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2022 4th International Conference on Energy systems and Electrical Power, ICESEP 2022

作者： Lai, GuangZhi Wang, Dong Li, HaoRan Zhao, Yi Ni, WeiChen Wen, JiaHao State Grid e-commerce Co. Ltd Beijing100053 China State Grid Tianjin Electric Power Company Tianjin300392 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China

Energy is the focus of recent years. As one of the most representative new energy sources, solar energy has the characteristics of large reserves and no pollution. The main way to use solar energy is photovoltaic (PV) power generation, and the PV module in the PV power generation system is the component that converts solar energy into electric energy. In the actual power generation process, PV modules often receive uneven solar illumination due to the shadow caused by clouds, trees, buildings, etc., resulting in changes in the output characteristics of PV modules and reduced output efficiency. Therefore, modeling of PV modules under shading condition is very important. This paper presents two simple methods for solving the parameters of PV module models, which require few parameters and are easy to obtain. A modeling method of PV modules under shading condition is also presented. And then the modeling method is verified with the experiment result. Finally, an error criterion for PV module modeling under shading condition is proposed to measure the goodness of the modeling. Combining with the two parameter solving methods, the errors of this PV module modeling method under shading condition of the error criterion proposed in this paper are 3.24% and 2.51%, respectively, which meet the requirements for engineering use. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Solar energy

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Event-Triggered Energy Optimization of Wireless Sensor Networks 19

Event-Triggered Energy Optimization of Wireless Sensor Netwo...

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19th IEEE International Conference on Networking, Sensing and control, ICNSC 2022

作者： Liu, Lu Song, Ruizhuo Wei, Qinglai School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory of Management and Control for Complex Systems Beijing China

ISBN: (纸本)9781665472432

Aiming at limited communication and energy re-sources in wireless sensor networks (WSN s), this paper proposes an energy management scheme of WSNs via adaptive dynamic programming (ADP) based on event-triggered mecha-nism (ETM). The optimal control strategy obtained by iteration can schedule the sensor nodes and make the nodes switch between working and sleeping situations, thus improving the energy utilization and extending the service life of the energy-constrained WSNs. Firstly, the mathematical model of WSNs is established, and the state is estimated by extended Kalman filter (EKF) algorithm to improve the measurement accuracy. Then, ADP solves the designed value function to achieve the scheduling plan. On the premise of system stability, ETM is applied to activate the controller on demand, which can reduce communication burden and save WSNs energy consumption. Finally, the simulation experiment reveals that the proposed algorithm can reduce the unnecessary triggering times of the controller effectively while ensuring the requirements, and avoid data congestion and interaction resource waste. © 2022 IEEE.

关键词： Energy utilization

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Estimation and compensation of periodic disturbance using internal-model-based equivalent-input-disturbance approach

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Science China(Information Sciences) 2022年第8期65卷 150-163页

作者： Qicheng MEI Jinhua SHE Zhentao LIU Min WU School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Engineering Tokyo University of Technology

This paper presents an improved equivalent-input-disturbance(EID) approach to deal with periodic disturbances. The approach has two degrees of freedom. One is an improved EID compensator, in which a repetitive controller is inserted in this study. The other is a conventional servo system for a reference *** improved EID compensator estimates and compensates for periodic disturbances without steady-state error, and the servo system ensures a satisfactory tracking performance. The improved EID compensator is designed using the linear-matrix-inequality(LMI) method. Three parameters in an LMI are selected using the particle-swarm-optimization(PSO) algorithm. The state-feedback gain of the conventional servo system is designed using the linear-quadratic-regulator(LQR) method. Simulation results of a rotational control system demonstrate the validity of the approach and its advantage over others.

关键词： equivalent input disturbance (EID) linear matrix inequality (LMI) linear quadratic regulator (LQR) particle swarm optimization (PSO) periodic disturbance repetitive control

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A Double Node Thin-Film Thermocouples for In-Situ measurement

A Double Node Thin-Film Thermocouples for In-Situ Measuremen...

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2022 International Conference on Automation, Robotics and Computer engineering, ICARCE 2022

作者： Ma, Rong Zhang, Meiju Zhang, Zhongkai Huang, Manguo Liang, Xiaobo Liu, Jiangjiang Liu, Zhaojun Tian, Bian Xi'An Jiaotong University State Key Laboratory for Mechanical Manufacturing Systems Engineering Xi'an China Aviation Key Laboratory of Science and Technology on Special Condition Monitoring Sensor Technology Beijing Changcheng Aeronautic Measurement and Control Technology Research Institute Beijing China

ISBN: (纸本)9781665475488

The design, fabrication, testing and implementation of a new high-performance tungsten-rhenium thin film thermocouple are introduced. In this paper, tungsten-rhenium TFTCs are taken as the research object, after simulation analysis in COMSOL software and design, it is made by screen-printing technology and magnetron sputtering. This kind of thin film thermocouple primarily utilizes two kinds of electrode materials with varying composition combination, mainly tungsten with 5% rhenium and tungsten with 26% rhenium. Furthermore, high-temperature annealing is performed to maintain the mechanical properties and thus improve thermoelectric performance. The results demonstrate that the performance is reliable in the temperature range of 150-600 C° with a repeatability of 2.02%, providing application value for high-temperature in-situ sensing. © 2022 IEEE.

关键词： Thermocouples

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Bayesian Exponential Regularized Tensor Based Approach for Sparse Geomagnetic Data Completion

Bayesian Exponential Regularized Tensor Based Approach for S...

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2023 International Conference on Sensing, measurement and Data Analytics in the Era of Artificial Intelligence, ICSMD 2023

作者： Li, Guoyu Bin, Junchi Liu, Huan School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Engineering University of British Columbia OkanaganBCV1V 1V7 Canada

ISBN: (纸本)9798350318012

Geomagnetic data is vital for predicting earthquakes and magnetic storms. In this regard, a new Bayesian exponential regularized tensor completion framework for sparse geomagnetic data, i.e. BERTC, is proposed to address this problem in the study. First, the spatiotemporal geomagnetic data is reshaped into a 3D tensor with days and hours that features random missing elements. Second, a Gibbs sampling algorithm is developed to achieve probabilistic inference on matrices' factors and corresponding parameters in this model. Thus, the sparse tensor can be gradually optimized to fill the missing entries during iterations. Third, an exponential regularizer is proposed to reduce oscillations before and after iterations to enhance imputation quality further. Finally, the derived factor matrices are aggregated from Gibbs sampling to complete the sparse tensor. Numerical geomagnetic datasets from 13 cities are employed, and extensive comparison experiments are conducted to evaluate the imputation performance of the BERTC. The results show the superiority of the proposed BERTC compared to the state-of-the-art methods in terms of imputation accuracy, with an approximate improvement of the imputation accuracy as no less than 20%. © 2023 IEEE.

关键词： Matrix algebra

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Distributed solver for linear matrix inequalities: an optimization perspective

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control Theory and Technology 2021年第4期19卷 507-515页

作者： Weijian Li Wen Deng Xianlin Zeng Yiguang Hong Department of Automation University of Science and Technology of ChinaHefei 230027AnhuiChina Key Lab of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China

In this paper,we develop a distributed solver for a group of strict(non-strict)linear matrix inequalities over a multi-agent network,where each agent only knows one inequality,and all agents co-operate to reach a consensus solution in the intersection of all the feasible *** formulation is transformed into a distributed optimization problem by introducing slack variables and consensus ***,by the primal–dual methods,a distributed algorithm is proposed with the help of projection operators and derivative ***,the convergence of the algorithm is analyzed,followed by illustrative simulations.

关键词： Distributed computation Distributed optimization Linear matrix inequalities Primal-dual method

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Stable control and Disturbance Rejection Strategy for Planar 2R Underactuated Robot via Intelligent Algorithm 48

Stable Control and Disturbance Rejection Strategy for Planar...

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Huang, Zixin Wan, Xiao Zhou, Yaosheng Wang, Lejun Wang, Liheng School of Electrical and Information Engineering Wuhan Institute of Technology Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan Institute of Technology School of Electrical and Information Engineering Wuhan China Wuhan Institute of Technology School of Innovation and Entrepreneurship Wuhan China Chongqing University of Posts and Telecommunications Chongqing Key Laboratory of Complex Systems and Bionic Control Chongqing China

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

Stable control and active disturbance rejection strategy is proposed for planar 2R underactuated robot via intelligent algorithm in this paper. At first, we build the dynamic model and describe the control characteristic. After that, we design PD controller for the active link. According to the underactuated constraint, we then optimize the parameters of controller by using the differential evolution algorithm (DEA), so that we can ensure the target states of all links could eventually be reached at the identical time. And the simulation results indicate the strategy is effective. © 2022 IEEE.

关键词： Disturbance rejection

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An IMU Error Correction Method Based on Multithreshold ZV Detection and SRCKF

An IMU Error Correction Method Based on Multithreshold ZV De...

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2023 International Conference on Cyber-Physical Social Intelligence, ICCSI 2023

作者： Luo, Jialiang Chen, Shichao Lv, Yisheng Sun, Wenqiao Yang, Fan Xu, Ruijie Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems China Institute of Automation Chinese Academy of Sciences The Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited The State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Institute of Automation Chinese Academy of Sciences The State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing China Transportation and Economics Research Institute Center of National Railway Intelligent Transportation System Engineering and Technology China Academy of Railway Sciences Corporation Limited China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Rail Transit Shan Dong JiaoTong University The State Key Laboratory for Management and Control of Complex System Jinan China The Hong Kong Polytechnic University Department of Aeronautical and Aviation Engineering Hong Kong Hong Kong

ISBN: (纸本)9798350312492

With the rapid development and widespread application of Inertial measurement Units (IMUs), IMU-based human localization has become critically important in environments lacking Global Navigation Satellite systems (GNSS) signals. Methods such as UWB/WIFI and other anchor-based localization have been employed to enhance the positioning accuracy. However, these methods are susceptible to the environmental interference and increased costs. In contrast, SINS-based localization methods eliminate reliance on the external data. However, this method can suffer from drift errors due to cumulative integration errors. Inertial navigation error correction techniques like Zero Detection Update Technology (ZUPT) provide potential solutions to address drift errors. This paper proposes an error correction method based on the multithreshold zero-velocity detection and Square Root Cubature Kalman Filter (SRCKF) updates. Compared to the single fixed threshold detection, the multi-threshold zero-velocity detection reduces the likelihood of missed zero velocity detection and false alarms, providing accurate time intervals for error correction. Experimental results demonstrate that the SRCKF-based algorithm reduces position deviation to approximately 0.3146 meters, corresponding to an error ratio of1.14%. The proposed method enables cost-effective and accurate pedestrian localization, driving advancements in the field. © 2023 IEEE.

关键词： Cost effectiveness

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Non-convex Optimization Based On Deep Koopman Operator

Non-convex Optimization Based On Deep Koopman Operator

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Jun Guo Yubin Jia Panxiao Yong Jun Zhou Zhimin Liu School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education Southeast University Nanjing China

Non-convex optimization problems are prevalent in various fields, and finding the global optimal solution for such problems remains challenging. This paper proposes an optimization method based on deep Koopman operator, which leverages the power of deep neural networks to provide a data-driven architecture for the Koopman function. The Koopman operator is used to linearly represent non-convex problems, and the proposed method utilizes model predictive control to optimize the resulting linear systems. Simulation results show that this method can solve the non-convex optimization problem effectively, quickly and accurately, while obtaining the global optimal solution.

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SDSFusion: A Semantic-Aware Infrared and Visible Image Fusion Network for Degraded Scenes

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IEEE Transactions on Image Processing 2025年 34卷 3139-3153页

作者： Chen, Jun Yang, Liling Yu, Wei Gong, Wenping Cai, Zhanchuan Ma, Jiayi China University of Geosciences School of Automation Wuhan 430074 China Automation for Complex Systems Hubei Key Laboratory of Advanced Control and Intelligent Wuhan 430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan 430074 China China University of Geosciences Faculty of Engineering Wuhan 430074 China Macau University of Science and Technology School of Computer Science and Engineering Macau Macao Wuhan University Electronic Information School Wuhan 430072 China

A single-modal infrared or visible image offers limited representation in scenes with lighting degradation or extreme weather. We propose a multi-modal fusion framework, named SDSFusion, for all-day and all-weather infrared and visible image fusion. SDSFusion exploits the commonality in image processing to achieve enhancement, fusion, and semantic task interaction in a unified framework guided by semantic awareness and multi-scale features and losses. To address the disparity between infrared and visible images in degraded scenes, we differentiate modal features in a unified fusion model. Unlike existing joint fusion methods, we propose an adversarial generative network that refines the reconstruction of low-light images by embedding fused features. It provides feature-level brightness supplementation and image reconstruction to refine brightness and contrast. Extensive experiments in degraded scenes confirm that our approach is superior to state-of-the-art approaches in visual quality and performance, demonstrating the effectiveness of interaction improvement. © 1992-2012 IEEE.

关键词： adversarial generative network image fusion Multi-modal fusion semantic awareness

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