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Erratum to “An adaptive controller for nonlinear teleoperators” [Automatica 46 (2010) 155–159]

Automatica 2011年第5期47卷 1093-1094页

作者： Emmanuel Nuño Romeo Ortega Luis Basañez Department of Computer Science CUCEI University of Guadalajara Guadalajara Mexico Laboratoire des Signaux et Systèmes SUPÉLEC Gif-sur-Yvette France Institute of Industrial and Control Engineering Technical University of Catalonia Barcelona Spain

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Distributed Optimization via Gradient Descent with Event-Triggered Zooming over Quantized Communication

arXiv

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arXiv 2023年

作者： Rikos, Apostolos I. Jiang, Wei Charalambous, Themistoklis Johansson, Karl H. The Department of Electrical and Computer Engineering Division of Systems Engineering Boston University BostonMA02215 United States Hong Kong The Department of Electrical and Computer Engineering School of Engineering University of Cyprus Nicosia1678 Cyprus The Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland The Division of Decision and Control Systems KTH Royal Institute of Technology StockholmSE-100 44 Sweden

In this paper, we study unconstrained distributed optimization strongly convex problems, in which the exchange of information in the network is captured by a directed graph topology over digital channels that have limited capacity (and hence information should be quantized). Distributed methods in which nodes use quantized communication yield a solution at the proximity of the optimal solution, hence reaching an error floor that depends on the quantization level used;the finer the quantization the lower the error floor. However, it is not possible to determine in advance the optimal quantization level that ensures specific performance guarantees (such as achieving an error floor below a predefined threshold). Choosing a very small quantization level that would guarantee the desired performance, requires information packets of very large size, which is not desirable (could increase the probability of packet losses, increase delays, etc) and often not feasible due to the limited capacity of the channels available. In order to obtain a communication-efficient distributed solution and a sufficiently close proximity to the optimal solution, we propose a quantized distributed optimization algorithm that converges in a finite number of steps and is able to adjust the quantization level accordingly. The proposed solution uses a finite-time distributed optimization protocol to find a solution to the problem for a given quantization level in a finite number of steps and keeps refining the quantization level until the difference in the solution between two successive solutions with different quantization levels is below a certain pre-specified threshold. Therefore, the proposed algorithm progressively refines the quantization level, thus eventually achieving low error floor with a reduced communication burden. The performance gains of the proposed algorithm are demonstrated via illustrative examples. © 2023, CC BY.

关键词： Directed graphs

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Optimal CPU scheduling in data centers via a finite-time distributed quantized coordination mechanism

arXiv

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arXiv 2021年

作者： Rikos, Apostolos I. Grammenos, Andreas Kalyvianaki, Evangelia Hadjicostis, Christoforos N. Charalambous, Themistoklis Johansson, Karl H. Division of Decision and Control Systems KTH Royal Institute of Technology StockholmSE-100 44 Sweden Department of Computer Science and Technology University of Cambridge Cambridge United Kingdom Alan Turing Institute London United Kingdom Department of Electrical and Computer Engineering University of Cyprus Nicosia1678 Cyprus Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo02150 Finland

In this paper we analyze the problem of optimal task scheduling for data centers. Given the available resources and tasks, we propose a fast distributed iterative algorithm which operates over a large scale network of nodes and allows each of the interconnected nodes to reach agreement to an optimal solution in a finite number of time steps. More specifically, the algorithm (i) is guaranteed to converge to the exact optimal scheduling plan in a finite number of time steps and, (ii) once the goal of task scheduling is achieved, it exhibits distributed stopping capabilities (i.e., it allows the nodes to distributely determine whether they can terminate the operation of the algorithm). Furthermore, the proposed algorithm operates exclusively with quantized values (i.e., 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 also provide examples to illustrate the operation, performance, and potential advantages of the proposed algorithm. Finally, by using extensive empirical evaluations through simulations we show that the proposed algorithm exhibits state-of-the-art performance. Copyright © 2021, The Authors. All rights reserved.

关键词： Multitasking

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Risk-Averse Learning with Non-Stationary Distributions

arXiv

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arXiv 2024年

作者： Wang, Siyi Wang, Zifan Yi, Xinlei Zavlanos, Michael M. Johansson, Karl H. Hirche, Sandra Department of Electrical and Computer Engineering Technical University of Munich Munich80333 Germany Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden Lab for Information & Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States Mechanical Engineering and Material Science Duke University DurhamNC27708 United States

Considering non-stationary environments in online optimization enables decision-maker to effectively adapt to changes and improve its performance over time. In such cases, it is favorable to adopt a strategy that minimizes the negative impact of change to avoid potentially risky situations. In this paper, we investigate risk-averse online optimization where the distribution of the random cost changes over time. We minimize risk-averse objective function using the Conditional Value at Risk (CVaR) as risk measure. Due to the difficulty in obtaining the exact CVaR gradient, we employ a zeroth-order optimization approach that queries the cost function values multiple times at each iteration and estimates the CVaR gradient using the sampled values. To facilitate the regret analysis, we use a variation metric based on Wasserstein distance to capture time-varying distributions. Given that the distribution variation is sub-linear in the total number of episodes, we show that our designed learning algorithm achieves sub-linear dynamic regret with high probability for both convex and strongly convex functions. Moreover, theoretical results suggest that increasing the number of samples leads to a reduction in the dynamic regret bounds until the sampling number reaches a specific limit. Finally, we provide numerical experiments of dynamic pricing in a parking lot to illustrate the efficacy of the designed algorithm. Copyright © 2024, The Authors. All rights reserved.

关键词： Learning algorithms

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Nuclear Human research development in National institutes of Technology

Nuclear Human research development in National Institutes of...

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International Conference on engineering Education (ICEED)

作者： Seiji Kino Eiji Takada Hideki Tenzou Fumito Sakamoto Atsushi Minoda Shigekazu Suzuki Seiki Saito Itaru Nakamura Chisato Mouri Yasuo Ohta National Institute of Technology Japan Executive Director Tokyo Japan Dept. of Electrical and Control Systems Engineering National Institute of Technology Toyama Japan Dept. of Electronic Systems Engineering National Institute of Technology Mitoyo Japan Dept. of Electrical and Computer Engineering National Institute of Technology Akita Japan Dept. of Electrical Engineering and Computer Science National Institute of Technology Matsue Japan Dept. of Mechanical Engineering National Institute of Technology Iwaki Japan Dept. of Electrical Engineering National Institute of Technology Kushiro Japan Dept. of Electrical and Electronic Engineering National Institute of Technology Kirishima Japan Kagawa College National Institute of Technology Mitoyo Japan Head Office for Research Strategy Nagaoka University of Technology Nagaoka Japan

In the field of nuclear engineering, national colleges have been carrying out important roles with about 10 % of graduates obtaining jobs in nuclear related companies. Although national colleges do not have special courses and classes for nuclear engineering, we have been trying to educate our students in cooperation with universities and industries through the activities of the Japan Nuclear Human Resource Development Network. With aide from the Ministry of Education, Culture, Sports, Science and Technology, we have been developing a short term curriculum for nuclear education consisting of lectures, experiments and facility tours. Moreover, we have developed a textbook for nuclear engineering basics and texts for experiments. In order to let the students understand the background of radiation, radiation dose measurements have been conducted by the students of more than 33 colleges. In the fiscal year of 2015, a new trial of remote lecture connecting 51 national colleges began. Through these education programs, we aim to help our students to understand radiation and nuclear engineering correctly, and to have their own opinions on this important matter.

关键词： Physics Conferences Inductors engineering education Companies Industries

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IoT control and layer formation of FDM on polycarbonate based aluminium

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Materials Today: Proceedings 2021年 45卷 2809-2811页

作者： A. Chinnasamy L.M. Varalakshmi G. Jims John Wessley T. Malini S. Sanjith Mohammed Firdos Alam Sheikh Department of Computer Science and Engineering Sri Sairam Engineering College Chennai 600044 Tamil Nadu India Department of Instrumentation & Control Engineering Sri Manakula Vinayagar Engineering College Puducherry 605107 India Department of Aerospace Engineering Karunya Institute of Technology and Sciences Coimbatore 641114 Tamil Nadu. India Department of EEE Sri Krishna College of Engineering and Technology Coimbatore 641008 Tamil Nadu. India Department of Computer Science St. Alphonsa College of Arts and Science Soosaipuram 629157 Tamil Nadu India Department of Computer Science and Engineering Mewar University Chittorgarh 312901 Rajasthan India

Internet of Things (IoT) is an essential role in fabrication of components with high quality and low cost. In additive manufacturing, Fusion Deposition Modeling (FDM) is an effective technique to fabricate metal and non metals. The polycarbonate (PC) has more attractive properties such as strength, toughness, high temperature resistance and layer bonding. It is accumulated to the aluminium 7075 alloy by fusion deposition modeling technique. The adhesive strength between polycarbonate and aluminium depends on the layers. In this paper, FDM process parameters and data were analyzed through IoT. The microcontroller, network and sensors have been used to develop the FDM process. The layer strength was measured with the change of peel angle, speed and peeling force. The maximum layer strength and optimal factors have been analyzed through taguchi method.

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A dual plasmonic core-shell Pt/[TiN@TiO_(2)]catalyst for enhanced photothermal synergistic catalytic activity of VOCs abatement

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Nano Research 2022年第8期15卷 7071-7080页

作者： Anqi Li Qianpeng Zhang Shuaiqi Zhao Yanan Chong Peng Wu Yifei Li Xiaojing Jin Guangxu Chen Yongcai Qiu Shihe Yang Daiqi Ye Guangdong Provincial Key Laboratory of Atmospheric Environment and Pollution Control School of Environment and EnergySouth China University of TechnologyGuangzhou 510006China Department of Electronic and Computer Engineering The Hong Kong University of Science and TechnologyClear Water BayKowloonHong KongChina Guangzhou HKUST Fok Ying Tung Research Institute NanshaGuangzhou 511458China State Key Laboratory of Luminescent Materials and Devices South China University of TechnologyGuangzhou 510640China Guangdong Key Lab of Nano-Micro Material Research School of Chemical Biology and Biotechnology Shenzhen Graduate SchoolPeking UniversityShenzhen 518055China

Volatile organic compounds(VOCs)are ubiquitous organic pollutants affecting atmospheric environment and human *** development of new efficient and environmentally friendly materials utilizing photothermal synergistic catalysis for purification of VOCs is still ***,we design and prepare a core–shell TiN@TiO_(2)nanostructure integrating with nanoscaled Pt(Pt/[TiN@TiO_(2)])by an attractive quenching *** strong light-harvesting capability of Pt and TiN components improve light-to-heat utilization efficiency by their intrinsic surface plasmon resonance *** TiO_(2)component upon the surface and the coexisting coupling effect of Pt0 and Pt2+enhance the photocatalytic effect of the *** a result,the catalytic performance is significantly improved with toluene(120 ppm)conversion of 100%under the gas hourly space velocity of 72,000 mL·g^(−1)·h^(−1)and light illumination of 500 mW·cm^(−2).The desired catalyst thus achieves highly efficient coupling effect of photocatalysis and light-to-heat conversion for promoting VOCs abatement.

关键词： core-shell Pt/[TiN@TiO_(2)]catalyst volatile organic compounds(VOCs)abatement photothermal synergistic catalysis full spectrum sunlight utilization

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Deep autoencoder for off-line design-space dimensionality reduction in shape optimization

Deep autoencoder for off-line design-space dimensionality re...

引用

AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference, 2018

作者： D’Agostino, Danny Serani, Andrea Diez, Matteo Campana, Emilio F. Dept. of Computer Control and Management Engineering ‘A. Ruberti’ Sapienza University of Rome CNR-INSEAN Via Ariosto 25 Rome00185 Italy CNR-INSEAN National Research Council-Marine Technology Research Institute Via di Vallerano 139 Rome00128 Italy CNR-DIITET National Research Council-Dept. of Engineering ICT and Technologies for Energy and Transportation Piazzale Aldo Moro 7 Rome00185 Italy University of Iowa United States

ISBN: (数字)9781624105326

ISBN: (纸本)9781624105326

In shape optimization, design improvements significantly depend on the dimension and variability of the design space. High dimensional and variability spaces are more difficult to explore, but also usually allow for more significant improvements. The assessment and breakdown of design-space dimensionality and variability are therefore key elements to shape optimization. A linear method based on the principal component analysis has been developed in earlier research to build a reduced-dimensionality design-space, resolving the 95% of the original geometric variance. The paper presents an extension of the method to more efficient nonlinear approaches. Specifically, the use of a deep autoencoder is presented and discussed. The method is demonstrated for the design-space dimensionality reduction and hydrodynamic optimization of the hull form of a USS Arleigh Burke-class destroyer. A comparison with the linear method is finally shown and discussed. © 2018, (publisher Name). All Rights reserved.

关键词： Shape optimization

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Preemptive Single Processor Scheduling with Distinct Due Windows and Minimization of Maximum Earliness and Tardiness

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IFAC Proceedings Volumes 2009年第13期42卷 228-233页

作者： A. Janiak W.A. Janiak R. Januszkiewicz Institute of Computer Engineering Control and Robotics Wroclaw University of Technology Janiszewskiego 11/17 50-372 Wroclaw Poland tel.: +48-71-320-2107 fax.:+48-71-321-2677 Faculty of Computer Science and Management Wroclaw University of Technology Lukasiewicza 5 50-371 Wroclaw Poland

Abstract Problem of scheduling n preemptive jobs on a single processor is studied, in which for each job a distinct due window is given in advance. If a job is completed within its due window, then it incurs no penalty. Otherwise, it incurs a job-independent earliness or tardiness cost. The objective is to find a job schedule such that a maximum of weighted costs associated with earliness and tardiness is minimized. Properties of optimal solutions of this problem are established and an algorithm based on them is presented. It is proved that the analysed problem is solvable in O ( n 2 ) time.

关键词： scheduling algorithms preemption earliness-tardiness due windows

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Matrix Completion over Finite Fields: Bounds and Belief Propagation Algorithms

arXiv

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arXiv 2023年

作者： Soleymani, Mahdi Liu, Qiang Mahdavifar, Hessam Balzano, Laura Halıcıoglu Data Science Institute University of California San Diego United States The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China The Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor United States

We consider the low rank matrix completion problem over finite fields. This problem has been extensively studied in the domain of real/complex numbers, however, to the best of authors' knowledge, there exists merely one efficient algorithm to tackle the problem in the binary field, due to Saunderson et al. [1]. In this paper, we improve upon the theoretical guarantees for the algorithm provided in [1]. Furthermore, we formulate a new graphical model for the matrix completion problem over the finite field of size q, Fq, and present a message passing (MP) based approach to solve this problem. The proposed algorithm is the first one for the considered matrix completion problem over finite fields of arbitrary size. Our proposed method has a significantly lower computational complexity, reducing it from O(n2r+3) in [1] down to O(n2) (where, the underlying matrix has dimension n × n and r denotes its rank), while also improving the performance. Copyright © 2023, The Authors. All rights reserved.

关键词： Message passing

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