Systems & Control: Foundations & Applications

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Systems & Control: Foundations & Applications

Series Editor

Tamer Başar, University of Illinois at Urbana-Champaign, Urbana, IL, USA

Editorial Board

Karl JohanÅström, Lund University of Technology, Lund, Sweden Han-Fu Chen, Academia Sinica, Beijing, China

Bill Helton, University of California, San Diego, CA, USA Alberto Isidori, Sapienza University of Rome, Rome, Italy Miroslav Krstic, University of California, San Diego, CA, USA H. Vincent Poor, Princeton University, Princeton, NJ, USA Mete Soner, ETH Zürich, Zürich, Switzerland;

Swiss Finance Institute, Zürich, Switzerland

Former Editorial Board Member

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Tamer Ba

şar

Editor

Uncertainty in Complex

Networked Systems

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Editor Tamer Başar

Department of Electrical and Computer Engineering

University of Illinois at Urbana-Champaign Urbana, IL, USA

ISSN 2324-9749 ISSN 2324-9757 (electronic)

Systems & Control: Foundations & Applications

ISBN 978-3-030-04629-3 ISBN 978-3-030-04630-9 (eBook)

https://doi.org/10.1007/978-3-030-04630-9

Library of Congress Control Number: 2018962123 © Springer Nature Switzerland AG 2018

This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, speciﬁcally the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microﬁlms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed.

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This book is published under the imprint Birkhäuser,www.birkhauser-science.comby the registered company Springer Nature Switzerland AG

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Preface

This book on Uncertainty in Complex Networked Systems is a collection of chapters compiled in memory of Roberto Tempo, who was a member of the Editorial Advisory Board of these Series until his untimely death on January 14, 2017, during a skiing excursion at the Alps near his home town in Northwestern Italy. The volume consists of 17 chapters written by world experts on uncertainty in systems, robustness, networked and network systems, social networks, distributed and ran-domized algorithms, and multi-agent systems—topical areas Roberto Tempo has contributed to profusely during his proliﬁc research career. A salient common feature of all the chapters is that, besides they all addressing the general broadﬁeld of complex systems, networks, and uncertainty, at least one author on each chapter was a research collaborator of Dr. Tempo.

Before describing briefly the contents of the chapters comprising this volume, I will provide a brief account of Roberto Tempo’s life story. More details can be found in the obituary that appeared in volume 78, pages 341–342, of the IFAC journal Automatica in April 2017. He was the Editor-in-Chief of Automatica at the time of his death.

Roberto Tempo was born in Cuorgnè, Italy, in 1956. In 1980, he graduated in Electrical Engineering from Politecnico di Torino, Italy. After a period spent at Politecnico di Torino, he joined the National Research Council of Italy (CNR) at the research institute IEIIT, Torino, where he had been a Director of Research of Systems and Computer Engineering since 1991. He held visiting and research positions at Tsinghua University and the Chinese Academy of Sciences in Beijing, Kyoto University, The University of Tokyo, University of Illinois at Urbana-Champaign, German Aerospace Research Organization in Oberpfaffenhofen, and Columbia University in New York. He was elected a Fellow of the IEEE (2000), a Distinguished Member of the IEEE Control Systems Society (2005), a Fellow of IFAC (2007), and a Corresponding Member of the Academy of Sciences, Institute of Bologna, Italy, Class Engineering Sciences (2011). He served as President of the IEEE Control Systems Society (2010), as General Co-Chair for the IEEE Conference on Decision and Control, Florence, Italy (2013), as Program Chair of theﬁrst joint IEEE Conference on Decision and Control and European Control

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Conference, Seville, Spain (2005), as Editor for Technical Notes and Correspondence of the IEEE Transactions on Automatic Control (2005–2009), and as a Senior Editor of the same journal (2011–2014). He had a long association with Automatica, starting in 1992 as an Associate Editor, then (from 1996) as the Editor of the subject area “System and Control Theory”, and for 11 years as Deputy Editor-in-Chief, before becoming Editor-in-Chief in 2015.

Roberto Tempo’s research activities were initially focused on the analysis and design of complex systems subject to uncertainty. He pioneered the development of randomized algorithms for robust control, generating in this topical area trend-setting papers which appeared in international journals, books, and confer-ences, culminating in the publication, with co-authors, of the monograph Randomized Algorithms for Analysis and Control of Uncertain Systems, Springer, London, which appeared in two editions in 2005 and 2013, and became a standard reference in theﬁeld. His research then evolved toward the analysis and control of complex networked uncertain systems. In this area, he contributed to a number of important areas of application, among which the most relevant and prominent were his work on algorithms for PageRank computation in the Google search engine, and distributed localization of wireless sensor networks. More recently, he had focused his research on algorithmic approaches toward understanding how individuals in a group influence each other to reach a consensus—an activity that culminated in the publication of a Science article. Over the years, several of his publications received paper awards, including the“IEEE Control Systems Magazine Outstanding Paper Award” for the 2014 paper “The PageRank Problem, Multi-agent Consensus and Web Aggregation: A Systems and Control Viewpoint”, and an “Automatica Outstanding Paper Prize Award” for the 1990 paper “The Robust Root Locus”.

Now, coming back to the contents of this volume, the 17 chapters comprising this volume have been organized into three parts: Robustness (Part I), Randomization and Probabilistic Methods (Part II), and Distributed Systems and Algorithms (Part III).

Part I is comprised of four chapters. Theﬁrst chapter, titled “Uncertain Systems: Time-Varying Versus Time-Invariant Uncertainties” by F. Blanchini and

P. Colaneri, provides a survey of several decades of robustness investigation for uncertain systems with a critical view. The second chapter, titled “Cooperative Resilient Estimation of Uncertain Systems Subjected to a Biasing Interference” by

V. Ugrinovskii, surveys some recent results on the analysis and design of networks of robust filters which cooperate to produce high fidelity estimates for uncertain plants, with application to the problem of detecting and neutralizing biasing attacks on distributed observer networks. The third chapter, titled “Robust Static Output Feedback Design with Deterministic and Probabilistic Certificates” by D. Arzelier,

F. Dabbene, S. Formentin, D. Peaucelle, and L. Zaccarian, addresses, using a new bilinear matrix inequality (BMI) formulation, the problem of static output design for uncertain linear systems by iterative optimization procedures with either determin-istic or probabildetermin-istic viewpoints, exploiting the fact that Lyapunov certiﬁcates are separated from the control gain design variables. The fourth, and last, chapter of this part, titled“Robust Control Against Uncertainty Quartet: A Polynomial Approach”

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by D. Zhao, C. Chen, S. Z. Khong, and L. Qiu, introduces a unifying framework to address different types of uncertainty in systems modeling and control, the uncer-tainty quartet, which combines the additive, multiplicative, subtractive and divisive uncertainties, and in this framework it develops an elementary robust control theory, involving mostly polynomial manipulations.

Part II of the volume is comprised of six chapters. The ﬁrst one, titled “Randomization in Robustness, Estimation, and Optimization” by B. Polyak and

P. Shcherbakov, addresses the question of when a random choice (in various decision-making scenarios, such as optimization) would be better than a determin-istic one, and provides a survey of some recent results in this domain. The second one, titled “Stabilization of Deterministic Control Systems Under Random Sampling: Overview and Recent Developments” by A. Tanwani, D. Chatterjee,

and D. Liberzon, addresses the problem of stabilizing continuous-time deterministic control systems via a sample-and-hold scheme under random sampling using the framework of piecewise deterministic Markov processes. The third one, titled “Robust Design Through Probabilistic Maximization” by T. Alamo, J. M. Manzano,

and E. F. Camacho, studies randomized maximization methods for robust design under uncertainty, providing in this context concentration inequalities that lead to probabilistic guarantees on the obtained design parameters. The fourth one, titled “Compressive Sensing and Algebraic Coding: Connections and Challenges” by

M. Vidyasagar and M. Lotfi, provides an overview of known results on compressive sensing using both probabilistic and deterministic approaches, followed by some new constructions of sparse binary measurement matrices, based on LDPC (low density parity check) codes, and a description of the authors’ selected recent results that lead to the fastest available algorithms for compressive sensing in specific situations. Thefifth chapter of this part, titled “Stochastic Optimization for Energy Storage Allocation in Smart Grids in the Presence of Uncertainty” by M. Bucciarelli,

S. Paoletti, and A. Vicino, deals with the application area of smart grids, focusing on the problem of optimal siting and sizing of energy storage systems in a distribution network. The sixth, and last, one of this part, titled“A Data-Driven Basis Function Approach in Nonparametric Nonlinear System Identiﬁcation” by E.-W. Bai and

C. Cheng, proposes a data driven orthogonal basis function approach for non-parametricfinite impulse response (FIR) nonlinear system identification, where the basis functions are notfixed a priori and match the structure of the unknown system automatically.

The last part of the volume, Part III, is comprised of seven chapters. Theﬁrst one, titled “Perspectives on Network Systems and Mathematical Sociology” by

F. Bullo and N. E. Friedkin, provides an overview of a large group of literature on the mathematics of network systems and its application to the study of dynamical models for the evolution of opinions and influence systems, presenting both mathematical results and empirical ﬁndings. The second one, titled “Distributed Randomized Algorithms for PageRank Computation: Recent Advances” by H. Ishii

and A. Suzuki, provides an overview of recent studies on distributed algorithms for PageRank computation that have been developed in the systems control area, and following that introduces a new class of distributed algorithms based on a simple

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but novel interpretation, further demonstrating its advantages over existing ones via analysis and numerical simulations. The third one, titled“Distributed Optimization in Multi-agent Networks Using One-bit of Relative State Information” by J. Zhang

and K. You, is concerned with the design of distributed discrete-time algorithms to cooperatively solve an additive cost optimization problem in multiagent networks, with the striking feature that the algorithms use only the sign of relative state information between neighbors. The fourth one, titled“Analysis of a Distributed Consensus Based Economic Dispatch Algorithm” by R. Mudumbai, S. Dasgupta,

and M. M. M. U. Rahman, presents a consensus-based approach to the optimal economic dispatch of power generators in a smart microgrid, where the generators independently adjust their power-frequency primary controller setpoints using three pieces of information as delineated in the chapter. Theﬁfth one, titled “Impact of Quantized Inter-agent Communications on Game-Theoretic and Distributed Optimization Algorithms” by E. Nekouei, T. Alpcan, and R. J. Evans, addresses

the issue of handling the impact of the uncertainty that is generated by quantized inter-agent communications in game-theoretic and distributed optimization algo-rithms, and uses the information-theoretic notion of differential entropy power to establish universal bounds on the maximum exponential convergence rates of primal-dual and gradient-based Nash seeking algorithms under quantized com-munications. The sixth one, titled “Fault Diagnosis for Uncertain Networked Systems” by F. Boem, C. Keliris, T. Parisini, and M. M. Polycarpou, provides an

overview of results on a model-based distributed fault diagnosis approach to uncertain nonlinear large-scale networked systems to speciﬁcally address the presence of measurement noise, modeling uncertainty, and the presence of delays and packet dropouts when viewed as a networked system. The seventh, and last, one, titled “Networked Quantum Systems” by I. R. Petersen, considers the

mod-elling and realization of quantum networks from a control theory point of view, focusing particularly on quantum linear systems.

I thank all authors referenced above for their contributions to this book, where each chapter has maintained a wonderful balance between being expository and providing new results and identifying fruitful future directions in research—all on topics that were dear to Roberto. I am conﬁdent that the book will prove to be a high-demand reference volume to a broad community of researchers interested in uncertainty, complexity, robustness, optimization, algorithms, and networked sys-tems, for many years to come—as a real tribute to the memory of Roberto Tempo.

Urbana, USA Tamer Başar

September 2018

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Systems & Control: Foundations & Applications