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Sasahara, H., Ishizaki, T., Imura, J.-i., Sandberg, H. & Johansson, K. H. (2023). Distributed Design of Glocal Controllers via Hierarchical Model Decomposition. IEEE Transactions on Automatic Control, 68(10), 6146-6159
Open this publication in new window or tab >>Distributed Design of Glocal Controllers via Hierarchical Model Decomposition
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2023 (English)In: IEEE Transactions on Automatic Control, ISSN 0018-9286, E-ISSN 1558-2523, Vol. 68, no 10, p. 6146-6159Article in journal (Refereed) Published
Abstract [en]

This article proposes a distributed design method of controllers with a glocal (global/local) information structure for large-scale network systems. The glocal controller of interest has a hierarchical structure, wherein a global subcontroller coordinates a set of disjoint local subcontrollers. The global subcontroller regulates interarea oscillations among subsystems, while local subcontrollers individually regulate intraarea oscillations of the respective subsystem. The distributed design of the glocal controller is addressed to enhance the scalability of controller synthesis, where the global subcontroller and all local subcontrollers are designed independently of each other. A design problem is formulated for subcontroller sets such that any combination of subcontrollers each of which belongs to its corresponding set guarantees stability of the closed-loop system. The core idea of the proposed method is to represent the original network system as a hierarchical cascaded system composed of reduced-order models representing the interarea and intraarea dynamics, referred to as hierarchical model decomposition. Distributed design is achieved by virtue of the cascade structure. The primary findings of this study are twofold. First, a tractable solution to the distributed design problem and an existence condition of the hierarchical model decomposition are presented. Second, a clustering method appropriate for the proposed framework and a robust extension are provided. Numerical examples of a power grid highlight the practical relevance of the proposed method.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Keywords
Network systems, Reduced order systems, Oscillators, Power system stability, Power grids, Power system dynamics, Mathematical models, Distributed design, glocal control, large-scale systems, model reduction
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-338959 (URN)10.1109/TAC.2023.3234919 (DOI)001076908400022 ()2-s2.0-85147233467 (Scopus ID)
Note

QC 20231101

Available from: 2023-11-01 Created: 2023-11-01 Last updated: 2024-03-18Bibliographically approved
Selvaratnam, D., Das, A. & Sandberg, H. (2023). Electrical Fault Localisation Over a Distributed Parameter Transmission Line. In: 2023 62nd IEEE Conference on Decision and Control, CDC 2023: . Paper presented at 62nd IEEE Conference on Decision and Control, CDC 2023, Singapore, Singapore, Dec 13 2023 - Dec 15 2023 (pp. 7088-7093). Institute of Electrical and Electronics Engineers (IEEE)
Open this publication in new window or tab >>Electrical Fault Localisation Over a Distributed Parameter Transmission Line
2023 (English)In: 2023 62nd IEEE Conference on Decision and Control, CDC 2023, Institute of Electrical and Electronics Engineers (IEEE) , 2023, p. 7088-7093Conference paper, Published paper (Refereed)
Abstract [en]

Motivated by the need to localise faults along electrical power lines, this paper adopts a frequency-domain approach to parameter estimation for an infinite-dimensional linear dynamical system with one spatial variable. Since the time of the fault is unknown, and voltages and currents are measured at only one end of the line, distance information must be extracted from the post-fault transients. To properly account for high-frequency transient behaviour, the line dynamics is modelled directly by the Telegrapher's equation, rather than the more commonly used lumped-parameter approximations. First, the governing equations are non-dimensionalised to avoid ill-conditioning. A closed-form expression for the transfer function is then derived. Finally, nonlinear least-squares optimisation is employed to search for the fault location. Requirements on fault bandwidth, sensor bandwidth and simulation time-step are also presented. The result is a novel end-to-end algorithm for data generation and fault localisation, the effectiveness of which is demonstrated via simulation.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
National Category
Energy Engineering
Identifiers
urn:nbn:se:kth:diva-343711 (URN)10.1109/CDC49753.2023.10383452 (DOI)001166433805128 ()2-s2.0-85184823148 (Scopus ID)
Conference
62nd IEEE Conference on Decision and Control, CDC 2023, Singapore, Singapore, Dec 13 2023 - Dec 15 2023
Note

Part of ISBN 9798350301243

QC 20240222

Available from: 2024-02-22 Created: 2024-02-22 Last updated: 2024-04-05Bibliographically approved
She, B., Gracy, S., Sundaram, S., Sandberg, H., Johansson, K. H. & Paré, P. E. (2023). Epidemics Spread Over Networks: Influence of Infrastructure and Opinions. In: Cyber–Physical–Human Systems: Fundamentals and Applications (pp. 429-456). Wiley
Open this publication in new window or tab >>Epidemics Spread Over Networks: Influence of Infrastructure and Opinions
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2023 (English)In: Cyber–Physical–Human Systems: Fundamentals and Applications, Wiley , 2023, p. 429-456Chapter in book (Other academic)
Abstract [en]

In this chapter, we focus on epidemics spreading over networks. Over the last several decades, researchers across multiple communities have studied epidemics, among which are the classical epidemic models that assume that the population is well mixed. These classical models have been shown to be useful for studying epidemic outbreaks in densely connected populations. However, motivated by the need to understand epidemics at a more fine-grained level (encompassing heterogeneity in individual characteristics or contacts), networked models of epidemic spread have started to gain significant attention in recent years. In this chapter, we consider two types of epidemic spreading models that capture the notation of human-in-the-plant. We first provide a background on modeling, analysis, and applications of networked epidemic models. We show that networked epidemic models are capable of tracing the origin of an outbreak, which aids in developing control strategies for eradicating an epidemic. In the second part of this chapter, we discuss how some cyber–physical–human systems (CPHS) can propagate, or hinder, the spread of epidemics over networks. CPHS are composed of a series of interconnected systems that interact with one another. As such, these are extremely appealing for modeling, analyzing, and eradicating epidemics by capturing the impact of infrastructure, economy, and human factors. Next, we highlight two of our recent works that consider the combination of CPHS with epidemics spreading over networks. In the first work, we model an epidemic spreading process over connected communities by coupling the opinions of these communities over a social network. We analyze the influence of the opinions regarding the outbreak on the epidemic spreading process. In the second work, we consider an epidemic spreading process over connected communities with a shared resource (e.g. a water resource, a supermarket, and a metro station). We model the epidemic spreading process by considering the influence of the shared resource and show that the shared resource is critical in determining the shape of the epidemic (i.e. amount of population infected, hospitalized, recovered, etc.). Finally, we conclude by providing insights on potential future research directions.

Place, publisher, year, edition, pages
Wiley, 2023
Keywords
Cyber-physical human system, Epidemic modeling, Infrastructure, Networked dynamical systems, Opinion dynamics
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-333955 (URN)10.1002/9781119857433.ch16 (DOI)2-s2.0-85165105701 (Scopus ID)
Note

Part of ISBN 9781119857433 9781119857402

QC 20230818

Available from: 2023-08-18 Created: 2023-08-18 Last updated: 2023-08-18Bibliographically approved
Umsonst, D., Ruths, J. & Sandberg, H. (2023). Finite Sample Guarantees for Quantile Estimation: An Application to Detector Threshold Tuning. IEEE Transactions on Control Systems Technology, 31(2), 921-928
Open this publication in new window or tab >>Finite Sample Guarantees for Quantile Estimation: An Application to Detector Threshold Tuning
2023 (English)In: IEEE Transactions on Control Systems Technology, ISSN 1063-6536, E-ISSN 1558-0865, Vol. 31, no 2, p. 921-928Article in journal (Refereed) Published
Abstract [en]

In threshold-based anomaly detection, we want to tune the threshold of a detector to achieve an acceptable false alarm rate. However, tuning the threshold is often a non-trivial task due to unknown detector output distributions. A detector threshold that provides an acceptable false alarm rate is equivalent to a specific quantile of the detector output distribution. Therefore, we use quantile estimators based on order statistics to estimate the detector threshold. The estimation of quantiles from sample data has a more than a century-long tradition and we provide three different distribution-free finite sample guarantees for a class of quantile estimators. The first is based on the Dvoretzky-Kiefer-Wolfowitz (DKW) inequality, the second utilizes the Vysochanskij-Petunin inequality, and the third is based on exact confidence intervals for a beta distribution. These guarantees are then compared and used in the detector threshold tuning problem. We use both simulated data as well as data obtained from an experimental setup with the Temperature Control Lab to validate the guarantees provided. 

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Keywords
Detector threshold tuning, fault detection, finite sample guarantees, quantile estimation, Behavioral research, Electric power transmission networks, Errors, Image resolution, Sampling, Behavioral science, False alarm rate, Faults detection, Finite sample guarantee, Finite samples, Power grids, Threshold tuning, Tuning
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-328103 (URN)10.1109/TCST.2022.3199668 (DOI)000860940500001 ()2-s2.0-85139425024 (Scopus ID)
Note

QC 20230602

Available from: 2023-06-02 Created: 2023-06-02 Last updated: 2023-06-02Bibliographically approved
Selvaratnam, D., Farokhi, F., Shames, I. & Sandberg, H. (2023). Manipulating the Posterior Support of a Discrete Bayesian Estimator Under Full Sensor Control. In: : . Paper presented at 22nd IFAC World Congress, Yokohama, Japan, Jul 9 2023 - Jul 14 2023 (pp. 252-257). Elsevier B.V.
Open this publication in new window or tab >>Manipulating the Posterior Support of a Discrete Bayesian Estimator Under Full Sensor Control
2023 (English)Conference paper, Published paper (Refereed)
Abstract [en]

The asymptotic implausibility problem is introduced from the perspective of an adversary that seeks to drive the belief of a recursive Bayesian estimator away from a particular set of parameter values. It is assumed that the adversary controls all sensors informing the estimator, and can transmit false measurements stochastically according to a fixed distribution of its choice. First, we outline a method for verifying whether a given distribution solves the problem. We then consider the class of spoofing attacks, and show that the asymptotic implausibility problem has a solution if and only if it can be solved by a spoofing attack. Attention is restricted to finite parameter and observation spaces.

Place, publisher, year, edition, pages
Elsevier B.V., 2023
Keywords
Bayesian Estimation, Cyber-Physical Systems, Network Security, Network Systems, Resilient Control Systems, Signal Processing
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-343696 (URN)10.1016/j.ifacol.2023.10.1577 (DOI)2-s2.0-85184960090 (Scopus ID)
Conference
22nd IFAC World Congress, Yokohama, Japan, Jul 9 2023 - Jul 14 2023
Note

Part of ISBN 9781713872344

QC 20240222

Available from: 2024-02-22 Created: 2024-02-22 Last updated: 2024-02-22Bibliographically approved
Alisic, R., Kim, J. & Sandberg, H. (2023). Model-Free Undetectable Attacks on Linear Systems Using LWE-Based Encryption. IEEE Control Systems Letters, 7, 1249-1254
Open this publication in new window or tab >>Model-Free Undetectable Attacks on Linear Systems Using LWE-Based Encryption
2023 (English)In: IEEE Control Systems Letters, E-ISSN 2475-1456, Vol. 7, p. 1249-1254Article in journal (Refereed) Published
Abstract [en]

We show that the homomorphic property, a desired property in encrypted control, can lead to failure in the cyber defense of a dynamical control system from undetectable attacks, even though individual signal sequences remain unknown to the attacker. We consider an encryption method based on the Learning with Errors (LWE) problem and demonstrate how model-free undetectable attacks on linear systems over integers can be computed from sampled inputs and outputs that are encrypted. Previous work has shown that computing such attacks is possible on nonencrypted systems. Applying this earlier work to our scenario, with minor modifications, typically amplifies the error in encrypted messages unless a short vector problem is solved. Given that an attacker obtains a short vector, we derive the probability that the attack is detected and show how it explicitly depends on the encryption parameters. Finally, we simulate an attack obtained by our method on an encrypted linear system over integers and conduct an analysis of the probability that the attack will be detected.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Keywords
Detectors, Trajectory, Encryption, Linear systems, Dynamical systems, Control systems, Sensors, Sampled-data control, quantized systems
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-324532 (URN)10.1109/LCSYS.2023.3234004 (DOI)000917748200002 ()2-s2.0-85147205024 (Scopus ID)
Note

QC 20230307

Available from: 2023-03-07 Created: 2023-03-07 Last updated: 2023-08-25Bibliographically approved
Pare, P. E., Janson, A., Gracy, S., Liu, J., Sandberg, H. & Johansson, K. H. (2023). Multilayer SIS Model With an Infrastructure Network. IEEE Transactions on Control of Network Systems, 10(1), 295-307
Open this publication in new window or tab >>Multilayer SIS Model With an Infrastructure Network
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2023 (English)In: IEEE Transactions on Control of Network Systems, E-ISSN 2325-5870, Vol. 10, no 1, p. 295-307Article in journal (Refereed) Published
Abstract [en]

In this article, we develop a layered networked spread model for a susceptible-infected-susceptible pathogen-borne disease spreading over a human contact network and an infrastructure network, and refer to it as a layered networked susceptible-infected-water-susceptible model (SIWS). The "W" in SIWS represents any infrastructure network contamination, not necessarily restricted to a water distribution network. We identify sufficient conditions for the existence, uniqueness, and stability of various equilibria of the aforementioned model. Further, we study an observability problem, where, assuming that the measurements of the pathogen levels in the infrastructure network are available, we provide a necessary and sufficient condition for estimation of the sickness levels of the nodes in the human contact network. Our results are illustrated through an in-depth set of simulations.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Keywords
Statistics, Sociology, Observability, Pathogens, Analytical models, Water resources, Epidemics, Epidemic processes, infrastructure networks, stability
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-326648 (URN)10.1109/TCNS.2022.3203352 (DOI)000967202900001 ()2-s2.0-85137588992 (Scopus ID)
Note

QC 20230508

Available from: 2023-05-08 Created: 2023-05-08 Last updated: 2024-03-18Bibliographically approved
Alanwar, A., Gassmann, V., He, X., Said, H., Sandberg, H., Johansson, K. H. & Althoff, M. (2023). Privacy-preserving set-based estimation using partially homomorphic encryption. European Journal of Control, 71, 100786, Article ID 100786.
Open this publication in new window or tab >>Privacy-preserving set-based estimation using partially homomorphic encryption
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2023 (English)In: European Journal of Control, ISSN 0947-3580, E-ISSN 1435-5671, Vol. 71, p. 100786-, article id 100786Article in journal (Refereed) Published
Abstract [en]

The set-based estimation has gained a lot of attention due to its ability to guarantee state enclosures for safety-critical systems. However, collecting measurements from distributed sensors often requires out-sourcing the set-based operations to an aggregator node, raising many privacy concerns. To address this problem, we present set-based estimation protocols using partially homomorphic encryption that pre-serve the privacy of the measurements and sets bounding the estimates. We consider a linear discrete-time dynamical system with bounded modeling and measurement uncertainties. Sets are represented by zonotopes and constrained zonotopes as they can compactly represent high-dimensional sets and are closed under linear maps and Minkowski addition. By selectively encrypting parameters of the set repre-sentations, we establish the notion of encrypted sets and intersect sets in the encrypted domain, which enables guaranteed state estimation while ensuring privacy. In particular, we show that our protocols achieve computational privacy using the cryptographic notion of computational indistinguishability. We demonstrate the efficiency of our approach by localizing a real mobile quadcopter using ultra-wideband wireless devices.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
Set-based estimation, Homomorphic encryption, Zonotopes, Constrained zonotopes
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-326585 (URN)10.1016/j.ejcon.2023.100786 (DOI)000967698800001 ()2-s2.0-85151403204 (Scopus ID)
Note

QC 20230508

Available from: 2023-05-08 Created: 2023-05-08 Last updated: 2023-05-08Bibliographically approved
Tegling, E., Bamieh, B. & Sandberg, H. (2023). Scale fragilities in localized consensus dynamics. Automatica, 153, Article ID 111046.
Open this publication in new window or tab >>Scale fragilities in localized consensus dynamics
2023 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 153, article id 111046Article in journal (Refereed) Published
Abstract [en]

We consider distributed consensus in networks where the agents have integrator dynamics of order two or higher (n≥2). We assume all feedback to be localized in the sense that each agent has a bounded number of neighbors and consider a scaling of the network through the addition of agents in a modular manner, i.e., without re-tuning controller gains upon addition. We show that standard consensus algorithms, which rely on relative state feedback, are subject to what we term scale fragilities, meaning that stability is lost as the network scales. For high-order agents (n≥3), we prove that no consensus algorithm with fixed gains can achieve consensus in networks of any size. That is, while a given algorithm may allow a small network to converge, it causes instability if the network grows beyond a certain finite size. This holds in families of network graphs whose algebraic connectivity, that is, the smallest non-zero Laplacian eigenvalue, is decreasing towards zero in network size (e.g. all planar graphs). For second-order consensus (n=2) we prove that the same scale fragility applies to directed graphs that have a complex Laplacian eigenvalue approaching the origin (e.g. directed ring graphs). The proofs for both results rely on Routh–Hurwitz criteria for complex-valued polynomials and hold true for general directed network graphs. We survey classes of graphs subject to these scale fragilities, discuss their scaling constants, and finally prove that a sub-linear scaling of nodal neighborhoods can suffice to overcome the issue.

Place, publisher, year, edition, pages
Elsevier BV, 2023
Keywords
Fundamental limitations, Large-scale systems, Multi-agent networks
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-331604 (URN)10.1016/j.automatica.2023.111046 (DOI)000993915200001 ()2-s2.0-85154053849 (Scopus ID)
Note

QC 20230711

Available from: 2023-07-11 Created: 2023-07-11 Last updated: 2023-07-11Bibliographically approved
Keijzer, T., Ferrari, R. M. G. & Sandberg, H. (2023). Secure State Estimation Under Actuator and Sensor Attacks Using Sliding Mode Observers. IEEE Control Systems Letters, 7, 2071-2076
Open this publication in new window or tab >>Secure State Estimation Under Actuator and Sensor Attacks Using Sliding Mode Observers
2023 (English)In: IEEE Control Systems Letters, E-ISSN 2475-1456, Vol. 7, p. 2071-2076Article in journal (Refereed) Published
Abstract [en]

Interconnections in modern systems make them vulnerable to adversarial attackers both by corrupting communication channels and compromising entire subsystems. The field of secure state estimation (SSE) aims to provide correct state estimation even when an unknown part of the measurement signals is corrupted. In this letter, we propose a solution to a novel generalized SSE problem in which full subsystems can be compromised, corrupting both the actuation and measurement signals. For a full system with p measurements, the proposed sliding mode observer (SMO)-based solution allows for up to p attack channels which can be arbitrarily distributed amongst attacks on actuation and measurement signals. This is a much larger class of attacks than considered in the existing literature. The method is demonstrated on 10 interconnected mass-spring-damper subsystems.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2023
Keywords
Secure state estimation, cyber-attacks, sliding mode observers
National Category
Control Engineering
Identifiers
urn:nbn:se:kth:diva-333568 (URN)10.1109/LCSYS.2023.3284393 (DOI)001018640700008 ()2-s2.0-85162651108 (Scopus ID)
Note

QC 20230803

Available from: 2023-08-03 Created: 2023-08-03 Last updated: 2023-08-03Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-1835-2963

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