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检索条件"主题词=distributed algorithms"

共 6170 条记录，以下是1571-1580 订阅

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distributed reconfigurable formation generator for Mini Aerial Vehicles

Distributed reconfigurable formation generator for Mini Aeri...

引用

25th IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Brinon-Arranz, Lara Muschinowski, Matthieu Dumon, Jonathan Marchand, Nicolas Univ Grenoble Alpes CNRS Grenoble INP GIPSA Lab Grenoble France

ISBN: (纸本)9781538680940

This video presents a distributed trajectory generator for formation control of multi-robot systems. The desired formation is defined by its geometric parameters but the position of each robot in the formation is not predefined a priori. The contribution is the design of a distributed algorithm to compute the robots' positions with respect to a given target while maintaining a particular formation which can be reconfigured on-line. A tracking controller ensures the convergence of the robots to their desired positions.

关键词： Generators Intelligent robots Trajectory Multi-robot systems distributed algorithms

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distributed algorithm for solving linear algebraic equations: An implicit gradient neural network approach

Distributed algorithm for solving linear algebraic equations...

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Control Technology and Applications (CCTA),

作者： Peijun Wang Wenwu Yu Guanghui Wen School of Mathematics Southeast University Nanjing China

This brief investigates the online solving problem for linear algebraic equation Ax = b by means of the principle of consensus in multi-agent systems, where A ∈ ℝ m×n and b ∈ Rn. To be specific, we choose m autonomous agents and agent i knows only the i-th row of [A b] under a fixed and connected undirected communication topology. Under local interactions, by designing an implicit gradient neural network based algorithm, it is shown that all the agents' states which starting from any different initial conditions can converge exponentially fast to one of the solutions to Ax = b, if the matrix A has full row rank. It is worth noting that the proposed algorithm is fully distributed. In addition, it is shown that the proposed algorithm is effective in obtaining least square solutions for no-solution cases. Finally, computer simulations verify and demonstrate the efficiency of the proposed methods for solving linear algebraic equations.

关键词： Mathematical model Neural networks Signal processing algorithms Convergence distributed algorithms Heuristic algorithms Iterative methods

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distributed Evolutionary Games Reaching Power Indexes: Navigability in a Social Network of Smart Objects 16

Distributed Evolutionary Games Reaching Power Indexes: Navig...

引用

European Control Conference (ECC)

作者： Barreiro-Gomez, Julian Tembine, Hamidou NYUAD Learning & Game Theory Lab Saadiyat CampusPOB 129188 Abu Dhabi U Arab Emirates

ISBN: (纸本)9783952426982

In the context of coalitional games, a power index allows to determine the magnitude of contributions associated to each player, i.e., a power index provides information about how influential or relevant a player is in a cooperative interaction. Nevertheless, if the number of involved players is big, then the computation of a power index might become intractable. In this paper, we show how to construct a full-potential game whose Nash equilibrium coincides with the Shapley or Banzhaf power index for a family of characteristic functions. Therefore, distributed non-cooperative algorithms can be used for cooperative-game purposes. As a consequence, both the computational time and the information requirements are reduced, allowing the use of power indexes in large-scale systems. As an illustrative example, we present a large-scale social network of smart objects where it is desired to enhance the navigability by means of local decisions.

关键词： Power indexes Nash equilibrium distributed algorithms large-scale systems

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Cyber-Power Testbed for distributed Monitoring and Control

Cyber-Power Testbed for Distributed Monitoring and Control

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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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distributed Average Consensus under Quantized Communication via Event-Triggered Mass Summation 57

Distributed Average Consensus under Quantized Communication ...

引用

57th IEEE Conference on Decision and Control (CDC)

作者： Rikos, Apostolos I. Hadjicostis, Christoforos N. Univ Cyprus Dept Elect & Comp Engn Nicosia Cyprus

ISBN: (纸本)9781538613955

The goal of distributed average consensus in multi-agent systems is for the nodes, each associated with some initial value, to obtain the average (or some value close to the average) of these initial values. In this paper, we present and analyze a distributed averaging algorithm which operates exclusively on quantized values (specifically, the information stored, processed and exchanged between neighboring agents is subject to deterministic uniform quantization) and relies on event-driven updates (e.g., to reduce energy consumption, communication bandwidth, network congestion, and/or processor usage). We characterize the properties of the proposed distributed averaging protocol and show that its execution, on any time-invariant and strongly connected digraph, will allow all agents to reach, in finite time, a common consensus value represented as the ratio of two integers that is equal to the exact average. We conclude with examples that illustrate the operation, performance, and potential advantages of the proposed algorithm.

关键词： Quantized average consensus event-triggered distributed algorithms quantization digraphs multi-agent systems

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distributed Cost-Optimized Placement for Latency-Critical Applications in Heterogeneous Environments 15

Distributed Cost-Optimized Placement for Latency-Critical Ap...

引用

15th IEEE International Conference on Autonomic Computing (ICAC)

作者： Mehta, Amardeep Elmroth, Erik Umea Univ Dept Comp Sci Umea Sweden

ISBN: (纸本)9781538651391

Mobile Edge Clouds (MECs) with 5G will create new opportunities to develop latency-critical applications in domains such as intelligent transportation systems, process automation, and smart grids. However, it is not clear how one can cost-efficiently deploy and manage a large number of such applications given the heterogeneity of devices, application performance requirements, and workloads. This work explores cost and performance dynamics for IoT applications, and proposes distributed algorithms for automatic deployment of IoT applications in heterogeneous environments. Placement algorithms were evaluated with respect to metrics including number of required runtimes, applications' slowdown, and the number of iterations used to place an application. Iterative search-based distributed algorithms such as Size Interval Actor Assignment in Groups (SIAA_G) outperformed random and bin packing algorithms, and are therefore recommended for this purpose. Size Interval Actor Assignment in Groups at Least Utilized Runtime (SIAA_G_LUR) algorithm is also recommended when minimizing the number of iterations is important. The tradeoff of using SIAA_G algorithms is a few extra runtimes compared to bin packing algorithms.

关键词： Mobile Edge Clouds Fog Computing IoTs distributed algorithms

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A fast network-decomposition algorithm and its applications to constant-time distributed computation 1

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22nd International Colloquium on Structural Information and Communication Complexity (SIROCCO)

作者： Barenboim, Leonid Elkin, Michael Gavoille, Cyril Open Univ Israel Raanana Israel Ben Gurion Univ Negev Beer Sheva Israel Univ Bordeaux LaBRI Bordeaux France

ISBN: (数字)9783319252582

ISBN: (纸本)9783319252575

A partition (C-1, C-2, . . . ,C-q) of G = (V, E) into clusters of strong (respectively, weak) diameter d, such that the supergraph obtained by contracting each C-i is l-colorable is called a strong (resp., weak) (d, l)-network-decomposition. Network-decompositions were introduced in a seminal paper by Awerbuch, Goldberg, Luby and Plotkin in 1989. Awerbuch et al. showed that strong (d, l)-network-decompositions with d = l = exp {O(root logn log logn)} can be computed in distributed deterministic time O(d). Even more importantly, they demonstrated that network-decompositions can be used for a great variety of applications in the message-passing model of distributed computing. The result of Awerbuch et al. was improved by Panconesi and Srinivasan in 1992: in the latter result d = l = exp{O(root logn)}, and the running time is O(d) as well. In another remarkable breakthrough Linial and Saks (in 1992) showed that weak (O(logn), O(logn))-network-decompositions can be computed in distributed randomized time O(log(2)n). Much more recently Barenboim (2012) devised a distributed randomized constant-time algorithm for computing strong network decompositions with d = O(1). However, the parameter l in his result is O (n(1/2+epsilon)). In this paper we drastically improve the result of Barenboim and devise a distributed randomized constant-time algorithm for computing strong (O(1), O(n(epsilon)))-network-decompositions. As a corollary we derive a constant-time randomized O(n(epsilon))-approximation algorithm for the distributed minimum coloring problem, improving the previously bestknown O(n(1/2+epsilon)) approximation guarantee. We also derive other improved distributed algorithms for a variety of problems. Most notably, for the extremely well-studied distributed minimum dominating set problem currently there is no known deterministic polylogarithmic-time algorithm. We devise a deterministic polylogarithmic-time approximation algorithm for this problem, addressing an open proble

关键词： distributed algorithms Local algorithms Dominating sets Coloring Spanners

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A distributed Adaptive Observer for Leader-Follower Networks

A Distributed Adaptive Observer for Leader-Follower Networks

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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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Asynchronous distributed Optimization via Dual Decomposition and Block Coordinate Ascent

Asynchronous Distributed Optimization via Dual Decomposition...

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IEEE Annual Conference on Decision and Control

作者： Yankai Lin Iman Shames Dragan Nesic Department of Electrical and Electronic Engineering The University of Melbourne Parkville Victoria Australia

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

We study a class of distributed optimization problems of minimizing the sum of potentially non-differentiable convex objective functions (without requiring strong convexity). A novel approach to the analysis of asynchronous distributed optimization is developed. An iterative algorithm based on dual decomposition and block coordinate ascent is implemented in an edge based manner. We extend available results in the literature by allowing multiple and potentially overlapping blocks to be updated at the same time with non-uniform probabilities assigned to different blocks. Sublinear convergence with probability one is proved for the algorithm under the aforementioned weak assumptions. A numerical example is provided to illustrate the effectiveness of the algorithm.

关键词： Optimization Linear programming Convergence distributed algorithms Communication networks Program processors Stochastic processes

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A Differentially Private distributed Solution Approach to the Model Predictive Control of Building Clusters 57

A Differentially Private Distributed Solution Approach to th...

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57th IEEE Conference on Decision and Control (CDC)

作者： Xiao, Yingying Hou, Xiaodong Cai, Jie Hu, Jianghai Purdue Univ Sch Elect & Comp Engn W Lafayette IN 47907 USA Univ Oklahoma Sch Aerosp & Mech Engn Norman OK 73019 USA

ISBN: (纸本)9781538613955

Coordinated control of a cluster of buildings can lead to reduced energy usage and demand charge. However, it requires individual buildings to share local data, e.g., their energy demands. The leak of such data could potentially be used by third parties to infer sensitive information such as occupancy that could be used to the detriment of building occupants. In this paper, using the notion of differential privacy, a distributed algorithm based on the Alternating Direction Method of Multiplier (ADMM) algorithm is proposed for the coordinated control of building clusters that can provide guaranteed levels of privacy for individual buildings by adding noises to the data being exchanged. Theoretical bounds on the strength of noises needed to achieve given privacy levels are derived, and the performance suboptimality caused by the added noise is demonstrated through simulations.

关键词： Buildings Differential privacy Privacy Optimization Cooling distributed algorithms

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