inControl

Outline
00:00 - Intro
01:31 - Mexico City to Leningrad: a communist girlfriend, and a year of Russian
05:40 - Sliding modes at the source
10:38 - France: Ioan Landau, Laurent Praly, and dynamic normalization
16:25 - Continuity, robustness, and the Rohrs counterexamples
24:18 - On Gerhard Kreisselmeier
28:04 - Illinois and Mexico
35:31 - Mark Spong, Twente, and passivity-based control
46:32 - Energy shaping, damping injection, and total energy shaping
49:50 - IDA-PBC, written on a napkin in a Paris café
58:09 - Putting Energy Back in Control, Slotine, and the dissipation obstacle
1:02:50 - Where good problems come from: knock on the practitioners' door
1:06:23 - Immersion and invariance
1:13:40 - Power shaping, Brayton and Moser, and shifted passivity
1:19:29 - Power systems and going back to Russia
1:27:23 - DREM: the adjugate trick that decouples parameter estimation
1:31:11 - Sensorless observers
1:34:44 - A seminar in Yakubovich's flat and on data-driven control
1:41:47 - Advice to the next generation
1:44:43 - Outro

Links
Romeo Ortega's website: https://facultad.itam.mx/facultad/romeo-ortega-martinez
Utkin, "Variable structure systems with sliding modes": https://doi.org/10.1109/TAC.1977.1101446
Variable structure systems with chattering reduction: https://doi.org/10.1016/0005-1098(84)90076-1
Robustness of discrete-time direct adaptive controllers (dynamic normalization): https://doi.org/10.1109/TAC.1985.1103890
Robustness of adaptive controllers, a survey: https://doi.org/10.1016/0005-1098(89)90023-X
Comments on the robust stability analysis of adaptive controllers using normalizations: https://doi.org/10.1109/9.28033
Feuer & Morse, "Adaptive control of single-input single-output linear systems": https://doi.org/10.1109/TAC.1978.1101822
Rohrs, Valavani, Athans & Stein, "Robustness of continuous-time adaptive control algorithms in the presence of unmodeled dynamics": https://doi.org/10.1109/TAC.1985.1104070
Åström's commentary on the Rohrs et al. paper: https://doi.org/10.1109/TAC.1985.1104066
Hsu & Costa, "Bursting phenomena in continuous-time adaptive systems with a sigma-modification": https://doi.org/10.1109/TAC.1987.1104440
Karafyllis & Krstić, "Robust Adaptive Control: Deadzone-Adapted Disturbance Suppression": https://doi.org/10.1137/1.9781611978438
Discrete-time model reference adaptive control using generalized sampled-data hold functions: https://doi.org/10.1109/9.50351
Kreisselmeier, "The generation of adaptive law structures for globally convergent adaptive observers": https://doi.org/10.1109/TAC.1979.1102066
Gao, Bosso, Wang, Saussié & Yi, "Input-output data-driven stabilization of continuous-time linear MIMO systems": https://arxiv.org/abs/2511.06524
Adaptive motion control of rigid robots, a tutorial (where "passivity-based control" is coined): https://doi.org/10.1016/0005-1098(89)90054-X
Takegaki & Arimoto, "A new feedback method for dynamic control of manipulators": https://doi.org/10.1115/1.3139651
Torque regulation of induction motors: https://doi.org/10.1016/0005-1098(93)90059-3
Passivity-based Control of Euler-Lagrange Systems: https://doi.org/10.1007/978-1-4471-3603-3
PID Passivity-Based Control of Nonlinear Systems with Applications: https://doi.org/10.1002/9781119694199
PID passivity-based control of port-Hamiltonian systems (all passive outputs): https://doi.org/10.1109/TAC.2017.2732283
Energy-shaping of port-controlled Hamiltonian systems by interconnection: https://doi.org/10.1109/CDC.1999.830260
Interconnection and damping assignment passivity-based control of port-controlled Hamiltonian systems (IFAC High Impact Paper Award 2026): https://doi.org/10.1016/S0005-1098(01)00278-3
Putting energy back in control: https://doi.org/10.1109/37.915398
Slotine, "Putting physics in control": https://doi.org/10.1109/37.9164
Chang, Bloch, Leonard, Marsden & Woolsey, "The equivalence of controlled Lagrangian and controlled Hamiltonian systems": https://doi.org/10.1051/cocv:2002045
The matching conditions of controlled Lagrangians and IDA-passivity based control: https://doi.org/10.1080/00207170210135939
Control by interconnection and standard passivity-based control of port-Hamiltonian systems: https://doi.org/10.1109/TAC.2008.2006930
Ferguson & Borja, "Control-by-interconnection beyond Casimirs and connections to IDA-PBC": https://doi.org/10.1109/TAC.2026.3661486
Immersion and invariance, a new tool for stabilization and adaptive control of nonlinear systems: https://doi.org/10.1109/TAC.2003.809820
Nonlinear and Adaptive Control with Applications: https://doi.org/10.1007/978-1-84800-066-7
Brayton & Moser, "A theory of nonlinear networks I": https://doi.org/10.1090/qam/169746
Power shaping, a new paradigm for stabilization of nonlinear RLC circuits: https://doi.org/10.1109/TAC.2003.817918
Passivity of nonlinear incremental systems: https://doi.org/10.1016/j.sysconle.2007.03.011
Interconnection and damping assignment approach to control of PM synchronous motors: https://doi.org/10.1109/87.960344
An energy-shaping approach to the design of excitation control of synchronous generators: https://doi.org/10.1016/S0005-1098(02)00177-2
Transient stabilization of multimachine power systems with nontrivial transfer conductances: https://doi.org/10.1109/TAC.2004.840477
Conditions for stability of droop-controlled inverter-based microgrids: https://doi.org/10.1016/j.automatica.2014.08.009
A parameter estimation approach to state observation of nonlinear systems (PEBO): https://doi.org/10.1016/j.sysconle.2015.09.008
Performance enhancement of parameter estimators via dynamic regressor extension and mixing (DREM): https://doi.org/10.1109/TAC.2016.2614889
On modified parameter estimators for identification and adaptive control: https://doi.org/10.1016/j.arcontrol.2020.06.002
Generalized parameter estimation-based observers (GPEBO): https://doi.org/10.1016/j.automatica.2021.109635
Sensorless control of surface-mount permanent-magnet synchronous motors: https://doi.org/10.1109/TPEL.2009.2025276
A globally exponentially convergent sensorless observer for the IPMSM: https://doi.org/10.1016/j.automatica.2025.112138
Willems, "The behavioral approach to open and interconnected systems": https://doi.org/10.1109/MCS.2007.906923
Abramovich, Kuznetsov & Leonov, "V. A. Yakubovich, mathematician, father of the field": https://doi.org/10.1016/j.ifacol.2015.09.150

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Podcast info
Podcast website: https://www.incontrolpodcast.com/
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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
08:35 - What is PID control?
12:15 - The history: Minorsky, 1922, and steering ships
21:00 - The lambda method, IMC, and analytical tuning
28:45 - Set-point weighting and two degrees of freedom
32:50 - Automatic tuning and the relay feedback problem
40:35 - The Lund school and Karl Johan Åström
50:20 - PID is nearly optimal
57:30 - PID tuning: the elephant in the room
1:01:35 - Open problems and the one-third rule
1:05:45 - Feedforward: the unsung hero
1:15:00 - PID as a building block in large-scale control
1:21:40 - Teaching, outsourcing, and lost knowledge
1:28:15 - PID in the AI age
1:32:25 - Microalgae and sustainable process control
1:40:05 - Advice for young researchers and the future of PID

Links
Hägglund & Guzmán, "Give us PID controllers and we can control the world": https://doi.org/10.1016/j.ifacol.2024.08.018
Minorsky, "Directional Stability of Automatically Steered Bodies": https://doi.org/10.1111/j.1559-3584.1922.tb04958.x
Hazen, "Theory of Servo-Mechanisms": https://doi.org/10.1016/S0016-0032(34)90254-4
Ziegler & Nichols, "Optimum Settings for Automatic Controllers": https://doi.org/10.1115/1.4019264
Dahlin, "Designing and Tuning Digital Controllers" (the lambda method): https://skoge.folk.ntnu.no/puublications_others/1968_Dahlin%20-%20Designing%20and%20tuning%20digital%20controllers.pdf
Rivera, Morari & Skogestad, "Internal Model Control: PID Controller Design": https://skoge.folk.ntnu.no/publications/1986/Rivera86/Rivera86.pdf
Åström & Hägglund, "Automatic Tuning of Simple Regulators": https://cse.lab.imtlucca.it/~bemporad/teaching/controllodigitale/pdf/Astrom-ACC89.pdf
Hägglund & Åström, "Industrial Adaptive Controllers Based on Frequency Response Techniques": https://doi.org/10.1016/0005-1098(91)90052-4
Åström & Hägglund, "The Future of PID Control": https://doi.org/10.1016/S0967-0661(01)00062-4
Hägglund, "A Unified Discussion on Signal Filtering in PID Control": https://doi.org/10.1016/j.conengprac.2013.03.012
Theorin & Hägglund, "Derivative Backoff: The Other Saturation Problem": https://doi.org/10.1016/j.jprocont.2015.06.008
Hägglund, mid-ranging control (2021): https://skoge.folk.ntnu.no/puublications_others/apc-papers/midranging-control-vpc-hagglund-2020.pdf
Guzmán & Hägglund, "Simple Tuning Rules for Feedforward Compensators": https://doi.org/10.1016/j.jprocont.2010.10.007
Guzmán, Hägglund, Veronesi & Visioli, "Performance Indices for Feedforward Control": https://doi.org/10.1016/j.jprocont.2014.12.004
Del Hoyo, Hägglund, Guzmán & Moreno: https://doi.org/10.1016/j.conengprac.2023.105636
Pawlowski, Guzmán, Normey-Rico & Berenguel, "Improving Feedforward Disturbance Compensation in GPC": Improving feedforward disturbance compensation capabilities in Generalized Predictive Control
Guzmán & Hägglund, "Feedforward Control: Analysis, Design, Tuning Rules, and Implementation": https://books.google.it/books/about/Feedforward_Control.html?id=f_C00AEACAAJ
Normey-Rico & Guzmán, "Unified PID Tuning Approach for Dead-Time Processes": https://doi.org/10.3182/20120328-3-IT-3014.00006
Soltesz & Cervin, "When Is PID a Good Choice?": https://doi.org/10.1016/j.ifacol.2018.06.074
Grimholt, PID optimality: https://skoge.folk.ntnu.no/publications/thesis/2018_grimholt/phd-thesis-grimholt-2018.pdf
Hägglund & Guzmán, "Development of Basic Process Control Structures": https://doi.org/10.1016/j.ifacol.2018.06.202
Skogestad, "Advanced Control Using Decomposition and Simple Elements": https://doi.org/10.1016/j.arcontrol.2023.100903
Guzmán, Hägglund et al., "Understanding PID Design Through Interactive Tools": https://doi.org/10.3182/20140824-6-ZA-1003.01328
ISA-TR5.9-2023, "Proportional-Integral-Derivative Control Algorithms and Performance": https://www.isa.org/products/isa-tr5-9-2023-proportional-integral-derivative-pi
Vilanova & Visioli, "PID Control in the Third Millennium": https://books.google.it/books/about/PID_Controllers.html?id=FsyhngEACAAJ
Brian Douglas — control engineering education videos: https://engineeringmedia.com/videos
A Practical Guide to PID Controller Implementation: https://arxiv.org/abs/2604.15918

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Podcast info
Podcast website: https://www.incontrolpodcast.com/
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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
02:25 - 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/
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
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

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
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/
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
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/376r5r9x

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.