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2023 Jiangsu Annual Conference on automation, JACA 2023

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)9781839539848

This paper presents an enhanced friction compensation anti-disturbance control strategy for improving the speed regulation control performance of a permanent magnet synchronous motor operating in low-speed mode. This is achieved via friction modelling and lumped disturbance compensation by seamlessly integrating extended state observer (ESO) and Kalman filter algorithms. Considering that nonlinear friction torque can not be ignored at low speeds, a piece-wise linearized friction model is first established based on speed estimation of Kalman filter and ESO. Then feed-forward compensation of friction torque and lumped disturbance estimation is conducted to reduce speed fluctuation during load changes at low speeds. Comparative simulation studies in the presence of measurement noises, external disturbances and nonlinear friction torque are conducted to validate the proposed algorithm with improved performance. © The Institution of engineering & Technology 2023.

关键词： Kalman filters

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Pedestrian object detection algorithm based on lightweight YOLOv7 in complex street scenarios

Pedestrian object detection algorithm based on lightweight Y...

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2023 International Conference on Algorithm, Imaging Processing, and Machine Vision, AIPMV 2023

作者： Cheng, Shangqi Niu, Hongxia Key Laboratory of Opt-Electronic Technology and Intelligent Control of Ministry of Education Lanzhou Jiaotong University Lanzhou730070 China Key Laboratory of Plateau Traffic Information Engineering and Control of Gansu Province Lanzhou730070 China School of Automation and Electrical Engineering Lanzhou Jiaotong University Lanzhou730070 China

ISBN: (纸本)9781510672444

In view of the problems of excessive parameter setting and large calculation of YOLOv7 in pedestrian object detection in complex street scenarios, this paper proposes a lightweight method to improve YOLOv7 algorithm. Under the YOLOv7 framework, Partial Convolution (PConv) is integrated into the convolution of the original algorithm, replacing part of the convolution in the original convolution layer, and the SEAttention attention module is introduced to ensure the detection accuracy of the lightweight algorithm. The experimental results on the home-made data set show that, compared with the original YOLOv7 algorithm, the number of model parameters decreased by 11.0% in the improved YOLOv7 algorithm, and the algorithm calculation volume decreased by 19.4%, while ensuring the high accuracy of the original YOLOv7 algorithm. In this paper, the algorithm reduces the number of parameters and calculations, and achieves the balance of lightweight and accuracy. © 2024 SPIE.

关键词： Convolution

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Thermal control of Offshore Floating Photovoltaic Inverters Based on Single-Phase Immersion Cooling 25

Thermal Control of Offshore Floating Photovoltaic Inverters ...

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25th IEEE China Conference on System Simulation Technology and its Application, CCSSTA 2024

作者： Zhang, Laidong Wang, Chunjie Fu, Qiang Chen, Peng Cui, Lin Tianjin University of Technology Tianjin Key Laboratory of New Energy Power Conversion Transmission and Intelligent Control School of Electrical Engineering and Automation Tianjin China National Ocean Technology Center Tianjin China

ISBN: (纸本)9798350366600

Offshore floating photovoltaic (FPV) inverters face more severe heat accumulation and temperature rise problems due to the upgrade of protection level. Current research mainly focuses on the structural changes of the heat sinks, but this can exacerbate water accumulation and salt deposition, accelerating corrosion and limiting its heat dissipation performance. Therefore, this paper proposes a single-phase immersion cooling scheme. The proposed scheme involved the selection of three coolants: FC-40, Novec-7700, and PMX561, which are subjected to rigorous thermal simulation analyses under 35 C. Compared with the original inverter model, the junction temperature of the IGBT module in the new models is reduced by 3.0 C, 3.1 C and 2.2 C, respectively. Meanwhile, the junction temperature of the bus capacitor is reduced by 15.5 C, 15.9 C and 12.0 C, respectively. The temperature of the remaining components is also improved significantly. This result validates the effectiveness of the scheme proposed in this paper. © 2024 IEEE.

关键词： Seawater corrosion

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Cooperative Hierarchical Coverage control of Multi-Agent Systems with Non-holonomic Constraints in Poriferous Environments

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IEEE Transactions on control of Network Systems 2025年第2期12卷 1512-1520页

作者： Zou, Jiayu Zhang, Hai-Tao Zhai, Chao Xing, Ning Ma, Yong Liu, Xingjian Huazhong University of Science and Technology School of Artificial Intelligence and Automation The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China China University of Geosciences School of Automation China The MOE Engineering Research Center of Intelligent Technology for Geo-Exploration Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Academician Workstation of China COSCO Shipping Corporation Ltd. Shanghai200120 China Wuhan University of Technology Sanya Science and Education Innovation Park Sanya572000 China Wuhan University of Technology Chongqing Research Institute Chongqing401120 China

It has long posed a challenging task to optimally deploy multi-agent systems (MASs) to cooperatively coverage poriferous environments in real cooperative detection applications. In response to this challenge, this paper proposes a hierarchical coverage control (HCC) protocol for MASs to perform sector-based coverage operations. First, a distributed Voronoi partition-based sweep-and-assign protocol, combined with a sectorial partition method, is developed, enabling the segmentation of a whole poriferous region into multiple sectorial sub-subregions. Following this procedure, an extreme search scheme is developed to determine the optimal amount of agents for each subregion. After this allocation, a distributed controller is proposed to deploy the agents, considering non-holonomic constraints, into designated niche positions. Additionally, sufficient conditions are derived to guarantee the asymptotical stability of the present HCC. The analytical challenge of the present study stems from the non-convex characteristics inherent in the loss function induced by porous environments. This non-convexity renders the task of globally optimizing the assignment of MASs intractable. Finally, numerical simulations are conducted to validate the effectiveness of the present coverage control approach. © 2014 IEEE.

关键词： Nonlinear control systems

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Exchange Strategies for Multi-Colony Ant Algorithms in Dynamic Environments 13

Exchange Strategies for Multi-Colony Ant Algorithms in Dynam...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Mavrovouniotis, Michalis Li, Changhe Yazdani, Danial Handjimitsis, Diofantos Eratosthenes Centre of Excellence Limassol Cyprus Cyprus University of Technology Department of Civil Engineering and Geomatics Limassol Cyprus School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China University of Technology Sydney Faculty of Engineering & Information Technology Sydney Australia

ISBN: (纸本)9798350308365

In dynamic optimization problems where optimal solutions change over time, traditional ant colony optimization (ACO) algorithms face limitations. This study explores the adaptation of multi-colony ACO algorithms, known for their enhanced search capabilities in stationary problems, to tackle optimization problems in dynamic environments. Various strategies for exchanging information between colonies, which is a critical factor influencing algorithm performance, are investigated. Using the dynamic traveling salesman problem as a foundation, we generate test cases to reflect real-world complexities. Our results on a set of problem instances reveal that the choice of communication strategy between colonies significantly impacts the adaptability and efficiency of multi-colony ACO algorithms in tracking moving optimum. © 2024 IEEE.

关键词： Ant colony optimization

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Smooth quadrotor trajectory generation for tracking a moving target in cluttered environments

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Science China(Information Sciences) 2021年第7期64卷 132-147页

作者： Lele XI Zhihong PENG Lei JIAO Ben M.CHEN School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System Peng Cheng Laboratory Department of Mechanical and Automation Engineering The Chinese University of Hong Kong

In this paper, we present a trajectory generation method of a quadrotor, based on the optimal smoothing B-spline, for tracking a moving target with consideration of relative tracking pattern or limited field of view of the onboard sensor in cluttered environments. Compared to existing methods, safe flying zone,vehicle physical limits, and smoothness are fully considered to guarantee flight safety, kinodynamic feasibility, and tracking performance. To tackle the cluttered environments, a parallel particle swarm optimization algorithm is applied to find the feasible waypoints that the generated trajectory should be as close to as possible, with consideration of the target's future state as well as obstacles to trade off the tracking performance and flight safety. Then, a sequential motion planning method, considering the above constraints, is applied and embedded into a cost function for solving the problem of robust tracking trajectory generation for the quadrotor via a convex optimization approach. The feasibility and effectiveness of the proposed method are verified by numerical simulations.

关键词： quadrotor target tracking trajectory generation B-spline convex optimization

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Digital Twin based Train Delay Prediction System:Design and Realization 41

Digital Twin based Train Delay Prediction System:Design and ...

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第41届中国控制会议

作者： Shuai Chen Xingtang Wu Min Zhou Haifeng Song Hairong Dong State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University School of Automation Science and Electrical Engineering Beihang University School of Electronic Information Engineering Beihang University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

This paper proposes a digital twin-based train delay prediction system for a high-speed railway network to realize real-time train delay ***,a deep learning model is proposed for delay prediction,whose input is the current state of the system,while output,is the predicted *** a system following the digital twin perspective is designed to observe the train operation state and transmit the state information to the delay prediction unit to fulfill the delay prediction *** architecture of the digital twin system is designed,and the actual infrastructure data and *** data of the Beijing Railway Bureau are adopted to construct a prototype *** function of the system is verified with numerous experiments.

关键词： High-speed railway train delay prediction digital twin

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Identification Method of Electric Meter Reading Based on YOLOv7 and DCNN 6

Identification Method of Electric Meter Reading Based on YOL...

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6th Asia Symposium on Image Processing, ASIP 2024

作者： Changping, Mu Liqing, Geng Genghuang, Yang Peng, Zhou Tianjin University of Technology and Education Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin300222 China Tianjin University of Technology and Education School of Automation and Electrical Engineering Tianjin300222 China

ISBN: (纸本)9798350376159

Meter reading recognition is an essential indispensable part of intelligent grid inspection systems. However, due to limitations in the installation angles of monitoring cameras, captured images often suffer from angle issues, thereby reducing recognition accuracy. Therefore, this paper proposes a two-stage detection and recognition algorithm based on YOLOv7-tiny and DCNN networks. Firstly, the key point detection algorithm of YOLOv7 is improved by adding the EVC module, which enables the model to extract image features more comprehensively. Utilizing the Wingloss loss function, key point detection of meter reading regions is achieved. Then, perspective transformation is performed on the meter reading regions based on key point coordinate information to correct the images. Secondly, the deep convolutional neural network (DCNN-CTC) algorithm is employed for text recognition in images. Through extensive experiments with actual meter data, the results indicate that compared to YOLOv5 and CRNN methods, the proposed approach can recognize various meter reading information from different shooting angles with an increased accuracy rate of 5.8%. © 2024 IEEE.

关键词： Convolutional neural networks

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Fire Detection Method Based on Depthwise Separable Convolution and YOLOv3

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International Journal of automation and computing 2021年第2期18卷 300-310页

作者： Yue-Yan Qin Jiang-Tao Cao Xiao-Fei Ji School of Information and Control Engineering Liaoning Shihua UniversityFushun 113001China School of Automation Shenyang Aerospace UniversityShenyang 110136China

Recently,video-based fire detection technology has become an important research topic in the field of machine *** paper proposes a method of combining the classification model and target detection model in deep learning for fire ***,the depthwise separable convolution is used to classify fire images,which saves a lot of detection time under the premise of ensuring detection ***,You Only Look Once version 3(YOLOv3)target regression function is used to output the fire position information for the images whose classification result is fire,which avoids the problem that the accuracy of detection cannot be guaranteed by using YOLOv3 for target classification and position *** the same time,the detection time of target regression for images without fire is greatly reduced *** experiments were tested using a network public *** detection accuracy reached 98%and the detection rate reached *** method not only saves the workload of manually extracting flame characteristics,reduces the calculation cost,and reduces the amount of parameters,but also improves the detection accuracy and detection rate.

关键词： Fire detection depthwise separable convolution fire classification You Only Look Once version 3(YOLOv3) target regression

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Research on electricity forecast of large industrial consumers based on combination model 9

Research on electricity forecast of large industrial consume...

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9th International Conference on Energy Materials and Electrical engineering, ICEMEE 2023

作者： Wu, Qi Wang, Dong-Tao Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin University of Technology and Education Tianjin300222 China School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin300222 China

ISBN: (纸本)9781510672765

This paper investigates the application of neural network formulas, supported by statistical basic analysis techniques and machine learning, to forecast the monthly electricity consumption of large industrial consumers in a specific province. Firstly, we utilize the SARIMA model, GM (1,1) model, and LSTM neural network model to individually forecast electricity consumption based on data collected from January 2016 to December 2022. Subsequently, we combine these three models using a weighted technique to create a comprehensive forecasting model. Finally, we evaluate the performance of the model by assessing the maximum prediction error and employing the MAPE analysis criteria. The results demonstrate that the combined model outperforms the alternative models, indicating its superior prediction accuracy. Therefore, the combined model can be effectively employed as a forecasting technique for large industrial consumers in the region to predict electricity consumption for the 12-month period of 2023. This approach presents a novel method for predicting electricity consumption among industrial users in this sector. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Data modeling Power consumption Autoregressive models Education and training Neural networks Performance modeling Power grids Statistical analysis Statistical modeling Sustainability

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