Outline
00:00 - Intro
02:25 - Bachelier and the Théorie de la Spéculation
03:05 - Stochastic processes, Brownian motion, and the heat equation
09:45 - Poincaré's verdict, obscurity, and rediscovery
13:50 - Robert C. Merton: from hot rods to MIT
19:25 - Dynamic programming and Itô calculus
24:35 - Merton's portfolio problem as stochastic optimal control
31:10 - Options, dynamic hedging, and the Black–Scholes–Merton equation
39:50 - LTCM: the dream team
46:30 - August 1998: the crash
49:00 - Fat tails and the ten-sigma defense
51:40 - The ghosts of 2008 and echoes in the AI boom
54:00 - Robustness embraced at last: Hansen and Sargent
57:45 - Outro

Links
Bachelier's thesis, "Théorie de la Spéculation" (1900): https://www.numdam.org/item/10.24033/asens.476.pdf
Courtault et al., "Louis Bachelier on the Centenary of Théorie de la Spéculation": https://doi.org/10.1111/1467-9965.00098
Merton's Nobel autobiography: https://www.nobelprize.org/prizes/economic-sciences/1997/merton/biographical/
Merton's MIT "Infinite History" interview: https://infinite.mit.edu/video/robert-c-merton-phd-%E2%80%9970/
Mandelbrot, "The Variation of Certain Speculative Prices": https://doi.org/10.1086/294632
Merton, "Optimum Consumption and Portfolio Rules in a Continuous-Time Model": https://doi.org/10.1016/0022-0531(71)90038-X
Moehle & Boyd, "A Certainty Equivalent Merton Problem": https://doi.org/10.1109/LCSYS.2021.3111534
Brigo & Mercurio, "Interest Rate Models: Theory and Practice": https://doi.org/10.1007/978-3-540-34604-3
Armstrong, Brigo & Hanzon, "Optimal Projection Filters with Information Geometry": https://doi.org/10.1007/s41884-023-00108-x
Hu & Zhou, "Constrained Stochastic LQ Control with Random Coefficients, and Application to Portfolio Selection": https://doi.org/10.1137/S0363012904441969
Black & Scholes, "The Pricing of Options and Corporate Liabilities": https://doi.org/10.1086/260062
Merton, "Theory of Rational Option Pricing": https://doi.org/10.2307/3003143
Merton, "Option Pricing When Underlying Stock Returns Are Discontinuous": https://doi.org/10.1016/0304-405X(76)90022-2
Scholes' Nobel lecture: https://www.nobelprize.org/prizes/economic-sciences/1997/scholes/lecture/
Merton's Nobel lecture: https://www.nobelprize.org/prizes/economic-sciences/1997/merton/lecture/
Markowitz, "Portfolio Selection": https://doi.org/10.2307/2975974
Michael Lewis, "Liar's Poker": https://en.wikipedia.org/wiki/Liar%27s_Poker
Edwards, "Hedge Funds and the Collapse of Long-Term Capital Management": https://doi.org/10.1257/jep.13.2.189
Lowenstein, "When Genius Failed": https://en.wikipedia.org/wiki/When_Genius_Failed
Taleb, "Statistical Consequences of Fat Tails": https://arxiv.org/abs/2001.10488
Taleb & West, "Working with Convex Responses: Antifragility from Finance to Oncology": https://doi.org/10.3390/e25020343
Taleb, "The Black Swan": https://en.wikipedia.org/wiki/The_Black_Swan:_The_Impact_of_the_Highly_Improbable
Taleb, "Fooled by Randomness": https://en.wikipedia.org/wiki/Fooled_by_Randomness
Man Group, "The AI Bubble: Hidden Risks and Opportunities": https://www.man.com/insights/the-ai-bubble
Sen. Warren's remarks at the Vanderbilt Policy Accelerator: https://www.banking.senate.gov/newsroom/minority/warren-remarks-at-vanderbilt-policy-accelerator-event-highlighting-economic-and-financial-risks-of-potential-ai-crash
Meng & Chen, "Artificial Intelligence and Systemic Risk": https://arxiv.org/abs/2604.03272
Doyle, "Guaranteed Margins for LQG Regulators": https://doi.org/10.1109/TAC.1978.1101791
Safonov & Athans, "Gain and Phase Margin for Multiloop LQG Regulators": https://doi.org/10.1109/TAC.1977.1101470
Hansen & Sargent, "Robust Control and Model Uncertainty": https://doi.org/10.1257/aer.91.2.60
Hansen & Sargent, "Wanting Robustness in Macroeconomics": http://www.tomsargent.com/research/wanting.pdf

Support the show

Podcast info
Podcast website: https://www.incontrolpodcast.com/
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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
02:10 - London in the 1960s
12:40 - From Oxford to Imperial College: David Mayne and the discrete-time Riccati equation
18:05 - The "global tour": Montenegro roads, hitch-hiking to Istanbul, and the San Francisco waterfront
22:30 - Feedback and causality between stochastic processes
31:15 - The system identification years
40:50 - Model complexity, the bias–variance trade-off, and concentration inequalities
52:05 - Adaptive control: living through a golden era
1:00:30 - McGill, George Zames, and CIFAR's "institute without walls," and COCOLOG
1:09:45 - Mean field games: the China connection, the cell-phone problem, and Nash Certainty Equivalence
1:20:15 - The Lasry–Lions simultaneous discovery
1:24:40 - From graphons to graphexons: sparse networks, Laplexions, and geometry
1:31:00 - Linear Stochastic Systems, Popper, and falsifiability
1:35:20 - Advice to young researchers
1:38:00 - Outro

Links
Peter Caines' website: https://www.mcgill.ca/cim/caines
Linear Stochastic Systems: https://epubs.siam.org/doi/book/10.1137/1.9781611974713
  On the discrete-time matrix Riccati equation of optimal control: https://doi.org/10.1080/00207177008931892
Feedback between stationary stochastic processes: https://doi.org/10.1109/TAC.1975.1101008
Prediction-error identification methods for stationary stochastic processes: https://doi.org/10.1109/TAC.1976.1101304
Asymptotic normality of prediction-error estimators for approximate system models: https://doi.org/10.1109/CDC.1978.268066
Discrete-time multivariable adaptive control (Axelby Award): https://doi.org/10.1109/TAC.1980.1102363
Discrete-time stochastic adaptive control: https://doi.org/10.1137/0319052
25 seminal control papers of the 20th century: https://books.google.ca/books/about/Control_Theory.html?id=eVhGAAAAYAAJ
COCOLOG: A conditional observer and controller logic for finite machines: https://epubs.siam.org/doi/10.1137/S0363012992226636
Hierarchical hybrid control systems: https://doi.org/10.1109/9.664153
On the hybrid optimal control problem: https://ieeexplore.ieee.org/document/4303244
Bode Lecture: https://ieeecss.org/presentation/bode-lecture/mean-field-stochastic-control
The cell-phone problem - Large population stochastic wireless power control: https://doi.org/10.1109/CDC.2003.1272542
Large-population stochastic dynamic games - McKean-Vlasov and the Nash Certainty Equivalence principle: https://projecteuclid.org/journals/communications-in-information-and-systems/volume-6/issue-3/Large-population-stochastic-dynamic-games--closed-loop-McKean-Vlasov/cis/1183728987.full
Large-population cost-coupled LQG with nonuniform agents and decentralized ε-Nash equilibria: https://doi.org/10.1109/TAC.2007.904450
Social optima in mean field LQG control: https://doi.org/10.1109/TAC.2012.2183439
ε-Nash mean field games with major and minor agents: https://arxiv.org/abs/1209.5684
Graphon mean field games and their equations: https://doi.org/10.1137/20M136373X
Mean field games on large sparse network limits - Laplexion dynamics on graphexons: https://www.sciencedirect.com/science/article/pii/S240589632500388X
Murray Wonham oral history: https://www.youtube.com/watch?v=8IBZyRo0vDk

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Podcast info
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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
01:30 - Origin story: Naples, electrical engineering, and the fascination with chaos
08:00 - What is chaos?
15:00 - DC-DC converters and discontinuity-induced bifurcations
22:00 - Piecewise-smooth dynamical systems
26:55 - Complex networks, synchronization, and pinning control
40:30- Synthetic biology: from gene regulatory networks to multicellular control
58:00 - COVID-19: a network epidemic model for Italy
1:02:00 - Multiscale control, statistical mechanics, and physics-informed control
1:19:10 - State of the field and the IEEE CSS
1:26:35 - Advice to young researchers
1:29:00 - Outro

Links
Mario's website: https://sites.google.com/site/dibernardogroup/home
Scuola Superiore Meridionale: https://www.ssm.unina.it/
Chaos by James Gleick: https://en.wikipedia.org/wiki/Chaos:_Making_a_New_Science
Control of chaos:https://en.wikipedia.org/wiki/Control_of_chaos
Erasmus programme: https://en.wikipedia.org/wiki/Erasmus_Programme
An Adaptive Approach to the Control and Synchronization of Continuous-time Chaotic Systems: https://doi.org/10.1142/S0218127496000254
Piecewise-smooth Dynamical Systems: Theory and Applications: https://doi.org/10.1007/978-1-84628-708-4 
Bifurcations in nonsmooth dynamical systems: https://doi.org/10.1137/050625060 Controllability of complex networks via pinning:
https://doi.org/10.1103/PhysRevE.75.046103 
Criteria for global pinning-controllability of complex networks: https://doi.org/10.1016/j.automatica.2008.07.007
Controllability of complex networks: https://doi.org/10.1038/nature10011
Controlling complex networks with complex nodes: https://doi.org/10.1038/s42254-023-00566-3
Analysis, design and implementation of a novel scheme for in-vivo control of synthetic gene regulatory networks: https://doi.org/10.1016/j.automatica.2011.01.073
In-vivo Real-time Control of Protein Expression from Endogenous and Synthetic Gene Networks: https://doi.org/10.1371/journal.pcbi.1003625
A network model of Italy shows that intermittent regional strategies can alleviate the COVID-19 epidemic: https://doi.org/10.1038/s41467-020-18827-5
A Continuification-Based Control Solution for Large-Scale Shepherding: 
https://arxiv.org/abs/2411.04791
Shepherding control and herdability in complex multiagent systems: https://doi.org/10.1103/PhysRevResearch.6.L032012
Nonreciprocal field theory for decision-making in multi-agent control systems: https://doi.org/10.1038/s41467-025-63071-4

Support the show

Podcast info
Podcast website: https://www.incontrolpodcast.com/
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Facebook: https://tinyurl.com/3z24yr43
Twitter: https://twitter.com/IncontrolP
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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
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/
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Facebook: https://tinyurl.com/3z24yr43
Twitter: https://twitter.com/IncontrolP
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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

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Podcast info
Podcast website: https://www.incontrolpodcast.com/
Apple Podcasts: https://tinyurl.com/5n84j85j
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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
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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/376r5r9x

Support the show

Podcast info
Podcast website: https://www.incontrolpodcast.com/
Apple Podcasts: https://tinyurl.com/5n84j85j
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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.

Outline
00:00 – Intro
07:22 – Anatomy of a feedback loop
15:12 – A brief historical recap on the history of feedback
23:40 – Inventing the negative feedback amplifier
34:28 – Feedback in biology, economics, society, and ... board games!
52:44 – Negative vs positive feedback
59:15 – Feedback, causality, and the arrow of time
1:06:22 – Classics: fundamental limitations, uncertainty, robustness
1:21:30 – Adaptive control: learning in the loop
1:29:50 – Modern AI feedback loops (RL, social media, alignment)
1:40:40 – Outro

Links
Watt’s flyball governor: https://tinyurl.com/ne5nene3
Maxwell - "On Governors": https://tinyurl.com/2a7cxj7m
Black - "Inventing the negative-feedback amplifier": https://tinyurl.com/yevsemdp
Nyquist Criterion: https://tinyurl.com/33hfbw8m
Bode's integral: https://tinyurl.com/53sxkdzu
Wiener - "Cybernetics": https://tinyurl.com/yta899ay
Apoptosis: https://tinyurl.com/mcxjycka
Predator–prey dynamics (Lotka–Volterra): https://tinyurl.com/5cvx33tn
Bird migration cues (photoperiodism): https://tinyurl.com/y2e7t22v
Neuron action potentials: https://tinyurl.com/2wemwdn4
Economic equilibrium & feedback: https://tinyurl.com/nhdx7r3s
Echo chambers: https://tinyurl.com/4v8yk7e8
Game design: https://tinyurl.com/bdhdhv38
Gap metric (Vinnicombe): https://tinyurl.com/y9nw3yve
Georgiou, Smith - "Feedback Control and the Arrow of Time": https://tinyurl.com/5xvj76jr
Annaswamy, Fradkov - "A Historical Perspective of Adaptive Control and Learning": https://tinyurl.com/4nfew8vm
Algorithmic trading flash crash (2010): https://tinyurl.com/2dsrs8j2
AI alignment: https://tinyurl.com/yvs3wnj8

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
03:12 - Early life
09:07 - St. Petersburg: Stability of Ellipsoidal Bodies
20:13 - Kharkov: The General Problem of the Stability of Motion
34:37 - Back to St. Petersburg: Probability & Academy
46:22 - Tragic end
49:50 - Posthumous recognition 
57:49 - Legacy
1:20:39 - Outro

Links
A. M. Lyapunov: https://tinyurl.com/3kjuhfns
S. Lyapunov: https://tinyurl.com/mury7p3s
Smirnov's bio: https://tinyurl.com/6wpffh3z
Bissell's essay: https://tinyurl.com/3ds3hubj
Sechenov: https://tinyurl.com/ypsr37vc
Krylov: https://tinyurl.com/44wez8w5
Krylov subspace: https://tinyurl.com/bw527uh2
Chebyshev: https://tinyurl.com/2n35usfr
The General Problem of Stability of Motion: https://tinyurl.com/mv2jchv2
Lyapunov stability: https://tinyurl.com/bb59vcuf
Central limit theorem: https://tinyurl.com/3r36p458
Van der Pol oscillator: https://tinyurl.com/3s68yyhr
Massera’s theorem: https://tinyurl.com/2zjmtvjw
LaSalle’s invariance principle: https://tinyurl.com/pjnrp3fh
Krasovskii: https://tinyurl.com/junbujsw
Popov criterion: https://tinyurl.com/uyt3kx5b
Control Lyapunov function: https://tinyurl.com/3v7bnusj
Artstein–Sontag formula: https://tinyurl.com/3fdebmm3
Input-to-state stability: https://tinyurl.com/3nca9nj6
Lyapunov equation: https://tinyurl.com/mvakw3yw
Hybrid systems: https://tinyurl.com/v39up6wk
Control barrier function: https://tinyurl.com/sy4p5jj
Dominance theory: https://tinyurl.com/msvnd4dv

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.