A control-theoretic approach to distributed optimization
分布式优化的控制理论方法
基本信息
- 批准号:1936648
- 负责人:
- 金额:$ 38万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2019
- 资助国家:美国
- 起止时间:2019-09-15 至 2021-08-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Optimization arises naturally in a variety of areas, such as managing wireless spectrum utilization, efficiently distributing power in the electrical grid, or solving machine learning problems. The scale of such applications has been steadily growing, often forcing data to be processed in different physical locations linked via a communication network. The ensuing computational task is mediated by distributed optimization algorithms that carefully orchestrate a combination of local computations and global synchronization with the other computing nodes. These distributed algorithms are critical in ensuring the safety, reliability, efficiency, and performance of large-scale systems. This project aims to develop a systematic approach for analyzing and designing such distributed algorithms. This project will view distributed optimization algorithms as dynamical systems with feedback; decisions made at a given time affect the state of the system at future times, and therefore affect future decisions, and so on. The advantage of this viewpoint is that it allows one to leverage tools and methodology from control theory, which is a well established engineering discipline used in the design of modern safety-critical systems such as aircraft, automobiles, and industrial plants. Applying these sophisticated tools to distributed optimization algorithms will allow us to move away from conventional incremental design methods and has the potential to be highly transformative. It will lead to better distributed algorithms, but also more principled and automated design methods that can allow algorithms to be directly synthesized and specialized for the task at hand.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
优化自然会出现在各种领域,例如管理无线频谱利用率,有效地分配电网中的电力,或解决机器学习问题。这些应用的规模一直在稳步增长,往往迫使数据在通过通信网络连接的不同物理位置进行处理。随后的计算任务由分布式优化算法介导,所述分布式优化算法仔细地协调本地计算和与其他计算节点的全局同步的组合。这些分布式算法对于确保大规模系统的安全性、可靠性、效率和性能至关重要。该项目旨在开发一种系统的方法来分析和设计此类分布式算法。这个项目将分布式优化算法视为具有反馈的动态系统;在给定时间做出的决策会影响系统在未来时间的状态,从而影响未来的决策,等等。这种观点的优点是,它允许人们利用控制理论的工具和方法,这是一种在现代安全关键系统(例如飞机、汽车和工业设备)的设计中使用的成熟的工程学科。将这些复杂的工具应用于分布式优化算法将使我们能够摆脱传统的增量设计方法,并具有高度变革的潜力。它将带来更好的分布式算法,但也会带来更有原则和自动化的设计方法,可以允许算法直接合成并专门用于手头的任务。该奖项反映了NSF的法定使命,并被认为值得通过使用基金会的评估来支持智力优点和更广泛的影响审查标准。
项目成果
期刊论文数量(2)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Systematic Analysis of Distributed Optimization Algorithms over Jointly-Connected Networks
- DOI:10.1109/cdc42340.2020.9303998
- 发表时间:2020-03
- 期刊:
- 影响因子:0
- 作者:Bryan Van Scoy;Laurent Lessard
- 通讯作者:Bryan Van Scoy;Laurent Lessard
Analysis and Design of First-Order Distributed Optimization Algorithms Over Time-Varying Graphs
- DOI:10.1109/tcns.2020.2988009
- 发表时间:2019-07
- 期刊:
- 影响因子:4.2
- 作者:Akhil Sundararajan;Bryan Van Scoy;Laurent Lessard
- 通讯作者:Akhil Sundararajan;Bryan Van Scoy;Laurent Lessard
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Laurent Lessard其他文献
NUCLEAR FACTOR-κB CYTOPLASMATIC STAINING INTENSITY IS AN INDEPENDENT PREDICTOR OF BIOCHEMICAL RECURRENCE AFTER RADICAL PROSTATECTOMY FOR CLINICALLY LOCALIZED PROSTATE CANCER
- DOI:
10.1016/s0022-5347(09)62148-0 - 发表时间:
2009-04-01 - 期刊:
- 影响因子:
- 作者:
Hendrik Isbarn;Laurent Lessard;Pierre I Karakiewicz;Thorsten Schlomm;Hartwig Huland;Guido Sauter;Jens Köllermann;Hans Heinzer;Markus Graefen;Fred Saad - 通讯作者:
Fred Saad
1093: NFKB Expression Predicts Biochemical Recurrence in Patients with Positive Margin Prostate Cancer
- DOI:
10.1016/s0022-5347(18)38330-7 - 发表时间:
2004-04-01 - 期刊:
- 影响因子:
- 作者:
Vincent Fradet;Laurent Lessard;Anne-Marie Mes-Masson;Louis R. Begin;Paul Perrotte;Pierre I. Karakiewicz;Fred Saad - 通讯作者:
Fred Saad
LARGE-SCALE VALIDATION OF NF-kB p65 AS A PROSTATE CANCER PROGNOSTIC MARKER
- DOI:
10.1016/s0022-5347(08)62059-5 - 发表时间:
2008-04-01 - 期刊:
- 影响因子:
- 作者:
Laurent Lessard;Louis R Begin;Thorsten Schlomm;Jens Kollermenn;Markus Graefen;Pierre I Karakiewicz;Anne-Marie Mes-Masson;Fred Saad - 通讯作者:
Fred Saad
Optimal control of a fully decentralized quadratic regulator
- DOI:
10.1109/allerton.2012.6483198 - 发表时间:
2012-10 - 期刊:
- 影响因子:0
- 作者:
Laurent Lessard - 通讯作者:
Laurent Lessard
Performance certification of interconnected nonlinear systems using ADMM
使用 ADMM 互连非线性系统的性能认证
- DOI:
- 发表时间:
2014 - 期刊:
- 影响因子:0
- 作者:
Chris Meissen;Laurent Lessard;M. Arcak;A. Packard - 通讯作者:
A. Packard
Laurent Lessard的其他文献
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{{ truncateString('Laurent Lessard', 18)}}的其他基金
CAREER: Automated Analysis and Design of Optimization Algorithms
职业:优化算法的自动分析和设计
- 批准号:
2136945 - 财政年份:2021
- 资助金额:
$ 38万 - 项目类别:
Continuing Grant
A control-theoretic approach to distributed optimization
分布式优化的控制理论方法
- 批准号:
2139482 - 财政年份:2021
- 资助金额:
$ 38万 - 项目类别:
Standard Grant
Analysis and design of decentralized control systems in the presence of uncertain latency or system parameters
存在不确定延迟或系统参数的分散控制系统的分析和设计
- 批准号:
2136317 - 财政年份:2020
- 资助金额:
$ 38万 - 项目类别:
Standard Grant
CAREER: Automated Analysis and Design of Optimization Algorithms
职业:优化算法的自动分析和设计
- 批准号:
1750162 - 财政年份:2018
- 资助金额:
$ 38万 - 项目类别:
Continuing Grant
CRII: CIF: Universal Analysis of Optimization Algorithms
CRII:CIF:优化算法的通用分析
- 批准号:
1656951 - 财政年份:2017
- 资助金额:
$ 38万 - 项目类别:
Standard Grant
Analysis and design of decentralized control systems in the presence of uncertain latency or system parameters
存在不确定延迟或系统参数的分散控制系统的分析和设计
- 批准号:
1710892 - 财政年份:2017
- 资助金额:
$ 38万 - 项目类别:
Standard Grant
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A control-theoretic approach to distributed optimization
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