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26th International Conference on Industrial Technology, ICIT 2025

作者： Chen, Yiheng Yin, Fan Chen, Xiaochong Ren, Yi Hu, Jie Wu, Min 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

ISBN: (纸本)9798331521950

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. © 2025 IEEE.

关键词： Particle swarm optimization (PSO)

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GPIO Based Iterative Learning control for Manipulators with Time-Varying Disturbances

GPIO Based Iterative Learning Control for Manipulators with ...

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Chinese control Conference (CCC)

作者： Huangyuwei Lu Zuo Wang Jiankun Sun Xi Xiao Shihua Li School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex systems of Engineering Ministry of Education Nanjing China Shenzhen Research Institute Southeast University Shenzhen China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration Nanjing China

To improve the disturbance rejection ability and repetitive tracking accuracy of manipulators, a composite iterative learning control (ILC) scheme via generalized proportional integral observer (GPIO) is proposed. A high-order polynomial is first employed to model the time-varying disturbances that include unmodeled dynamics, parameter uncertainties and load fluctuations. A GPIO is then designed to estimate the disturbances and high-order time derivatives. By introducing estimations into a PD-type ILC at each iteration, a composite control scheme is obtained, such that the undesirable influence of time-varying disturbances can be effectively attenuated in the repetitive tracking process of manipulators. In this paper, the rigorous stability analysis of the closed-loop system is presented to guarantee that the tracking error exponentially converges to zero as the iteration number tends to infinity. The effectiveness of the proposed control scheme is finally verified by simulation results.

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Road Underground Target Detection in Ground Penetrating Radar Images Based on YOLO Models

Road Underground Target Detection in Ground Penetrating Rada...

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Chinese Automation Congress (CAC)

作者： Ting Li Wei Xue Xinya Yang Dongchang Wu Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

Ground penetrating radar (GPR) is extensively employed for subsurface road target detection, offering benefits such as convenience, nondestructive testing, rapid data acquisition, and superior resolution. Despite these advantages, interpreting GPR data often depends on the expertise of professionals, resulting in low detection efficiency and low accuracy. To address these challenges, this study introduces an intelligent detection technique for GPR images, utilizing an enhanced YOLOv5 framework. First, considering the problems of the small amount of GPR image datasets and the unclear characteristics caused by the complex underground media, a Dense-C3 module is built by utilizing the structure of DenseNet to enhance the network's capability for extracting features. Subsequently, a channel and spatial hybrid attention module is introduced into the backbone for feature refinement and improving the efficiency. Finally, the multi-class focal loss function is devised to enhance the precision in cases of imbalanced sample classes. Experimental results show that the proposed model surpasses the original YOLOv5 model and various contemporary advanced models.

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$H_{\infty}$ control against mixed DoS attacks for cyber-physical systems

$H_{\infty}$ control against mixed DoS attacks for cyber-phy...

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Industrial Cyber-Physical systems (ICPS)

作者： Hui-Ting Wang Chuan-Ke Zhang Yong He School of Automation China University of Geosciences 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

This article focuses on the $H_{\infty}$ control against mixed denial of service (DoS) attacks for cyber-physical systems (CPSs), where attacks are under zero-input and hold-input strategies. By introducing a unified model describing the simultaneous existence of the two attacks, the CPS can be converted to a switched system with one delay. To ensure control performance, the type-dependent average dwell time (ADT) is applied for the first time to pose constraints on the occurrence frequency of DoS attacks. In the meantime, multiple discontinuous Lyapunov functions (MDLFs) are employed. Upon this, the global uniform exponential stability (GUES) and $H_{\infty}$ performance of the closed-loop system are guaranteed. Finally, the effectiveness of our theoretical results is verified by a numerical example.

关键词： Switched systems Time-frequency analysis Stability Cyber-physical systems Delays control theory Closed loop systems

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A multiple-time-scale control strategy for burden distribution and blast supply of a BF

A multiple-time-scale control strategy for burden distributi...

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Chinese control and Decision Conference, CCDC

作者： Yunpeng Guo Jianqi An Guoyu Zhao Min Wu Qingyi Wang School of Automation China University of Geosciences 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

The operations of blast furnaces (BFs) are very vital for the long-term stability of the iron making process. The burden distribution and blast supply are the two major operation systems of BFs. At present, the researches are lack effective adjustment methods for the BF operations combined with burden distribution and blast supply. The burden distribution affects the iron making process on a long time scale, while the blast supply affects the iron making process on a short time scale. This paper presents a multi-time sampling-data adjustment strategy for the BF operations aiming at optimizing GUR on multiple time scales. First, this paper analyzes the relationship between the gas utilization ratio (GUR) and the burden distribution, the blast supply on multiple time scales. Then, this paper establishes a prediction model of GUR on the long time scale and the short time scale based on autoregressive integrated moving average (ARIMA). Next, this paper provides a control strategy of burden distribution and a control strategy of blast supply by a prediction model based on support vector regression (SVR). Finally, this paper makes experiments and applies this method in a real-world BF. The analysis of the results shows the control strategy of the BF operations provides a good guide on making a suitable decision for burden distribution and blast supply.

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Pipeline Anomaly Detection Based on KPCA and Cosine Distance Prototypical Network 26

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

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26th International Conference on Industrial Technology, ICIT 2025

作者： Yi, Kang Liu, Xin Hu, Wenkai Li, Yupeng 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

ISBN: (纸本)9798331521950

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. © 2025 IEEE.

关键词： Frequency domain analysis

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AMG: A Depression Detection Model with Autoencoder and Multi-Head Graph Convolutional Network

AMG: A Depression Detection Model with Autoencoder and Multi...

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Chinese control Conference (CCC)

作者： Han-Guang Wang Qing-Hao Meng Li-Cheng Jin Jian-Bang Wang Hui-Rang Hou Tianjin Key Laboratory of Process Measurement and Control Institute of Robotics and Autonomous Systems School of Electrical and Information Engineering Tianjin University Tianjin China China Southern Power Grid Company Limited Guangzhou China

Depression is a common chronic mental disorder characterized by high prevalence, recurrence, suicide rate, disability rate and heavy disease burden. Depression assessment based on questionnaires is subjective, therefore, a novel framework to is hereby designed to detect depression automatically and obj ectively. The framework first utilizes a two-way autoencoder to extract the hidden features from the original differential entropy features. The new features are used to generate the channel connectivity graph, using the multi-head attention mechanism. Next, the new features and graphs are input into the graph convolutional network (GCN) to aggregate spatial information. Finally, the output from GCN is passed to a fully connected layer and a soft layer to obtain the predicted label. Experiments are performed on Multimodal Open Dataset for Mental-disorder Analysis dataset. A final accuracy of 88.68% and a cross entropy loss of 2.4532 are obtained, when using ten-fold cross validation, outperforming other traditional machine learning methods including SVM, KNN, decision tree.

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Motion Analysis and Experiment of Sheet Small Magnetron Soft Robot 8

Motion Analysis and Experiment of Sheet Small Magnetron Soft...

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8th International Conference on control Science and systems engineering, ICCSSE 2022

作者： Ma, Haoyun Zhang, Pan Wu, Jundong Wang, Yawu School of Automation China University of Geosciences Hubei Wuhan430 074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Hubei Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Hubei Wuhan430074 China

ISBN: (纸本)9781665484138

In the past, most robots used rigid structures. With the development of intelligent materials, more and more soft materials began to be used in the manufacture of robots. Magnetic-driven soft robot is one of its important branches. Because of the flexibility of magnetoelastic composite robots and the harmlessness of magnetic field to human body, a magnetically-controlled soft robot has broad application prospects in medical fields such as disease diagnosis and treatment in human body. A small lamellate magnetic soft robot is designed in this paper with the advantages of small volume, light weight, high deformation, fast and simple manufacture. And it can be driven without wire under the control of the magnetic field formed by the three-dimensional Helmholtz coil. The robot can walk and crawl on the surface of magnetically-controlled. The motion characteristics of the magnetic soft robot such as crawling step length and bending height are analyzed. The data are collected through experiments to analyze the relationship between the control signal and the motion characteristics. © 2022 IEEE.

关键词： Motion analysis

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Joint Optimization of Uplink Spectrum Efficiency and UAV Trajectory in Cell-Free UAV Networks

Joint Optimization of Uplink Spectrum Efficiency and UAV Tra...

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IEEE/ACM Int'l Conference on & Int'l Conference on Cyber, Physical and Social Computing (CPSCom) Green Computing and Communications (GreenCom)

作者： Jian He Chunyu Pan Qian Chen The Key Laboratory of Information and Communication Systems Ministry of Information Industry and the Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China School of Architecture and Transportation Engineering Guilin University of Electronic Technology Guilin China

The flexible mobility characteristics of unmanned aerial vehicle (UAV) lead to frequent handover and inter cell interference issues in traditional cellular based UAV assisted communication systems. Establishing cell-free UAV (CF-UAV) networks without cell boundaries will effectively alleviate this problem and has been an important research. However, the movement of the UAV results in time-varying channels. Therefore, the joint dynamic and reasonable UAV trajectory optimization and power allocation are very important for in CF-UAV networks. The expression of pilot transmission, channel estimation, uplink transmission spectrum efficiency (SE) have been derived based on the assumption of Rician channel between UAVs and access point (AP). SE optimization algorithm for CF-UAV networks combined with the Angle search and multi-UAV trajectory optimization strategy has been proposed in this paper. Simulation results show that the proposed algorithm performs better performance than comparison schemes, which SE improves by 37% compared with Angle search.

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Modeling of Steel Plate Temperature Field for Plate Shape control in Roller Quenching Process

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IFAC-PapersOnLine 2023年第2期56卷 6894-6899页

作者： Wen Zhang Min Wu Sheng Du Luefeng Chen Jie Hu Xuzhi Lai School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan 430074 China

The temperature is of signification to control the plate shape during roller quenching process. The plate shape has an important influence on the use performance of steel plate. This paper presents a temperature field model, which can be used to control the plate shape. Firstly, the cooling mechanism during quenching is analyzed, and the heat transfer coefficients of each surface are obtained. Secondly, the temperature field model is established by using the heat conduction equation, and the cooling uniformity in the width and thickness directions is evaluated. Thirdly, based on the temperature field model and cooling uniformity, a typical plate shape control structure is designed. Finally, the temperature field model is verified, and the results show that this model can accurately simulate the temperature of steel plate.

关键词： Roller quenching process Temperature field model Cooling uniformity Plate shape control

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