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The ‘‘Control for Societal-scale Challenges: Road Map 2030’’ by the IEEE Control Systems Society (Eds. A. M. Annaswamy, K. H. Johansson, and G. J. Pappas) was published a week ago. This roadmap is a remarkable piece of work, over 250 pages, an outstanding list of authors and coverage of almost anything you can imagine, and more.
If you somehow found your way to this website, then I can only strongly recommend reading this document.
Despite many of us being grounded in traditional engineering disciplines, I do agree with the sentiment of this roadmap that the most exciting (future) work is interdisciplinary, this is substantiated by many examples from biology. Better yet, it is stressed that besides familiarizing yourself with the foundations, it is of quintessential importance (and fun I would say) to properly dive into the field where you hope to apply these tools.
‘‘Just because you can formulate and solve an optimization problem does not mean that you have the correct or best cost function.’’ p. 32
Section 4.A on Learning and Data-Driven Control also contains many nice pointers, sometimes alluding to a slight disconnect between practice and theory.
‘‘Sample complexity may only be a coarse measure in this regard, since it is not just the number of samples but the “quality” of the samples that matters.’’ p. 142
The section on safety is also inspiring, just stability will not be enough anymore. However, the most exciting part for me was Chapter 6 on education. The simple goal of making students excited early-on is just great. Also, the aspiration to design the best possible material as a community is more than admirable.
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