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检索条件"主题词=distributed algorithms"

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Cyber-Power Testbed for distributed Monitoring and Control

Cyber-Power Testbed for Distributed Monitoring and Control

引用

Workshop on Modeling and Simulation of Cyber-Physical Energy Systems (MSCPES) Held as Part of CPS Week

作者： Krishnan, V. V. G. Gopal, S. Nie, Z. Srivastava, A. Washington State Univ Sch Elect Engn & Comp Sci Pullman WA 99164 USA

ISBN: (纸本)9781538641057

The power grid is becoming increasingly complex with multi-domain and multi-physics interaction given enhanced automation, increasing DERs, active distribution system and push for resiliency. The centralized control for such a complex system will be slow, non-scalable and prone to failures. The local controllers for such system will be non-optimal, hard coded and not fault-tolerant. The preferred control architecture for such system will be distributed architecture as it is relatively fast, scalable and robust. The distributed architecture supports the power grid monitoring and control for enhanced resiliency and reliability, but need to be tested and validated before field implementation. This paper presents a cyber-power testbed architecture to validate distributed applications in the power grid. distributed Remedial Action Scheme (DRAS) algorithm is validated using the testbed as an example distributed control testcase. DRAS has been implemented using a distributed computing platform called Resilient Information Architecture Platform for Smart Grid (RIAPS). Developed cyber-power testbed utilizes Real Time Digital Simulator, Phasor Measurement Units and CISCO FOG routers with RIAPS platform. The testbed is validated through online simulations of IEEE 14-bus test system with distributed control under various cyber failures for satisfactory response.

关键词： Cyber-Physical Test Bed distributed algorithms Decentralized Control Remedial Action State Estimation

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Analyzing the Effect of Information Stagnancy on the distributed Stochastic Algorithm Extended Abstract 17

Analyzing the Effect of Information Stagnancy on the Distrib...

引用

17th International Conference on Autonomous Agents and MultiAgent Systems (AAMAS)

作者： SamadiDana, Saeid Mailler, Roger Univ Tulsa Tulsa OK 74104 USA

ISBN: (纸本)9781450356497

Despite the fact that many real world problems change over time, many distributed Constraint Optimization Problem (DCOP) algorithms assume that the problem is constant or changing at a negligible rate. In addition, these algorithms also assume that changes to the environment are instantaneously observable. However, in highly dynamic environments with communication delays, both of these assumptions can be violated resulting in problem solving with out-of-date information. In this study, we explore the relationship between environmental dynamics, information stagnancy, and solution quality in Dynamic DCOP problems. By using recent advances in the analysis of dynamic, distributed problems, we show that information stagnancy can be characterized and used to accurately predict the behavior of a protocol. To evaluate our finding, we use the distributed Stochastic Algorithm (DSA) as a basis. Through extensive empirical testing, we show that the prediction function is accurate.

关键词： DCOP Dynamic distributed algorithms Data Stagnancy Constraint Optimization Thermodynamics

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A distributed Adaptive Observer for Leader-Follower Networks

A Distributed Adaptive Observer for Leader-Follower Networks

引用

American Control Conference

作者： Daniel A. Burbano-L Randy A. Freeman Kevin M. Lynch New York University 6 MetroTech Center NY 11201 United States Northwestern University Evanston IL 60208-3118 United States Northwestern University Evanston IL 60208-3111 United States

ISBN: (纸本)9781538679012;9781538679265

We consider the problem of designing distributed algorithms that enable a group of agents (followers) to track a reference trajectory generated by a leader agent. Such algorithms are an integral part of a variety of distributed estimation and control techniques like the attitude control problem for spacecraft formation flying. Existing methods assume that the leader's reference dynamics are fully known to one or more follower agents, and they typically require significant amounts of inter-agent communication. In this paper, we propose a novel distributed adaptive observer in which no follower agent knows the leader's reference dynamics. In addition, our method does not require as much inter-agent communication as existing methods. We use appropriate Lyapunov functions to prove convergence, and we present numerical examples to demonstrate the efficacy of our approach.

关键词： Agents attitude control Formation flight Distribute dynamics Leaders Leadership Self tuning distributed algorithms Converge Communication Research

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Consensus based distributed algorithm for economic dispatch in power systems 14

Consensus based distributed algorithm for economic dispatch ...

引用

14th IEEE International Conference on Control and Automation (ICCA)

作者： Ma, Kai Yu, Yangqing Zhu, Shanying Yang, Jie Guan, Xinping Yanshan Univ Sch Elect Engn Qinhuangdao 066004 Hebei Peoples R China Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China Shanghai Jiao Tong Univ Minist Educ Key Lab Syst Control & Informat Proc Shanghai 200240 Peoples R China

ISBN: (纸本)9781538660898

In this paper, a distributed discrete-time algorithm is presented to solve the economic dispatch problem. We aim to search for the optimal power generations so that the total generation cost is minimized with the supply and demand reaching the balance. The iterative procedure is designed as gradient descent method in combination with a consensus process. Without a central unit, the generators in the power system need to work collaboratively and exchange local information according to the communication topology. Simulation studies are conducted on the IEEE 9 bus system to examine the effectiveness of the proposed algorithm. From the simulation results, we can observe that the proposed algorithm shows the validity and good convergence performance to seek the optimal solution. The balance between supply and demand can be achieved with increasing the economic benefits of the power system.

关键词： Economics Optimization distributed algorithms Generators Heuristic algorithms Power generation Power system stability"

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A distributed Algorithm for Achieving the Conservation Principle

A Distributed Algorithm for Achieving the Conservation Princ...

引用

American Control Conference

作者： Wang, Xuan Mou, Shaoshuai Purdue Univ Sch Aeronaut & Astronaut W Lafayette IN 47906 USA

ISBN: (纸本)9781538654286

A distributed and continuous update is proposed for multi-agent networks to achieve the conservation principle, in which each agent can only communicate with its nearby neighbors. The information known to each agent is part of the overall conservation constraint, which is determined by states of its neighbors. Different from achieving consensus, agents in the networks control states that might not necessarily be in the same dimension. Given the underlying network to be undirected and connected, the proposed update drives all agents' states to converge asymptotically to constants satisfying the nonlinear conservation principle, under mild assumptions. The assumption is relaxed when the conservation principle is linear, for which the convergence is exponentially fast. Both analytical results and numerical simulations are provided, followed by applications in achieving least square solutions in a distributed way.

关键词： Convergence Nickel distributed algorithms Resource management Manganese Numerical simulation Decentralized control"

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distributed Self-Adjusting Tree Networks

Distributed Self-Adjusting Tree Networks

引用

IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Bruna Peres Otavio A. de O. Souza Olga Goussevskaia Chen Avin Stefan Schmid UFMG Brazil BGU Israel University of Venna Austria

We consider the problem of designing dynamic network topologies that self-adjust to the (possibly changing) traffic pattern they serve. Such demand-aware networks currently receive much attention, especially in the context of datacenters, due to emerging technologies supporting the fast reconfiguration of the physical topology. We present the first fully distributed, provably efficient self-adjusting network. Our network called DiSptayNet relies on algorithms that perform decentralized and concurrent topological adjustments to account for changes in the demand. We present a rigorous formal analysis of the correctness and performance of DiSptayNet, which can be seen as an interesting generalization of analyses known from sequential self-adjusting datastructures. We also report on results from extensive trace-driven simulations.

关键词： Network topology Topology Peer-to-peer computing distributed algorithms Routing Upper bound Knowledge engineering

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A Randomized Block Subgradient Approach to distributed Big Data Optimization

A Randomized Block Subgradient Approach to Distributed Big D...

引用

IEEE Annual Conference on Decision and Control

作者： Francesco Farina Giuseppe Notarstefano Department of Electrical Electronic and Information Engineering “G. Marconi” Università di Bologna Bologna Italy

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

This paper introduces a novel distributed algorithm over static directed graphs for solving big data convex optimization problems in which the dimension of the decision variable can be extremely high and the objective function can be nonsmooth. In the proposed algorithm nodes in the network update and communicate only blocks of their current solution estimate rather than the entire vector. The algorithm consists of two main steps: a consensus step and a subgradient update on a single block of the optimization variable (which is then broadcast to neighbors). Agents are shown to asymptotically achieve consensus by studying a block-wise consensus protocol over random graphs. Then convergence to the optimal cost is proven in expected value by exploiting the consensus of agents estimates and randomness of the algorithm. Finally, as a numerical example, a distributed linear classification problem is solved by means of the proposed algorithm.

关键词： Optimization Linear programming Stochastic processes Big Data Convergence distributed algorithms Convex functions

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N-Dimensional distributed Network Localization with Noisy Range Measurements and Arbitrary Anchor Placement

N-Dimensional Distributed Network Localization with Noisy Ra...

引用

American Control Conference

作者： Pedro P. V. Tecchio Nikolay Atanasov Shahin Shahrampour George J. Pappas University of Pennsylvania Philadelphia PA 19104 University of California San Diego CA 92093 Texas A&M University College Station TX 77843

ISBN: (纸本)9781538679012;9781538679265

This work presents a distributed algorithm for node localization problems in static sensor networks in n-dimensions. We focus on networks in which n + 1 nodes with known locations (anchors) are arbitrarily placed among all other nodes with unknown locations. In the noiseless case, barycentric coordinates computed from range measurements are used to transform the non-convex node localization problem into a standard linear system of equations. Meanwhile, adding independent zero mean Gaussian noise to range measurements turns all barycentric coordinates to dependent random variables with no known standard distribution which may not even be identically distributed. Relying on online optimization methods, we provide a distributed online gradient descent algorithm to solve the noisy range-only localization problem. Finally, comparisons among simple barycentric coordinate averaging, a centralized gradient descent formulation and our distributed algorithm are provided.

关键词： Ranging measurements distributed algorithms Centrobaric Sensor networks Random variable Boat anchors distributed NETWORKS Linear system Coordinates Linear system of equations

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A distributed HALS Algorithm for Euclidean Distance-Based Nonnegative Matrix Factorization

A Distributed HALS Algorithm for Euclidean Distance-Based No...

引用

IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Yohei Domen Tsuyoshi Migita Norikazu Takahashi Graduate School of Natural Science and Technology Okayama University Okayama Japan

ISBN: (数字)9781728124858

ISBN: (纸本)9781728124865

This paper proposes a distributed algorithm for multiple agents to perform the Nonnegative Matrix Factorization (NMF) based on the Euclidean distance. The matrix to be factorized is partitioned into multiple blocks, and each block is assigned to one of the agents forming a two-dimensional grid network. Each agent handles a small number of entries of the factor matrices corresponding to the assigned block, and updates their values by using information coming from the neighbors. It is shown that the proposed algorithm simulates the hierarchical alternating least squares method, which is well known as a fast algorithm for NMF based on the Euclidean distance, by making use of a finite-time distributed consensus algorithm.

关键词： Signal processing algorithms Euclidean distance Optimization Matrix decomposition Partitioning algorithms distributed algorithms Nickel

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Optimal Opponent Selection for distributed Multi-Agent Self-Classification

Optimal Opponent Selection for Distributed Multi-Agent Self-...

引用

IEEE Global Conference on Communications (GLOBECOM) / Workshop on Wireless Networking and Control for UAV

作者： Zou, Hang Nait-Belaid, Youba Kieffer, Michel Univ Paris Saclay Univ Paris Sud Cent Supelec L2SCNRS 3 Rue Joliot Curie F-91192 Gif Sur Yvette France

ISBN: (纸本)9781538647271

This paper considers a mobile multi-agent system (e.g., a crowdsensing or crowdsourcing application) in which agents are characterized by their discrete-valued Level of Ability (LoA) at doing some sensing or data processing task. Agents are not aware of their LoA and are willing to estimate it without the help of a central classification authority, in order to determine whether their contribution will improve or degrade the performance of the global network. Using their estimated LoA, agents may then voluntarily restrain themselves to participate to the activity of the multi-agent system, without being banned by some central control authority. For that purpose, agents, when they meet, perform pairwise comparison tests (PCT) able to determine which is the best agent of a pair of competing agents. Two maximum a posteriori (MAP) estimators of the LoA of each agent are proposed using the results of several PCTs. These MAP estimators are then employed to determine, for a given agent, the LoA of the next opponent that minimizes its probability of LoA estimation error. Simulations results show that the proposed optimal opponent selection approach provides better results than simply choosing opponents at random, or always choosing the opponents with the best LoA.

关键词： distributed algorithms Estimation Multi-agent systems

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