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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Nadji Hadroug Tarek Idris Bisker Abdellah Kouzou Abdelhamid Iratni Ahmed Hafaifa Ilhami Colak Applied Automation and Industrial Diagnostics Laboratory Faculty of Science and Technology University of Djelfa DZ Algeria Control and Energy Management Laboratory (CEM Lab) ENIS Sfax Tunisia Faculty of Science and Technology University of Bordj Bou Arreridj DZ Algeria Department of Electrical and Electronics Engineering Nisantasi University Sarıyer İstanbul Turkey

The practice of control strategies and their applications on industrial systems requires reliable models in implementation, with an identification of their variables involved in the control sequence. Indeed, several complexity limitations of these systems require the use of linearization around the operating points, to ensure the stability of the system. To this end, this work proposes the development of a closed-loop identification strategy, applied to a two-shaft gas turbine, using a linear control with state feedback. This approach makes it possible to meet stability objectives by ensuring better performance in control variables of the studied gas turbine.

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Distributed Event-Triggered Bandit Convex Optimization With Time-Varying Constraints

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IEEE Transactions on control of Network Systems 2025年

作者： Zhang, Kunpeng Yi, Xinlei Wen, Guanghui Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao Northeastern University State Key Laboratory of Synthetical Automation for Process Industries Shenyang110819 China Ministry of Education Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Shanghai201210 China Southeast University School of Automation Nanjing210096 China University of Groningen Engineering and Technology Institute Groningen Faculty of Science and Engineering GroningenAG 9747 Netherlands KTH Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science Stockholm10044 Sweden KTH Royal Institute of Technology Digital Futures Stockholm10044 Sweden

This paper considers the distributed bandit convex optimization problem with time-varying inequality constraints over a network of agents, where the goal is to minimize network regret and cumulative constraint violation. Existing distributed online algorithms solving this problem require that each agent broadcasts its decision to its neighbors at each iteration. However, communication resources are often limited. To better utilize communication resources, we propose a distributed event-triggered online primal-dual algorithm with two-point bandit feedback. Under several classes of appropriately chosen decreasing parameter sequences and non-increasing event-triggered threshold sequences, we establish dynamic network regret and network cumulative constraint violation bounds. These bounds are comparable to the results achieved by distributed event-triggered online algorithms with full-information feedback. Finally, a numerical example is provided to verify the theoretical results. © 2014 IEEE.

关键词： Optimization algorithms

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METHODOLOGY OF MODELING THE DETECTION OF LIMESCALE DEPOSITS IN SANITARY INSTALLATIONS 21

METHODOLOGY OF MODELING THE DETECTION OF LIMESCALE DEPOSITS ...

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21st International Multidisciplinary Scientific Geoconference: Water Resources, Forest, Marine and Ocean Ecosystems, SGEM 202

作者： Czajkowski, Adrian Remiorz, Leszek Pawlak, Sebastian Remiorz, Eryk Szygula, Jakub Miscea.pl Engineering Sp. z o.o. Poland Department of Power Engineering and Turbomachinery Faculty of Energy and Environmental Engineering Silesian University of Technology Poland Doctoral School The Silesian University of Technology Poland Faculty of Mechanical Engineering Scientific and Didactic Laboratory of Nanotechnology and Materials Technologies Poland Department of Mining Mechanization and Robotisation Faculty of Mining Safety Engineering and Industrial Automation Silesian University of Technology Poland Department of Distributed Systems and Informatic Devices Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Poland

ISBN: (纸本)9786197603361

The article presents the issue of scale deposits in sanitary installations. Scale contributes to improper operation of sanitary devices and leads to their degradation. Scale build-up in pipes and measuring elements results in higher water consumption due to inaccurate estimation of this resource consumption. The consequence is that devices based on process automation do not work properly due to disturbances in the actual water flow. The formation of deposits also leads to economic and ecological losses, as sanitary installations elements have to be replaced, which affects the increased use of raw materials and the generation of waste. This is not in line with current trends and global objectives related to circular economy. Scale also results in increased energy consumption and reduced energy efficiency. This is due to the resistance of the flows and the increased work of the pumps. Scale has insulating properties, which results in less efficient heat transfer. In this stady, a mathematical model was developed to detect the formation of scale deposits in sanitary installations. On this basis, it is possible to control the quality status of sanitary installation components. In this way, by taking appropriate action at an early stage of the formation of deposits, it can extend the life of the installation. Having information on scale deposits, it will help avoid wasting water and lead to more accurate measurement of water flows. This is important for the proper operation of devices such as heat pumps, where their operation is automated and requires precise measurements of the energy processes taking place. Scale is a significant problem for households, and also for factories or public institutions that are exposed to hard water environments. © 2021 International Multidisciplinary Scientific Geoconference. All rights reserved.

关键词： Deposits

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FASR-Net: Unsupervised Shadow Removal Leveraging Inherent Frequency Priors

arXiv

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arXiv 2025年

作者： Lin, Tao Wang, Qingwang Liang, Qiwei Tang, Minghua Sun, Yuxuan Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming China College of Mechatronics and Control Engineering Shenzhen University Shenzhen China

Shadow removal is challenging due to the complex interaction of geometry, lighting, and environmental factors. Existing unsupervised methods often overlook shadow-specific priors, leading to incomplete shadow recovery. To address this issue, we propose a novel unsupervised Frequency Aware Shadow Removal Network (FASR-Net), which leverages the inherent frequency characteristics of shadow regions. Specifically, the proposed Wavelet Attention Downsampling Module (WADM) integrates wavelet-based image decomposition and deformable attention, effectively breaking down the image into frequency components to enhance shadow details within specific frequency bands. We also introduce several new loss functions for precise shadow-free image reproduction: a frequency loss to capture image component details, a brightness-chromaticity loss that references the chromaticity of shadow-free regions, and an alignment loss to ensure smooth transitions between shadowed and shadow-free regions. Experimental results on the AISTD and SRD datasets demonstrate that our method achieves superior shadow removal performance. Copyright © 2025, The Authors. All rights reserved.

关键词： Wavelet decomposition

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Design and Experiment of a Magnetic Shape Memory Alloy Actuator 3

Design and Experiment of a Magnetic Shape Memory Alloy Actua...

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3rd International Academic Exchange Conference on Science and Technology Innovation, IAECST 2021

作者： Zeng, Yulu Zhu, Zhifang Wan, Jiaxin Zhao, Ran Huang, Senlin Nanchang Institute of Technology Jiangxi Province Key Laboratory of Precision Drive Control Nanchang China Faculty of Mechanical Engineering and Automation Nanchang Institute of Technology Jiangxi Province Key Laboratory of Precision Drive Control Zhejiang Sci-Tech University Nanchang China Zhongyuan University of Technology Zhongyuan-Petersburg Aviation College Zhengzhou China

ISBN: (纸本)9781665402675

This paper presented a large displacement precision actuator based on magnetic shape memory alloy (MSMA). A Ni-Mn-Ga rod was chosen as the driving source for the proposed actuator. The structure of the actuator was designed, and the its parameters are determined by calculation. The magnetic field is simulated by the finite element simulation software. After determining that the magnetic field meets the requirements, the prototype is made for experiments. The experimental results show that the maximum output displacement of the magnetic shape memory alloy actuator reaches 1.07mm when the pre-stress is 0 MPa. Which indicates that the design of the device is reasonable and is of great significance for broadening the application field of micro-displacement actuators. © 2021 IEEE.

关键词： Magnetic fields

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Algorithm of acid temperature setup model based on the CBR 32

Algorithm of acid temperature setup model based on the CBR

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第32届中国控制与决策会议

作者： ZHU Xiao-yan LI Song-hua CAO Jiao-zhao SUN Jie ZHANG Shi-bang Engineering Training Center Shenyang Jianzhu University School of Mechanical Engineering Shenyang Jianzhu University State Key Laboratory of Rolling and Automation Northeastern University Information & Control Engineering Faculty Shenyang Jianzhu University

ISBN: (数字)9781728158556

ISBN: (纸本)9781728158563

In the continuous pickling line,the acid temperature setup accuracy was low,which not only caused excessive pickling defects,but also caused excessive consumption of hydrochloric acid and a decrease in pickling *** order to solve this problem,the acid temperature setup model based on case-based reasoning(CBR) technology was established by using a large amount of production data with good temperature setting *** the model was put into operation on a 1450 mm pickling and rolling line,the average pickling defect ratio decreased from 14.99904% to 11.7332% and the fluctuation range of the pickling defect ratio was effectively *** application showed that the setup accuracy of the acid temperature model was effectively *** the number of strip steel production increases,the model has the adaptive ability to change with the working conditions,which is suitable for industrial promotion.

关键词： Case-based reasoning acid temperature pickling and rolling line similarity function pickling defect

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Towards Intelligent and Trustworthy Crowdsourcing Systems with Cyber-physical Social Intelligence via Retrieval-augmented Generation

Towards Intelligent and Trustworthy Crowdsourcing Systems wi...

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Cyber-Physical Social Intelligence (ICCSI), International Conference on

作者： Jing Yang Xingxia Wang Qinghua Ni Yuhang Liu Jing Wang Fei-Yue Wang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Innovation Engineering Macau University of Science and Technology Macao China Macau University of Science and Technology Macao China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350376739

ISBN: (纸本)9798350376746

In recent years, crowdsourcing systems that tackle complex tasks through the collective efforts of many individuals have garnered substantial attention. However, the existing crowd-sourcing systems face some challenges such as overreliance on human experience and effort, information overload, and risks of privacy breaches. To overcome these challenges, this paper proposes an intelligent and trustworthy crowdsourcing frame-work based on blockchain and retrieval-augmented generation. The framework centers around foundational models to integrate the three distinct and sequentially interdependent phases: task decomposition, task allocation or recommendation, and task execution, enabling the automatic provision of a personalized, comfortable, and efficient user experience. Blockchain and smart contracts are utilized to protect user privacy and interests without leaning on any third trusted authority. Additionally, the operational process of the framework is explained and validated by taking printed circuit board design and manufacturing as a case study and ChatGPT as its generator.

关键词： Crowdsourcing Retrieval augmented generation Smart contracts Privacy breach User experience Stability analysis Blockchains Social intelligence Resource management Reliability

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A Unified Formulation of Geometry-aware Discrete Dynamic Movement Primitives

arXiv

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arXiv 2022年

作者： Abu-Dakka, Fares J. Saveriano, Matteo Kyrki, Ville Electronic and Computer Science Department Faculty of Engineering Mondragon Unibertsitatea Arrasate20500 Spain Automatic Control Lab Department of Industrial Engineering University of Trento Trento Italy Intelligent Robotics Group Department of Electrical Engineering and Automation Aalto University Aalto Finland

Learning from demonstration (LfD) is considered as an efficient way to transfer skills from humans to robots. Traditionally, LfD has been used to transfer Cartesian and joint positions and forces from human demonstrations. The traditional approach works well for some robotic tasks, but for many tasks of interest, it is necessary to learn skills such as orientation, impedance, and/or manipulability that have specific geometric characteristics. An effective encoding of such skills can be only achieved if the underlying geometric structure of the skill manifold is considered and the constrains arising from this structure are fulfilled during both learning and execution. However, typical learned skill models such as dynamic movement primitives (DMPs) are limited to Euclidean data and fail in correctly embedding quantities with geometric constraints. In this paper, we propose a novel and mathematically principled framework that uses concepts from Riemannian geometry to allow DMPs to properly embed geometric constrains. The resulting DMP formulation can deal with data sampled from any Riemannian manifold including, but not limited to, unit quaternions and symmetric and positive definite matrices. The proposed approach has been extensively evaluated both on simulated data and real robot experiments. The performed evaluation demonstrates that beneficial properties of DMPs, such as convergence to a given goal and the possibility to change the goal during operation, apply also to the proposed formulation. © 2022, CC BY-NC-ND.

关键词： Demonstrations

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Energy Optimization of Wind Turbines via a Neural control Policy Based on Reinforcement Learning Markov Chain Monte Carlo Algorithm

arXiv

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arXiv 2022年

作者： Aghaei, Vahid Tavakol Agababaoglu, Arda Bawo, Biram Naseradinmousavi, Peiman Yıldırım, Sinan Yeşilyurt, Serhat Onat, Ahmet Istinye University Faculty of Engineering and Natural Sciences Electrical and Electronics Engineering Istanbul Turkey Sabanci University Orhanli Tuzla Istanbul34956 Turkey Delivers AI ITU Arı Technological Park Istanbul Turkey Sabanci University Faculty of Engineering and Natural Sciences Mechatronics Engineering Istanbul Turkey San Diego State University Dynamic Systems and Control Laboratory San Diego United States Sabanci University Faculty of Engineering and Natural Sciences Industrial Engineering Istanbul Turkey Istanbul Technical University Control and Automation Engineering Istanbul Turkey

This study focuses on the numerical analysis and optimal control of vertical-axis wind turbines (VAWT) using Bayesian reinforcement learning (RL). We specifically address small-scale wind turbines, which are well-suited to local and compact production of electrical energy on a small scale, such as urban and rural infrastructure installations. Existing literature concentrates on large scale wind turbines which run in unobstructed, mostly constant wind profiles. However urban installations generally must cope with rapidly changing wind patterns. To bridge this gap, we formulate and implement an RL strategy using the Markov chain Monte Carlo (MCMC) algorithm to optimize the long-term energy output of a wind turbine. Our MCMC-based RL algorithm is a model-free and gradient-free algorithm, in which the designer does not have to know the precise dynamics of the plant and its uncertainties. Our method addresses the uncertainties by using a multiplicative reward structure, in contrast with additive reward used in conventional RL approaches. We have shown numerically that the method specifically overcomes the shortcomings typically associated with conventional solutions, including, but not limited to, component aging, modeling errors, and inaccuracies in the estimation of wind speed patterns. Our results show that the proposed method is especially successful in capturing power from wind transients;by modulating the generator load and hence the rotor torque load, so that the rotor tip speed quickly reaches the optimum value for the anticipated wind speed. This ratio of rotor tip speed to wind speed is known to be critical in wind power applications. The wind to load energy efficiency of the proposed method was shown to be superior to two other methods;the classical maximum power point tracking method and a generator controlled by deep deterministic policy gradient (DDPG) method. © 2022, CC BY-NC-ND.

关键词： Reinforcement learning

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Narrowband Noise Signal Characteristics Corresponding to Their Strong Latent Correlation for Information-Measuring Systems 10

Narrowband Noise Signal Characteristics Corresponding to The...

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10th Mediterranean Conference on Embedded Computing, MECO 2021

作者： Chernov, Evgeniy I. Sobolev, Nikolay E. Bondarchuk, Alexander A. Shulyakov, Andrey V. Ryazan State Radio Engineering University Named after V.F. Utkin RSREU Faculty of Automation and Information Technologies in Control Ryazan Russia 'Globus' Ryazan Design Bureau JSC Ryazan Russia LLC 'Institute of Problem Developments' Ryazan Russia

ISBN: (纸本)9780738133614

the regions of characteristics of narrow-band noise signals corresponding to a strong hidden correlation between these signals are correctly determined. The signals under consideration are as follows: the signal at center frequency and the sum of signals at specular frequencies simultaneously extracted from broadband bandwidth-limited noise dominated by shot noise. The characteristics being analyzed included specular frequency range and narrowband filter selectivity (narrowband noise spectral bands). Research method is based on the method to assess latent correlation of narrowband noise signals earlier developed by the authors. The research results presented can be of interest for scientists, engineers and metrologists engaged in digital signal processing who apply specular noise method for useful signal extraction from noise. © 2021 IEEE.

关键词： Shot noise

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