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Duality and Approximation Methods for Cooperative Optimization and Control

Duality and Approximation Methods for Cooperative Optimization and Control
Author: Mathias Bürger
Publisher: Logos Verlag Berlin GmbH
Total Pages: 166
Release: 2014
Genre: Mathematics
ISBN: 3832536248

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This thesis investigates the role of duality and the use of approximation methods in cooperative optimization and control. Concerning cooperative optimization, a general algorithm for convex optimization in networks with asynchronous communication is presented. Based on the idea of polyhedral approximations, a family of distributed algorithms is developed to solve a variety of distributed decision problems, ranging from semi-definite and robust optimization problems up to distributed model predictive control. Optimization theory, and in particular duality theory, are shown to be central elements also in cooperative control. This thesis establishes an intimate relation between passivity-based cooperative control and network optimization theory. The presented results provide a complete duality theory for passivity-based cooperative control and lead the way to novel analysis tools for complex dynamic phenomena. In this way, this thesis presents theoretical insights and algorithmic approaches for cooperative optimization and control, and emphasizes the role of convexity and duality in this field.


Duality for Nonconvex Approximation and Optimization

Duality for Nonconvex Approximation and Optimization
Author: Ivan Singer
Publisher: Springer Science & Business Media
Total Pages: 366
Release: 2007-03-12
Genre: Mathematics
ISBN: 0387283951

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The theory of convex optimization has been constantly developing over the past 30 years. Most recently, many researchers have been studying more complicated classes of problems that still can be studied by means of convex analysis, so-called "anticonvex" and "convex-anticonvex" optimizaton problems. This manuscript contains an exhaustive presentation of the duality for these classes of problems and some of its generalization in the framework of abstract convexity. This manuscript will be of great interest for experts in this and related fields.


Cooperative and Graph Signal Processing

Cooperative and Graph Signal Processing
Author: Petar Djuric
Publisher: Academic Press
Total Pages: 866
Release: 2018-07-04
Genre: Computers
ISBN: 0128136782

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Cooperative and Graph Signal Processing: Principles and Applications presents the fundamentals of signal processing over networks and the latest advances in graph signal processing. A range of key concepts are clearly explained, including learning, adaptation, optimization, control, inference and machine learning. Building on the principles of these areas, the book then shows how they are relevant to understanding distributed communication, networking and sensing and social networks. Finally, the book shows how the principles are applied to a range of applications, such as Big data, Media and video, Smart grids, Internet of Things, Wireless health and Neuroscience. With this book readers will learn the basics of adaptation and learning in networks, the essentials of detection, estimation and filtering, Bayesian inference in networks, optimization and control, machine learning, signal processing on graphs, signal processing for distributed communication, social networks from the perspective of flow of information, and how to apply signal processing methods in distributed settings. Presents the first book on cooperative signal processing and graph signal processing Provides a range of applications and application areas that are thoroughly covered Includes an editor in chief and associate editor from the IEEE Transactions on Signal Processing and Information Processing over Networks who have recruited top contributors for the book


An Index

An Index
Author: A. V. Balakrishnan M. Thoma
Publisher: Springer
Total Pages: 35
Release: 2013-11-21
Genre: Science
ISBN: 3662254492

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Convex Optimization in Signal Processing and Communications

Convex Optimization in Signal Processing and Communications
Author: Daniel P. Palomar
Publisher: Cambridge University Press
Total Pages: 513
Release: 2010
Genre: Computers
ISBN: 0521762227

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Leading experts provide the theoretical underpinnings of the subject plus tutorials on a wide range of applications, from automatic code generation to robust broadband beamforming. Emphasis on cutting-edge research and formulating problems in convex form make this an ideal textbook for advanced graduate courses and a useful self-study guide.


Duality in Optimization and Variational Inequalities

Duality in Optimization and Variational Inequalities
Author: C.j. Goh
Publisher: Taylor & Francis
Total Pages: 344
Release: 2002-05-10
Genre: Mathematics
ISBN: 9780415274791

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This comprehensive volume covers a wide range of duality topics ranging from simple ideas in network flows to complex issues in non-convex optimization and multicriteria problems. In addition, it examines duality in the context of variational inequalities and vector variational inequalities, as generalizations to optimization. Duality in Optimization and Variational Inequalities is intended for researchers and practitioners of optimization with the aim of enhancing their understanding of duality. It provides a wider appreciation of optimality conditions in various scenarios and under different assumptions. It will enable the reader to use duality to devise more effective computational methods, and to aid more meaningful interpretation of optimization and variational inequality problems.


Distributed Model Predictive Control Made Easy

Distributed Model Predictive Control Made Easy
Author: José M. Maestre
Publisher: Springer Science & Business Media
Total Pages: 601
Release: 2013-11-10
Genre: Technology & Engineering
ISBN: 9400770065

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The rapid evolution of computer science, communication, and information technology has enabled the application of control techniques to systems beyond the possibilities of control theory just a decade ago. Critical infrastructures such as electricity, water, traffic and intermodal transport networks are now in the scope of control engineers. The sheer size of such large-scale systems requires the adoption of advanced distributed control approaches. Distributed model predictive control (MPC) is one of the promising control methodologies for control of such systems. This book provides a state-of-the-art overview of distributed MPC approaches, while at the same time making clear directions of research that deserve more attention. The core and rationale of 35 approaches are carefully explained. Moreover, detailed step-by-step algorithmic descriptions of each approach are provided. These features make the book a comprehensive guide both for those seeking an introduction to distributed MPC as well as for those who want to gain a deeper insight in the wide range of distributed MPC techniques available.


Emergent Behavior Detection and Task Coordination for Multiagent Systems

Emergent Behavior Detection and Task Coordination for Multiagent Systems
Author: Jing Wang
Publisher: Springer Nature
Total Pages: 250
Release: 2021-10-23
Genre: Technology & Engineering
ISBN: 3030868931

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This book addresses problems in the modeling, detection, and control of emergent behaviors and task coordination in multiagent systems. It presents a unified solution to such problems in terms of distributed estimation, distributed control, and optimization of interaction topologies and dynamics. Four aspects of the technical solutions in the book are presented: First, the impact of interaction dynamics on the convergence conditions related to interaction topologies is discussed, utilizing a discontinuous cooperative control algorithm of updated design. Second, distributed least-squares and Kalman filtering algorithms for agents with limited interactions are elaborated upon. Third, a general framework of distributed nonlinear control is established, and distributed adaptive control for nonlinear systems with more general uncertainties is presented. Based on the proposed framework, a distributed nonlinear controller is designed to deal with task coordination of robotic systems with nonholonomic constraints. Finally, the problem of optimal multiagent task coordination is addressed and solutions based on approximate dynamic programming and approximate distributed gradient estimation are presented. Emergent Behavior Detection and Task Coordination for Multiagent Systems is of interest to practicing engineers in areas such as robotics and cyber-physical systems, researchers in the field of systems, controls, and robotics, and senior undergraduate and graduate students.