, process, and learn from it. Strategic swarm learning aims to experiment, measure, and learn from these interacting coopetitive systems. We will revisit how these coopetitive systems use feedback strategies with minimal communication to learn and improve by experience as anthills are created as a by-product of worker ants.

A System and Feedback View of Reopening After Covid-19

Dr. Dominique Duncan, University of Southern California

Abstract: The Coronavirus Disease 2019 (COVID-19) pandemic has warranted a myriad of business closures across the United States and around the world in efforts to mitigate the spread of the virus. To measure the objective effects of reopening businesses in the midst of this pandemic, it is imperative to study how these reopenings affect the overall infection rates in their respective counties. We have used data from the COVID-19 Data Archive (COVID-ARC) to gain a data-driven understanding of the implications of reopening businesses and schools amidst the COVID-19 pandemic and its effect on county-level infection rates. The importance of data harmonization, to compare data acquired across various sites, prior to analysis will be discussed. The role of feedback control and optimization applied to mitigating the spread of COVID-19 related to various business closures and reopenings will be presented.

Speaker bios:

Dr. Daniel Abramovitch earned degrees in Electrical Engineering from Clemson (BS) and Stanford (MS and Ph.D.). After a brief stay at Ford Aerospace, he worked at HP Labs for 11 1/2 years, studying control issues for optical and magnetic disk drives.  He moved to Agilent Labs shortly after the spinoff from HP, where he has spent 20 years working on test and measurement systems.  He is currently in Agilent’s Mass Spectrometry Division working on improved real-time computational architectures for Agilent’s mass spectrometers.  Danny is a Senior Member of the IEEE and was Vice Chair for Industry and Applications for the 2004 American Control Conference (ACC), for Workshops at the 2006 and 2022 ACC, for Special Sessions at the 2007 ACC, and for Industry and Applications for the 2009 ACC. He was Program Chair for the 2013 ACC and General Chair of the 2016 ACC in Boston. He has organized tutorial sessions on disk drives, atomic force microscopes, phase-locked loops, laser interferometry, and how business models and mechanics affect control design. He was Chair of the IEEE CSS History Committee from 2001 to 2010.  Danny had the original idea for the clocking mechanism behind the DVD+RW optical disk format.  He was on the team that prototyped Agilent’s first 40Gbps Bit Error Rate Tester (BERT).  He and Gene Franklin were awarded the 2003 IEEE Control Systems Magazine Outstanding Paper Award. He was a Keynote Lecturer at the 2015 MSC in Sydney.  His recent work for Agilent was on high speed atomic force microscopes and high precision interferometers, and currently works on improving the real-time control, data collection, and signal processing chain on Agilent’s Mass Spectrometers.  He is part of the team that introduced the multi-award winning Ultivo Tandem Quad Mass Spec in 2017. He is the holder of over 20 patents and has published over 50 reviewed technical papers.

Dr. Dominique Duncan is an assistant professor of neurology at the Laboratory of Neuro Imaging of the USC Stevens Neuroimaging and Informatics Institute. Prior to her current position she was a postdoctoral scholar at the Mathematics Department at the University of California, Davis, a postdoctoral fellow at the Department of Neurology and Neurological Sciences at the Stanford University School of Medicine. She received her PhD in Electrical Engineering from Yale University in 2013 and a BS in Mathematics from the University of Chicago in 2007 as well as a BA in Polish Literature and minor in Computational Neuroscience. During her collaborating with neurologists and neuroscientists from the Yale University School of Medicine, and mathematicians, engineers, and computer scientists. She is a recipient of a University of Chicago Scholarship, Yale University Faculty of Engineering Fellowship, NSF REU scholarship, summer undergraduate program in engineering research scholar at the University of California, Berkeley, several travel awards from the National Science Foundation (NSF), the National Institute of Health (NIH), and the Association for Women in Mathematics (AWM) Travel Award. She is passionate about teaching international students and about community and outreach service. She has an established record of holding leadership positions that include being the Chair of the University of California, Davis Postdoctoral Scholars Association, Council Member in the Stanford University Postdoctoral Association, senator representing engineering for the Yale University Graduate and Professional Student Senate, President of the University of Chicago Polish American Student Association, Chair of the University of Chicago Committee on Recognized Student Organizations, University of Chicago Student Government Executive Committee member, American Automatic Control Council (AACC) TC on Education member, IEEE Control System Society (CSS) TC on Control Education member, and appointed member of IFAC TC on Control Education. She has been a frequent speaker on "Math & Epilepsy" at workshops for elementary, middle and high school students and teachers.

Dr. Richard 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 and Dynamical Systems and Bioengineering at Caltech. Murray's research is in the application of feedback and control to network systems with applications in biology and autonomy. Current projects include design of safety-critical control systems and synthetic biology.

Dr. Babatunde A. Ogunnaike is the William L. Friend Chaired Professor of chemical engineering and, until October 1, 2019, dean of the College of Engineering at the University of Delaware. He received the B.Sc. degree in Chemical Engineering from the University of Lagos, Nigeria; the M.S. degree, in Statistics and the Ph.D. degree in Chemical Engineering both from the University of Wisconsin–Madison. He is the author or co-author of four books including a widely used textbook, Process Dynamics, Modeling and Control, and Random Phenomena: Fundamentals of Probability and Statistics for Engineers. His awards include the American Institute of Chemical Engineers 1998 CAST Computing Practice Award, the 2007 ISA Eckman Award, the 2008 AACC Control Engineering Practice award and the 2018 AIChE Warren K. Lewis Award. He was named a fellow of the American Institute of Chemical Engineers in 2009, a fellow of the American Association for the Advancement of Science in 2015; Fellow of the international Federation of Automatic Control (IFAC) in 2017; he was also elected to fellowship of the Nigerian Academy of Engineering and elected to the US National Academy of Engineering both in 2012.

Dr. Lucy Pao is a Palmer Endowed Chair Professor in the Electrical, Computer, and Energy Engineering Department and a Professor (by courtesy) in the Aerospace Engineering Sciences Department at the University of Colorado Boulder. She earned B.S., M.S., and Ph.D. degrees in Electrical Engineering from Stanford University. Her research has primarily focused on engineering control systems, with applications ranging from atomic force microscopes to multi-megawatt wind energy systems. She is a Fellow of the IEEE and IFAC. Selected awards include a National Science Foundation CAREER Award, an Office of Naval Research Young Investigator Award, an IFAC World Congress Young Author Prize, an IEEE Control Systems Magazine Outstanding Paper Award (with K. Johnson), a SIAM Journal on Control and Optimization Best Paper Prize (with J. Marden and H. P. Young), the AACC Control Engineering Practice Award, the European Academy of Wind Energy Scientific Award, and the ASME Nyquist Lecturer Award. Selected past professional society activities include being General Chair of the American Control Conference, an elected member of the IEEE Control Systems Society Board of Governors, Member of the US Defense Science Study Group, and Member of the IFAC Executive Board.  Selected current activities include being a Fellow of the Renewable and Sustainable Energy Institute, the Education Liaison on the IFAC Technical Board, and the IFAC Pavel J. Nowacki Distinguished Lecturer.

Dr. Hamidou Tembine received the M.S. degree in Applied Mathematics from Ecole Polytechnique (Palaiseau, Paris, France) in 2006 and the Ph.D. degree in Computer Science from University of Avignon in 2009. His current research interests include evolutionary games, mean-field-type games and applications. In December 2014, Tembine received the IEEE ComSoc Outstanding Young Researcher Award for his promising research activities for the benefit of the society. He was the recipient of 10 best article awards in the applications of game theory. He is author of the book on "Distributed Strategic Learning for Wireless Engineers" (published by CRC Press, Taylor & Francis 2012), and co-author of the book "Game Theory and Learning in Wireless Networks" (Elsevier Academic Press). Tembine has been co-organizer of several scientific meetings on game theory in networking, wireless communications, smart energy and transportation systems. He is a senior member of IEEE.  He is recipient of the Next Einstein Fellow award 2017.

Dr. Nicole Xu received her Ph.D. in Bioengineering from Stanford University, M.S. in Bioengineering from the California Institute of Technology, and B.S.E. in Bioengineering from the University of Pennsylvania. Currently, she is a National Research Council Postdoctoral Associate working at the U.S. Naval Research Laboratory. Her research interests include bioinspired design and approaches in underwater robots. In her doctoral work, Dr. Xu developed a robotic system to control live jellyfish swimming, which has received international attention, including magazine features, newspaper articles, and interviews on BBC World News TV and radio.