inControl

Outline00:00 - Intro01:06 - The big idea03:42 - Controllability, observability, and  ... the space race!14:52 - Kálmán and the state-space paradigm00:00 - The math and intuition: state-space basics, definitions, and duality00:00 - A touch of nonlinearity00:00 - Developments in the field: a chronological tour00:00 - Controllability and observability: quo vaditis?00:00 - OutroLinksKálmán: https://tinyurl.com/bdzj7mtrControllability: https://tinyurl.com/28s5zxpnObservability: https://tinyurl.com/yjxncxdnPaper - "Contributions to the theory of optimal control": https://tinyurl.com/9wwf8pvhPaper - "Discovery and Invention": https://tinyurl.com/ryfn463nKálmán's speech -  Kyoto Prize : https://tinyurl.com/2ahrjdahPaper - Controllability of complex networks: https://tinyurl.com/3zk99n4sSupport the showPodcast infoPodcast website: https://www.incontrolpodcast.com/Apple Podcasts: https://tinyurl.com/5n84j85jSpotify: https://tinyurl.com/4rwztj3cRSS: https://tinyurl.com/yc2fcv4yYoutube: https://tinyurl.com/bdbvhsj6Facebook: https://tinyurl.com/3z24yr43Twitter: https://twitter.com/IncontrolPInstagram: https://tinyurl.com/35cu4kr4Acknowledgments and sponsorsThis 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.

Outline00:00 - Intro00:42 - “Research should be fun”02:02 - Early steps in research09:00 - Book writing and meeting C. Desoer18:33 - Control synthesis via the factorization approach25:46 - The graph metric 29:27 - Robotics and CAIR36:00 - Randomized algorithms40:41 - On learning44:05 - Neural networks48:40 - Tata, hidden Markov models, and large deviations theory55:48 - Picking problems and role of luck58:07 - Compressed sensing and non-convex optimization01:02:17 - Interplay between control and machine learning01:09:10 - Advice to future students01:13:29 - Future of controlLinksSagar’s website: https://tinyurl.com/4hwruajsHilbert: https://tinyurl.com/ykpdh929Feedback Systems: https://tinyurl.com/2k3jsdatHow to Write Mathematics: https://tinyurl.com/35794bv9Nonlinear systems: https://tinyurl.com/2fdtnjcmC. Desoer: https://tinyurl.com/svhknrenControl Systems Synthesis — A Factorization Approach: https://tinyurl.com/59wdc4svAryabhata: https://tinyurl.com/43x6hfhpA Brief History of the Graph Topology: https://tinyurl.com/49uftzdkRobot Dynamics and Control: https://tinyurl.com/5b4cmt7mCAIR: https://tinyurl.com/rajdtxaxRandomized algorithms for robust controller synthesis using statistical learning theory: https://tinyurl.com/wanpyeucR. Tempo: https://tinyurl.com/jkufdwarVC dimension: https://tinyurl.com/mvwk8afmLearning and Generalisation: https://tinyurl.com/2s3mzh8hAre Analog Neural Networks Better Than Binary Neural Networks? https://tinyurl.com/3fnk27xcHidden Markov Processes: https://tinyurl.com/t5frrvfzAn Introduction to Compressed Sensing: https://tinyurl.com/fc6a8eerSupport the showPodcast infoPodcast website: https://www.incontrolpodcast.com/Apple Podcasts: https://tinyurl.com/5n84j85jSpotify: https://tinyurl.com/4rwztj3cRSS: https://tinyurl.com/yc2fcv4yYoutube: https://tinyurl.com/bdbvhsj6Facebook: https://tinyurl.com/3z24yr43Twitter: https://twitter.com/IncontrolPInstagram: https://tinyurl.com/35cu4kr4Acknowledgments and sponsorsThis 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.

Anders Rantzer, a Professor in Automatic Control at Lund University, dives into his extensive journey through robust control and hybrid systems. He discusses Kharitonov's theorem and integral quadratic constraints, illuminating their significance in stability analysis. Rantzer emphasizes the adaptive nature of control systems and their relevance in real-world applications like energy grids and personalized medicine. His insights on the duality of Lyapunov's theorems showcase the evolution of control theory, while offering valuable advice for students eager to forge connections in the field.

Outline00:00 - Intro01:07 - Early steps02:47 - Why control?05:20 - The move to the US07:40 - The first journal paper13:30 - What is backstepping?17:08 - Grad school25:10 - Stochastic stabilization29:53 - The interest in PDEs43:24 - Navier-Stokes equations52:12 - Hyperbolic PDEs and traffic models57:51 - Predictors for long delays1:08:14 - Extremum seeking1:27:14 - Safe control1:36:30 - Interplay between machine learning and control1:42:28 - Back to the roots: robust adaptive control1:50:50 - On service1:55:54 - AdviceLinksMiroslav’s site: https://flyingv.ucsd.edu/Tuning functions paper: https://tinyurl.com/yznv6r9rP. Kokotović: https://tinyurl.com/mwmbm9yhSeparation and swapping:  https://tinyurl.com/y4fre6t8Adaptive nonlinear stabilizers: https://tinyurl.com/4a9wmmvxKKK book: https://tinyurl.com/2kw2b4k6Stochastic nonlinear stabilization: https://tinyurl.com/4td3537aFollow-up with unknown covariance: https://tinyurl.com/4c4n7fd7Boundary state feedbacks for PIDEs: https://tinyurl.com/4e9y4tdrBoundary Control of PDEs: https://tinyurl.com/d8x38bmjStabilization of Navier–Stokes systems: https://tinyurl.com/4a8cbjemTraffic congestion control: https://tinyurl.com/525jphs5Delay compensation: https://tinyurl.com/5yz6uj9pNonlinear predictors for long delays: https://tinyurl.com/7wvce6vyStability of extremum seeking: https://tinyurl.com/mr5cvzd3Nash equilibrium seeking: https://tinyurl.com/yeywrysnInverse optimal safety filters: https://tinyurl.com/9dkrpvkkNeural operators for PDE control: https://tinyurl.com/5yynsp7vBode lecture: https://tinyurl.com/mp92cs9uCSM article: Support the showPodcast infoPodcast website: https://www.incontrolpodcast.com/Apple Podcasts: https://tinyurl.com/5n84j85jSpotify: https://tinyurl.com/4rwztj3cRSS: https://tinyurl.com/yc2fcv4yYoutube: https://tinyurl.com/bdbvhsj6Facebook: https://tinyurl.com/3z24yr43Twitter: https://twitter.com/IncontrolPInstagram: https://tinyurl.com/35cu4kr4Acknowledgments and sponsorsThis 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.

Manfred Morari, Emeritus Professor at ETH Zurich and a distinguished figure in control theory, shares his insights on the evolution of control systems. He discusses his transformative journey from chemical engineering, emphasizing the importance of blending theory with real-world applications. Morari highlights advancements in PID controller design, robust control, and model predictive control while noting the critical role of collaboration with industry. He also reflects on the integration of AI within control systems, addressing the challenges and opportunities that arise from this intersection.

Explore the remarkable journey of Richard Bellman, the father of dynamic programming, tracing his transition from an early life in Brooklyn to pivotal roles during WWII and at Princeton. Hear about his moral dilemmas at Los Alamos and the RAND Corporation amidst the Cold War. Delve into his groundbreaking contributions to control theory and the curse of dimensionality. Discover the resilience of a man who continued to innovate in mathematics, even after personal challenges, leaving a profound legacy in artificial intelligence and optimization.

Karl Henrik Johansson, a Professor at KTH Royal Institute of Technology and Director of Digital Futures, dives into fascinating topics like hybrid systems and wireless control. He shares insights from his PhD journey and the significance of relay feedback in PID tuning. The discussion highlights the future of transportation, focusing on platooning in freight and innovations in autonomous vehicles. Johansson also addresses cybersecurity concerns in control systems and emphasizes the need for collaborative research to tackle societal challenges ahead.

Munther Dahleh, the William Coolidge Professor at MIT, shares his remarkable insights into control theory and its societal implications. He discusses the evolution of data systems, emphasizing their role in addressing complex issues like renewable energy and electric vehicles. The conversation touches on the intricacies of agile robotics and motion planning, intertwined with human-AI interactions. Dahleh also explores the dynamics of information flow in social networks and the importance of analytical thinking in engineering education, inspiring future innovators to embrace challenges.

Bart De Moor, a Professor at KU Leuven, dives into the fascinating realms of subspace identification and linear algebra. He shares insights from his academic journey, influenced by giants like Willems and his experiences at Stanford alongside Golub and Kailath. The discussion touches on the evolution of machine learning and its connection to quantum information. Bart also offers valuable advice on entrepreneurship, emphasizing the importance of networking and intellectual property for future innovators.

Francesco Bullo, an expert in geometric control, robotic networks, and mathematical sociology, discusses his research journey from Italy to California. Topics include robotic locomotion, academic environments, networked systems, contraction theory, coupled oscillators in power grids, and the art gallery problem. Bullo also shares insights on writing, publishing, and professional service in the field of control systems.