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第三十八届中国控制会议

作者： Peilun Ouyang Weihua Cao Min Wu Chao Gan Fawen Wang School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Hubei Institute of Urban Geological Engineering

Drilling system software is crucial for the complex geological drilling process due to its vital role in improving the drilling efficiency and safety. In this paper, a Model-View-controller(MVC) pattern-based software framework and data architecture of an intelligent drilling system are proposed. First, four main functional requirements, namely, data fusion and visualization, safety assessment and efficiency calculation, efficiency and safety optimization, and coordination control have been analyzed. After that, a four-layers is established based on the above analysis and MVC pattern. Finally, a new online data architecture has been presented at the end of this paper. The proposed software framework and data architecture form a basis for the monitoring of the drilling process.

关键词： Model-View-controller intelligent Drilling Software Framework Data Architecture

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Voltage Sensitivity of Tag Antennas for Inductively Coupled RFID systems

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Journal of Physics: Conference Series 2021年第1期1738卷

作者： Cheng Jin Jixuan Zhu School of Automation China University of Geosciences (Wuhan) Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China

This paper describes a parameter of voltage sensitivity to recognize the performance differences of tag antennas for inductively coupled RFID systems. Based on the equivalent circuit model of the RFID tag and reader, an expression for the voltage sensitivity is educed. Then, the design steps of measuring platform to obtain the voltage sensitivity of tag antenna are introduced in detail. Finally, the feasibility of the proposed method was verified with the market available tag antennas through the measuring platform.

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A Bioinspired retinal neural network for accurately extracting small-target motion information in cluttered backgrounds

arXiv

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arXiv 2021年

作者： Huang, Xiao Qiao, Hong Li, Hui Jiang, Zhihong School of Mechatronical Engineering Advanced Innovation Center for Intelligent Robots and Systems Key Laboratory of Biomimetic Robots and Systems of Chinese Ministry of Education Beijing Institute of Technology Beijing100081 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Beijing Key Laboratory of Research and Application for Robotic Intelligence of’Hand-Eye-Brain’ Interaction Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

—Robust and accurate detection of small moving targets in cluttered moving backgrounds is a significant and challenging problem for robotic visual systems to perform search and tracking tasks. Inspired by the neural circuitry of elementary motion vision in the mammalian retina, this paper proposes a bioinspired retinal neural network based on a new neurodynamics-based temporal filtering and multiform 2-D spatial Gabor filtering. This model can estimate motion direction accurately via only two perpendicular spatiotemporal filtering signals, and respond to small targets of different sizes and velocities through adjusting the dendrite field size of spatial filter. Meanwhile, an algorithm of directionally selective inhibition is proposed to suppress the target-like features in the moving background, which can reduce the influence of background motion effectively. Extensive synthetic and real-data experiments show that the proposed model works stably for small targets of a wider size and velocity range, and has better detection performance than other bioinspired models. Additionally, it can also extract the information of motion direction and motion energy accurately and rapidly. Copyright © 2021, The Authors. All rights reserved.

关键词： Ophthalmology

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Vibration fatigue analysis and research of URV shunt reactor 14

Vibration fatigue analysis and research of URV shunt reactor

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14th IEEE Conference on Industrial Electronics and Applications, ICIEA 2019

作者： Li, Shengmin Zheng, Zhicong Liang, Jining Xiao, Yamin Faculty of Automation and Information Engineering Xi'an University Ot Technology Xi'an710048 China Intelligent Information Processing Shaanxi Key Laboratory of Complex System Control Xi' an710048 China

ISBN: (纸本)9781538694909

Problems of vibration fatigue in UHV reactor is mentioned, comparative analysis of several commonly used fatigue analysis methods, finally, the modal superposition method is used to calculate the structural fatigue caused by vibration. Through analysis of reactor vibration data, the reason for using frequency domain signals as fatigue frequency domain load spectrum to calculate the service life of reactors. In order to perform reactor fatigue analysis, a finite element model of the reactor was first built using ANSYS Workbench finite element integration software, the frequency response function FRF is obtained by harmonic response analysis, and then the vibration time domain signal are transformed into frequency signal as load spectrum input with the power density spectrum, finally, nCode fatigue analysis software is used to estimate the service life of the reactor. © 2019 IEEE.

关键词： Finite element method

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A Bioinspired approach-sensitive neural network for collision detection in cluttered and dynamic backgrounds

arXiv

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arXiv 2021年

—Rapid, accurate and robust detection of looming objects in cluttered moving backgrounds is a significant and challenging problem for robotic visual systems to perform collision detection and avoidance tasks. Inspired by the neural circuit of elementary motion vision in the mammalian retina, this paper proposes a bioinspired approach-sensitive neural network (ASNN) that contains three main contributions. Firstly, a direction-selective visual processing module is built based on the spatiotemporal energy framework, which can estimate motion direction accurately via only two mutually perpendicular spatiotemporal filtering channels. Secondly, a novel approach-sensitive neural network is modeled as a push-pull structure formed by ON and OFF pathways, which responds strongly to approaching motion while insensitivity to lateral motion. Finally, a method of directionally selective inhibition is introduced, which is able to suppress the translational backgrounds effectively. Extensive synthetic and real robotic experiments show that the proposed model is able to not only detect collision accurately and robustly in cluttered and dynamic backgrounds but also extract more collision information like position and direction, for guiding rapid decision making. © 2021, CC BY.

关键词： Mammals

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An Anti-Rolling control Method of Rudder Fin system Based on Adrc Decoupling and Ddpg Parameter Adjustment

SSRN

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SSRN 2022年

作者： Sun, Mingxiao Zhang, Wenyu Zhang, Yongde Luan, Tiantian Yuan, Xiaoliang Li, Xiaogang School of Automation Harbin University of Science and Technology No.52 Xuefu Road Nangang District Heilongjiang Province Harbin City150080 China Heilongjiang Provincial Key Laboratory of Complex Intelligent System and Integration Harbin University of Science and Technology No.52 Xuefu Road Nangang District Heilongjiang Province Harbin City150080 China Key Laboratory of Advanced Manufacturing and Intelligent Technology Ministry of Education Harbin University of Science and Technology No.52 Xuefu Road Nangang District Heilongjiang Province Harbin City150080 China Wuxi CREG Urban Rail Transit Equipment Co. Ltd No. 1061 Jiaoshan Road Xishan Development Zone Jiangsu Province Wuxi214000 China

To achieve high-precision attitude control of ships, the output delay, state coupling, and controller parameter maladjustment of the rudder fin joint anti-rolling system are studied. A predictive anti-rolling method based on active disturbance rejection control (ADRC) and deep deterministic policy gradient (DDPG) is proposed. The external forces on the ship are analyzed, and a three-degree-of-freedom mathematical model considering rolling, yawing, and pitching is established. The model is decoupled using the idea of ADRC total disturbance for the state coupling problem, then the pitch ADRC controller and the roll-yaw predictive observer are designed respectively. In pitch ADRC, the nonlinear extended state observer (NLESO) is used to observe the total disturbance between models. And the total disturbance observations are feedforward compensated to the error control law. As a result, the rapidity of reference output tracking and robustness of total disturbance are realized. The roll-yaw predictive observer solves the output delay by feeding the predicted output back to the controller instead of the actual output. To ensure the accuracy of the prediction output, the DDPG algorithm is introduced to modify the parameters of the prediction observer in real-time. Finally, state constraints are added to solve the rudder angle and fin angle control laws. © 2022, The Authors. All rights reserved.

关键词： controllers

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Observer-based finite time H ∞ control of nonlinear discrete time-varying systems with an adaptive event-triggered Mechanism

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Journal of the Franklin Institute 2020年第16期357卷 11668-11689页

作者： Menghua Chen Hamid Reza Karimi Jian Sun School of Automation Beijing Institute of Technology Beijing 100081 China Department of Mechanical Engineering Politecnico di Milano Milan 20156 Italy Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing 100081 China

The problem of finite time stability and synthesis is discussed for nonlinear discrete time-varying systems by using the T-S fuzzy model. To reduce the communication network resources, two adaptive event-triggered mechanisms (AETMs) are taken into consideration in sensor-to-observer (S/O) and observer-to-controller (O/C) channels. The thresholds of the AETMs are adjusted according to the estimation error rather than some fixed ones. Sufficient conditions for developing an observer-based time-varying control are obtained, which ensure the time-varying error system to be finite time stable and satisfy the H ∞ performance simultaneously. Moreover, using the singular value decomposition technique, recursive linear matrix inequalities conditions are obtained for computing the gains of the controller and observer. Finally, the superiority and applicability of the proposed method are demonstrated by examples.

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Global Rice Multi-Class Segmentation Dataset (RiceSEG): A Comprehensive and Diverse High-Resolution RGB-Annotated Images for the Development and Benchmarking of Rice Segmentation Algorithms

arXiv

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arXiv 2025年

作者： Zhou, Junchi Wang, Haozhou Kato, Yoichiro Nampally, Tejasri Rajalakshmi, P. Balram, M. Katsura, Keisuke Lu, Hao Mu, Yue Yang, Wanneng Gao, Yangmingrui Xiao, Feng Chen, Hongtao Chen, Yuhao Li, Wenjuan Wang, Jingwen Yu, Fenghua Zhou, Jian Wang, Wensheng Hu, Xiaochun Yang, Yuanzhu Ding, Yanfeng Guo, Wei Liu, Shouyang Engineering Research Center of Plant Phenotyping Ministry of Education Jiangsu Collaborative Innovation Center for Modern Crop Production Academy for Advanced Interdisciplinary Studies Sanya Institute of Nanjing Agricultural University Nanjing Agricultural University Nanjing China Graduate School of Agricultural and Life Sciences The University of Tokyo Tokyo Japan Department of Artificial Intelligence Indian Institute of Technology Hyderabad India Department of Electrical Engineering Indian Institute of Technology Hyderabad India Institute of Biotechnology Professor Jayashankar Telangana Agricultural State University Hyderabad India Graduate School of Agriculture Kyoto University Kyoto Japan Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China National Key Laboratory of Crop Genetic Improvement National Center of Plant Gene Research Hubei Key Laboratory of Agricultural Bioinformatics Huazhong Agricultural University Wuhan China State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China the Institute of Agricultural Resources and Regional Planning Chinese Academy of Agricultural Sciences Beijing China Center for Geospatial Information Shenzhen Institutes of Advanced Technology Chinese Academy of Science Shenzhen China School of Information and Electrical Engineering Shenyang Agricultural University Shenyang China Rice Research Institute Jilin Academy of Agricultural Sciences Changchun China Institute of Crop Sciences National Key Facility for Crop Gene Resources and Genetic Improvement Chinese Academy of Agricultural Sciences Beijing China Yuan Long Ping High-Tech Agriculture Co. Ltd. Changsha China

Developing computer vision–based rice phenotyping techniques is crucial for precision field management and accelerating breeding, thereby continuously advancing rice production. Among phenotyping tasks, distinguishing image components is a key prerequisite for characterizing plant growth and development at the organ scale, enabling deeper insights into eco-physiological processes. However, due to the fine structure of rice organs and complex illumination within the canopy, this task remains highly challenging, underscoring the need for a high-quality training dataset. Such datasets are scarce, both due to a lack of large, representative collections of rice field images and the time-intensive nature of annotation. To address this gap, we established the first comprehensive multi-class rice semantic segmentation dataset, RiceSEG. We gathered nearly 50,000 high-resolution, ground-based images from five major rice-growing countries (china, Japan, India, the Philippines, and Tanzania), encompassing over 6,000 genotypes across all growth stages. From these original images, 3,078 representative samples were selected and annotated with six classes (background, green vegetation, senescent vegetation, panicle, weeds, and duckweed) to form the RiceSEG dataset. Notably, the sub-dataset from china spans all major genotypes and rice-growing environments from the northeast to the south. Both state-of-the-art convolutional neural networks and transformer-based semantic segmentation models were used as baselines. While these models perform reasonably well in segmenting background and green vegetation, they face difficulties during the reproductive stage, when canopy structures are more complex and multiple classes are involved. These findings highlight the importance of our dataset for developing specialized segmentation models for rice and other crops. The RiceSEG dataset is publicly available at ***. © 2025, CC BY.

关键词： Semantic Segmentation

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control system Design for Weight on Bit in complex Geological Drilling Process

Control System Design for Weight on Bit in Complex Geologica...

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第三十八届中国控制会议

作者： Sike Ma Min Wu Jun Cheng Luefeng Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

With the increase in drilling depth, the encountered formations become more complicated, and industrial controller for weight on bit has limited precision due to the uncertain and varying formations. In this paper, we design a scheme of control system for weight on bit to achieve higher control precision in complex geological drilling process. A double-loop control structure is introduced, which involves with two system models: a multi-degree-of-freedom lumped parameter drill string model and a finite element bit-rock interaction model. The effect of varying formations on weight on bit is analyzed, and a control strategy for control system is presented in this paper.

关键词： Drilling process weight on bit control system drill string model bit-rock interaction model uncertain formations

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Design of Smart Home Monitoring and control system Based on Zigbee and WIFI

Design of Smart Home Monitoring and Control System Based on ...

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第三十八届中国控制会议

作者： Chentao Li Kaifeng Dong Fang Jin Junlei Song Wenqin Mo School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

Smart Home system is the use of home life associated with hardware and related application technology, the introduction of home appliance automation, remote control, intelligent processing technology in a traditional home environment, to design a provide users with comprehensive information exchange capabilities, in order to enhanced home life safety, comfort and convenience of home systems. At present, there are problems such as complicated wiring, single service, and high price in this field. In response to these problems, this paper designs a smart home system based on Zigbee and WIFI. The system consists of a terminal node, a gateway node and a remote control terminal. The terminal node and the gateway node form a home internal network through Zigbee technology, and the remote control terminal accesses and controls the home internal network through WIFI.

关键词： Smart home Zigbee WIFI Wireless transmission Remote control

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