
In this episode I talk to the very wonderful Carmen Amo Alonso about her (award-winning) PhD research on distributed and localised MPC. We also cover super interesting and useful concepts such as system-level synthesis and ADMM, as well as her internship working at Tesla!You can access the transcript at: https://docs.google.com/document/d/1SErvHtKoE18QzelHDUh9im6AeG3zKPWZLRoNGx5BUyg/edit?usp=sharingFollow the podcast on LinkedIn: https://www.linkedin.com/company/coffee-and-control-podcast/Or connect with me directly: https://www.linkedin.com/in/lucy-hodgins-733a30175/ ReferencesCarmen: https://camoalon.github.io/JPL: https://www.jpl.nasa.gov/John Doyle: https://ieeecss.org/contact/john-doyleFeedback in biological control: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9867859https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9867794Thesis: https://thesis.caltech.edu/15262/3/Carmen_Amo_Alonso_Caltech_PhD_Thesis.pdfDistributed localised MPC paper: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9939038 Professor Melanie Zeilinger: https://nccr-automation.ch/about/people/melanie-zeilinger-0SLS for robust nonlinear optimal control: https://arxiv.org/pdf/2301.04943 Professor Nikolai Matni: https://nikolaimatni.github.io/ System-level synthesis tutorial: https://arxiv.org/abs/1904.01634 YouTube videos on DLMPC: https://www.youtube.com/watch?v=mF2Wbriy2Zghttps://www.youtube.com/watch?v=IhtuGZp8QM0&t=302sADMM survey paper: https://arxiv.org/abs/2208.03700Professor James Anderson: https://www.columbia.edu/~ja3451/ Data-driven DLMCP: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9772975Willems fundamental lemma: https://eprints.soton.ac.uk/262195/1/PersistencyExcitation.pdfPaolo Rapisarda episode: https://open.spotify.com/episode/076dEw28abILPAbT5qA6aw Implementing DLMP on GPUs: https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9831839Clubes de Ciencia: Mexico: https://clubesdeciencia.mx/ Peru: https://clubesdecienciaperu.org/Terry Sejnowski: https://biology.ucsd.edu/research/faculty/tsejnowski
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