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42nd Chinese control Conference, CCC 2023

作者： Peng, Yu-Fei Fan, Yu-Long He, Yong Shangguan, Xing-Chen 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

In this paper, the master-slave synchronization issue of chaotic Lur' e systems with time-varying-delay feedback control is investigated. Firstly, the synchronization problem of chaotic system is transformed into the stability problem of chaotic synchronization error system, which is studied based on Lyapunov-Krasovskii functional (LKF) method. Secondly, a novel augmented LKF with more cross terms that related to time-varying delay is proposed. Based on the application of the relaxation integral inequality and the reciprocally convex matrix inequality, an improved synchronization criterion is derived by using the cubic function negative-determination lemma. Finally, a numerical simulation example demonstrates the effectiveness and advantages of the proposed methods. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Synchronization

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A Novel Hybrid Model for Online Prediction of Rate of Penetration (ROP) in Drilling Process

A Novel Hybrid Model for Online Prediction of Rate of Penetr...

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2023 China Automation Congress, CAC 2023

作者： Wang, Yao Gan, Chao 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 Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

ISBN: (纸本)9798350303759

In this paper, a novel hybrid model is proposed for online prediction of rate of penetration (ROP) in drilling process, which including two parts (online data pre-processing and online hybrid modeling). In the first part, threshold filtering and Savitzky Golay (SG) filtering are both employed to enhance the quality of drilling data considering the expert experience and data characteristics. In the next part, a novel hybrid model with error compensation is established, which is combined the Bingham sub-model and gradient boosting decision tree (GBDT) sub-model. To better capture the dynamic changes of ROP, the hybrid model is updated with moving window strategy. Finally, compared simulation results with well-known ROP prediction models indicate the efficiency of the hybrid model. © 2023 IEEE.

关键词： Error compensation

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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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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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Spatial Resolution Enhancement in OFDR Using a Modified Cohen's Class Analysis

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Journal of Lightwave Technology 2025年第12期43卷 5915-5922页

作者： Liang, Changshuo Wang, Yu Gao, Yan Zhang, Hongjuan Jin, Baoquan Bai, Qing Taiyuan University of Technology College of Electrical and Power Engineering Taiyuan030024 China Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control Systems Ministry of Education and Shanxi Province Taiyuan030024 China Shanxi Transportation Technology Research & Development Co. Ltd Shanxi Taiyuan030006 China

We proposed a demodulation algorithm for optical frequency domain reflectometry (OFDR) sensing system which utilizes a Cohen's class analysis with a modified kernel function to improve spatial resolution and hold a reliable sensing accuracy. With the enhanced time-frequency concentration of Cohen's class analysis compared to conventional short-time Fourier transform (STFT), the trade-off between spatial resolution and sensing accuracy is mitigated. The procedure of the proposed Cohen's class analysis algorithm and the demodulation method with this algorithm are expounded in steps with the advantages explained in theory. The experiment results demonstrate that the OFDR system with the proposed algorithm is capable of sensing strain ranging from 0 to 1000 μϵ at 14 m sensing distance. As a comparison to conventional OFDR demodulation using STFT with window length of 200 points, the spatial resolution has improved from 6.05 mm to 0.16 mm, while the demodulation root mean square error (RMSE) reaches 2.91 × 10-3 nm in the strained area. © 1983-2012 IEEE.

关键词： Mean square error

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Energy-Aware Coverage control of Multi-Agent systems with control Barrier Function 42

Energy-Aware Coverage Control of Multi-Agent Systems with Co...

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42nd Chinese control Conference, CCC 2023

作者： Qu, Chengkai 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 Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

ISBN: (纸本)9789887581543

Geo-hazards have become one of the main disasters endangering the safety of people's lives and property in the world. In order to improve the early warning of disasters, a persistent monitoring method of multi-agent systems is proposed in this work. To ensure that the agent's energy is never exhausted, the set invariance constraint is included in the optimization problem. The goal is to minimize the difference between the actual control input of the robot and the nominal control input corresponding to the task to be performed. Moreover, the control barrier function (CBF) is used to transform the forward invariance of a subset of the robot state space into a control input constraint. The coverage control method in an uncertain environment is verified by numerical simulation. This work provides new insights into effective monitoring and early warning of geo-hazards. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Multi agent systems

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A Novel intelligent Method for Extracting the Multi-Domain Features of Ground Penetrating Radar Data

A Novel Intelligent Method for Extracting the Multi-Domain F...

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2023 China Automation Congress, CAC 2023

作者： Zhang, Run Gan, Chao 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)9798350303759

Ground Penetrating Radar (GPR) features are vital for accurately predicting the formation environment in the tunnel engineering. In this paper, a novel intelligent method for extracting the multi-domain (time domain, time frequency domain, and spatial domain) features of ground penetrating radar data is proposed. Firstly, the GPR exploration data is read to obtain the relative amplitude matrix. Secondly, multi-domain features are obtained using the following methods. The relative amplitude matrix of GPR is averaged by rows to obtain the time domain feature called the average relative amplitude(ARA). The S-transform is used to extract the time frequency domain feature called the average maximum weight frequency(AMWF) of the electromagnetic waves. And the events of the GPR images are highlighted by using Gaussian filtering and edge detection, and the spatial domain feature called the maximum event length(M EL) is obtained through contour detection. Finally, the three extracted multi-domain features are stored in the GPR feature database. Compared simulation results verify the effectiveness of the proposed method. © 2023 IEEE.

关键词： Matrix algebra

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Stability Analysis for Amplidyne Electrical systems with Time-Varying Delay via a Negative-Determination Quadratic Function Lemma 42

Stability Analysis for Amplidyne Electrical Systems with Tim...

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42nd Chinese control Conference, CCC 2023

作者： Huang, Hong-Jian Wang, Hong-Zhang Fan, Yu-Long Xie, Ke-You 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

In this paper, the stability of Amplidyne Electrical systems (AESs) with a time-varying delay is studied. Firstly, the model of AESs with a time-varying delay is established. Secondly, an augmented Lyapunov-Krasovskii functional (LKF) is constructed. Then, a less conservative delay-dependent stability criterion for AESs with a time-varying delay is obtained by utilizing the generalized reciprocally convex combination and an advanced negative-determination quadratic function lemma. Finally, the superiority and effectiveness of the proposed criterion is verified by a numerical example. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Rotating magnetic amplifiers

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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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Trend Features Extraction of Apparent Resistivity in Tunnel Engineering

Trend Features Extraction of Apparent Resistivity in Tunnel ...

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2023 China Automation Congress, CAC 2023

作者： Zhou, Kai Cao, Weihua Gan, Chao 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)9798350303759

Troublesome incidents like sudden water inflows increase the risk of collapse accidents in tunnel excavation. In this study, a data-driven underground water prediction method is proposed based on trend features extracted from apparent resistivity. A novel framework is developed for extracting trend features from the contour lines of apparent resistivity. These trend features are subsequently integrated with numerical features from the resistivity matrix for classification. The effectiveness of the proposed method is demonstrated by apparent resistivity data from real tunnel engineering. The result indicates that the classification accuracy of the proposed method outperforms the method without feature extraction. © 2023 IEEE.

关键词： Feature extraction

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