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In this thesis we study stability from several viewpoints. After covering the practical importance, the rich history and the ever-growing list of manifestations of stability, we study the following. (i) (Statistical identification of stable dynamical syste ...
In light of the challenges posed by climate change and the goals of the Paris Agreement, electricity generation is shifting to a more renewable and decentralized pattern, while the operation of systems like buildings is increasingly electrified. This calls ...
Modern optimization is tasked with handling applications of increasingly large scale, chiefly due to the massive amounts of widely available data and the ever-growing reach of Machine Learning. Consequently, this area of research is under steady pressure t ...
We study the problem of performance optimization of closed -loop control systems with unmodeled dynamics. Bayesian optimization (BO) has been demonstrated to be effective for improving closed -loop performance by automatically tuning controller gains or re ...
Microorganisms are essential for life on Earth, performing key roles in numerous biological processes. Their influence extends across a wide spectrum, from human health and ecological balance to advancements in biotechnology and industrial applications. Th ...
This paper proposes a data-driven control design method for nonlinear systems that builds upon the Koopman operator framework. In particular, the Koopman operator is used to lift the nonlinear dynamics to a higher-dimensional space where the so-called obse ...
Modern control synthesis methods rely on accurate models to derive a performant controller. Obtaining a good model is often a costly step, and has led to a renewed interest in data-driven synthesis methods. Frequency-response-based synthesis methods have b ...
This paper introduces a novel method for data-driven robust control of nonlinear systems based on the Koopman operator, utilizing Integral Quadratic Constraints (IQCs). The Koopman operator theory facilitates the linear representation of nonlinear system d ...
A novel approach for linear parameter-varying (LPV) controller synthesis for adaptive rejection of time-varying sinusoidal disturbances is proposed. Only the frequency response data of a linear time-invariant (LTI) multiple-input multiple-output (MIMO) sys ...
In this paper, the challenge of asymptotically rejecting sinusoidal disturbances with unknown time-varying frequency and bounded rate is explored. A novel data-driven approach for designing linear parameter-varying (LPV) con- troller is introduced, leverag ...
