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42nd Chinese Control Conference, CCC 2023

作者： Pan, Qian-Long Jin, Li He, Yong Liu, Zhou-Zhou 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)9789887581543

This paper investigates the delay-dependent stability of time-delayed load frequency control (LFC) systems with multiple energy structures based on Lyapunov theory and linear matrix inequality (LMI) technology. Firstly, a multi-area delayed LFC model considering multiple renewable energy structures is established. Then, in order to improve the computation efficiency of stability analysis of large scale LFC systems, a new reconstruction technique for system model is proposed. Next, the improved delay-dependent stability criteria are established based on reconstructed model by using the Lyapunov stability theory. Finally, case studies are based on two-area LFC systems. Comparing with the criterion based on the original model without reconstruction, the calculation efficiency of proposed stability criteria has been greatly improved with the cost of small accuracy, and the calculation accuracy is better than the previous methods. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Stability criteria

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Exponential Stability Analysis for Delayed Neural Networks via A Cubic Function Negative-Determination Lemma 42

Exponential Stability Analysis for Delayed Neural Networks v...

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42nd Chinese Control Conference, CCC 2023

作者： Zhao, Wen-Xuan Liu, Yun-Fan Fan, Yu-Long Zhang, Chuan-Ke 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)9789887581543

This paper concerns with the exponential stability of delayed neural networks via Lyapunov-Krasovskii functional (LKF) method. Initially, an improved augmented delay-product-type LKF containing an additional double integral state is established, which introduces more delayed states and has less conservatism. In the LKF's derivative, the function has high order of delay due to the existence of exponent. Thus, in order to obtain tractable linear matrix inequalities, three state vectors are used to reduce the order of the function to cubic. Secondly, to achieve the negative-definiteness requirement, a negative-determination lemma for cubic functions with less conservatism is employed. Then, a less conservative delay-dependent stability criterion for neural networks with time-varying delays is established. Finally, the validity of the proposed delay-dependent stability criterion is illustrated by two numerical examples. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Neural networks

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Displacement Prediction of Landslide Using SARIMA Model Based on Seasonal Characteristic 42

Displacement Prediction of Landslide Using SARIMA Model Base...

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42nd Chinese Control Conference, CCC 2023

作者： Wu, Ruoxi Lu, Chengda Yu, Wanke Wu, Min Lai, Xuzhi 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)9789887581543

Landslide displacement prediction is an important and indispensable part of landslide monitoring and warning. The change of the displacement is always considered being related to inducing factors, which are aimed at improving accuracy of the predicted model. However, the seasonal characteristic of the displacement, which has not been carefully analyzed, reveals the law of inducing factors. In order to gain a deeper understanding of characteristics, the Baijiabao landslide is taken as an example. The variational mode decomposition (VMD) method, which can extract effective information well, is introduced to decompose the displacement. Introducing the seasonal parameters, the seasonal autoregressive integrated moving average (SARIMA) model is established to predict the displacement subseries. Finally, accumulative displacement prediction values are obtained by superimposing the predicted subseries. With higher accuracy and lower error, the VMD-SARIMA model proves a better option in application compared with VMD-ARIMA, SARIMA and ARIMA models. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Variational mode decomposition

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Model-free Adaptive Control of Dielectric Elastomer Actuator 16th

Model-free Adaptive Control of Dielectric Elastomer Actuator

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16th International Conference on intelligent Robotics and Applications, ICIRA 2023

作者： Mao, Dun Zhang, Yue Wu, Jundong Wang, Yawu 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)9789819964918

Soft robots are usually driven by soft actuators, and the dielectric elastomer actuator (DEA) is recognized as one of the most promising soft actuators. However, the DEA has complex nonlinear char- acteristics, which brings great challenges to its control. So, how to use the appropriate method to control the DEA has become a problem worth pondering. This paper proposes three model-free adaptive control (MFAC) methods to realize the tacking control of the DEA. These meth- ods avoid the complex process of establishing the dynamic model of the DEA, and only need the input and output data to control. Thus, these methods have a strong adaptability and generalization ability. To verify the effectiveness of the proposed methods, some simulations are imple- mented. More importantly, some actual experiments are implemented to further demonstrate the validity of the methods. The root-mean-square errors (RMSEs) of the simulation results are less than 0.35%, and the RMSEs of the actual experimental results can be maintained at about 6.5%, which fully reflects the excellence of the proposed methods. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.

关键词： Mean square error

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Convolutional Neural Network Based Detection of Seasonal Features in Time Series Data 11

Convolutional Neural Network Based Detection of Seasonal Fea...

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11th IEEE Global Conference on Consumer Electronics, GCCE 2022

作者： Hu, Kuang Yue, Kun School of Information Science and Engineering Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China

ISBN: (纸本)9781665492324

Seasonal features of various kinds of time-varying nodes in large-scale complex networks could facilitate the effective network optimization. It is necessary to find the nodes with seasonal features from the limited labeled training set. In this paper, we proposed a sequence convolutional neural network model to detect the seasonal features in time series data, as well as the method of time series upscaling and subsequence embedding as data preprocessing. Experimental results show the effectiveness of our proposed model. © 2022 IEEE.

关键词： Embeddings

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Multi-Scale Time Series Segmentation Network Based on Eddy Current Testing for Detecting Surface Metal Defects

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 528-538页

作者： Xiaorui Li Xiaojuan Ban Haoran Qiao Zhaolin Yuan Hong-Ning Dai Chao Yao Yu Guo Mohammad S.Obaidat George Q.Huang the School of Intelligence Science and Technology University of Science and Technology Beijing the Beijing Advanced Innovation Center for Materials Genome Engineering the Key Laboratory of Intelligent Bionic Unmanned Systems and the Institute of Materials Intelligent Technology Liaoning Academy of Materials IEEE the Department of Computer Science Hong Kong Baptist University the School of Computer and Communication Engineering Key Laboratory of Advanced Materials and Devices for Post-Moore Chips Ministry of Education University of Science and Technology Beijing the Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing the School of Computer and Communication Engineering University of Science and Technology Beijing the King Abdullah Ⅱ School of Information Technology The University of Jordan the Department of Computational Intelligence the School of Computing SRM University the School of Engineering The Amity University The Hong Kong Polytechnic University

In high-risk industrial environments like nuclear power plants, precise defect identification and localization are essential for maintaining production stability and safety. However, the complexity of such a harsh environment leads to significant variations in the shape and size of the defects. To address this challenge, we propose the multivariate time series segmentation network(MSSN), which adopts a multiscale convolutional network with multi-stage and depth-separable convolutions for efficient feature extraction through variable-length templates. To tackle the classification difficulty caused by structural signal variance, MSSN employs logarithmic normalization to adjust instance distributions. Furthermore, it integrates classification with smoothing loss functions to accurately identify defect segments amid similar structural and defect signal subsequences. Our algorithm evaluated on both the Mackey-Glass dataset and industrial dataset achieves over 95% localization and demonstrates the capture capability on the synthetic dataset. In a nuclear plant's heat transfer tube dataset, it captures 90% of defect instances with75% middle localization F1 score.

关键词： Eddy current testing nondestructive testing semantic segmentation time series analysis

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Multi-Agent Coverage Control with High-order Voronoi Partitions in Non-convex Environments 42

Multi-Agent Coverage Control with High-order Voronoi Partiti...

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42nd Chinese Control Conference, CCC 2023

作者： Wu, Yuming Zhai, Chao 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)9789887581543

At present, most research on the coverage of multi-agent systems is based on Euclidean distance. This does not consider the existence of obstacles and has great limitations in the application. In this paper, a kind of coverage control problem based on high-order geodesic Voronoi partition is practically investigated. It allows multiple agents to monitor an area with obstacles to achieve the monitoring of the overall environment. As a result, the geodesic distance is introduced as a metric form. Based on the geodesic distance, point-by-point scanning on the layer is taken to achieve high-order Voronoi diagram division. The coverage algorithm can be implemented in a distributed manner through the exchange of location information with each other, and the Lloyd algorithm is added to realize the movement of the sensor toward the optimal position. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Multi agent systems

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Detection of Stealthy False Data Injection Attacks Against Cyber-Physical systems:A Stochastic Coding Scheme

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Journal of systems Science & complexity 2022年第5期35卷 1668-1684页

作者： GUO Haibin PANG Zhonghua SUN Jian LI Jun State Key Lab of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China Beijing Institute of Technology Chongging Innovation Center Chongqing 401120China Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of TechnologyBeijing 100144China China Industrial Control Systems Cyber Emergency Response Team Beijing 100040China

This paper,from the view of a defender,addresses the security problem of cyber-physical systems(CPSs)subject to stealthy false data injection(FDI)attacks that cannot be detected by a residual-based anomaly detector without other defensive *** detect such a class of FDI attacks,a stochastic coding scheme,which codes the sensor measurement with a Gaussian stochastic signal at the sensor side,is proposed to assist an anomaly detector to expose the FDI *** order to ensure the system performance in the normal operational context,a decoder is adopted to decode the coded sensor measurement when received at the controller *** this detection scheme,the residual under the attack can be significantly different from that in the normal situation,and thus trigger an *** design condition of the coding signal covariance is derived to meet the constraints of false alarm rate and attack detection *** minimize the trace of the coding signal covariance,the design problem of the coding signal is converted into a constraint non-convex optimization problem,and an estimation-optimization iteration algorithm is presented to obtain a numerical solution of the coding signal covariance.A numerical example is given to verify the effectiveness of the proposed scheme.

关键词： Attack detection cyber-physical systems(CPSs) stealthy FDI attacks stochastic coding

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Analysis of coupled axial-torsional vibration of drill-string with an inclination angle 41

Analysis of coupled axial-torsional vibration of drill-strin...

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第41届中国控制会议

作者： Jiahao Zhang Chengda Lu Hengyu Huang Jun Gao Min Wu 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 CCTEG Xi'an Research Institute

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Drill-string vibration has a great negative influence on the safety and efficiency of geological *** that the influence of drill-string inclination is not well considered in the literature,this paper develops a novel drill-string vibration model for geological drilling with inclined ***,the correlation between the inclination angle of borehole and the axial and torsional forces on the drill-string is *** on this,a drill-string motion model with the parameters of inclination angle is ***,the bit-rock interaction is considered as two processes,axial cutting and torsional friction,and an axial-torsional coupled bit-rock interaction model with state-dependent time delay is *** combining the established drill-string motion model and bit-rock interaction model,a coupled axial-torsional vibration model of drill-string in inclined borehole is obtained with the effect of borehole wall friction taken into *** drill-string vibration model proposed in this paper is more general,and includes the existing coupled drill-string vibration model of vertical borehole,which is closer to the actual situation.

关键词： drill-string vibration drill-string inclination bit-rock interaction

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Nonlinear Delay-control of Hopf Bifurcation and Stability Switches in a Generlized Logistic Model 8

Nonlinear Delay-control of Hopf Bifurcation and Stability Sw...

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8th Annual International Conference on Network and Information systems for Computers, ICNISC 2022

作者： Li, Shunyi School of Mathematics and Statistics Qiannan Normal University for Nationalities Guizhou China Key Laboratory of Complex Systems and Intelligent Optimization of Guizhou Guizhou Duyun China

ISBN: (纸本)9781665453516

A generlized Logistic model with nonlinear delayed harvest controlling is considered. The conditions for the stability and local Hopf bifurcation of the equilibrium point are obtained. Numerical examples show that our control strategy can not only control the Hopf bifurcation of the system, but also control the stability switches phenomenon. These are all very useful for the survival of the population. © 2022 IEEE.

关键词： Hopf bifurcation

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