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Deep Learning-based Moving Object Segmentation:Recent Progress and Research Prospects

Machine Intelligence Research 2023年第3期20卷 335-369页

作者： Rui Jiang Ruixiang Zhu Hu Su Yinlin Li Yuan Xie Wei Zou College of Information Engineering Shanghai Maritime UniversityShanghai201306China School of Computer Science and Technology East China Normal UniversityShanghai200062China Research Center of Precision Sensing and Control Institute of AutomationChinese Academy of SciencesBeijing100190China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing100190China

Moving object segmentation(MOS),aiming at segmenting moving objects from video frames,is an important and challenging task in computer vision and with various *** the development of deep learning(DL),MOS has also entered the era of deep models toward spatiotemporal feature *** paper aims to provide the latest review of recent DL-based MOS methods proposed during the past three ***,we present a more up-to-date categorization based on model characteristics,then compare and discuss each category from feature learning(FL),and model training and evaluation *** FL,the methods reviewed are divided into three types:spatial FL,temporal FL,and spatiotemporal FL,then analyzed from input and model architectures aspects,three input types,and four typical preprocessing subnetworks are *** terms of training,we discuss ideas for enhancing model *** terms of evaluation,based on a previous categorization of scene dependent evaluation and scene independent evaluation,and combined with whether used videos are recorded with static or moving cameras,we further provide four subdivided evaluation setups and analyze that of reviewed *** also show performance comparisons of some reviewed MOS methods and analyze the advantages and disadvantages of reviewed MOS methods in terms of ***,based on the above comparisons and discussions,we present research prospects and future directions.

关键词： Moving object segmentation(MOS) change detection background subtraction deep learning(DL) video understanding

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Anti-disturbance Low Speed Regulation control of PMSMs Using Modified Extended State Observer Based on Rotor Position

Anti-disturbance Low Speed Regulation Control of PMSMs Using...

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2024 Jiangsu Annual Conference on automation, JACA 2024

作者： Xu, Lei Mao, Linxuan Li, Shihua School of Electronic Science and Engineering Southeast University Nanjing210096 China School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China

ISBN: (纸本)9781837242689

A modified extended state observer (ESO) based rotor position algorithm is proposed for improving low speed regulation control performance. The speed signal is often obtained by differentiating the position signal. However, the position signal of encoder with quantization errors results in crawling and shaking at low speeds. Considering quantization error as a type of noise limited their own accuracy, the environmental influences like mechanical vibration and electromagnetic interference also lead to noise in rotor position. The modified ESO method incorporated a Kalman filter (KF) is proposed to reduce the negative impact of noise. Due to differential amplification noise, the position signal is used instead of traditional speed signal for observers design because of its undesirable characteristics at low speed. The modified ESO based on rotor position is used to estimate both speed signal and disturbances to enhance the low speed performance in the presence of disturabances and measurement noise. The friction model is embedded for above integrated structure due to its nonliearity at low speeds. Considering the negative effects of measurement noise and disturbance at low speeds, it has verified that the proposed algorithm has better dynamic and steady-state performance and anti-disturbance ability through simulation. © The Institution of engineering & Technology 2024.

关键词： State estimation

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Self-Supervised Learning with Min-Max Distance Approach for Few-Shot Steel Surface Defects Recognition 43

Self-Supervised Learning with Min-Max Distance Approach for ...

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43rd Chinese control Conference, CCC 2024

作者： Wang, Tianlei Chen, Xinyao Li, Zeliang Zhou, Zhencai Zhou, Zhiheng Wuyi University School of Electronic and Information Engineering Jiangmen China Jiangmen Key Laboratory of Kejie Semiconductor Bonding Technology and Control System Jiangmen China Wuyi University School of Mechanical and Automation Engineering Jiangmen China Guangdong Province Kejie Machinery Automation Company Technical Department Jiangmen China

ISBN: (纸本)9789887581581

Surface defects in steel are crucial for quality inspection in the manufacturing of industrial metal products. While deep learning methods have been extensively studied in this field, the lack of large-scale annotated defect samples imposes significant labeling pressure, making training fully supervised deep models challenging. In response to this issue, we employ self-supervised learning for few-shot recognition, effectively learning representations from limited unlabeled data and achieving defect recognition with a small amount of labeled samples. In particular, we construct Other encoder with multi-view information and Base encoder with single view information based on the distillation self-supervised learning framework through the multi-crops mechanism, and the Other encoders and Base encoders perform information share. Our main contribution is that, based on this framework, we propose a new regularization method to solve the problem of instances deviating from the center of self-supervised clustering by minimizing the maximum instance distance (MMD). In testing, fine-tuning the MMD pre-trained model with a small number of labeled data achieves superior recognition performance on the steel surface defect dataset NEU, significantly outperforming other testing methods. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Self-supervised learning

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Differentially Private Distributed Parameter Estimation

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Journal of Systems Science & Complexity 2023年第1期36卷 187-204页

作者： WANG Jimin TAN Jianwei ZHANG Ji-Feng School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing 100083China Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China

Data privacy is an important issue in control systems,especially when datasets contain sensitive information about *** this paper,the authors are concerned with the differentially private distributed parameter estimation problem,that is,we estimate an unknown parameter while protecting the sensitive information of each ***,the authors propose a distributed stochastic approximation estimation algorithm in the form of the differentially private consensus+innovations(DP-CI),and establish the privacy and convergence property of the proposed ***,it is shown that the proposed algorithm asymptotically unbiased converges in mean-square to the unknown parameter while differential privacy-preserving holds for finite number of ***,the exponentially damping step-size and privacy noise for DP-CI algorithm is *** estimate approximately converges to the unknown parameter with an error proportional to the step-size parameter while differential privacy-preserving holds for all *** tradeoff between accuracy and privacy of the algorithm is effectively ***,a simulation example is provided to verify the effectiveness of the proposed algorithm.

关键词： Differential privacy distributed parameter estimation stochastic approximation

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Stability and performance analysis of the compressed Kalman filter algorithm for sparse stochastic systems

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Science China(Technological Sciences) 2024年第2期67卷 380-394页

作者： LI RongJiang GAN Die XIE SiYu LüJinHu Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China School of Mathematical Sciences University of Chinese Academy of SciencesBeijing 100049China Zhongguancun Laboratory Beijing 100049China School of Aeronautics and Astronautics University of Electronic Science and Technology of ChinaChengdu 611731China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China

This paper considers the problem of estimating unknown sparse time-varying signals for stochastic dynamic *** deal with the challenges of extensive sparsity,we resort to the compressed sensing method and propose a compressed Kalman filter(KF)*** algorithm first compresses the original high-dimensional sparse regression vector via the sensing matrix and then obtains a KF estimate in the compressed low-dimensional ***,the original high-dimensional sparse signals can be well recovered by a reconstruction *** ensure stability and establish upper bounds on the estimation errors,we introduce a compressed excitation condition without imposing independence or stationarity on the system signal,and therefore suitable for feedback *** further present the performance of the compressed KF ***,we show that the mean square compressed tracking error matrix can be approximately calculated by a linear deterministic difference matrix equation,which can be readily evaluated,analyzed,and ***,a numerical example demonstrates that our algorithm outperforms the standard uncompressed KF algorithm and other compressed algorithms for estimating high-dimensional sparse signals.

关键词： sparse signal compressed sensing Kalman filter algorithm compressed excitation condition stochastic stability tracking performance

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Identification modeling of micro thrust cold gas propulsion system 41

Identification modeling of micro thrust cold gas propulsion ...

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第41届中国控制会议

作者： Yuheng Wang Jun Long Tao Wang Xudong Wang Xuhui Liu Bo Wang School of Automation Beijing Institute of Technology Beijing Institute of Control Engineering China Academy of Space Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Cold gas propulsion system is the most widely used propulsion technology for Drag-free spacecraft at home and *** flow output is generated by feedback-loop control of valve opening of piezoelectric proportional valve,and then the micro flow is converted into micro *** to the inherent nonlinear characteristics of piezoelectric actuator in piezoelectric proportional valve,such as hysteresis,creep,temperature drift,as well as the mechanical structure of valve body,fluid flow,there are nonlinear factors,resulting in a nonlinear relationship between the output flow rate of the system and the driving ***,in order to realize control compensation,the nonlinear link in the system should be analyzed first,a reasonable mathematical model should be *** paper analyses the structure of each link of the system and determines the nonlinear factor of the *** analyze the reason why the existing model is not suitable for the whole model of piezoelectric proportional *** with the analysis of the theoretical model,an improved BW model is proposed:the linear ARX model is combined with the BW hysteresis component *** order information of the linear component is determined through the system structure identification,and the unknown parameters in the model are identified by the genetic algorithm,and the curve mean absolute error of fitting is 0.2643 mg/s,and the goodness of fit is 97%.Furthermore,the proposed soft measurement method of valve core displacement can reconstruct the displacement output of valve core without adding displacement sensor,which is used for the design of feedback-loop *** system model established in this paper has guiding significance for the controller design of the cold gas propulsion system,the structural improvement of the piezoelectric proportional valve and the nonlinear compensation.

关键词： Drag-free spacecraft Micro-newton-level piezoelectric cold gas thruster System identification

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DESIGN OF EUTROPHICATION MONITORING PLATFORM FOR CHAOHU CONNECTED RIVER CHANNEL BASED ON LoRa AND DEEP LEARNING

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: Electrical engineering and Computer Science 2023年第3期85卷 285-296页

作者： Kong, Bing Yu, Mei Ye, Song Xu, Xiaoyong Xiang, Rong School of Electronic Engineering Chaohu University Hefei Anhui China Graduate School Angeles University Foundation Manila Philippines School of Chemistry & Material Engineering Chaohu University Hefei Anhui China Industrial Process Control Optimization and Automation Engineering Research Center Chaohu University Hefei Anhui China Key Laboratory of Novel Ceramic and Powder Engineering Chaohu University Anhui China

Traditional methods cannot meet the requirements of real-time monitoring and scientific prevention and control of blue-green algae bloom. This paper uses multi-parameter sensors, LoRa module, 4G module, PLC and shore-based video acquisition device to build a monitoring platform to achieve real-time monitoring of multiple locations and real-time collection of video images;Aiming at the problem of image motion blur caused by shore-based video in water surface fluctuation, the Multi-scale Revolution Neural Network is used to effectively eliminate the visual artifacts of motion blur image, improve the monitoring accuracy of blue-green algae bloom, and meet the actual needs. © 2023, Politechnica University of Bucharest. All rights reserved.

关键词： Eutrophication

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A Multi-Channel Adaptive Cancellation Algorithm for Active Suppression of Motion-Induced Noise in Magnetic Antennas 3

A Multi-Channel Adaptive Cancellation Algorithm for Active S...

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3rd IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2024

作者： Hu, Mingyi Song, Junlei Yan, Yi Liu, Ying Li, Xiaoxue Dong, Kaifeng Jin, Fang Mo, Wenqin Hui, Yajuan School of Automation China University of Geosciences Wuhan430074 China Ministry of Education Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China

ISBN: (纸本)9798331540319

During super low frequency (SLF) magnetic induction communication, the sensitive antenna carried by autonomous underwater vehicles (AUVs) is highly susceptible to vibration, resulting in a large amount of noise in communication signals, which seriously affects communication performance. The type of motion-induced noise typically exhibits randomness and nonlinearity. Based on the strong correlation between the motion-induced noise and the antenna's vibration signal, we propose a multi-channel normalized least mean square (MCNLMS) algorithm. The algorithm utilizes the six degrees of freedom vibration acceleration information from both ends of the magnetic antenna as the reference signal input for the canceller, providing more comprehensive information related to motion-induced noise than the single-channel adaptive noise cancellation algorithm. Experimental results indicate that the MCNLMS algorithm demonstrates effective suppression of the motion-induced noise, achieving an average reduction of approximately 7 dB within the 160-170 Hz communication band. Additionally, it exhibits improved stability and faster convergence. © 2024 IEEE.

关键词： Adaptive algorithms

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Continuous Non-Singular Terminal Sliding Mode control for High Pressure Common Rail Systems Using a FTDO 41

Continuous Non-Singular Terminal Sliding Mode Control for Hi...

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第41届中国控制会议

作者： Zheng Yuan Chen Dai Hao Sun Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

High pressure common rail(HPCR) technology has been widely applied in diesel *** tracking speed and the steady-state fluctuations of the rail pressure determine the performance of the HPCR *** this paper,the fuel injection disturbance which has a main impact on rail pressure fluctuations is fully *** on fluid dynamics and Newtonian mechanics,a nonlinear model of the HPCR system is *** order to suppress the fuel injection disturbance,a finitetime disturbance observer(FTDO) based continuous non-singular terminal sliding mode controller(CNTSMC+FTDO) is designed based on the three-step analysis *** is proved that the system tracking error can converge to the equilibrium point in a finite ***,a group of simulations and experiments are conducted in Simulink and the more realistic AMESim environment respectively and the results verify the effectiveness and feasibility of the proposed algorithm.

关键词： High pressure common rail Non-singular terminal sliding mode FTDO Rail pressure control AMESim

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A Fully Soft Bionic Grasping Device with the Properties of Segmental Bending Shape and Automatically Adjusting Grasping Range

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Journal of Bionic engineering 2022年第5期19卷 1334-1348页

作者： Lingjie Gai Xiaofeng Zong School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China

In this paper,we propose a fully Soft Bionic Grasping Device(SBGD),which has advantages in automatically adjusting the grasping range,variable stiffness,and controllable bending *** device consists of soft gripper structures and a soft bionic bracket *** adopt the local thin-walled design in the soft gripper *** design improves the grippers’bending efficiency,and imitate human finger’s segmental bending *** addition,this work also proposes a pneumatic soft bionic bracket structure,which not only can fix grippers,but also can automatically adjust the grasping space by imitating the human adjacent fingers’opening and closing *** to the above advantages,the SBGD can grasp larger or smaller objects than the regular grasping ***,to grasp small objects reliably,we further present a new Pinching Grasping(PG)*** great performance of the fully SBGD is verified by *** work will promote innovative development of the soft bionic grasping robots,and greatly meet the applications of dexterous grasping multi-size and multi-shape objects.

关键词： Fully soft bionic grasping device Local thin-walled grippers Soft bionic bracket Adjust grasping range automatically Segmental bending shape New pinching grasping method

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