inControl

Alberto Padoan
  • 4.0（3）
  • 科学

The first podcast on control theory. inControl shop: https://incontrolpodcast.myshopify.com/

  1. 2日前

    ep48 - Romeo Ortega: From sliding modes to adaptive, passivity-based and energy-shaping control

    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 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.

  2. 8月17日

    ep47 - Tore Hägglund and José Luis Guzman: the art of PID control

    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 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.

  3. 7月15日

    ep46 - The fall of LTCM: Bachelier, Merton, and Black–Scholes ... when stochastic control met Wall Street

    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 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.

  4. 6月15日

    ep45 - Peter Caines: from stochastic and adaptive control to mean field games, graphons, and beyond!

    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 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.

  5. 5月15日

    ep44 - Mario di Bernardo: From Circuits to Cells and Swarms — Control meets Complexity

    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 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.

  6. 4月15日

    ep43 - Steve Brunton: DMD, Koopman, SINDy, Eigensteve Channel, HydroGym, Optimization, and much more

    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.

  7. 3月16日

    ep42 - inControl guide to ... the Nyquist criterion

    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.

  8. 2月16日

    ep41 - A minimal history of optimal control

    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.

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番組について

The first podcast on control theory. inControl shop: https://incontrolpodcast.myshopify.com/

情報

  • クリエイター
    Alberto Padoan
  • 配信期間
    22年 - 26年
  • エピソード
    48
  • 制限指定
    不適切な内容を含む
  • Copyright
    © 2026 inControl
  • 番組のWebサイト
    inControl

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