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An Active Suppression Method Considering Input Time-Delay for Stick-Slip Vibration in the Drilling Procedure 42

An Active Suppression Method Considering Input Time-Delay fo...

引用

42nd Chinese control Conference, CCC 2023

作者： Sun, Hao Lu, Chengda He, Zhaoqing Tian, Shengnan Ma, Zhejiaqi 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)9789887581543

This paper uses the wave equation to explain the torsional motion of the drill-string system. Solving the wave equation with the D'Alembert method, a neutral time-delay model of the drill-string system is obtained. The disturbance input, caused by the bit-rock interaction, is given consideration, and an equivalent-input-disturbance (EID) based controller is designed to mitigate the disturbance in the established model. In the actual drilling procedure, the system input time-delay increases as the length of the drill columns increases. If the influence of system input time-delay in the drilling procedure is ignored, it will most likely lead to the drill-string system instability and cause serious consequences. The essential contribution of this paper is the incorporation of input time-delay into the EID based control structure. Considering the system's input time-delay, the proposed model is more practical and has significant implications for stick-slip vibration assessment and control in drilling procedures. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Time delay

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Image Super-Resolution of Residual-Dense Connected Networks in Unmanned Deep-Sea Exploration Equipment 42

Image Super-Resolution of Residual-Dense Connected Networks ...

引用

42nd Chinese control Conference, CCC 2023

作者： Chu, Jiajun Cao, Weihua Gan, Chao Yang, Yulong 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

Deep-sea unmanned exploration equipment is an important tool for exploring and developing the resources in the ocean, and it can survey the deep-sea environment more visually with the help of visual images. However, the complex and variable environment and the low resolution of the underwater lens lead to the poor resolution of the images acquired by the equipment. In this paper, we propose a residual-dense connected method applied to unmanned deep-sea exploration equipment to improve it's image resolution. The method uses dense connections within the residual structure to improve the model detail information acquisition to ensure accuracy and model stability of model. Secondly, through the study of the model performance, a high precision residual-dense connected model with less computational effort is designed. Finally, the model is trained and tested using environmental images in deep-sea conditions, and it is demonstrated that the method can be applied to deep-sea unmanned exploration equipment for fast, accurate, and stable image super-resolution processing. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Image resolution

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Stability Analysis of Delayed T-S Fuzzy systems via the Fuzzy Line-Integral Method 42

Stability Analysis of Delayed T-S Fuzzy Systems via the Fuzz...

引用

42nd Chinese control Conference, CCC 2023

作者： Liu, Zhou-Zhou Jin, Li He, Yong School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

ISBN: (纸本)9789887581543

This paper focuses on the problem of stability analysis for Takagi-Sugeno systems with time-varying delays. Firstly, a suitable Lyapunov-Krasovskii functional (LKF) containing fuzzy line-integral Lyapunov functional is constructed, which can introduce membership functions information while avoiding emerging the time-derivatives of membership functions. Then, a generalized free-matrix-based integral inequality is applied to estimate the derivative of the LKF. As a result, a less conservative stability criterion is obtained. Finally, a numerical example is carried out to illustrate the effectiveness and merits of our method. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Membership functions

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State Estimation for Markov Jump Genetic Oscillator Networks Based on Hidden Markov Model 42

State Estimation for Markov Jump Genetic Oscillator Networks...

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42nd Chinese control Conference, CCC 2023

作者： Ruan, Banming Wan, Xiongbo 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 addresses the problem of state estimation for Markov jump genetic oscillator networks with time-varying delays based on hidden Markov model. Two non-identical types of time-varying delays, that is, the intercellular coupling delay, and the regulatory delay are considered in consideration in genetic oscillator networks. Then a state estimator is designed by solving a set of linear matrix inequalities that can be solved with existing software. Finally, The effectiveness of state estimation approach can then be demonstrated through a numerical example. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Hidden Markov models

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Fault Diagnosis for Industrial Alarm Floods Based on Discrete Hidden Markov Model 42

Fault Diagnosis for Industrial Alarm Floods Based on Discret...

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42nd Chinese control Conference, CCC 2023

作者： Huang, Xiwen Hu, Wenkai Cao, Weihua 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

A fault diagnosis method based on Discrete Hidden Markov Models is proposed in this paper to identify the fault causing alarm flood sequences. The proposed method consists of the following steps: First, the alarm flood data is pre-processed to ensure that all sequences are of uniform length, and a separate Discrete Hidden Markov model is trained for each fault to capture the relationship between the fault and the alarm sequences. Second, given an observation sequence, the log-likelihood probability values under different Discrete Hidden Markov models are calculated and the maximum probability is selected to determine the type of corresponding fault. Last, the feasibility of the proposed method is verified by simulation data obtained from a public industrial model. The results show that the method can effectively identify the faults that trigger alarm floods. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Failure analysis

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Semantic Segmentation of Historical Landslide Based on Improved U-Net 42

Semantic Segmentation of Historical Landslide Based on Impro...

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42nd Chinese control Conference, CCC 2023

作者： Qu, Hanqi Lu, Chengda Pan, Yutong Zeng, Yuxuan 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)9789887581543

Landslide disasters are extremely destructive. Accurate identification of landslides plays an important role in disaster assessment, loss control and post-disaster reconstruction. This paper proposes a semantic segmentation landslide identification method based on improved U-Net. The deep convolution neural network and jump connection method is used for end-to-end semantic segmentation to achieve deep feature extraction and fusion of different receptive fields, thus enriching feature information. SENet modules are adopted to enhance the ability of the model to extract important features, so as to further improve the accuracy of model recognition. Extensive experiments show that our improved U-Net achieves better performance than the original algorithm on our landslide datasets. The results of Iou are improved by 4.12% which demonstrates our work is of great significance for the research of landslide area identification. Finally, the model is deployed to the web and applied to the geological hazard intelligent monitoring system to realize the landslide identification task. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Landslides

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Collaborative SLAM System Based on Shared Priori Maps

Collaborative SLAM System Based on Shared Priori Maps

引用

International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Wu, Chunxu Shou, Yicheng Li, Zhen Liu, Xiangdong School of Automation and Key Laboratory for Intelligent Control and Decision on Complex Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789811966125

Multi-robot system outperforms in efficiency for cooperative task, where the challenging burden of information exchange for surrounding environment is facilitated by collaborative simultaneous localization and mapping (SLAM). However, the utilization of environmental information, i.e., mapping, should be specifically put into efficient use and merged from the viewpoint of computation saving and localization accuracy improvement. Towards these issues, this paper proposes the Collaborative SLAM system based on shared priori maps which includes multi-agent initialization and a new map sharing and reuse mechanism among various active agents in an incremental way. Finally, based on the data set recorded in the actual laboratory environment, the proposed Collaborative SLAM system is evaluated from the perspectives of localization accuracy and computational power consumption. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Mapping

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Evaluation of Landslide Susceptibility Based on SVM with GWO Algorithm 42

Evaluation of Landslide Susceptibility Based on SVM with GWO...

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42nd Chinese control Conference, CCC 2023

作者： Zeng, Yuxuan Lu, Chengda Pan, Yutong Qu, Hanqi 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)9789887581543

Since landslide is one of the most universal natural disasters in China, the study of regional landslide susceptibility evaluation is important to protect people's lives and property. This paper analyzes the geospatial characteristics of the Zigui-Badong section in the Three Gorges. By Pearson correlation analysis methodselects, nine impact factors of landslide susceptibility are extracted from the aspects of topography and geomorphology, geological environment, and hydrological conditions, used to establish the evaluation index system of landslide susceptibility. On the above data basis, the paper applies a support vector machine (SVM) model and an SVM model for gray wolf optimization (GWO) to the susceptibility evaluation of landslides, and product landslide susceptibility index maps according to the results. The research area is divided into four regions by jenks method on the map: high-risk, medium-risk, low-risk, and very low-risk areas. Applying the accuracy, confusion matrix, and receiver operating characteristic (ROC) curve to evaluate the model, The prediction accuracy of the GWO-SVM model and the SVM model is 88.55 % and 82.82 % respectively, the comparison proves that the GWO-SVM model is much more accurate, which can provide a reference for the study of regional landslide susceptibility. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Landslides

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Design and Implementation of Gaussian Filter for Nonlinear System with Randomly Delayed Measurements and Correlated Noises 42

Design and Implementation of Gaussian Filter for Nonlinear S...

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42nd Chinese control Conference, CCC 2023

作者： Cui, Weijie Wang, Xinmei Hu, Qian Du, Fei 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

A new Gaussian approximate (GA) filter for nonlinear systems with one-step randomly delayed measurement and correlated noise is proposed in this paper. Firstly, a general framework of Gaussian filter is designed under Gaussian assumption on the conditional density. Then, the implementation of Gaussian filter is transformed into the approximation of the Gaussian weighted integral in the proposed frame. Secondly, a new cubature Kalman filtering(CKF)algorithm is developed on the basis of the spherical-radial cubature rule. The efficiency and superiority of the proposed method are illustrated in the numerical examples. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Nonlinear systems

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Spatially Dense Multi-Target Track Segment Association Algorithm 42

Spatially Dense Multi-Target Track Segment Association Algor...

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42nd Chinese control Conference, CCC 2023

作者： Yao, Yan Yan, Liping Xia, Yuanqing School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (纸本)9789887581543

In the field of radar data processing, track interruption seriously affects target tracking, track fusion, and other tasks. The existing track segment association algorithms have low correlation accuracy in dense distributed or long-time interruption situations. To this purpose, a dense multi-target track segment association (DMTTSA) algorithm is proposed. Firstly, two identical networks based on the multi-head probability sparse (ProbSparse) self-attention are used to capture the long-term dependencies of the tracks. Then, the bidirectional quadruplet hard sample loss (BiQuaHard loss) is constructed to make the tracks belonging to the same targets closer and the tracks belonging to the different targets farther. Finally, DMTTSA takes the closest track pairs in the feature space as the associated tracks and divides the unassociated tracks into the birth and dead tracks in chronological order. Some comparative experiments are carried out to show the anti-noise performance of the DMTTSA, as well as the effectiveness of solving the problem of dense multi-target track interruption. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Target tracking

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