Igor Mezić – författare

This book provides a broad overview of state-of-the-art research at the intersection of the Koopman operator theory and control theory. It also reviews novel theoretical results obtained and efficient numerical methods developed within the framework of Koopman operator theory.The contributions discuss the latest findings and techniques in several areas of control theory, including model predictive control, optimal control, observer design, systems identification and structural analysis of controlled systems, addressing both theoretical and numerical aspects and presenting open research directions, as well as detailed numerical schemes and data-driven methods. Each contribution addresses a specific problem. After a brief introduction of the Koopman operator framework, including basic notions and definitions, the book explores numerical methods, such as the dynamic mode decomposition (DMD) algorithm and Arnoldi-based methods, which are used to represent the operator in a finite-dimensional basis and to compute its spectral properties from data. The main body of the book is divided into three parts:theoretical results and numerical techniques for observer design, synthesis analysis, stability analysis, parameter estimation, and identification;data-driven techniques based on DMD, which extract the spectral properties of the Koopman operator from data for the structural analysis of controlled systems; andKoopman operator techniques with specific applications in systems and control, which range from heat transfer analysis to robot control.A useful reference resource on the Koopman operator theory for control theorists and practitioners, the book is also of interest to graduate students, researchers, and engineers looking for an introduction to a novel and comprehensive approach to systems and control, from pure theory to data-driven methods.

This book provides a broad overview of state-of-the-art research at the intersection of the Koopman operator theory and control theory. It also reviews novel theoretical results obtained and efficient numerical methods developed within the framework of Koopman operator theory.The contributions discuss the latest findings and techniques in several areas of control theory, including model predictive control, optimal control, observer design, systems identification and structural analysis of controlled systems, addressing both theoretical and numerical aspects and presenting open research directions, as well as detailed numerical schemes and data-driven methods. Each contribution addresses a specific problem. After a brief introduction of the Koopman operator framework, including basic notions and definitions, the book explores numerical methods, such as the dynamic mode decomposition (DMD) algorithm and Arnoldi-based methods, which are used to represent the operator in a finite-dimensional basis and to compute its spectral properties from data. The main body of the book is divided into three parts:theoretical results and numerical techniques for observer design, synthesis analysis, stability analysis, parameter estimation, and identification;data-driven techniques based on DMD, which extract the spectral properties of the Koopman operator from data for the structural analysis of controlled systems; andKoopman operator techniques with specific applications in systems and control, which range from heat transfer analysis to robot control.A useful reference resource on the Koopman operator theory for control theorists and practitioners, the book is also of interest to graduate students, researchers, and engineers looking for an introduction to a novel and comprehensive approach to systems and control, from pure theory to data-driven methods.

This book provides a broad overview of state-of-the-art research at the intersection of the Koopman operator theory and control theory. It also reviews novel theoretical results obtained and efficient numerical methods developed within the framework of Koopman operator theory.The contributions discuss the latest findings and techniques in several areas of control theory, including model predictive control, optimal control, observer design, systems identification and structural analysis of controlled systems, addressing both theoretical and numerical aspects and presenting open research directions, as well as detailed numerical schemes and data-driven methods. Each contribution addresses a specific problem. After a brief introduction of the Koopman operator framework, including basic notions and definitions, the book explores numerical methods, such as the dynamic mode decomposition (DMD) algorithm and Arnoldi-based methods, which are used to represent the operator in a finite-dimensional basis and to compute its spectral properties from data. The main body of the book is divided into three parts:theoretical results and numerical techniques for observer design, synthesis analysis, stability analysis, parameter estimation, and identification;data-driven techniques based on DMD, which extract the spectral properties of the Koopman operator from data for the structural analysis of controlled systems; andKoopman operator techniques with specific applications in systems and control, which range from heat transfer analysis to robot control.A useful reference resource on the Koopman operator theory for control theorists and practitioners, the book is also of interest to graduate students, researchers, and engineers looking for an introduction to a novel and comprehensive approach to systems and control, from pure theory to data-driven methods.

The analysis and control of mixing is of great interest because of the potential for optimizing the performance of many flow processes. This monograph presents a unique overview of the physics, mathematics and state-of-the-art theoretical/numerical modeling and experimental investigations of mixing. It approaches the subject of mixing from many angles: presents theoretical and experimental results, discusses laminar and turbulent flows, considers macro and micro scales, elaborates on purely advective and advective-diffusive flows, and considers conceptual and industrial-relevant mixing devices. This monograph provides an essential reading for graduate students and postdoctoral researches interested in the investigation of mixing, and constitutes an indispensable reference for mechanical, chemical and aeronautical engineers, and applied mathematicians in universities and industries.

Flow Control and Optimization is increasingly incorporated in the design of engineering devices ranging from aircraft and space vehicles to micro?uidic devices. Research in this ?eld aims to integrate knowledge in ?ow physics with theoretical advances and novel experimental capabilities and engineering devices capable of materializing advanced design concepts. In turn controlled ?ow phenomena exhibit a new arrays of physics and open frontiers for further interdisciplinary research in ?uid mechanics and all the engineering domains that it a?ects. This collection of papers in ?ow control, showcases representatives lines of work in the area of ?ow control demonstrating the interdisciplinary character and high scienti?c merit of this ?eld. The authors of these articles are among the pioneering researchers in this ?eld and continue to explore the frontiers in ?ow control and optimization. We hope that this volume, while largely representing work by the authors prior to 2004, contributes in providing an authoritative report on this rapidly changing ?eld.

Flow Control and Optimization is increasingly incorporated in the design of engineering devices ranging from aircraft and space vehicles to micro?uidic devices. Research in this ?eld aims to integrate knowledge in ?ow physics with theoretical advances and novel experimental capabilities and engineering devices capable of materializing advanced design concepts. In turn controlled ?ow phenomena exhibit a new arrays of physics and open frontiers for further interdisciplinary research in ?uid mechanics and all the engineering domains that it a?ects. This collection of papers in ?ow control, showcases representatives lines of work in the area of ?ow control demonstrating the interdisciplinary character and high scienti?c merit of this ?eld. The authors of these articles are among the pioneering researchers in this ?eld and continue to explore the frontiers in ?ow control and optimization. We hope that this volume, while largely representing work by the authors prior to 2004, contributes in providing an authoritative report on this rapidly changing ?eld.