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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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Semantic Segmentation of Historical Landslide Based on Improved U-Net

Semantic Segmentation of Historical Landslide Based on Impro...

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Chinese control Conference (CCC)

作者： Hanqi Qu Chengda Lu Yutong Pan Yuxuan Zeng 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

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.

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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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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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Design and application of a one-stop mobile application sharing platform for steel enterprises

Design and application of a one-stop mobile application shar...

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第42届中国控制会议

作者： Xinzhe Chen Luefeng Chen Jie Hu Qingfeng Yang Min Wu Witold Pedrycz 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 Department of Electrical and Computer Engineering University of Alberta

As China's steel production accounts for an increasing share of the world's output, the intelligent transformation of the steel industry is becoming increasingly urgent. To address issues such as low levels of mobile informationization in steel enterprises and the lack of an industry-specific mobile application platform, it is of great significance to establish a shared mobile application platform for the steel industry. In this paper, the requirements of the platform were analyzed, and the platform's functions were designed. The software design of the platform was then carried out, and the entire mobile application sharing platform was developed, effectively improving the production management efficiency of steel enterprises. The results indicate that the platform can effectively meet the needs of steel enterprises and has significant engineering significance.

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LBM modeling of three-dimensional mixed convection in CZ crystal growth on curvilinear coordinates system

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Results in Physics 2024年 61卷

作者： Zhang, Ni Liu, Ding The Department of Automation Xi'an Key Laboratory of Advanced Control and Intelligent Process Xi'an University of Posts and Telecommunications Xi'an 710121 China The Shaanxi Key Laboratory of Complex System Control and Intelligent of Information Processing Xi'an University of Technology Xi'an 710048 China

A three-dimensional (3D) thermal lattice Boltzmann model of crystal growth is presented to study the magneto-hydrodynamics (MHD) mixed convection in the melt of Czochralski silicon single crystal growth in this paper. In order to solve the problem of lattice Boltzmann method's difficulty in solving the flow of 3D cylindrical cavity, the 3D physical model of crystal growth is transformed from the Cartesian coordinate system to the Curvilinear coordinate system. And the irregular grids in the Cartesian coordinate system are transformed into regular grids in the Curvilinear coordinate system to facilitate the establishment of the Lattice Boltzmann model. Under the above operations, two coupled distribution functions are established to solve the governing equations. Two D3Q19 models are adopted to solve the melt velocity and temperature. And the 3D lattice Boltzmann modeling of crystal growth with cylinder boundary is realized by interpolation in Curvilinear coordinate system. The comparison with the experiment and other references proves that the proposed model and boundary treatment scheme is correct and it proposes a new way for studying the 3D crystal growth or other similar 3D cylindrical cavity simulations. Furthermore, the unstable melt flow for two cases are also simulated in this paper and the critical Reynolds number are also obtained. Results show that the introduction of the transverse magnetic field enhances the stability of the crystal growth system and increases the adjustable range of crystal rotation parameter. The obtained conclusion has an important reference for adjusting the process parameters during the CZ crystal growth. © 2024 The Author(s)

关键词： 3D mixed convection Computer simulation Heat transfer Lattice Boltzmann Method Silicon single crystal growth

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Dynamics Modeling Method of Offshore Drilling Experimental system Based on Double-Layer Stewart Parallel Mechanism

Dynamics Modeling Method of Offshore Drilling Experimental S...

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第42届中国控制会议

作者： Chenxuan Wang Zhejiaqi Ma Chengda Lu Sheng Du Min Wu School of Future Technology 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 School of Automation China University of Geosciences

Establishing the dynamics model of the offshore drilling experimental system can better complete the offshore drilling test in the laboratory environment and reduce the cost of testing.A dynamical modeling method for the offshore drilling experimental system built on the double-layer Stewart parallel mechanism is ***,the kinematic and dynamical characteristics of the double-layer Stewart parallel mechanism are combined with the Lagrange method and the virtual work method to establish the dynamics model of the *** a parameter identification scheme is designed using a nonlinear gray system estimation method based on the trust-domain reflection algorithm,and the model parameters are *** model is downscaled to improve the feasibility of the identification scheme and the accuracy of the identified *** actual experimental system data verify this model's correctness and the model parameters' accuracy.

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A Pipeline Leak Detection Method Based on MGD-KLD and On-Delay Timer

A Pipeline Leak Detection Method Based on MGD-KLD and On-Del...

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Chinese control Conference (CCC)

作者： Jiaqi He Yan Yuan Wenkai Hu 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

Leaks in natural gas pipelines can cause very serious safety accidents, and timely detection and remedial action can greatly reduce the losses. In recent years, pipeline leak detection has received extensive studies. Most methods use pressure sensors or acoustic sensors to detect pipelines, but there are certain limitations on the usage scenarios and detection time delays. On this basis, this paper selects maglev vibration detector to detect the vibration signal of pipelines. The difficulty lies in that, sudden changes in vibration signals due to external disturbances, may lead to false alarms. Therefore, this paper proposes a pipeline leak detection method using Multivariate Gaussian Distribution based Kullback-Leibler Divergence (MGD-KLD) and on-delay timer to reduce false alarms during the detection process. In this paper, by constructing a simulated pipeline platform for leak experiments and applying the above method to process the experimental data, the false alarm rate of pipeline leak detection can be effectively reduced.

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Bounded Tracking of Uncertain Multiagent systems with Time-Delays and Multiplicative Noises

Bounded Tracking of Uncertain Multiagent Systems with Time-D...

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Industrial Cyber-Physical systems (ICPS)

作者： Guoliu Chen Xiaofeng Zong 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 focuses on the bounded tracking control of general linear multi-agent systems(MASs), considering the effects of inevitable communication time-delays, measurement noises, and uncertain disturbances in practical applications. Firstly, the bounded tracking control problem of uncertain MASs under multiplicative noises is transformed into the boundedness problem of stochastic differential delay equations. Then, the upper bound of agent tracking is calculated by means of linear variation, variation of constants formula and stochastic analysis theory, and sufficient conditions are given for the system to achieve the bounded tracking control.

关键词： Sufficient conditions Upper bound Uncertainty Measurement uncertainty Stochastic processes Cyber-physical systems Mathematical models

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Photovoltaic abnormal data cleaning based on fuzzy clustering-quartile algorithm

Photovoltaic abnormal data cleaning based on fuzzy clusterin...

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Industrial Cyber-Physical systems (ICPS)

作者： Yidong Li Danyun Li 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

The irradiance-power curve is an important basis for examining the operating status of photovoltaic power stations. In the actual operation process, sensor failure, abnormal communication and equipment damage will bring a large number of abnormal values to the output data of photovoltaic power plants. It will have a significant impact on a variety of applications based on photovoltaic output data. This paper analyzes the typical outliers on the irradiance-power curve and proposes a photovoltaic output data cleaning method based on fuzzy clustering algorithm and quartile algorithm. By comparing with the quartile method, it is proved that this method can effectively identify abnormal data when there are a large number of outliers in the photovoltaic output data.

关键词： Photovoltaic systems Training Clustering algorithms Prediction algorithms Cleaning Filling Data models

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