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Chinese control Conference (CCC)

作者： Yuming Wu Chao Zhai 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

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.

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ASTARS Aided NOMA Covert Communication Networks

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IEEE Transactions on Vehicular Technology 2025年

作者： Yue, Xinwei Song, Xinlong Zhao, Jingjing Huang, Chongwen Jin, Hongxu Xiang, Wei Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing102206 China Beijing Information Science and Technology University Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing102206 China Beihang University School of Electronic and Information Engineering Beijing100191 China Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China Xidian University State Key Laboratory of Integrated Service Networks Xi'an710071 China Hangzhou310027 China Zunyi Normal University School of Information Engineering Zunyi563006 China La Trobe University School of Computing Engineering and Mathmatical Sciences MelbourneVIC3086 Australia

The active simultaneously transmitting and reflecting surface (STARS) has been proposed as a complement of passive STARS (PSTARS) to inhibit the double path-loss. This paper applies the active STARS (ASTARS) to aid in non-orthogonal multiple access (NOMA) covert communications over cascaded rice fading channels, where two wardens are located on the opposite sides of ASTARS to monitor the transmission information. More specifically, we derive approximate expressions for detection error probability of two wardens. The optimal detection threshold and minimum detection error probability are presented in the worst covert scenarios. The covert transmission rate expressions for a coupe of covert users are further deduced by taking into account imperfect/perfect successive interference cancellation. The experimental simulation results are presented to confirm that: 1) The detection error probability of ASTARS-NOMA networks is superior to that of ASTARS assisted-orthogonal multiple access (ASTARS-OMA) and PSTARS aided NOMA networks;2) As the number of active elements increases, the covert transmission rates of ASTARS-NOMA networks become larger relative to ASTARS-OMA;and 3) ASTARS-NOMA has ability to provide the enhanced system throughput in delay-tolerant transmission mode. © 2025 IEEE.

关键词： Fading channels

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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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Chinese Automation Congress (CAC)

作者： Yao Wang Chao Gan Weihua Cao 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

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.

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Template Matching and Trend Feature Analysis-Based Data Pre-Processing Method for Seismic Wave Detection

Template Matching and Trend Feature Analysis-Based Data Pre-...

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Chinese Automation Congress (CAC)

作者： Zheng Xu Chao Gan Weihua Cao 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

In this paper, a template matching and trend feature analysis-based data pre-processing method for seismic wave detection is proposed with two stages. In the first stage, it involves extracting the rock physical parameters from seismic wave detection results using OCR (Optical Character Recognition) method, and extracting the original rock physical parameters from the raw rock property table using keyword matching method. Using the rock physical parameters as a template, a template matching approach is employed to eliminate abnormal values from the original rock physical parameters. In the next stage, a technique is proposed to extract trend features of rock physical parameters for conducting advanced geological forecasting, which considered the expertise of experts in interpreting seismic wave detection data. Finally, the effectiveness of the proposed method is verified by the compared simulation results.

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Robust Finite-Time Stabilization of Stochastic Parabolic PDE systems via Non-Fragile Spatial Sampled-Data control

Robust Finite-Time Stabilization of Stochastic Parabolic PDE...

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IEEE Conference on Decision and control

作者： Xiaofang Hu Feida Song Leimin Wang 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

This paper addresses the robust finite-time stabi-lization (FTS) issue for stochastic parabolic PDE systems via non-fragile spatial sampled-data control scheme. First, a class of distributed parameter systems characterized by the delayed stochastic parabolic partial differential equation is developed for analyzing the effects of stochastic disturbance, structural uncertainty, and discrete delay on the system performance. Then, a non-fragile spatial sampled-data control scheme is established by setting sampling points in the spatial domain, which effectively saves communication resources and ensures that the closed-loop system maintains good performance when the controller is perturbed. Moreover, based on the partial differential equation theory, stochastic analysis approach, and the extended Wirtinger's inequality technique, several criteria are provided to ensure the robust FTS of stochastic parabolic PDE systems in the mean square sense. Lastly, a numerical example is provided to verify the feasibility of the suggested stabilization criteria and control scheme.

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

State Estimation for Markov Jump Genetic Oscillator Networks...

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Chinese control Conference (CCC)

作者： Banming Ruan Xiongbo Wan 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

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.

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Imbalance control with stratified voltage of modularized CC-to-CV converter for auto and seamless module switching

Imbalance control with stratified voltage of modularized CC-...

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International Conference on Power Electronics (ICPE)

作者： Jie Cai Zhijian Fang Yuangeng Xia Xiaoxian Song 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

Constant current (CC) based power distribution is widely used in the submarine power supply grid for its robustness against cable impedance and short circuit faults. An input-series-output-parallel (ISOP) modularized CC-to-CV converter is be used to provide constant voltage (CV) for the submarine instruments. In this paper, an imbalance control with stratified voltage is proposed for the modularized CC-to-CV converter by switching modules to adjust the power. The power of each power module is decided by the output voltage realizing auto and seamless module switching. Specially, only one module is regulated to adjust the power, other modules are out of control working either in full power or in standby, improving the efficiency for light power conditions. The modeling and analysis of the modularized CC-to-CV converter is also presented, as well as the proposed the control method. Finally, a prototype is built to verify the proposed method.

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Asynchronous Fault Detection for Fuzzy systems Based on Dynamic Event-Triggered Mechanism

Asynchronous Fault Detection for Fuzzy Systems Based on Dyna...

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Chinese control Conference (CCC)

作者： Yuxi Wang Xiongbo Wan School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China

This article investigates the asynchronous fault detection (FD) problem for fuzzy systems with event-triggered mechanism (ETM). A new dynamic ETM (DETM) is adopted to further reduce the waste of network resources. Considering the impact of asynchronous premise variables brought by ETM, a design criterion for fuzzy FD filter (FDF) is derived. A reasonable residual evaluation function is constructed and an appropriate threshold is set. To ensure the error dynamics be asymptotically stable with a prescribed $H_{\infty}$ performance, we construct a new Lyapunov function that contains an internal dynamic variable in the ETM. A sufficient condition satisfying the proposed performance index is derived. Finally, we provide a numerical simulation to verify the effectiveness of the proposed asynchronous FD strategy under dynamic event-triggered (ET) communication.

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Prediction of Silicon Content in Molten Iron of Blast Furnace Based on Multi-dimensional Sequential Characteristic Reconstruction

Prediction of Silicon Content in Molten Iron of Blast Furnac...

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Industrial Cyber-Physical systems (ICPS)

作者： Zhuofu Zhang Weihua Cao Jie Hu Qifu Chen 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

Molten iron is the primary output of blast furnace production. The content of silicon in molten iron clearly correlates with blast furnace temperature. However, due to the intricate conditions of blast furnace production, the silicon content in molten iron is nonlinear and unstable. Therefore, this paper adopts variational mode decomposition (VMD) to decompose and extract the feature information of the real silicon content data of LY Steel in March 2022, then uses Grey Wolf optimization (GWO) algorithm to optimize the parameters of the support vector regression (SVR) prediction model, and takes the decomposed data as model input for experimental verification. By comparing the predicted results with the real historical data of blast furnace production, it is found that the degree of fit is about 94.2%, which offers a new idea for the prediction of silicon content.

关键词： Support vector machines Production Predictive models Blast furnaces Prediction algorithms Feature extraction Silicon

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Displacement Prediction of Landslide Using SARIMA Model Based on Seasonal Characteristic

Displacement Prediction of Landslide Using SARIMA Model Base...

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Chinese control Conference (CCC)

作者： Ruoxi Wu Chengda Lu Wanke Yu Min Wu Xuzhi Lai 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

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.

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