52nd IEEE Conference on Decision and Control最新文献_第6页

Coordinated output regulation of multiple heterogeneous linear systems 多非均匀线性系统的协调输出调节

52nd IEEE Conference on Decision and Control Pub Date : 2013-12-01 DOI: 10.1109/CDC.2013.6760204

Ziyang Meng, Tao Yang, Dimos V. Dimarogonas, K. Johansson

引用次数: 28

Multi-agent differential graphical games: Nash online adaptive learning solutions 多智能体微分图形游戏:纳什在线自适应学习解决方案

52nd IEEE Conference on Decision and Control Pub Date : 2013-12-01 DOI: 10.1109/CDC.2013.6760804

M. Abouheaf, F. Lewis

引用次数: 29

Periodic behaviors in multi-agent systems with input saturation constraints 具有输入饱和约束的多智能体系统的周期行为

52nd IEEE Conference on Decision and Control Pub Date : 2013-12-01 DOI: 10.1109/CDC.2013.6760577

Tao Yang, Ziyang Meng, Dimos V. Dimarogonas, K. Johansson

引用次数: 4

State estimation under quantized measurements: A Sigma-Point Bayesian approach 量子化测量下的状态估计:西格玛点贝叶斯方法

52nd IEEE Conference on Decision and Control Pub Date : 2013-12-01 DOI: 10.1109/CDC.2013.6760677

C. Manes, F. Martinelli

引用次数: 7

Local voting protocol in decentralized load balancing problem with switched topology, noise, and delays 具有交换拓扑、噪声和延迟的分散负载平衡中的本地投票协议问题

52nd IEEE Conference on Decision and Control Pub Date : 2013-12-01 DOI: 10.1109/CDC.2013.6760611

N. Amelina, O. Granichin, Aleksandra Kornivetc

{"title":"Local voting protocol in decentralized load balancing problem with switched topology, noise, and delays","authors":"N. Amelina, O. Granichin, Aleksandra Kornivetc","doi":"10.1109/CDC.2013.6760611","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760611","url":null,"abstract":"In this paper the applicability of the local voting protocol with nonvanishing step-size for decentralized stochastic network load balancing is studied under nonstationary problem formulation. The network system was considered to have a switched topology, and the control strategy uses noisy and delayed measurements. Nonvanishing (for example, constant) step-size allows to achieve the better convergence rate and copes with time-varying loads and productivities of agents (nodes). Conditions for achieving a suboptimal level of loading agents are established, and an estimate of the appropriate level of suboptimality is given depending on the step-size of the control algorithm, the structure of the averaged network and the statistical properties of noise and delays in measurements. Obtained theoretical results are illustrated by simulations of simultaneously processing of 106 tasks by 1024 agents with 2048 links. It is examined that the performance of the adaptive multi-agent strategy with redistribution of tasks among “connected” neighbors is significantly better than the performance of the strategy without redistribution.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125056877","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 20

Robust modeling of probabilistic uncertainty in smart Grids: Data ambiguous Chance Constrained Optimum Power Flow 智能电网中概率不确定性的鲁棒建模:数据模糊机会约束的最优潮流

52nd IEEE Conference on Decision and Control Pub Date : 2013-12-01 DOI: 10.1109/CDC.2013.6760556

D. Bienstock, M. Chertkov, S. Harnett

{"title":"Robust modeling of probabilistic uncertainty in smart Grids: Data ambiguous Chance Constrained Optimum Power Flow","authors":"D. Bienstock, M. Chertkov, S. Harnett","doi":"10.1109/CDC.2013.6760556","DOIUrl":"https://doi.org/10.1109/CDC.2013.6760556","url":null,"abstract":"Future Grids will integrate time-intermittent renewables and demand response whose fluctuating outputs will create perturbations requiring probabilistic measures of resilience. When smart but uncontrollable resources fluctuate, Optimum Power Flow (OPF), routinely used by the electric power industry to dispatch controllable generation over control areas of transmission networks, can result in higher risks. Our Chance Constrained (CC) OPF corrects the problem and mitigates dangerous fluctuations with minimal changes in the current operational procedure. Assuming availability of a reliable forecast parameterizing the distribution function of the uncertain resources, our CC-OPF satisfies all the constraints with high probability while simultaneously minimizing the cost of economic dispatch. For linear (DC) modeling of power flows, and parametrization of the uncertainty through Gaussian distribution functions the CC-OPF turns into convex (conic) optimization, which allows efficient and scalable cutting-plane implementation. When estimates of the Gaussian parameters are imprecise we robustify CC-OPF deriving its data ambiguous and still scalable implementation.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"173 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125794938","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11

New convergence and exact performance results for linear consensus algorithms using relative entropy and lossless passivity properties 利用相对熵和无损被动特性的线性一致性算法得到了新的收敛性和精确的性能结果

52nd IEEE Conference on Decision and Control Pub Date : 2013-12-01 DOI: 10.1109/CDC.2013.6761039

H. Mangesius

{"title":"New convergence and exact performance results for linear consensus algorithms using relative entropy and lossless passivity properties","authors":"H. Mangesius","doi":"10.1109/CDC.2013.6761039","DOIUrl":"https://doi.org/10.1109/CDC.2013.6761039","url":null,"abstract":"Despite the importance of the linear consensus algorithm for networked systems, yet, there is no agreement on the intrinsic mathematical structure that supports the observed exponential averaging behavior among n agents for any initial condition. Here we add to this discussion in linear consensus theory by introducing relative entropy as a novel Lyapunov function. We show that the configuration space of consensus systems is isometrically embedded into a statistical manifold. On projective n-1-space relative entropy is a common time-invariant Lyapunov function along solutions of the time-varying algorithm. For cases of scaled symmetry of the update law, we expose a gradient flow structure underlying the dynamics that evolve relative entropy in a steepest descent gradient scheme. On that basis we provide exact performance rates and upper bounds based on spectral properties of the update law governing the behavior on the statistical manifold. The condition of scaled symmetry allows to exhibit gradient flow structures for cases where the original update law is neither doubly stochastic, nor self-adjoint. The results related to the gradient flow structure are obtained by exploiting lossless passivity properties.We show that lossless passivity of a dynamical system implies a gradient flow structure on a manifold and vice versa. Exploiting lossless passivity amounts to constructing the combination of dissipation (pseudo)metric with Lyapunov function.","PeriodicalId":415568,"journal":{"name":"52nd IEEE Conference on Decision and Control","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123506284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Computation time analysis of a distributed optimization algorithm applied to automated irrigation networks 一种用于自动化灌溉网络的分布式优化算法的计算时间分析

52nd IEEE Conference on Decision and Control Pub Date : 2013-12-01 DOI: 10.1109/CDC.2013.6760207

A. Farhadi, M. Cantoni, P. Dower

引用次数: 4

Energy-efficient data collection in heterogeneous wireless sensor and actor networks 异构无线传感器和行动者网络中的节能数据采集

52nd IEEE Conference on Decision and Control Pub Date : 2013-12-01 DOI: 10.1109/CDC.2013.6760528

W. Abbas, H. Jaleel, M. Egerstedt

引用次数: 4

Reduced-order observers for nonlinear sampled-data systems with application to marine systems 非线性采样数据系统的降阶观测器及其在船舶系统中的应用

52nd IEEE Conference on Decision and Control Pub Date : 2013-12-01 DOI: 10.1109/CDC.2013.6760685

H. Katayama, Hirotaka Aoki

引用次数: 12