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作者： Nataliia Lutska Nataliia Zaiets Lidiia Vlasenko Andrii Zhyltsov dept. of Automation and Computer Technologies of Control Systems National University of Food Technologies Kyiv Ukraine dept. of Automation and Robotic Systems National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine dept. of Software Engineering and Cyber Security State University of Trade and Economics Kyiv Ukraine dept. of electromagnetic systems The Institute of Electrodynamics of the National Academy of Sciences of Ukraine Kyiv Ukraine

ISBN: (数字)9798350384499

ISBN: (纸本)9798350384505

The work demonstrates the process of developing a machine learning model for a system for monitoring and controlling the quality of predough at a bakery. This system will provide continuous analysis of the predough parameters, such as temperature, humidity, lifting force and titranic acidity, which will ensure timely detection of deviations in the quality of the predough and avoid production problems. In addition, it will help automate the quality control process and ensure the stability of production processes. Analysis and forecasting of dough parameters will improve the quality of produced bread or other bakery products. Management based also on the predicted values of technological indicators of the predough will allow the enterprise to avoid unnecessary costs of materials and energy and increase economic efficiency. As part of the study, seven machine learning models were created and reviewed, including three linear and four varieties of binary decision trees. An analysis of the best model - a regression decision tree - was carried out, confirming its effectiveness and the validity of the resulting hierarchical structure, in particular, the prediction of important indicators of predough with a high degree of reliability, which indicates its importance in practical applications in production. The created model can be used to monitor and control product quality in real time, allowing operators to quickly identify and correct any deviations in process performance. Also, by analyzing changes in the variables of the predough production process, it is possible to identify precursors of possible production accidents or deviations in product quality, which will allow timely measures to be taken to avoid them.

关键词： Force Process control Production Machine learning Quality control Humidity Predictive models Stability analysis Monitoring Thermal stability

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Distributed Optimization with Gradient Descent and Quantized Communication

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IFAC-PapersOnLine 2023年第2期56卷 5900-5906页

作者： Apostolos I. Rikos Wei Jiang Themistoklis Charalambous Karl H. Johansson Division of Decision and Control Systems KTH Royal Institute of Technology SE-100 44 Stockholm Sweden Digital Futures SE-100 44 Stockholm Sweden Department of Electrical Engineering and Automation School of Electrical Engineering Aalto University Espoo Finland Department of Electrical and Computer Engineering School of Engineering University of Cyprus Nicosia Cyprus

In this paper, we consider the unconstrained distributed optimization problem, in which the exchange of information in the network is captured by a directed graph topology, thus, nodes can only communicate with their neighbors. Additionally, in our problem, the communication channels among the nodes have limited bandwidth. In order to alleviate this limitation, quantized messages should be exchanged among the nodes. For solving this distributed optimization problem, we combine a gradient descent method with a distributed quantized consensus algorithm (which requires the nodes to exchange quantized messages and converges in a finite number of steps). Specifically, at every optimization step, each node (i) performs a gradient descent step (i.e., subtracts the scaled gradient from its current estimate), and (ii) performs a finite-time calculation of the quantized average of every node's estimate in the network. As a consequence, this algorithm approximately mimics the centralized gradient descent algorithm. We show that our algorithm asymptotically converges to a neighborhood of the optimal solution with linear convergence rate. The performance of the proposed algorithm is demonstrated via simple illustrative examples.

关键词： Distributed optimization quantized communication directed graphs finite-time consensus

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AggFollower: Aggressiveness Informed Car-Following Modeling

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-15页

作者： Chen, Xianda Yuan, Xinyi Zhu, Meixin Zheng, Xinhu Shen, Shaojie Wang, Xuesong Wang, Yinhai Wang, Fei-Yue Guangzhou China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Hong Kong SAR China School of Transportation Engineering Tongji University Shanghai China Department of Civil and Environmental Engineering University of Washington Seattle WA USA State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Car-following is the most common driving scenario where a following vehicle follows a lead vehicle in the same lane. One crucial factor of car-following behavior is driving style which affects speed and gap selection, acceleration pattern, and fuel consumption. However, existing car-following research used limited categories of driving style through pre-defined patterns and failed to encode driving style into data-driven car-following models. To address these limitations, we propose the Aggressiveness Informed Car-Following (AICF) modeling approach, which embeds driving style as a dynamic input feature in data-driven car-following models. In detail, We design driving aggressiveness tokens using four physical quantities (jerk, acceleration, relative speed, and relative spacing) to capture the heterogeneity of driving aggressiveness. These tokens were then embedded into a physics-informed Long Short-Term Memory (LSTM) based car-following model for trajectory prediction. To evaluate the effectiveness of our approach, we conducted extensive experiments based on 12,540 car-following events extracted from the HighD dataset and 24,093 events from the Lyft dataset. Compared to models devoid of considerations for driving aggressiveness levels, AICF exhibits superior efficacy in mitigating the Mean Square Error (MSE) of spacing and collision rate. To the best of our knowledge, this is the first work to directly incorporate real-time driving aggressiveness tokens as input features into data-driven car-following models, enabling a more comprehensive understanding of aggressiveness in car-following behavior. IEEE

关键词： Long short-term memory

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Quantized Distributed Nonconvex Optimization Algorithms with Linear Convergence under the Polyak–Lojasiewicz Condition

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IEEE Transactions on Automatic control 2025年

作者： Xu, Lei Yi, Xinlei Sun, Jiayue Shi, Yang Johansson, Karl H. Yang, Tao Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China University of Victoria Department of Mechanical Engineering VictoriaBCV8W 2Y2 Canada Tongji University Shanghai Institute of Intelligent Science and Technology Shanghai201804 China KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm100 44 Sweden

This paper considers distributed optimization for minimizing the average of local nonconvex cost functions, by using local information exchange over undirected communication networks. To reduce the required communication capacity, we introduce an encoder–decoder scheme. By integrating it with distributed gradient tracking and proportional integral algorithms, respectively, we then propose two quantized distributed nonconvex optimization algorithms. Assuming the global cost function satisfies the Polyak–Lojasiewicz condition, which does not require the global cost function to be convex and the global minimizer is not necessarily unique, we show that our proposed algorithms linearly converge to a global optimal point. Moreover, we show that a low data rate is sufficient to guarantee linear convergence when the algorithm parameters are properly chosen. The theoretical results are illustrated by numerical examples. © 1963-2012 IEEE.

关键词： Cost functions

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Complex Permeability Determination for EE Core Based on Flexible PCB Fixture and Magnetic Flux Path Length Analysis

Complex Permeability Determination for EE Core Based on Flex...

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China Power Supply Society Electromagnetic Compatibility Conference (CPEMC)

作者： Huamin Jie Zhenyu Zhao Yongqi Chang Changdong Wang Shiqi Jiang Richard Xian-Ke Gao Kye Yak See School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Department of Electrical and Computer Engineering National Univeristy of Singapore Singapore Singapore Department of Control Science and Engineering Harbin Institute of Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China A*STAR Institute of High Performance Computing Singapore Singapore

ISBN: (数字)9798331509552

ISBN: (纸本)9798331509569

The complex permeability of magnetic cores acts as a vital factor in electromagnetic interference (EMI) filtering choke design and optimization. Many efforts have been reported for toroid cores, but fewer target those with other shapes, such as EE, EI, UU, and UI cores. Owing to their commonly used in planar EMI filters, determining the complex permeability of them is of significance. Targeting EE cores, this paper presents a flexible printed circuit board (PCB)-based fixture adapter tailored designed for performing the measurement, while the corresponding core permeability can be calculated through magnetic flux path length analysis. The experiments validate the effectiveness and accuracy of the proposed methods, spanning a wide frequency range up to 120 MHz.

关键词： Magnetic flux Accuracy Flexible printed circuits Magnetic cores Fixtures Electromagnetic interference Permeability measurement Length measurement Permeability Inductors

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Methods of Reducing the Energy Consumption of Digital-Analog Converters and Increasing Their Metrological Reliability

Methods of Reducing the Energy Consumption of Digital-Analog...

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International Conference on Modern Problems of Radio Engineering, Telecommunications and computer Science

作者： Oleg Zastavnyy Orest Kochan Pavlo Bykovyy Anatoliy Sachenko Roman Kochan Volodymyr Kochan Department of Specialized Computer Systems West Ukrainian National University Termopil Ukraine Department of Information and Measurement Technologies Automation and Metrology Lviv Polytechnic National University Lviv Ukraine Department of Information Computer Systems and Control West Ukrainian National University Termopil Ukraine Research Institute for Intelligent Computer Systems of West Ukrainian National University Termopil Ukraine Department of Teleinformatics Kazimierz Pulaski University of Radom Radom Poland Department of Specialized Computer Systems Lviv Polytechnic National University Lviv Ukraine

ISBN: (数字)9798331520564

ISBN: (纸本)9798331520571

This work analyzes the possibility of reducing the energy consumption of digital-to-analog converters by minimizing the energy consumption of the elements that ensure their operation. Due to the fact that such decisions can lead to an increase in the temperature and time drift of the output voltage of the digital-to-analog converter, a method of its in-situ calibration during operation is proposed. The method also allows carrying out calibration of high-speed analog-digital converters.

关键词： Energy consumption Power demand Digital-analog conversion Voltage Reliability engineering Market research Calibration Telecommunications Integrated circuit reliability Analog-digital conversion

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Reduced Network Cumulative Constraint Violation for Distributed Bandit Convex Optimization under Slater’s Condition

arXiv

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arXiv 2024年

作者： Zhang, Kunpeng Yi, Xinlei Ding, Jinliang Cao, Ming Johansson, Karl H. Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai201800 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper studies the distributed bandit convex optimization problem with time-varying inequality constraints, where the goal is to minimize network regret and cumulative constraint violation. To calculate network cumulative constraint violation, existing distributed bandit online algorithms solving this problem directly use the clipped constraint function to replace its original constraint function. However, the use of the clipping operation renders Slater’s condition (i.e, there exists a point that strictly satisfies the inequality constraints at all iterations) ineffective to achieve reduced network cumulative constraint violation. To tackle this challenge, we propose a new distributed bandit online primal–dual algorithm. If local loss functions are convex, we show that the proposed algorithm establishes an O(T max{c,1−c})network regret bound and an O(T 1−c/2) network cumulative constraint violation bound, where T is the total number of iterations and c ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds, the network cumulative constraint violation bound is reduced to O(T 1−c). In addition, if local loss functions are strongly convex, for the case where strongly convex parameters are unknown, the network regret bound is reduced to O(T1−c), and the network cumulative constraint violation bound is O(T1−c/2) and O(T1−c) without and with Slater’s condition, respectively. For the case where strongly convex parameters are known, the network regret bound is further reduced to O)(log(T)), and the network cumulative constraint violation bound is reduced to O(log(T)T) and O(log(T)) without and with Slater’s condition, respectively. To the best of our knowledge, this paper is among the first to establish reduced (network) cumulative constraint violation bounds for (distributed) bandit convex optimization with time-varying constraints under Slater’s condition. Finally, a numerical example is provided to verify the theoretical results. Copyright © 2

关键词： Convex optimization

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PDAVIS: Bio-inspired Polarization Event Camera

PDAVIS: Bio-inspired Polarization Event Camera

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IEEE computer Society Conference on computer Vision and Pattern Recognition Workshops (CVPRW)

作者： Germain Haessig Damien Joubert Justin Haque Moritz B. Milde Tobi Delbruck Viktor Gruev AIT Austrian Institute of Technology Center for Vision Automation & Control High-Performance Vision Systems Vienna Austria Institute of Neuroinformatics University of Zurich and ETH Zurich Switzerland International Centre for Neuromorphic Systems The MARCS Institute Western Sydney University Sydney Australia Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign Urbana IL USA

The stomatopod (mantis shrimp) visual system has recently provided a blueprint for the design of paradigm-shifting polarization and multispectral imaging sensors, enabling solutions to challenging medical and remote sensing problems. However, these bioinspired frame-based cameras lack the high dynamic range and asynchronous polarization vision capabilities of the stomatopod visual system, limiting temporal resolution to ~12ms and dynamic range to ~72dB. Here we present a novel stomatopod-inspired polarization camera which mimics the sustained and transient biological visual pathways to save power and sample data beyond the maximum Nyquist frame rate. This bio-inspired sensor simultaneously captures both synchronous intensity frames and asynchronous polarization brightness change information with submillisecond latencies over a millionfold range of illumination. Our PDAVIS camera is comprised of 346x260 pixels, organized in 2-by-2 macropixels, which filter the incoming light with four linear polarization filters offset by 45°. Polarization information is reconstructed using both low-cost and low-latency event-based algorithms and more accurate but slower deep neural networks. Our sensor is used to image high dynamic range polarization scenes that vary at high speeds and to observe the dynamical properties of single collagen fibers in a bovine tendon under rapid cyclical ***: https://***/mFuCeTMWEqY

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Privacy Preservation for Cloud-Edge-Collaborative Energy Management System Using Post-Quantum Homomorphic Encryption

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IEEE Transactions on Smart Grid 2025年

作者： Jiang, Cheng Li, Xue Du, Dajun Qian, Hong Wen, Mi Wu, Lei Findeisen, Rolf Shanghai University of Electric Power Shanghai Key Laboratory of Power Station Automation Technology College of Automation Engineering Shanghai200090 China Shanghai University Shanghai Key Laboratory of Power Station Automation Technology School of Mechatronical Engineering and Automation Shanghai200072 China Shanghai University of Electric Power College of Computer Science and Technology Shanghai201306 China Advanced Cryptography and System Security Key Laboratory of Sichuan Province Chengdu610225 China Stevens Institute of Technology Department of Electrical and Computer Engineering HobokenNJ07030 United States TU Darmstadt Control and Cyber-Physical Systems Laboratory Darmstadt64227 Germany

Cloud-based energy management systems (EMS) in smart grids face privacy challenges, as existing methods based on traditional homomorphic encryption support limited operations and are vulnerable to quantum attacks. We propose a privacy preservation method for smart grid energy management system, leveraging edge-assisted computing and ring learning with errors (RLWE) homomorphic encryption. Our approach enables both addition and multiplication operations on encrypted smart grid data while defending against quantum threats. We demonstrate the methods security under the RLWE hardness assumption and validate its effectiveness through an experimental platform simulating smart grid environments. This work addresses computational limitations in current privacy-preserving techniques, enhancing data security for evolving smart grid technologies © 2010-2012 IEEE.

关键词： Power management (telecommunication)

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Anti-disturbance filter design for a class of stochastic systems with fading channels

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Science China(Information Sciences) 2020年第11期63卷 327-329页

作者： Yang LIU Zidong WANG Hongli DONG Hongjian LIU College of Electrical Engineering and Automation Shandong University of Science and Technology Department of Computer Science Brunel University London Institute of Complex Systems and Advanced Control Northeast Petroleum University School of Mathematics and Physics Anhui Polytechnic University

Dear editor,As a significant topic in control and signal processing communities, the filtering problem has been attracting persistent research attention in the past few decades [1]. In practical engineering, the parameter perturbations are unavoidable due mainly to exogenous disturbances, environmental changes and some other phenomena.

关键词： Stochastic systems fault detection model uncertainty anti-disturbance fading channel

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