Systems Theory in Data and Optimization
Proceedings of SysDO 2024
Buch in deiner Nähe kaufen
Beschreibung
This book contains the proceedings of the Symposium on Systems Theory in Data and Optimization (SysDO) held in Stuttgart, Germany, from 30th September to 2nd October 2024. It addresses theoretical and practical research questions arising at the intersection of systems and control theory, data, and optimization. The increasing prevalence of cyber-physical systems sparks the need for new methods to integrate measured data and different forms of feedback, especially optimization-based feedback, inside the decision-making mechanism. There are distinctive challenges that arise in this scenario, such as the existence of different time-scales, the need to guarantee sufficient richness of the collected data, and the effect of suboptimal decisions under uncertainty. This book presents new methods and applications addressing these challenges.
This book is a valuable source on latest research findings spanning diverse topics including:
- data-driven and learning-based control;
- theory and applications of machine learning;
- model predictive control; and
- optimization.
This book contains the proceedings of the Symposium on Systems Theory in Data and Optimization (SysDO) held in Stuttgart, Germany, from 30th September to 2nd October 2024. It addresses theoretical and practical research questions arising at the intersection of systems and control theory, data, and optimization. The increasing prevalence of cyber-physical systems sparks the need for new methods to integrate measured data and different forms of feedback, especially optimization-based feedback, inside the decision-making mechanism. There are distinctive challenges that arise in this scenario, such as the existence of different time-scales, the need to guarantee sufficient richness of the collected data, and the effect of suboptimal decisions under uncertainty. This book presents new methods and applications addressing these challenges.
This book is a valuable source on latest research findings spanning diverse topics including:
- data-driven and learning-based control;
- theory and applications of machine learning;
- model predictive control; and
- optimization.
Provides novel insights into the interaction of control, decision and systems theories and machine learning Presents contributions by an authoritative group of international experts inspire ideas for new research Develops novel algorithms to promote a cross-disciplinary approach and provide reliable solutions
Autor*in
Julian Berberich
Themen in »Systems Theory in Data and Optimization«
Conference Proceedings Systems Theory Control Theory Learning-based Control Optimization Algorithms Feedback Optimization Sequential Decision Making On-line Learning