[6/8] Control for Societal-Scale Challenges: Road Map 2030 [Education]

This video explores the importance of education in realizing the ambitious goals of this road map document. This follows Chapter 6 of the "Control for Societal-Scale Challenges: Road Map 2030" document.
www.ieeecss.org/control-socie...
The production of this video was supported by the IFAC.
Roadmap Abstract: The world faces some of its greatest challenges of modern time and how we address them will have a dramatic impact on the life for generations to come. Simultaneously, control systems, consisting of information enriched by various degrees of analytics followed by decision-making, are pervading a variety of sectors, not only in engineering but beyond, into financial services, socio-economic analysis, entertainment and sports, and political and social sciences. Increased levels of automation are sought after in various sectors and being introduced into new domains. All of these advances and transformations urge a shift in the conversation toward how control systems can meet grand societal- scale challenges. The document seeks to chart a roadmap for the evolution of control systems, identifying several areas where our discipline can have an impact over the next decade.
Edited by: Anuradha M. Annaswamy, Karl H. Johansson, and George J. Pappas
Authors: Andrew Alleyne, Frank Allgöwer, Aaron D. Ames, Saurabh Amin, James Anderson, Anuradha M. Annaswamy, Panos J. Antsaklis, Neda Bagheri, Hamsa Balakrishnan, Bassam Bamieh, John Baras, Margret Bauer, Alexandre Bayen, Paul Bogdan, Steven L. Brunton, Francesco Bullo, Etienne Burdet, Joel Burdick, Laurent Burlion, Carlos Canudas de Wit, Ming Cao, Christos G. Cassandras, Aranya Chakrabortty, Giacomo Como, Marie Csete, Fabrizio Dabbene, Munther Dahleh, Amritam Das, Eyal Dassau, Claudio De Persis, Mario di Bernardo, Stefano Di Cairano, Dimos V. Dimarogonas, Florian Dörfler, John C. Doyle, Francis J. Doyle III, Anca Dragan, Magnus Egerstedt, Johan Eker, Sarah Fay, Dimitar Filev, Angela Fontan, Elisa Franco, Masayuki Fujita, Mario Garcia-Sanz, Dennice Gayme, Wilhelmus P.M.H. Heemels, João P. Hespanha, Sandra Hirche, Anette Hosoi, Jonathan P. How, Gabriela Hug, Marija Ilić, Hideaki Ishii, Ali Jadbabaie, Matin Jafarian, Samuel Qing-Shan Jia, Tor Arne Johansen, Karl H. Johansson, Dalton Jones, Mustafa Khammash, Pramod Khargonekar, Mykel J. Kochenderfer, Andreas Krause, Anthony Kuh, Dana Kulić, Françoise Lamnabhi-Lagarrigue, Naomi E. Leonard, Frederick Leve, Na Li, Steven Low, John Lygeros, Iven Mareels, Sonia Martinez, Nikolai Matni, Tommaso Menara, Katja Mombaur, Kevin Moore, Richard Murray, Toru Namerikawa, Angelia Nedich, Sandeep Neema, Mariana Netto, Timothy O’Leary, Marcia K. O’Malley, Lucy Y. Pao, Antonis Papachristodoulou, George J. Pappas, Philip E. Paré, Thomas Parisini, Fabio Pasqualetti, Marco Pavone, Akshay Rajhans, Gireeja Ranade, Anders Rantzer, Lillian Ratliff, J. Anthony Rossiter, Dorsa Sadigh, Tariq Samad, Henrik Sandberg, Sri Sarma, Luca Schenato, Jacquelien Scherpen, Angela Schoellig, Rodolphe Sepulchre, Jeff Shamma, Robert Shorten, Bruno Sinopoli, Koushil Sreenath, Jakob Stoustrup, Jing Sun, Paulo Tabuada, Emma Tegling, Dawn Tilbury, Claire J. Tomlin, Jana Tumova, Kevin Wise, Dan Work, Junaid Zafar, Melanie Zeilinger
This video was produced at the University of Washington

[@IDontKnowMyName-tv1ze]

I feel so lucky to have found your channel. I am slowly working through as many of your lectures as I can between everything else I have to do and you are so good at bringing out my enthusiasm and optimism and interest in everything!

[@okhan5087]

Same here!

[@lpfagundeseai]

Same!!!

[@QuantumNeutrino]

Amazing! I loved the concept of Control Theory. It really encompasses all areas and society in a larger scale than anything else!

[@ehtishamullah1510]

Been watching Brian Douglas for years. Guy is the OG Controls teacher on YT. His videos helped me a lot during uni. Nowadays, I mostly watch your videos on data-driven control. If you can do a collaboration video or short discussion with him on the topic of teaching modern control, that would be super awesome.

[@cerbahsamir5119]

My favorites ❤ steve and douglas nice seeing u acknowledge his work ❤

[@declup]

Also keeping with the spirit of a modular approach to education:... Education should perhaps be abstracted out into its functional components, the two primary of which are (1) instruction and (2) accreditation. These two functions shouldn't always be performed by the same person or institution or at the same time. Education perhaps might be more efficient or more effective if students had different options of for providers of these two different activities. Other functional abstractions might include (3) query answering (as opposed to broad-picture instuction), (4) extra provision of examples or connections to separate domains, and (5) quality control" (that is, routine checks of a student's understanding).

[@williamdocter8789]

For state space control and modelling, consider starting in discrete time (x(k+1) =Ax(k) +Bu(k))since most if not all industrial multivariable constraint controllers and dynamic model identification packages are implemented in sample time. It lowers the bar on math pre-requisites for process control to linear algebra rather than calculus and differential equations. Building competency on discrete time "integration" by difference equations in algebra also builds the foundation of where calculus even comes from. I have been working industrial petrochemical implementations of Model Predictive Control (DMC) and RTO for 25 years and have not solved a continuous time domain differential equation by hand since grad school. At the university level, gatekeeping developing control engineers with differential equations course pre-requisites is a strategic mistake that has turned a big part of the capable talent pool away from process control

[@williamdocter8789]

I just read through chapter 6 of the roadmap - great stuff! It specifically focuses on university level, but I think the concepts of teaching application first and theory second it lays out should apply much much earlier in high school curricula which is exclusively theory with no application. Bombarding the advanced high school students for two years with trig identity gimmicks for solving cookie cutter single variable ode problems analytically bores students and leaves them wondering what is the point. They could be taught a simple difference equation representation of a dynamic system and controller in a week and be writing single variable linear simulations with PID control representing systems of their choice the next week. It is then small hops to multivariable or nonlinear simulations since coming up with equations to put in a simulation is orders of magnitude easier than solving those equations analytically. There was mention of matlab and python. I have used both and they are both capable, however, python is free (removes barrier to entry), has broader capability (database operations, business and IT applications,...), larger online community of practice and sharing, and in greater general demand in the marketplace (appears on large number of job requisitions in business, IT, engineering,...). No mention of ChatGPT and emerging AI co-pilots was made in the section, but these both remove barriers for getting started in programming, writing code and debugging code. In discussions I have had with university faculty so far the primary topic that comes up is use of these tools for cheating, however as an employer, my expectation is that students coming out of these programs know how to use the latest tools to efficiently and quickly deliver business impact. Businesses that don't figure this out early will find themselves uncompetitive in the not to distant future. Excerpts that resonated with me: section 6.B.1 "The traditional advice-“study mathematics and physics for a few years and then everything will fall into place”-simply does not work anymore. It requires attention spans that have been drastically shortened. Instead of bemoaning this new reality, we should adjust to it and adopt a new approach-perhaps completely reversing the instructional order" 6.B.2 "An introductory course need not delve into theoretical aspects-it can instead focus on practical tools and foundational concepts". I believe this reachable even at the high school level if the dynamic modeling is limited to difference equation representations."

[@Peaceluvr18]

The link for your book doesn't seem to work :/

[@abdjahdoiahdoai]

have you considered making a discord so people can talk more? 😂