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distributed Nash Equilibrium Seeking for Aggregative Games via Derivative Feedback

INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS 2020年第5期18卷 1075-1082页

作者： Zhang, Yawei Liang, Shu Ji, Haibo Univ Sci & Technol China Dept Automat Hefei 230027 Anhui Peoples R China Univ Sci & Technol Beijing Sch Automat & Elect Engn Key Lab Knowledge Automat Ind Proc Minist Educ Beijing 100083 Peoples R China

In this paper, we investigate a continuous-time distributed Nash equilibrium seeking algorithm for a class of aggregative games, with application to the real-time pricing demand response. To seek the Nash equilibrium via local communication among neighbors, by combining projected gradient dynamics and consensus tracking dynamics, we propose a novel distributed algorithm for the players. We prove the convergence of the distributed algorithm via a constructed Lyapunov function and the variational inequality technique, and show an illustrative simulation related to the energy consumption control in smart grids.

关键词： Aggregative games distributed algorithm energy consumption control Nash equilibrium projected gradient dynamics

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distributed Node Selection algorithm for Physical Layer Security in D2D Network

Distributed Node Selection Algorithm for Physical Layer Secu...

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International Conference on Cyber-Enabled distributed Computing and Knowledge Discovery (CyberC)

作者： Lu Weifeng Wang Mingji Xu Jia Chen Siguang Yang Lijun Xu Jian Nanjing Univ Posts & Telecommun Nanjing Peoples R China Nanjing Univ Sci & Technol Nanjing Peoples R China

ISBN: (纸本)9781728125428

In this paper, we aim to improve the physical layer security for Device-to-device (D2D) communication. To deal with the security challenges and optimize the system communication quality, this paper investigates the security and power consumption problem of underlay communication in a base station cell area with help of D2D user nodes. We propose a distributed algorithm to solve the optimization problem and adapt it to the instability and flexibility of the D2D network. This paper verifies that the global optimal value can be reached quickly by our algorithm, it means a larger secrecy capacity and a lower payment of power consumption.

关键词： Device-to-device Communication Physical Layer Security ADMM distributed algorithm

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Adaptive Routing algorithm for Information Management in distributed Microgrids in Smart Grid

Adaptive Routing Algorithm for Information Management in Dis...

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IFAC Workshop on Control of Smart Grid and Renewable Energy Systems (CSGRES)

作者： Jogunola, Olamide Adebisi, Bamidele Anoh, Kelvin Ikpehai, Augustine Hammoudeh, Mohammad Manchester Metropolitan Univ Fac Sci & Engn Manchester M1 5GD Lancs England Sheffield Hallam Univ Dept Engn & Math Sheffield S1 1WB S Yorkshire England

The increasing affordability of renewable energy resources is inspiring new interest in smart management techniques for the power grid. This paper presents an adaptive routing algorithm technique based on distributed dual-gradient update for facilitating communication among distributed energy resources (DER) units in smart grid. In particular, we consider the optimal message routing as a minimum cost flow problem among DER units in the network. The proposed technique employs a multi-commodity flow optimization, with the aim of minimizing the communication cost against network performances indicators such as throughput and delay. The results show that the proposed technique is able to route messages across the network in fewer processing steps than minimum spanning tree algorithm without any message drop. The algorithm is investigated for mesh, partial mesh and ring networks, with the result consistently showing potential cost savings and reduced complexity which can save significant amount of time when applied to a larger system. (C) 2019, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： distributed energy resources prosumer distributed algorithm communication network information flow management optimal power flow

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Quasi-Orthogonal Z-Complementary Pairs and Their Applications in Fully Polarimetric Radar Systems

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IEEE TRANSACTIONS ON INFORMATION THEORY 2021年第7期67卷 4876-4890页

作者： Wang, Jiahuan Fan, Pingzhi Zhou, Zhengchun Yang, Yang Southwest Jiaotong Univ Prov Key Lab Informat Coding & Transmission Chengdu 611756 Peoples R China South West Jiaotong Univ Sch Math Chengdu 611756 Peoples R China

One objective of this paper is to propose a novel class of sequence pairs, called "quasi-orthogonal Z-complementary pairs (QOZCPs)", each depicting Z-complementary property for their aperiodic auto-correlation sums and also having a low correlation zone when their aperiodic cross-correlation is considered. Construction of QOZCPs based on Successively distributed algorithms under Majorization Minimization (SDAMM) is presented. Another objective of this paper is to apply the proposed QOZCPs in fully polarimetric radar systems and analyse the corresponding ambiguity functions. It turns out that QOZCP waveforms are much more Doppler resilient than the known Golay complementary waveforms.

关键词： Sequence design Doppler resilience quasi-orthogonal Z-complementary pair fully polarimetric radar distributed algorithm majorization minimization algorithm

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distributed non-linear robust consensus-based sensor calibration for networked control systems

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IET CONTROL THEORY AND APPLICATIONS 2020年第9期14卷 1200-1208页

作者： Stankovic, Maja S. Antic, Dragan S. Univ Nis Fac Elect Nish Serbia Telekom Srbija Belgrade Serbia

In this study a new algorithm is proposed for distributed blind sensor macro-calibration in networked control systems robust to noise. The proposed distributed algorithm for estimation of gain and offset correction parameters is of stochastic approximation type, with local non-linear transformations of residuals. Convergence of the algorithm in mean-square and with probability one to consensus is proved for a large class of non-linear transformations, network properties and communication and measurement noise characteristics. The choice of the introduced non-linear transformations in accordance with the theory of robust statistics leads to the proposal of new calibration algorithms robustified w.r.t. noise. It is demonstrated by Monte Carlo simulation that the proposed algorithms are very efficient in the presence of large outliers from the point of view of both achievement of high convergence rate and adequate values of convergence points, outperforming the existing linear algorithms.

关键词： calibration networked control systems robust control measurement errors Monte Carlo methods estimation theory stochastic processes distributed algorithms probability mean square error methods distributed control nonlinear control systems distributed nonlinear robust consensus-based sensor calibration networked control systems distributed blind sensor macro-calibration stochastic approximation type measurement noise characteristics robust statistics linear algorithms distributed algorithm local nonlinear transformations Monte Carlo simulation

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distributed initialization-free algorithms for multi-agent optimization problems with coupled inequality constraints

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NEUROCOMPUTING 2020年 407卷 155-162页

作者： Li, Peng Zhao, Yiyi Hu, Jiangping Zhang, Yuping Ghosh, Bijoy Kumar Univ Elect Sci & Technol China Sch Automat Engn Chengdu 611731 Peoples R China Southwestern Univ Finance & Econ Sch Business Adm Chengdu 611130 Peoples R China Texas Tech Univ Dept Math & Stat Lubbock TX 79409 USA

This paper studies a resource optimization problem for a multi-agent network where all agents have local objective functions and local constraint sets. Meanwhile, the decision variables of all the agents need to satisfy a set of globally coupled inequality constraints. Then, a distributed continuous-time algorithm is designed with the help of the nonsmooth analysis theory and projection operator method. The proposed algorithm does not require each agent to send the gradient information of the cost function to its neighbors, which prevents the gradient information of agents leaking out. Moreover, the convergence analysis shows that the proposed algorithm can converge to the optimal solution starting from any initial allocation. Finally, a case study is presented for a resource allocation problem of a hybrid water-power network. (C) 2020 Elsevier B.V. All rights reserved.

关键词： distributed algorithm Multi-agent optimization Nonsmooth function Coupled inequality constraint Projection operator

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Optimal operation of distribution networks and multiple community energy prosumers based on mixed game theory

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ENERGY 2023年第PartB期278卷

作者： Zhao, Bingxu Duan, Pengfei Fen, Mengdan Xue, Qingwen Hua, Jing Yang, Zhuoqiang Taiyuan Univ Technol Key Coll Civil Engn Taiyuan 030024 Peoples R China Taiyuan Univ Sci & Technol Key Sch Transport & Logist Taiyuan 030024 Peoples R China

Community energy systems are currently transitioning from conventional consumers to prosumers. Under this context, the coordinated management of multiple community energy prosumers (CEPs) is explored this study in accordance with the same distribution network. The aim of this study is to facilitate the coordination of unit operations, demand response, and peer-to-peer (P2P) energy trading among CEP coalitions based on the distribution network operator (DSO) by setting electricity prices. Thus, a mixed game-based optimal operation model of DSO and CEP alliances is developed, integrating Stackelberg and cooperative games. The upper layer aims at maximizing DSO revenue, whereas the lower layer minimizes the operation costs of CEP cooperative alliances while allocating benefits in accordance with the Nash-Harsanyi bargaining theory. The model is solved with a two-stage distributed algorithm that integrates the bisection method and the alternating direction method of multipliers (ADMM). Furthermore, cloud energy storage (CES) is introduced to optimize the economics of CEP. The effectiveness of the proposed method is verified through a case study, demonstrating the collaborative optimal scheduling of multiple CEPs and reasonable benefit distribution. Accordingly, this study is conducive to expediting the effective and economical management of CEPs under distribution networks.

关键词： Mixed game Nash-harsanyi theory P2P energy Trading Cloud energy storage distributed algorithm

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distributed Adaptive Robust Voltage/VAR Control With Network Partition in Active Distribution Networks

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IEEE TRANSACTIONS ON SMART GRID 2020年第3期11卷 2245-2256页

作者： Li, Peishuai Zhang, Cuo Wu, Zaijun Xu, Yan Hu, Minqiang Dong, Zhaoyang Southeast Univ Sch Elect Engn Nanjing 210000 Peoples R China Nanjing Univ Sci & Technol Sch Automat Nanjing 210094 Peoples R China Univ New South Wales Sch Elect Engn & Telecommun Sydney NSW 2052 Australia Nanyang Technol Univ Sch Elect & Elect Engn Singapore Singapore

This paper proposes a distributed adaptive robust voltage/var control (DAR-VVC) method in active distribution networks to minimize power loss while keeping operating constraints under uncertainties. The DAR-VVC aims to coordinate on-load tap changers, capacitor banks and PV inverters in multiple operation stages through a distributed algorithm. To improve efficiency of the distributed algorithm, an affinity propagation clustering algorithm is employed to divide the distribution network by aggregating "the close nodes" together and setting "the far nodes" apart, leading to the network partition where the information exchange between adjacent sub-networks is reduced. Moreover, the virtual load which describes load characteristics of the sub-networks is applied to enhance the boundary conditions. To fully deal with the uncertainties, the proposed DAR-VVC is formulated in a robust optimization model which considers the worst case to guarantee solution robustness against uncertainty realization. Besides, this paper develops an alternating optimization procedure integrating a column-and-constraint generation algorithm and an alternating direction method of multipliers to solve the DAR-VVC problem. The proposed approach is tested on IEEE 33 and IEEE 123 bus distribution test system and numerical simulations verify high efficiency and full solution robustness of the DAR-VVC.

关键词： Uncertainty Optimization Voltage control Convex functions Inverters distributed algorithms Load modeling Affinity propagation clustering algorithm alternating optimization procedure distributed algorithm network partition robust optimization voltage VAR control

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distributed Separated-Decorrelation LMS algorithms Over Sensor Networks With Noisy Inputs

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2020年 68卷 4163-4177页

作者： Zhang, Sheng Zheng, Wei Xing Southwest Jiaotong Univ Sch Informat Sci & Technol Chengdu 611756 Peoples R China Western Sydney Univ Sch Comp Data & Math Sci Sydney NSW 2751 Australia

When the input is a highly correlated and noisy signal over sensor networks, it will lead to the severe performance degeneration of traditional distributed algorithms in terms of convergence rate and steady-state error. To tackle such an issue, this paper proposes distributed bias-compensated separated-decorrelation least mean-square (BC-SDLMS) algorithms. Due to the adoption of new separated-decorrelation structure and bias-compensated term, the steady-state mean-square error with the proposed algorithms can be reduced in comparison with the previous decorrelation schemes. The mean-square analysis is also carried out, which indicates that the proposed algorithms can converge to an unbiased solution. Moreover, an effective estimate for the noise variance at the input terminal of every node is designed. Finally, simulation comparisons are made between the proposed BC-SDLMS algorithms and the competing methods in terms of convergence rate and steady-state error for different colored and noisy inputs.

关键词： distributed algorithm separated decorrelation unbiased estimation adaptive filter

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Optimal algorithms for synchronous Byzantine k-set agreement

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THEORETICAL COMPUTER SCIENCE 2023年第1期973卷

作者： Delporte-Gallet, Carole Fauconnier, Hugues Raynal, Michel Safir, Mouna Univ Paris Cite IRIF Paris France Univ Rennes CNRS IRISA Inria F-35042 Rennes France Univ Mohammed VI Polytech UM6P CS Ben Guerir Morocco

This article is on k-set agreement (kSA) in an n-process synchronous message-passing system in which up to t processes can commit Byzantine failures. kSA is a decision problem in which at least each correct (i.e., non-Byzantine) process is assumed to propose and decide a value such that at most k different values are decided by the correct processes, in such a way that, if all the correct processes propose the same value v, they will decide v. This article investigates the possibility/impossibility domain of kSA in the presence of Byzantine processes. To this end it first extends a previous result and shows that kSA cannot be solved when (n < 2t + t/k) boolean AND (n - t >= k + 1). On the positive side, it presents two synchronous round-based algorithms that solve Byzantine kSA. These algorithms are optimal with respect to the value of k and the number of rounds. The first algorithm is a one-round algorithm that has two instances. The first assumes n > 2t + 1 and solves kSA for k >= [ n-t n-2t ] + 1, while the second assumes n <= 2t + 1 and solves kSA for k >= t +1 (so this second case does not require a majority of correct processes). The second algorithm is based on two new notions denoted Square and Regions that allow each correct process to locally build a global knowledge on which processes proposed which values. This algorithm has also two instances. The first assumes n = 3t and solves 2SA. The second assumes 2t + 1 < n <= 3t and solves kSA where k = n-t n-2t is an integer. It is worth noticing that the results presented in this article "almost" complete the possibility/impossibility cartography of kSA in synchronous Byzantine systems. The only case that remains open is when (n-t)/n-2t is not an integer.

关键词： Agreement problem Byzantine processes distributed algorithm distributed computability k-set agreement Message-passing Round-based algorithm Synchronous system

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