Outline
00:00 - Intro
01:07 - Early steps
02:47 - Why control?
05:20 - The move to the US
07:40 - The first journal paper
13:30 - What is backstepping?
17:08 - Grad school
25:10 - Stochastic stabilization
29:53 - The interest in PDEs
43:24 - Navier-Stokes equations
52:12 - Hyperbolic PDEs and traffic models
57:51 - Predictors for long delays
1:08:14 - Extremum seeking
1:27:14 - Safe control
1:36:30 - Interplay between machine learning and control
1:42:28 - Back to the roots: robust adaptive control
1:50:50 - On service
1:55:54 - Advice

Links
Miroslav’s site: https://flyingv.ucsd.edu/
Tuning functions paper: https://tinyurl.com/yznv6r9r
P. Kokotović: https://tinyurl.com/mwmbm9yh
Separation and swapping:  https://tinyurl.com/y4fre6t8
Adaptive nonlinear stabilizers: https://tinyurl.com/4a9wmmvx
KKK book: https://tinyurl.com/2kw2b4k6
Stochastic nonlinear stabilization: https://tinyurl.com/4td3537a
Follow-up with unknown covariance: https://tinyurl.com/4c4n7fd7
Boundary state feedbacks for PIDEs: https://tinyurl.com/4e9y4tdr
Boundary Control of PDEs: https://tinyurl.com/d8x38bmj
Stabilization of Navier–Stokes systems: https://tinyurl.com/4a8cbjem
Traffic congestion control: https://tinyurl.com/525jphs5
Delay compensation: https://tinyurl.com/5yz6uj9p
Nonlinear predictors for long delays: https://tinyurl.com/7wvce6vy
Stability of extremum seeking: https://tinyurl.com/mr5cvzd3
Nash equilibrium seeking: https://tinyurl.com/yeywrysn
Inverse optimal safety filters: https://tinyurl.com/9dkrpvkk
Neural operators for PDE control: https://tinyurl.com/5yynsp7v
Bode lecture: https://tinyurl.com/mp92cs9u
CSM article:

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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.