Searched for: subject%3A%22ADMM%22
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document
Zhai, P. (author), Rajan, R.T. (author)
Gaussian Process (GP) is a flexible non-parametric method which has a wide variety of applications e.g., field estimation using multi-agent systems. However, the training of the hyperparameters suffers from high computational complexity. Recently, distributed hyperparameter optimization with proximal gradients has been proposed to reduce...
conference paper 2023
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Feng, Cheng (author), Zheng, Kedi (author), Zhou, Yangze (author), Palensky, P. (author), Chen, Qixin (author)
With the proliferation of distributed energy resources (DERs), electricity consumers in virtual power plants (VPPs) are transitioning into prosumers and are encouraged to share surplus energy with peers. Nevertheless, large-scale energy sharing among thousands of prosumers may encounter communication-related challenges. Communication network...
journal article 2023
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Narasimhan, Adithya (author)
Electric vehicles are a fast-growing market in the automotive sector. In addition, the widespread use of renewable energy to power electric vehicles makes them sustainable, with considerably low greenhouse gas emissions. As a result, service providers are switching to fleets of electric vehicles to promote environmental sustainability. However,...
master thesis 2022
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Li, Qiongxiu (author), Heusdens, R. (author), Christensen, M.T. (author)
Privacy issues and communication cost are both major concerns in distributed optimization in networks. There is often a trade-off between them because the encryption methods used for privacy-preservation often require expensive communication overhead. To address these issues, we, in this paper, propose a quantization-based approach to achieve...
journal article 2022
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Orozco, Camilo (author), Borghetti, Alberto (author), De Schutter, B.H.K. (author), Napolitano, Fabio (author), Pulazza, Giorgia (author), Tossani, Fabio (author)
The paper presents a coordinated day-ahead and intra-day approach for the scheduling of the resources in a local energy community (LEC). The considered LEC consists of a collective of power prosumers that can directly trade energy with each other in addition to the external provider. The scheduling approach is based on the alternating...
journal article 2022
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Li, Qiongxiu (author), Lopuhaä-Zwakenberg, Milan (author), Heusdens, R. (author), Christensen, Mads Græsbøll (author)
Both communication overhead and privacy are main concerns in designing distributed computing algorithms. It is very challenging to address them simultaneously as encryption methods required for privacy-preservation often incur high communication costs. In this paper, we argue that there is a fundamental link between communication efficiency...
conference paper 2022
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Bosland, Liam (author)
A common problem in robotics is the simultaneous localization and mapping (SLAM) problem. Here, a robot needs to create a map of its surroundings while simultaneously localizing itself in this map. An unknown environment is assumed. Traditionally, it has been approached through filtering solutions. This paradigm has shifted to pose graph...
master thesis 2021
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Zhang, Jiadi (author)
In this thesis, the joint DOA-range estimation of stationary targets is investigated using multiple FMCW MIMOs with super-resolution capability. To address the low azimuth resolution problem of single small MIMO, a novel topology of array is used, which consists of multiple MIMOs arranged along the azimuth to increase azimuth resolution by...
master thesis 2019
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Luan, X. (author), De Schutter, B.H.K. (author), van den Boom, A.J.J. (author), Corman, F. (author), Lodewijks, G. (author)
We introduce a distributed optimization method for improving the computational efficiency of real-time traffic management approaches for large-scale railway networks. We first decompose the whole network into a pre-defined number of regions by using an integer linear optimization approach. For each resulting region, a mixed-integer linear...
journal article 2018
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Manss, C. (author), Shutin, Dmitriy (author), Leus, G.J.T. (author)
In processing spatially distributed data, multi-agent robotic platforms equipped with sensors and computing capabilities are gaining interest for applications in inhospitable environments. In this work an algorithm for a distributed realization of sparse bayesian learning (SBL) is discussed for learning a static spatial process with the...
conference paper 2018
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Telsang, B. (author), Navalkar, S.T. (author), van Wingerden, J.W. (author)
Nuclear norm based subspace identification methods have recently gained importance due to their ability to find low rank solutions while maintaining accuracy through convex optimization. However, their heavy computational burden typically precludes the use in an online, recursive manner, such as may be required for adaptive control. This...
conference paper 2017
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Telsang, B. (author)
The main contribution of this thesis is the development of an inherently adaptive controller which recursively implements a system identification and control routine. The main idea here, is that if system identification techniques can be made computationally light, and if they can be combined efficiently with a controller formulation, such a...
master thesis 2016
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Zhang, G. (author), Heusdens, R. (author)
Recently, the primal-dual method of multipliers (PDMM) has been proposed to solve a convex optimization problem defined over a general graph. In this paper, we consider simplifying PDMM for a subclass of the convex optimization problems. This subclass includes the consensus problem as a special form. By using algebra, we show that the update...
conference paper 2016
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Zhang, H.M. (author)
The Primal-Dual Method of Multipliers (PDMM) is a new algorithm that solves convex optimization problems in a distributed manner. This study focuses on the convergence behavior of the PDMM. For a deeper understanding, the PDMM algorithm was applied to distributed averaging and distributed dictionary learning problems. The results were compared...
master thesis 2015
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Lopes e Silva, J. (author)
We are currently facing an increasing amount of challenges in the area of photonics as more and more applications in need for active “photon control” sprout in different fields of science. Adaptive Optics (AO) is the subject which deals with measuring, reconstructing, and reshaping the phase of a photon wavefront in real-time and can, thus,...
master thesis 2014
Searched for: subject%3A%22ADMM%22
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