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IEEE International Conference on Industrial Technology (ICIT)

作者： Yiheng Chen Fan Yin Xiaochong Chen Yi Ren Jie Hu Min Wu School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

The sccheduling for pushing plan during the coking process critically affects the efficiency and stability of production. However, the complexity with mutiple-stage during production makes it difficult to design an efficient coke pushing plan. To address this issue, this paper proposes a scheduling method based on the particle swarm optimization algorithm. Firstly, the fuzzy c-means clustering is utilized to categorize actual operating conditions as either normal or abnormal, thereby facilitating the scheduling of pushing plan under disparate conditions. Subsequently, the scheduling problem for the pushing plan is transformed into a traveling salesman problem, and scheduling models under various conditions are established. Finally, to accelerate the convergence and enhance the algorithm's global search capability, an adaptive inertia adjustment strategy is employed to dynamically regulate the velocity and position of particles. The proposed method has been implemented in the coking process. Through the analysis of application results, the completion coefficient of pushing plan has been increased by 4.25%, demonstrating that the proposed has advantages in scheduling the pushing plan during the actual coking process.

关键词： Job shop scheduling Heuristic algorithms Clustering algorithms Production Traveling salesman problems Stability analysis Robustness complexity theory Particle swarm optimization Convergence

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Pipeline Anomaly Detection Based on KPCA and Cosine Distance Prototypical Network

Pipeline Anomaly Detection Based on KPCA and Cosine Distance...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Kang Yi Xin Liu Wenkai Hu Yupeng Li School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

Accurately and promptly detecting the pipeline anomaly is crucial to the safe operation of pipeline systems, while a difficulty lies in that many existing methods require massive data for training models. However, pipelines are running under normal state for the most of the time, and labeled pipeline anomaly data is usually scarce. Among the commonly used sensors, vibration sensors are widely utilized in pipeline detection because of their advantages such as easy installation and high sensitivity. However, the vibration signal shows non-stationary characteristics when anomalies occur, and are contaminated by noises, making it difficult to represent the actual state with features extracted from either the time or frequency domain. Accordingly, this paper proposes a pipeline anomaly detection method based on the KPCA (kernel principal component analysis) and cosine distance prototypical network. First, features are extracted from original signals; then, the feature dimension is reduced by KPCA; last, the cosine distance is introduced to the prototypical network for anomaly detection. The effectiveness of the proposed method is demonstrated by case studies involving experimental data.

关键词： Vibrations Training Time-frequency analysis Sensitivity Pipelines Sensor phenomena and characterization Feature extraction Time-domain analysis Anomaly detection Principal component analysis

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Measurement and modeling of magnetic declination error associated with horizontal drift

Measurement and modeling of magnetic declination error assoc...

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2021 International Conference on High Performance Computing and Communication, HPCCE 2021

作者： Qian, Junli Chen, Xingxing Wang, Minggui Ge, Jian Zhou, Chao Zhang, Jiantao School of Automation China University of Geosciences Wuhan Hubei430074 China Hubei Key Laboratory of Advance Control and Intelligent Automation for Complex Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan Hubei430074 China Hubei Earthquake Agency Wuhan Hubei430071 China

ISBN: (数字)9781510652019

ISBN: (纸本)9781510652002

In the long-Term observation of geomagnetic field, the levelness of coil vector magnetometer will affect the measurement of magnetic direction. Therefore, we propose an electrical detection method of instrument non-levelness, which realizes the quantitative calculation of non-levelness by measuring the maximum and minimum values of the resultant magnetic field during detection. Then, a horizontal error model of coil vector magnetometer is constructed, and the mapping from instrument non-levelness to declination measurement error can be realized by vector operation. The results show that when the non-levelness of the instrument is less than 10", the measurement of magnetic declination variation deviates from the real value by 3.4%;When the non-levelness of the instrument is less than 20", the measurement of magnetic declination variation deviates from the real value by 13.5%. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Vectors

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Voltage Sensitivity of Tag Antennas for Inductively Coupled RFID systems 2

Voltage Sensitivity of Tag Antennas for Inductively Coupled ...

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2020 2nd International Conference on Electronics and Communication, Network and Computer Technology, ECNCT 2020

作者： Jin, Cheng Zhu, Jixuan Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 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. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Equivalent circuits

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Fixed-Time and Preassigned-Time Synchronization of Delayed Inertial Neural Networks 36

Fixed-Time and Preassigned-Time Synchronization of Delayed I...

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36th Youth Academic Annual Conference of Chinese Association of automation, YAC 2021

作者： Zeng, Kan Wang, Leimin Cheng, Jiajun China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation Wuhan430074 China

ISBN: (纸本)9781665437127

This paper investigates the fixed-Time synchronization (FXTS) and the preassigned-Time synchronization (PATS) of inertial neural networks (INNs) by improved control strategies. Firstly, using the order-reduce method, a proper Lyapunov function is constructed and a FXTS controller is designed. Then, some novel conditions for TXTS of INNs are derived and a more precise estimate for the settling time are provided. Moreover, depending on the FXTS, another PATS controller is proposed, with which the PATS of INNs is also achieved. Finally, the correctness and validity of the FXTS and PATS results are illustrated by a numerical example. © 2021 IEEE.

关键词： Lyapunov functions

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

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

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On-Line Conference (ONCON), Industrial Electronics Society Annual

作者： Mingyi Hu Junlei Song Yi Yan Ying Liu Xiaoxue Li Kaifeng Dong Fang Jin Wenqin Mo Yajuan Hui School of Automation China University of Geosciences Wuhan China 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 China

ISBN: (数字)9798331540319

ISBN: (纸本)9798331540326

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.

关键词： Vibrations Industrial electronics Correlation Adaptive arrays Magnetic noise Approximation algorithms Noise cancellation Antennas Magnetic susceptibility Convergence

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Multi-Agent Coverage control in Non-Convex Annulus Region with Conformal Mapping

arXiv

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arXiv 2025年

作者： Feng, Xun Zhai, Chao School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems and Engineering Research Center of Intelligent Technology for Geo-exploration Ministry of Education Wuhan430074 China

Efficiently fulfilling coverage tasks in non-convex regions has long been a significant challenge for multi-agent systems (MASs). By leveraging conformal mapping, this paper introduces a novel sectorial coverage formulation to transform a non-convex annulus region into a topologically equivalent one. This approach enables the deployment of MASs in a non-star-shaped region while optimizing coverage performance and achieving load balance among sub-regions. It provides a unique perspective on the partitioned sub-regions to highlight the geodesic convex property of the non-star-shaped region. By utilizing the sectorial partition mechanism and the diffeomorphism property of conformal mapping, a decentralized control law is designed to drive MASs towards a desired configuration, which not only optimizes the global coverage cost but also ensures exponential convergence of equitable workload. Moreover, an iterative search algorithm is developed to identify the optimal approximation of multi-agent deployment in the non-star-shaped region. Theoretical analysis is conducted to confirm the asymptotic stability and global convergence with arbitrary small tolerance of the closed-loop system. Finally, numerical simulations demonstrate the practicality of the proposed coverage formulation with conformal mapping. Copyright © 2025, The Authors. All rights reserved.

关键词： Conformal mapping

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Dynamic Analysis and control of Fractional Order Memristor Hopfield Neural Network 42

Dynamic Analysis and Control of Fractional Order Memristor H...

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42nd Chinese control Conference, CCC 2023

作者： Liu, Feng Cai, Gang Zhou, Feifan Wang, Wei Wang, Hua Yang, Xiuqin School of Automation China University of Geosciences Wuhan430074 China Engineering Research Center of Ministry of Education for Intelligent Technology of Earth Exploration China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan4300748 China Boston University Department of Mechanical Engineering BostonMA02215 United States School of Education Minzu University of China Beijing100081 China

ISBN: (纸本)9789887581543

In this paper, a novel smooth magnetron is introduced to construct a fractional memristor Hopfield neural network (fractional order M-HNN). The local stability of equilibrium point are analyzed theoretically. Taking the memristor coupling strength coefficient and the fractional order as bifurcation parameters, the phase trajectory diagram, the bifurcation diagram of the system are drawn to analyze the influence on the dynamic behavior of the neural network. When the system parameters are fixed, the hyperchaos phenomenon of the fractional order M-HNN model is revealed. Finally, the PD controller is applied to the model to enhance the stability of the system. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Hopfield neural networks

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Accurate Identification and Localization of Transmission Lines under complex Lighting for Distribution Network Power Supply Operation Robots

Accurate Identification and Localization of Transmission Lin...

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2024 china automation Congress, CAC 2024

作者： Liu, Tianhe Chen, Xin Hu, Chenyu Jian, Xu Li, Shengzu Wang, Gang School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Equipment Technology Center State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan430077 China Distribution Department State Grid Hubei Electric Power Co. Ltd. Wuhan Power Supply Company 430070 China

ISBN: (纸本)9798350368604

Accurate identification and position of transmission lines is critical for robots to safely and effectively perform distribution network operations. However, such tasks are often challenged by complex lighting conditions, where depth information can be easily lost. Transmission lines have limited texture features and reflective surfaces, making it difficult to match image feature points. To address these challenges, this paper proposes a visual perception system for weak texture targets under complex lighting, based on an "eye-on-hand" configuration and a depth complementation algorithm. Furthermore, a high-precision identification and localization method for transmission line grasping points is developed, utilizing the fusion of binocular visual color maps and depth maps. The proposed method has been shown to effectively solve the problem of identifying and localizing the grasping points of transmission lines under complex lighting conditions. Experiments demonstrated that the method can improve the localization accuracy to within ±4mm, outperforming other algorithms. The method is characterized as simple and efficient, and it enhances the environmental adaptability of distribution network robots. © 2024 IEEE.

关键词： Binocular vision

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Trajectory-prediction-based Dynamic Tracking of a UGV to a Moving Target under Multi-disturbed Conditions

Trajectory-prediction-based Dynamic Tracking of a UGV to a M...

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IEEE International Conference on Robotics and automation (ICRA)

作者： Jinge Si Bin Li Yongkang Xu Liang Wang Chencheng Deng Shoukun Wang Junzheng Wang State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology School of Automation Beijing China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Tracking dynamic targets poses a significant challenge for Unmanned Ground Vehicles (UGVs). Existing methods often lack research on multi-disturbed conditions. To address this issue, we propose a trajectory-prediction-based dynamic tracking scheme, which includes target localization, trajectory prediction, and UGV control. Firstly, an estimation algorithm based on the Extended Kalman Filter (EKF) is employed to mitigate noise and estimate the absolute states of the target accurately. To enhance robustness, we present an Adaptive Trajectory Prediction (ATP) algorithm based on prediction anchors. In this method, a quantization standard for trajectory disturbance is designed for adaptive control. Subsequently, we iteratively solve prediction anchor points based on two motion models to robustly predict the target trajectory even in the presence of unknown disturbances. Finally, the Linear Time-Varying Model Predictive control (LTV-MPC) is utilized in the UGV controller for dynamic tracking. Experimental results demonstrate that the ATP exhibits superior prediction robustness and accuracy in perturbed environments compared to other prediction algorithms. In addition, the proposed scheme effectively achieves dynamic tracking of the Unmanned Aerial Vehicle (UAV) by the UGV under multi-disturbed conditions. Specifically, when the target moves at a speed of 1.0 m/s, the UGV can maintain a tracking error within 0.346 m.

关键词： Target tracking Accuracy Heuristic algorithms Noise Prediction algorithms Autonomous aerial vehicles Robustness

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