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arXiv 2023年

作者： Wang, Xihan Xu, Xi Gao, Yu Yang, Yi Yue, Yufeng Fu, Mengyin School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China

Modern object detectors take advantage of rectangular bounding boxes as a conventional way to represent objects. When it comes to fisheye images, rectangular boxes involve more background noise rather than semantic information. Although multi-point representation has been proposed, both the regression accuracy and convergence still perform inferior to the widely used rectangular boxes. In order to further exploit the advantages of multi-point representation for distorted images, Concentric Rectangles Regression Strategy(CRRS) is proposed in this work. We adopt smoother mean loss to allocate weights and discuss the effect of hyper-parameter to prediction results. Moreover, an accurate pixel-level method is designed to obtain irregular IoU for estimating detector performance. Compared with the previous work for muti-point representation, the experiments show that CRRS can improve the training performance both in accurate and stability. We also prove that multi-task weighting strategy facilitates regression process in this design. Source code is at https://***/IN2-ViAUn/Concentric-Rectangles-Loss. Copyright © 2023, The Authors. All rights reserved.

关键词： Semantics

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Discrete-time Linear Tracking control Based on Parallel System Theory

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Applied Mathematics and Nonlinear Sciences 2024年第1期9卷

作者： Gao, Junjie Chen, Mingliang Wei, Qinglai The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment China Nuclear Power Engineering Co. Ltd Guangdong Shenzhen518172 China

Inspired by parallel system theory, a novel parallel tracking controller is presented for discrete-time linear systems in this paper. The core point is to model the time derivative of system control, which makes the control system and the control law completely equivalent in mathematical form. First, the architecture of discrete-time linear parallel tracking control is introduced. Then, in the sight of the reachability of control systems, the pole assignment theorems are given. The merits of this presented method comparing with traditional feedback control are analyzed. Eventually, the efficiency of this method is proved through numerical results. © 2024 Gao, J., Chen, M. & Wei, Q.

关键词： Discrete time control systems

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Application of Deep Learning Method to Estimate Bottomhole Pressure Dynamics of Oil Wells 32

Application of Deep Learning Method to Estimate Bottomhole P...

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32nd IEEE International Symposium on Industrial Electronics, ISIE 2023

作者： Cheng, Haibo Li, Shichao Zeng, Peng Vyatkin, Valeriy State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Luleå University of Technology Electrical and Space Engineering Department of Computer Science Luleå Sweden Aalto University Department of Electrical Engineering and Automation Helsinki Finland

ISBN: (纸本)9798350399714

Surrogate models, which have become an effective and popular method to close loop reservoir management problems, use a data-driven approach to predict dynamic injection and production wells parameters and optimize waterflooding development. In this study, a deep learning-based surrogate model method is proposed to estimate bottomhole pressure (BHP) of production wells in waterflooding reservoirs. Bidirectional long short-term memory (BiLSTM) network, as an efficient deep learning approach, is applied to BHP estimation using fluctuation data. Extended Fourier amplitude sensitivity test (EFAST) method is employed to analyse the influence of different input factors on BHP dynamics, and a reduced dataset is rebuilt to predict BHP parameter based on BiLSTM-EFAST algorithm. The estimation results are tested on a dataset from Volve oilfield in North Sea, and compared with other deep learning methods. The test results indicate that the proposed method can achieve higher prediction accuracy. A reduced dataset-based approach provides a new attempt to reduce model complexity and improve calculation speed for big data-driven surrogate model in oil and gas industry. © 2023 IEEE.

关键词： Long short-term memory

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Pedestrian Trajectory Prediction by Modeling the Interactions using Social LSTM Extensions

Pedestrian Trajectory Prediction by Modeling the Interaction...

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Chinese automation Congress (CAC)

作者： Zeze Si Hongxia Zhao Haina Tang Fenghua Zhu Yisheng Lv Hao Lu State Key Laboratory for Management and Control of Complex Systems Institute of Autamation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academic of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China

In many driving situations, human mobility is an important topic in trajectory prediction. Considering the pedestrian trajectory as a sequence generative task, a prediction algorithm based on Social Long Short-Term Memory (Social LSTM) is implemented. In order to simulate the social interaction between pedestrians, Social Pooling (S-Pooling) is used to aggregate the hidden state of pedestrians, while the attention mechanism is utilized to aggregate information differently according to the importance of surrounding pedestrians. Furthermore, Convolutional Neural Networks (CNN) is introduced into Social LSTM model to consider both the interaction between people and the characteristic of scene scale in the prediction process. Experiments are carried out against baseline methods, and the results demonstrated that combining Social LSTM with attention mechanism or CNN can improve the performance of pedestrian trajectory prediction.

关键词： automation Aggregates Predictive models Prediction algorithms Trajectory Convolutional neural networks Task analysis

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Close-range Hot Spot Detection based on K-neighbor Algorithm and Experiment on Hot Spot Effect 4

Close-range Hot Spot Detection based on K-neighbor Algorithm...

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

作者： Na, ZhiXiong Wang, Dong Wang, ZiYue Wang, Jian Tang, Yu Zhang, ZiHan State Grid e-commerce Co. Ltd Beijing100053 China State Grid Tianjin Electric Power Company China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China

Abnormalities caused by the hot spot effect are very common in the application of photovoltaic modules, which seriously affect the life and power generation efficiency of photovoltaic modules. Therefore, the study of hot spot effect is of great significance to the development of photovoltaic industry in the future. By analyzing the hot spot effect and its causes, this paper lists possible factors that may affect the hot spot effect, uses the K-proximity algorithm for hot spot detection to classify the near-field infrared images obtained in photovoltaic power plants, and designs experiments to explore the influence of several factors on the hot spot effect, the influence characteristics of the shading area and the types of shading objects are deeply explored, and finally a certain summary is made. © 2022 institute of Physics Publishing. All rights reserved.

关键词： Infrared imaging

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A long prediction horizon fcs-mpc algorithm with disturbance preview for three-phase inverters

A long prediction horizon fcs-mpc algorithm with disturbance...

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2023 Jiangsu Annual Conference on automation, JACA 2023

作者： He, Xianghui Huang, Saijin Li, Guanjun Li, Haoyuan Wang, Xiangyu School of Automation Southeast University No. 2 Si Pai Lou Nanjing Jiangsu210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education China Jiangsu Engineering Technology Research Center for Energy Storage Conversion Application China Electric Power Research Institute Nanjing Jiangsu210003 China

ISBN: (纸本)9781839539848

This paper derives an efficient control algorithm to deal with the output voltage tracking control problem of threephase inverters with multiple disturbances (including parametric perturbations of filter, abrupt disturbances caused by load switching and harmonic disturbances brought by unbalanced loads and nonlinear loads). This accomplishment is realized through the long prediction horizon finite-control-set model predictive control (FCS-MPC) and the integration of a composite disturbance observer (CDO) and a disturbance preview model into the sphere decoding algorithm (SDA). This integration facilitates the estimation and prediction of future disturbance behaviors within the inverter system, which addresses the poor disturbance-rejection limitations inherent in conventional SDA approaches employed in previous studies. The algorithm also improves the dynamic performances of the output voltage. Simulations studies are illustrated to demonstrate the feasibility and effectiveness of the proposed control algorithm. Based on the presented results, the algorithm achieves good disturbance rejection capability and maintains small tracking error. © The Institution of Engineering & Technology 2023.

关键词： Disturbance rejection

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Cyber-physical -social systems for smart cities: An overview 1

Cyber-physical -social systems for smart cities: An overview

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Anwar, Noreen Xiong, Gang Lu, Wanze Ye, Peijun Zhao, Hongxia Wei, Qinglai Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation The Cloud Computing Center Chinese Academy of Sciences China School of Artificial Intelligence and Automation Beijing University of Technology Beijing100124 China

ISBN: (纸本)9781665433372

Cyber-physical social systems (CPSS) include cyberspace, physical space, and social space. Since the introduction of CPSS, human relationships with machinery and the physical world have altered as a new paradigm. Recent estimates indicate that approximately 60 percent of the world's population will live in cities by 2030. Large, dense cities can be highly productive, innovative, and very green per capita, hence ideal for our future. However, the huge influx of new people poses enormous challenges to their administrations. Smart cities are becoming a reality, therefore, to achieve higher efficiency, optimum use of resources, management and to strengthen several features of modern towns, several elements of modern cities are automated and integrated into Information and Communications Technology (ICT). Cities and infrastructure are growing all over the world, in providing end-users with increased performance, comfort, visibility and convenience, the Smart Cities concept is critical. This paper will discuss smart cities and the CPSS concept intensively with some of its key technologies, challenges, and further development by using CPSS. © 2021 IEEE.

关键词： Smart city

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Trajectory control of Multi-Axis Robotic Arms Based on Physics-Informed Neural Networks and Nonlinear Model Predictive control

Trajectory Control of Multi-Axis Robotic Arms Based on Physi...

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Chinese automation Congress (CAC)

作者： Yiqing Wang Changqing Xia Xi Jin Chi Xu Yanzhu Zhang School of Automation and Electrical Engineering Shenyang Ligong University Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Multi-axis robotic arms are extensively utilized in intelligent manufacturing scenarios, with trajectory control in flexible scenarios constituting a primary challenge. Physics-Informed Neural Networks (PINNs) represent advanced methods that integrate physical laws with data-driven approaches. Despite their outstanding performance in integrating theory and data, research on their application for controlling robotic arms in complex scenarios remains limited. This paper establishes a nonlinear dynamic model based on the physical relationships between the axes of robotic arms. In the absence of prior data, Sobol sequence random sampling is employed to generate data, which are subsequently trained using PINNs. Considering system noise, the Extended Kalman Filter (EKF) is utilized to predict the next state in noisy environments, and Nonlinear Model Predictive control (NMPC) is implemented to control the robotic arm for trajectory tracking, achieving real-time control. Simulation results demonstrate that the proposed Discrete Physics-Informed Predictive control (DPIPC) method exhibits smaller position and velocity errors with less fluctuation compared to the method in the reference, indicating superior control capabilities.

关键词： Fluctuations Trajectory tracking Simulation Noise Neural networks Manipulators Real-time systems Trajectory Manufacturing Predictive control

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Line-of-sight based three-dimensional path following control for an underactuated robotic dolphin

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Science China(Information Sciences) 2021年第1期64卷 215-226页

作者： Jincun LIU Zhenna LIU Junzhi YU State Key Laboratory for Turbulence and Complex System Department of Mechanics and Engineering ScienceBIC-ESATCollege of EngineeringPeking University Department of Electrical and Automation Shandong Labor Vocational and Technical College State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

This paper investigates the three-dimensional(3-D) path following control problem for an underactuated robotic dolphin. With a comprehensive consideration of the mechanical constraint and swimming principle of the robotic dolphin, a decoupling motion strategy is proposed to produce yaw and pitch maneuvers simultaneously. Then, kinematics and dynamics models for 3-D dolphin-like swimming are established,followed by simulations of the path following control. Furthermore, a novel lookahead based 3-D line-ofsight(LOS) guidance law is developed and implemented to obtain desired attitude angles with its simplicity,intuitiveness, and small computational footprint. Finally, simulation results illustrate the feasibility and effectiveness of the proposed path following control methods.

关键词： robotic dolphin path following 3-D LOS guidance law decoupling motion

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Temperature control System of Thermoelectric Cooler Based on Improved ADRC

Temperature Control System of Thermoelectric Cooler Based on...

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Chinese control and Decision Conference, CCDC

作者： Xiyuan Shan Tao Cai Zhicheng Zong Hongbo Mu School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing China

ISBN: (纸本)9781665478977

Aiming at the problems containing complex working conditions, modeling difficulties and long-time delay of thermoelectric cooler temperature control system, an improved ADRC control method combining ADRC and Smith predictor is proposed in this paper. ADRC deals with the disturbances and uncertain dynamics in the system, SP compensates the time delay to improve the control performance. Compared with the traditional PID controller, the proposed control method has faster response speed and stronger anti-disturbance ability, meanwhile, overcomes the dependence of Smith predictor on object parameters to a certain extent. Through simulation and experimental verification, a good control effect is obtained, which provides a positive guidance of the related application of thermoelectric cooler.

关键词： Robust control Employee welfare Delay effects Simulation Perturbation methods Predictive models control systems

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