**Prof. Henk van Waarde gave a talk on July 11th, 2022 in our group about “Kernel-based models for system analysis”**

## Biography (简介)

Henk van Waarde is an assistant professor in the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence at the University of Groningen in The Netherlands. During 2020- 2021 he held postdoctoral researcher positions at the University of Cambridge, UK, and at ETH Zürich, Switzerland. He obtained the master degree summa cum laude and Ph.D. degree cum laude in Applied Mathematics from the University of Groningen in 2016 and 2020, respectively. He was also a visiting researcher at University of Washington, Seattle in 2019-2020. His research interests include data-driven control, system identification and identifiability, networks of dynamical systems, and robust and optimal control. He was the recipient of the 2021 IEEE Control Systems Letters Outstanding Paper Award.

## Abstract

This talk introduces a computational framework to identify nonlinear input- output operators from data. The goal is to find operators that fit a set of system trajectories while satisfying prior knowledge in the form of integral quadratic constraints. The data fitting algorithm is thus regularized by suitable input-output properties required for system analysis and control design. This biased identification problem is shown to admit the tractable solution of a regularized least squares problem when formulated in a suitable reproducing kernel Hilbert space. The kernel- based framework is a departure from the prevailing state-space framework. It is motivated by fundamental limitations of nonlinear state-space models at combining the fitting requirements of data-based modeling with the input- output requirements of system analysis and physical modeling.