A framework for data-driven control with guarantees: Analysis, MPC and robust control -- F. Allgöwer

Lecture by Frank Allgöwer as part of the Summer School "Foundations and Mathematical Guarantees of Data-Driven Control" organized by EPFL & ETHZ.
June 14th, 2021
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Abstract: In this lecture, a unitary framework for data-driven control theory is presented, which does not rely on explicit model knowledge but still allows to give desirable theoretical guarantees. The framework relies on a result from behavioral systems theory, where it was shown that one data trajectory can be used to parametrize all further trajectories of an unknown linear system. Three concrete applications of the framework are presented in the form of easily implementable yet mathematically sound system analysis and controller design techniques: 1) a simple method to verify dissipativity properties of linear systems based on input-output data, 2) data-driven model predictive control schemes with guaranteed closed-loop stability for linear and nonlinear systems, and 3) a robust control-based approach for data-driven analysis and control of linear and nonlinear systems.

[@ezasokotela7523]

Very interesting work.

[@sajaydutta50]

Why it is blurred.