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Plug-and-play control and consensus algorithms for current sharing in DC microgrids

IFAC-PapersOnLine 2017年第1期50卷 12440-12445页

作者： Tucci, Michele Meng, Lexuan Guerrero, Josep M. Ferrari-Trecate, Giancarlo Dipartimento di Ingegneria Industriale e dell'Informazione Università degli Studi di Pavia Denmark Institute of Energy Technology Aalborg University Aalborg9220 Denmark Switzerland

In this paper, we propose a secondary consensus-based control layer for current sharing and voltage balancing in DC microGrids (mGs). Differently from existing approaches based on droop control, we assume decentralized Plug-and-Play (PnP) regulators at the primary level, as they provide voltage stabilization and their design complexity is independent of the mG size. We analyze the behavior of the closed-loop mG by approximating local primary control loops with unitary gains. This analysis can be extended to the more complex case where primary control loops are abstracted into first-order transfer functions (Tucci et al., 2016a). Besides showing stability, current sharing, and voltage balancing in the asymptotic régime, we describe how to design secondary controllers in a PnP fashion when Distributed Generation Units (DGUs) are added or removed. Theoretical results are complemented by simulations using a 5-DGUs mG implemented in Simulink/PLECS. © 2017

关键词： Complex networks Asymptotic stability Distributed parameter control systems Renewable energy resources Voltage control consensus algorithms Design complexity Distributed control Distributed generation units Electrical networks Renewable energy systems Voltage balancing Voltage stabilization

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Robust consensus algorithms for Multiscale Coordination Control of Multivehicle Systems With Disturbances

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2016年第2期63卷 1107-1119页

作者： Meng, Deyuan Jia, Yingmin Beihang Univ BUAA Div Res 7 Beijing 100191 Peoples R China Beihang Univ BUAA Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China

This paper aims to address a new class of multiscale coordination control problems for multivehicle systems that are subject to external disturbances. Each vehicle is measured by an independent scale due to the constraints of physical environments. Based on the nearest neighbor-interaction rules, three algorithms of different convergence rates are presented such that the vehicles are guaranteed to achieve consensuson a common quantity for all but of their own scales. Simulation tests are performed to validate the effectiveness and robustness of these consensus algorithms. By introducing a Lyapunov potential function, the consensus analysis is further achieved for the three multiscale algorithms, regardless of them with an exponential, finite-time, or fixed-time convergence rate and in the presence of bounded disturbances.

关键词： consensus algorithms exponential convergence finite-time convergence fixed-time convergence multiscale coordination multivehicle systems

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consensus-Based algorithms for Distributed Network-State Estimation and Localization

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IEEE TRANSACTIONS ON SIGNAL AND INFORMATION PROCESSING OVER NETWORKS 2017年第2期3卷 430-444页

作者： Soatti, Gloria Nicoli, Monica Savazzi, Stefano Spagnolini, Umberto Politecn Milan Dipartimento Elettron Informaz & Bioingn I-20133 Milan Italy CNR Inst Elect Comp & Telecommun Engn I-20133 Milan Italy

Recent advances of hardware design and radio technologies have opened the way for an emerging category of networkenabled smart physical devices as a result of convergence in computing and wireless communication capabilities. Inspired by biological interactions, distributed processing of data collected by individual devices is now becoming crucial to let the nodes self-learn relevant network-state information and self-organize without the support of a central unit. Focus of this paper is twofold. First, a novel network channel model tailored for dense deployments is developed and validated on real data. The model describes relevant channel features that are representative of site-specific static/dynamic multipath fading and are shared by all links of a network. Second, a new class of distributed weighted-consensus strategies is introduced to support distributed network calibration and localization in device-to-device networks. Network calibration allows the devices to self-learn the common channel parameters by successive refinements of local estimates and peer-to-peer information exchange. Network-localization enables each node to acquire augmented information about the whole network topology by distributed learning from local channel observations. The proposed distributed algorithms guarantee a fast convergence and can replace conventional centralized schemes. An experimental case study is discussed in a representative indoor environment for the purpose of system validation. Experimental results show that the proposed method can significantly improve the performance of conventional solutions.

关键词： Distributed estimation consensus algorithms channel modelling network localization

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Sparse Spectrum Sensing in Infrastructure-less Cognitive Radio Networks via Binary consensus algorithms 27

Sparse Spectrum Sensing in Infrastructure-less Cognitive Rad...

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27th IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC)

作者： Seif, Mohamed ElBatt, Tamer Seddik, Karim G. Nile Univ WINC Giza Egypt Cairo Univ Dept EECE Fac Engn Giza Egypt Amer Univ Cairo Elect & Commun Engn Dept New Cairo 11835 Egypt

ISBN: (纸本)9781509032549

Compressive Sensing has been utilized in Cognitive Radio Networks (CRNs) to exploit the sparse nature of the occupation of the primary users. Also, distributed spectrum sensing has been proposed to tackle the wireless channel problems, like node or link failures, rather than the common "centralized approach" for spectrum sensing. In this paper, we propose a distributed spectrum sensing framework based on consensus algorithms where SU nodes exchange their binary decisions to take global decisions without a fusion center to coordinate the sensing process. Each SU will share its decision with its neighbors, and at every new iteration each SU will take a new decision based on its current decision and the decisions it receives from its neighbors;in the next iteration, each SU will share its new decision with its neighbors. We show via simulations that the detection performance can tend to the performance of majority-rule Fusion Center based CRNs.

关键词： Compressive Sensing consensus algorithms and Cognitive Radio Network

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consensus algorithms for Distributed Spectrum Sensing Based on Goodness of Fit Test in Cognitive Radio Networks

Consensus Algorithms for Distributed Spectrum Sensing Based ...

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International Conference on Military Communications and Information Systems (ICMCIS)

作者： Teguig, Djamel Scheers, Bart Le Nir, Vincent Horlin, Franois Royal Mil Acad Dept CISS Brussels Belgium Univ Libre Bruxelles OPERA Wireless Commun Grp Brussels Belgium

ISBN: (纸本)9788393484850

In this paper, we study a consensus algorithm for distributed spectrum sensing (DSS) in cognitive radio networks (CRN) integrating a Goodness of Fit based spectrum sensing scheme. Existing work in this area often applies energy detector as a local spectrum sensing method for DSS, however in this case one needs to make the assumption that the noise level is the same at every node in the network, otherwise the threshold can not be set properly. In GoF based spectrum sensing, the threshold for the binary test depends only on the desired false alarm probability and not on the local noise powers. Motivated by this nice feature of GoF based spectrum sensing, we consider the goodness of fit (GoF) test statistic to be exchanged among cognitive radio (CR) users (consensus variable) instead of the energy. Moreover, a weighted consensus based DSS scheme is proposed and compared to the conventional consensus based on DSS. Simulations are conducted to show the effectiveness of the consensus algorithm based on GoF test.

关键词： Cognitive Radio Spectrum Sensing consensus algorithms Goodness of Fit test

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WOLFOWITZ'S THEOREM AND consensus algorithms IN HADAMARD SPACES

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PROCEEDINGS OF THE AMERICAN MATHEMATICAL SOCIETY 2015年第10期143卷 4403-4414页

作者： Grohs, P. Swiss Fed Inst Technol Zurich Dept Math CH-8092 Zurich Switzerland

We provide a generalization of Wolfowitz's theorem on the products of stochastic, indecomposable and aperiodic (SIA) matrices to metric spaces with nonpositive curvature. As a result we show convergence for a wide... 详细信息

关键词： SIA matrices consensus algorithms Hadamard space Wolfowitz theorem

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Convergence of max-min consensus algorithms

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AUTOMATICA 2015年 62卷 11-17页

作者： Shi, Guodong Xia, Weiguo Johansson, Karl Henrik Australian Natl Univ Res Sch Engn Canberra ACT 0200 Australia Dalian Univ Technol Sch Control Sci & Engn Dalian Peoples R China Royal Inst Technol Sch Elect Engn ACCESS Linnaeus Ctr Stockholm Sweden

In this paper, we propose a distributed max-min consensus algorithm for a discrete-time n-node system. Each node iteratively updates its state to a weighted average of its own state together with the minimum and maximum states of its neighbors. In order for carrying out this update, each node needs to know the positive direction of the state axis, as some additional information besides the relative states from the neighbors. Various necessary and/or sufficient conditions are established for the proposed max-min consensus algorithm under time-varying interaction graphs. These convergence conditions do not rely on the assumption on the positive lower bound of the arc weights. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： consensus algorithms Time-dependent graphs Asymptotic convergence

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Sparse Spectrum Sensing in Infrastructure-less Cognitive Radio Networks via Binary consensus algorithms

Sparse Spectrum Sensing in Infrastructure-less Cognitive Rad...

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IEEE Annual International Symposium on Personal, Indoor, and Mobile Radio Communications

作者： Mohamed Seif Tamer ElBatt Karim G. Seddik Wireless Intelligent Networks Center (WINC) Nile University Egypt Dept. of EECE Faculty of Engineering Cairo University Giza Egypt Electronics and Communications Engineering Department American University in Cairo New Cairo 11835 Egypt

ISBN: (纸本)9781509032556

关键词： Compressive Sensing consensus algorithms Cognitive Radio Network

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A consensus-Driven Distributed Moving Horizon Estimation Approach for Target Detection Within Unmanned Aerial Vehicle Formations in Rescue Operations

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DRONES 2025年第2期9卷 127-127页

作者： Bassolillo, Salvatore Rosario D'Amato, Egidio Notaro, Immacolata Univ Naples Parthenope Ctr Direzionale Isola C4 Dept Sci & Technol I-80143 Naples Italy Univ Campania L Vanvitelli Dept Engn Via Roma 29 I-81031 Aversa Italy

In the last decades, the increasing employment of unmanned aerial vehicles (UAVs) in civil applications has highlighted the potential of coordinated multi-aircraft missions. Such an approach offers advantages in terms of cost-effectiveness, operational flexibility, and mission success rates, particularly in complex scenarios such as search and rescue operations, environmental monitoring, and surveillance. However, achieving global situational awareness, although essential, represents a significant challenge, due to computational and communication constraints. This paper proposes a Distributed Moving Horizon Estimation (DMHE) technique that integrates consensus theory and Moving Horizon Estimation to optimize computational efficiency, minimize communication requirements, and enhance system robustness. The proposed DMHE framework is applied to a formation of UAVs performing target detection and tracking in challenging environments. It provides a fully distributed architecture that enables UAVs to estimate the position and velocity of other fleet members while simultaneously detecting static and dynamic targets. The effectiveness of the technique is proved by several numerical simulation, including an in-depth sensitivity analysis of key algorithm parameters, such as fleet network topology and consensus iterations and the evaluation of the robustness against node faults and information losses.

关键词： distributed state estimation Moving Horizon Estimation (MHE) consensus algorithms UAV formations rescue missions target detection target tracking

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Hybrid Raft-PoW Blockchain consensus Algorithm

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IEEE ACCESS 2025年 13卷 72067-72076页

作者： Ulukok, Mehtap Kose Sariyildiz, Irfan Evrim, Vesile Cyprus Aydin Univ Dept Software Engn TR-99010 Mersin Northern Cyprus Turkiye European Univ Lefke Dept Comp Engn TR-99010 Mersin Northern Cyprus Turkiye

The Raft consensus algorithm is widely used in private networks as an alternative to the energy-intensive PoW consensus algorithm in blockchains. The Raft consensus algorithm's voting mechanism performs well in reliable and well-planned networks with optimized timeouts. However, in unreliable or poorly configured networks, it encounters several challenges. These include multiple candidacies, repeated election cycles, insufficient or failed leader elections during network splits, prolonged leader election times and vulnerability to Sybil attacks. In this study, a novel Hybrid Raft-PoW consensus algorithm is introduced. It integrates the hash puzzle-based competition of the PoW consensus algorithm with the fast leader election mechanism of the Raft consensus algorithm. This combination ensures both speed and certainty in leader election, ensuring that leadership is delegated to the most capable nodes. At the same time, it promotes decentralization by ensuring a fair distribution across nodes, achieving at least 80% leadership distribution. Therefore, the proposed Hybrid Raft-PoW consensus algorithm improves or eliminates problems caused by Raft consensus algorithm's leader election mechanism.

关键词： Voting consensus algorithm Blockchains Security Leadership Partitioning algorithms Energy consumption Internet of Things Clustering algorithms Simulation Blockchain technology consensus algorithms proof of work raft

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