inControl

Outline
00:00 - Intro
01:15 - Origin story: early path and the road to science 
04:20 - On graphical visualization and aphantasia 
08:08 - The interest in fluid dynamics 
12:00 - Caltech, Jerry Marsden, and the move to the Pacific time zone 
19:43 - Dynamic Mode Decomposition (DMD) and the Koopman operator 
27:15 - On teaching and the Eigensteve channel 
39:22 - SINDy: Sparse Identification of Nonlinear Dynamics 
45:45 - Automatic knowledge creation and Explainable AI 
54:31 - HydroGym: RL benchmarks for fluid flow control 
1:01:37 - Optimization boot camp 
1:05:31 - Collimator 
1:13:18 - Outro
Links
Steve's website: https://www.eigensteve.com/
Eigensteve channel: https://www.youtube.com/c/eigensteve
Jerrold E. Marsden: https://en.wikipedia.org/wiki/Jerrold_E._Marsden
Aphantasia: https://en.wikipedia.org/wiki/Aphantasia
J. Nathan Kutz: https://amath.washington.edu/people/j-nathan-kutz
Clarence W. Rowley: https://cwrowley.princeton.edu/
DMD: https://en.wikipedia.org/wiki/Dynamic_mode_decomposition
Koopman operator: https://en.wikipedia.org/wiki/Koopman_operator
Dynamic Mode Decomposition book: https://epubs.siam.org/doi/book/10.1137/1.9781611974508
On Dynamic Mode Decomposition paper: https://doi.org/10.3934/jcd.2014.1.391
DMD with control: https://arxiv.org/abs/1409.6358
Compressed sensing and DMD: https://doi.org/10.3934/jcd.2015002
Modern Koopman Theory for Dynamical Systems: https://arxiv.org/abs/2102.12086
Deep learning for universal linear embeddings of nonlinear dynamics: https://doi.org/10.1038/s41467-018-07210-0
Data-driven discovery of Koopman eigenfunctions for control: https://doi.org/10.1088/2632-2153/abf0f5
PyDMD: https://github.com/PyDMD
Discovering governing equations from data by sparse identification of nonlinear dynamical systems: https://doi.org/10.1073/pnas.1517384113
Data-driven discovery of partial differential equations:
https://doi.org/10.1126/sciadv.1602614
SINDy for model predictive control in the low-data limit:
https://doi.org/10.1098/rspa.2018.0335
PySINDy: https://github.com/dynamicslab/pysindy
SINDy with control: https://arxiv.org/abs/2108.13404
SINDy review: https://doi.org/10.1146/annurev-control-030123-015238
Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control: http://www.databookuw.com
Explainable AI: Learning from the Learners: https://arxiv.org/abs/2601.05525
HydroGym: https://github.com/dynamicslab/hydrogym
Support the show
Podcast info
Podcast website: https://www.incontrolpodcast.com/
Apple Podcasts: https://tinyurl.com/5n84j85j
Spotify: https://tinyurl.com/4rwztj3c
RSS: https://tinyurl.com/yc2fcv4y
Youtube: https://tinyurl.com/bdbvhsj6
Facebook: https://tinyurl.com/3z24yr43
Twitter: https://twitter.com/IncontrolP
Instagram: https://tinyurl.com/35cu4kr4

Acknowledgments and sponsors
This episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund. The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to L. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, ETH studio and mirrorlake . Music was composed by A New Element.

Outline
00:00 – Intro
04:43 – Life and background
08:45 – Bell Labs
13:42 – Inventing the negative feedback amplifier
18:15 – Nyquist's landmark contributions
20:43 – Regeneration theory
27:10 – Frequency response
32:03 – Cauchy’s argument principle
36:05 – The Nyquist criterion
41:37 – Why is it so hard?
45:27 – Robustness, margins, and practical aspects
56:41 – Beyond the Nyquist criterion
1:04:25 – Pitfalls and common misunderstandings
1:07:00 – Outro
Links
Brian Douglas's video: http://y2u.be/sof3meN96MA
The Idea Factory: https://en.wikipedia.org/wiki/The_Idea_Factory
Inventing the Negative Feedback Amplifier: https://doi.org/10.1109/MSPEC.1977.6501721
Johnson–Nyquist noise:  https://doi.org/10.1103/PhysRev.32.110
Nyquist sampling theorem: https://en.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_sampling_theorem
Regeneration theory: https://doi.org/10.1002/j.1538-7305.1932.tb02344.x
Gain and phase margins: https://en.wikipedia.org/wiki/Bode_plot#Gain_margin_and_phase_margin
Routh–Hurwitz criterion: https://en.wikipedia.org/wiki/Routh%E2%80%93Hurwitz_stability_criterion
Åström’s lecture: https://archive.control.lth.se/media/Staff/KarlJohanAstrom/Lectures/ASMENyquistLecture2005.pdf
Scale-Relative Graphs: https://doi.org/10.1109/TAC.2023.3234016
Support the show
Podcast info
Podcast website: https://www.incontrolpodcast.com/
Apple Podcasts: https://tinyurl.com/5n84j85j
Spotify: https://tinyurl.com/4rwztj3c
RSS: https://tinyurl.com/yc2fcv4y
Youtube: https://tinyurl.com/bdbvhsj6
Facebook: https://tinyurl.com/3z24yr43
Twitter: https://twitter.com/IncontrolP
Instagram: https://tinyurl.com/35cu4kr4

Acknowledgments and sponsors
This episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund. The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to L. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, ETH studio and mirrorlake . Music was composed by A New Element.

Outline
00:00 - Intro
02:55 - Brachistochrone problem
20:52 - Beginning of the calculus of variations
32:00 - Principle of least action
42:37 - Maximum principle
1:02:35 - Dynamic programming
1:11:12 - Linear quadratic control
1:16:37 - Beyond optimal control: games, nonsmooth analysis, MPC, RL
1:28:40 - Outro
Links
300 years of optimal control: https://tinyurl.com/2s3t8se4
Brachistochrone: https://tinyurl.com/mwmv38ew
Acta Eruditorum, 1696: https://tinyurl.com/55yf5v49
Acta Eruditorum, 1697: https://tinyurl.com/2a7msaaj
Bernoulli family: https://tinyurl.com/y2vx2xdn
Leibniz–Newton calculus controversy: https://tinyurl.com/3974fdhd
Calculus of variations: https://tinyurl.com/3vvz8tuf
Beginning of the Calculus of Variations: https://tinyurl.com/mv6btxfn
Lagrangian mechanics: https://tinyurl.com/ycx5fv46
Euler–Lagrange equation: https://tinyurl.com/53yybvyx
Hamiltonian mechanics: https://tinyurl.com/yfrd8zhz
Hamilton–Jacobi equation: https://tinyurl.com/46m9cuvs
Pontryagin: https://tinyurl.com/35ehxnex
Pontryagin’s autobiography:  https://ega-math.narod.ru/LSP/book.htm
Discovery of the Maximum Principle: https://tinyurl.com/3s43nv4t
Maximum Principle: https://tinyurl.com/4f7352t4
Goddard problem: https://tinyurl.com/5n8swp2m
Hamilton–Jacobi–Bellman equation: https://tinyurl.com/4uemn5y4
Kalman filter: https://tinyurl.com/39zx5yry
Clarke: https://tinyurl.com/yj2tzcjb
MPC: https://tinyurl.com/4sf5pzvy
RL: https://tinyurl.com/ee5ne7sz
AlphaGo: https://tinyurl.com/ydrf8jsc
Support the show
Podcast info
Podcast website: https://www.incontrolpodcast.com/
Apple Podcasts: https://tinyurl.com/5n84j85j
Spotify: https://tinyurl.com/4rwztj3c
RSS: https://tinyurl.com/yc2fcv4y
Youtube: https://tinyurl.com/bdbvhsj6
Facebook: https://tinyurl.com/3z24yr43
Twitter: https://twitter.com/IncontrolP
Instagram: https://tinyurl.com/35cu4kr4

Acknowledgments and sponsors
This episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund. The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to L. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, ETH studio and mirrorlake . Music was composed by A New Element.

Outline
00:00 - Intro
03:18 - Early days: why control, M. Athans, and IDSS
12:21 - What is gain scheduling?
33:37 - Paradigm shifts & the ‘90s: Minnesota → Texas → LA
42:19 - Robustness & fundamental limitations of nonlinear systems
57:35 - Set-valued control & estimation
01:04:52 - Game theory & multi-agent control
01:28:18 - Learning & dissipativity in games & multi agent AI
01:45:03 - KAUST: building something new
01:53:33 - On human-algorithmic interaction
01:59:07 - Advice to future students: control, jiu-jitsu, and chatbots in education
2:10:02 - Outro

Links
Jeff’s website: https://tinyurl.com/52btmmz7
CSM interview: https://tinyurl.com/49wh98x7
Domain: feedbackcontrol.com
M. Athans: https://tinyurl.com/nhbw66wa
PhD thesis: https://tinyurl.com/5eyxkfm6
IDSS: https://tinyurl.com/bdenwy6d
Research on gain scheduling: https://tinyurl.com/55se8zcr
Overview of LPV systems: https://tinyurl.com/3ksff58b
Åström’s lecture: https://tinyurl.com/33mxkkfe
Necessity of the small gain theorem: https://tinyurl.com/mjn9eeb4
Sensitivity reduction for nonlinear plants: https://tinyurl.com/23tej5yp
Respect the unstable: https://tinyurl.com/3yww5eds
Differential inclusion: https://tinyurl.com/4yvc8vcc
Lectures on game theory: https://tinyurl.com/4z8hh3rn
Dynamic fictitious play: https://tinyurl.com/yc6wsxjj
Cooperative control and potential games: https://tinyurl.com/4hbmrt72
Dissipativity theory in game theory: https://tinyurl.com/3theyc7x
Population games, stable games, and passivity: https://tinyurl.com/zxwtzv6w
Game theory and control: https://tinyurl.com/yencrwm3
Higher-order uncoupled learning: https://tinyurl.com/37
Support the show
Podcast info
Podcast website: https://www.incontrolpodcast.com/
Apple Podcasts: https://tinyurl.com/5n84j85j
Spotify: https://tinyurl.com/4rwztj3c
RSS: https://tinyurl.com/yc2fcv4y
Youtube: https://tinyurl.com/bdbvhsj6
Facebook: https://tinyurl.com/3z24yr43
Twitter: https://twitter.com/IncontrolP
Instagram: https://tinyurl.com/35cu4kr4

Acknowledgments and sponsors
This episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund. The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to L. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, ETH studio and mirrorlake . Music was composed by A New Element.

Outline
00:00 - Intro
05:01 - Female Influencers in Control — The Backstory
08:08 - Sofya Kovalevskaya
15:21 - Irmgard Lotz
26:16 - A new wave of control influencers
34:26 - Some data
43:38 - What can one do? 
1:00:10 - Exhibition + survey
1:05:21 - Outro

Links
Female influencers in control project: https://tinyurl.com/mv879ahf
Charlotta Johnsson: https://tinyurl.com/343esbeu
Eva Westin: https://tinyurl.com/3p6fd5n8
Margret Bauer: https://tinyurl.com/47d35xzb
Sofya Kovalevskaya: https://tinyurl.com/4mmzruwc
Remembering Sofya Kovalevskaya: https://tinyurl.com/4cpw7vff
Irmgard Lotz: https://tinyurl.com/y2exmndm
Flow Computation Pioneer Irmgard Flügge-Lotz (1903–1974): https://tinyurl.com/4cy3xsp3
Discontinuous Automatic Control: https://tinyurl.com/yeys5dxx
Historical Female Influencers in Automatic Control: https://tinyurl.com/yxw4bjxe
Activity report: https://tinyurl.com/jwzn4z3c

Support the show
Podcast info
Podcast website: https://www.incontrolpodcast.com/
Apple Podcasts: https://tinyurl.com/5n84j85j
Spotify: https://tinyurl.com/4rwztj3c
RSS: https://tinyurl.com/yc2fcv4y
Youtube: https://tinyurl.com/bdbvhsj6
Facebook: https://tinyurl.com/3z24yr43
Twitter: https://twitter.com/IncontrolP
Instagram: https://tinyurl.com/35cu4kr4

Acknowledgments and sponsors
This episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund. The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to L. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, ETH studio and mirrorlake . Music was composed by A New Element.