Network-Based Analysis of Dynamical Systems: Methods for Controllability and Observability Analysis, and Optimal Sensor Placement
This book explores the key idea that the dynamical properties of complex systems can be determined by effectively calculating specific structural features using network science-based analysis. Furthermore, it argues that certain dynamical behaviours can stem from the existence of specific motifs in the network representation.

Over the last decade, network science has become a widely applied methodology for the analysis of dynamical systems. Representing the system as a mathematical graph allows several network-based methods to be applied, and centrality and clustering measures to be calculated in order to characterise and describe the behaviours of dynamical systems.

The applicability of the algorithms developed here is presented in the form of well-known benchmark examples. The algorithms are supported by more than 50 figures and more than 170 references; taken together, they provide a good overview of the current state of network science-based analysis of dynamical systems, and suggest further reading material for researchers and students alike. The files for the proposed toolbox can be downloaded from a corresponding website.

1134793451
Network-Based Analysis of Dynamical Systems: Methods for Controllability and Observability Analysis, and Optimal Sensor Placement
This book explores the key idea that the dynamical properties of complex systems can be determined by effectively calculating specific structural features using network science-based analysis. Furthermore, it argues that certain dynamical behaviours can stem from the existence of specific motifs in the network representation.

Over the last decade, network science has become a widely applied methodology for the analysis of dynamical systems. Representing the system as a mathematical graph allows several network-based methods to be applied, and centrality and clustering measures to be calculated in order to characterise and describe the behaviours of dynamical systems.

The applicability of the algorithms developed here is presented in the form of well-known benchmark examples. The algorithms are supported by more than 50 figures and more than 170 references; taken together, they provide a good overview of the current state of network science-based analysis of dynamical systems, and suggest further reading material for researchers and students alike. The files for the proposed toolbox can be downloaded from a corresponding website.

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Network-Based Analysis of Dynamical Systems: Methods for Controllability and Observability Analysis, and Optimal Sensor Placement

Network-Based Analysis of Dynamical Systems: Methods for Controllability and Observability Analysis, and Optimal Sensor Placement

Network-Based Analysis of Dynamical Systems: Methods for Controllability and Observability Analysis, and Optimal Sensor Placement

Network-Based Analysis of Dynamical Systems: Methods for Controllability and Observability Analysis, and Optimal Sensor Placement

Overview

This book explores the key idea that the dynamical properties of complex systems can be determined by effectively calculating specific structural features using network science-based analysis. Furthermore, it argues that certain dynamical behaviours can stem from the existence of specific motifs in the network representation.

Over the last decade, network science has become a widely applied methodology for the analysis of dynamical systems. Representing the system as a mathematical graph allows several network-based methods to be applied, and centrality and clustering measures to be calculated in order to characterise and describe the behaviours of dynamical systems.

The applicability of the algorithms developed here is presented in the form of well-known benchmark examples. The algorithms are supported by more than 50 figures and more than 170 references; taken together, they provide a good overview of the current state of network science-based analysis of dynamical systems, and suggest further reading material for researchers and students alike. The files for the proposed toolbox can be downloaded from a corresponding website.

Product Details

ISBN-13: 9783030364717
Publisher: Springer International Publishing
Publication date: 01/14/2020
Series: SpringerBriefs in Computer Science
Edition description: 1st ed. 2020
Pages: 110
Product dimensions: 6.10(w) x 9.25(h) x (d)

About the Author

Dr. János Abonyi is a Full Professor of Computer Science and Chemical Engineering at the Department of Process Engineering, University of Pannonia, Veszprém, Hungary. His other publications include the Springer titles Interpretability of Computational Intelligence-Based Regression Models, and (with Dr. Vathy-Fogarassy) Graph-Based Clustering and Data Visualization Algorithms.

Dr. Ágnes Vathy-Fogarassy is an Associate Professor at the Department of Computer Science and Systems Technology at the University of Pannonia.

Dániel Leitold is an Assistant Lecturer at the University of Pannonia.

Table of Contents

1. Introduction.- 2. Structural Controllability and Observability Analysis in Complex Networks.- 3. Reduction of Relative Degree by Optimal Control and Sensor Placement.- 4. Applications to the analysis of Heat Exchanger Networks.- 5. The NOCAD MATLAB/Octave Toolbox Developed for the Analysis of Dynamical Systems.- 6. Summary.
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