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检索条件"机构=Hubei Key Laboratory of Advanced Control and Intelligent Automation fo Complex 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...

引用

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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Dynamic Event-Triggered Synchronization control for complex Dynamical Networks 42

Dynamic Event-Triggered Synchronization Control for Complex ...

引用

42nd Chinese control Conference, CCC 2023

作者： Yang, Fuxiang 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 explores the finite-time synchronization of a class of discrete-time nonlinear singularly perturbed complex networks using a dynamic event-triggered mechanism (DETM). The DETM is designed to optimize packet transmission, aiming to conserve network resources. By constructing a Lyapunov function considering singularly perturbed parameters (SPPs) and DETM information, a sufficient condition for the dynamics of synchronization error system to be finite-time stable is given. The parameters of the synchronization controller can be determined by solving a set of matrix inequalities. The effectiveness of the proposed controller is demonstrated through a numerical example. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： complex networks

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2023 CAA Symposium on Fault Detection, Supervision and Safety for Technical Processes, SAFEPROCESS 2023

作者： Wang, Zhe Hu, Wenkai Li, Yupeng Wan, Xiongbo Cao, Weihua China University of Geosciences School of Automation 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)9798350337754

Effective identification of faults or abnormal conditions can help operators make corrective decisions and plan equipment maintenance. Sequence matching and cluster analysis are important methods to distinguish different faults. Most existing sequence matching methods mainly focus on alarm event sequences, which reflect the amplitude change characteristics of process data. However, due to the complexity of the equipment and the coupling between variables, alarm event sequences caused by different faults may still assemble each other in a certain extent, which makes it difficult to distinguish faults based on alarms only. To solve this problem, this paper proposes a sequence similarity analysis method combining both alarm and trend events. A qualitative trend representation method is proposed to extract trend changes as trend events. A feature event fusion method is proposed to generate a hybrid sequence to distinguish different fault sequences. The proposed method is evaluated based on data generated by the Tennessee Eastman process model. © 2023 IEEE.

关键词： Cluster analysis

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Model Predictive Load Frequency control for Power systems under New Event-triggered Mechanism† 42

Model Predictive Load Frequency Control for Power Systems un...

引用

42nd Chinese control Conference, CCC 2023

作者： Wang, Ziqian Wei, Fan 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 Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

ISBN: (纸本)9789887581543

In this article, we pay attention to event-based model predictive control (MPC) for load frequency control of multi-area power system. Considering the practical issues, the inputs are subject to hard constraints. A novel dynamic event-triggered mechanism (DETM) which contains an additive internal dynamic variable and an adjusting variable is designed to reduce data transmission burden. The MPC problem is expressed as a 'min-max' optimisation problem. By considering the effects of load disturbances and the DETM, we give the design approach for the controller which integrates H2 and H8 performance indexes through an auxiliary optimization problem. A simulation example is provided to verify the effectiveness of the proposed algorithm. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Model predictive control

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Asynchronous Fault Detection for Fuzzy systems Based on Dynamic Event-Triggered Mechanism 42

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

引用

42nd Chinese control Conference, CCC 2023

作者： Wang, Yuxi 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 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∞ 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. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Fault detection

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

Displacement Prediction of Landslide Using SARIMA Model Base...

引用

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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Anomaly Detection and Alarm Limit Design for In-Hole Bit Bounce Based on Interval Augmented Mahalanobis Distance 4th

Anomaly Detection and Alarm Limit Design for In-Hole Bit B...

引用

Proceedings of the 4th International Conference on Neural Computing for advanced Applications, NCAA 2023

作者： Hu, Bin Hu, Wenkai Zhang, Peng 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)9789819958467

Timely and accurate anomaly detection is of great importance for the safe operation of the drilling process. To detect bit bounce during the drilling process, this paper proposes a method based on interval augmentation Mahalanobis distance. The method first selects process variables that are closely related to bit bounce through mechanism analysis;secondly, data augmentation is performed on the selected data;then, the Mahalanobis distance statistic of normal data is calculated and its distribution threshold is designed using the Kernel Density Estimation method;finally, the Mahalanobis distance is calculated for the augmented online data and compared to the threshold to determine if a bit bounce is present. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Anomaly detection

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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-...

引用

2023 China automation Congress, CAC 2023

作者： Xu, Zheng 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

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. © 2023 IEEE.

关键词： Seismic waves

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Model-free Adaptive control of Dielectric Elastomer Actuator 16th

Model-free Adaptive Control of Dielectric Elastomer Actuator

引用

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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H∞State Estimation for Time-Delayed Static Neural Networks Using an Improved Delay-Product-Type LKF 42

H∞State Estimation for Time-Delayed Static Neural Networks ...

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42nd Chinese control Conference, CCC 2023

作者： Lao, Yong-He Fan, Yu-Long Luo, Liang-Tong 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 is concerned with H∞ performance state estimation of static neural networks with a time-varying delay. First, a PI estimator with exponential term is used to estimate neuron states based on output measurement. Second, an augmented Lyapunov-Krasovskii functional (LKF) containing delay-product-type non-integral terms and single integral terms is constructed by introducing negative definite terms. After that, a criterion with less conservatism is derived based on extended reciprocally convex matrix inequality. Finally, a numerical example is provided to reveal the effectiveness of the proposed approach. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： State estimation

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