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A Data-Driven Lifetime Prediction Method for Thermally Aged SiC MOSFET Applications

A Data-Driven Lifetime Prediction Method for Thermally Aged ...

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Prognostics and System Health Management Conference (PHM)

作者： Wenfa Kang Sen Tan Juan C. Vasquez Josep M. Guerrero Tobias Hertle Thomas Gietzold Andrew Benn Baoze Wei AAU Energy Aalborg University Aalborg Denmark Catalan Institution for Research and Advanced Studies (ICREA) Barcelona Spain Department of Electronic Engineering Technical University of Catalonia (UPC) Barcelona Spain Collins Aerospace HS Elektronik Systeme GmbH Collins Aerospace Electronic Control and Motor Systems (ECMS)

ISBN: (数字)9798350360585

ISBN: (纸本)9798350360592

Power semiconductor switches, such as Metal-Oxide Semiconductor Field-Effect Transistor (MOSFETs), are widely utilized in solid-state power controllers (SSPC) of electric vehicles, aircrafts and trains. Predictive Health Monitoring (PHM), coupled with the reliability analysis of MOSFETs, are of ut-most significance in power electronic systems. Among various PHM indicators, the ON-state resistance of MOSFETs stands out as a vital and indicative harbinger of failure. This paper introduces a data-driven methodology employing a Long-Short Term Memory (LSTM) algorithm to predict the variations of the ON-state resistance. The experimental dataset was derived from subjecting the MOSFET to power cycling under thermal stress conditions. Furthermore, the model's efficacy was scrutinized utilizing a minor fraction of the dataset for training the LSTM algorithm, showcasing robust performance. Additionally, the proposed model was validated across diverse MOSFET degradation datasets, affirming its universal applicability.

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Event-Triggered Attack-Tolerant control for Quadrotor UAV

Event-Triggered Attack-Tolerant Control for Quadrotor UAV

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第40届中国控制会议

作者： Haiming Li Shiqi Zheng Chenghao Zhao Haitao Jian Shihao Wang 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

In view of the loss of speed caused by the attack of the four-rotor UAV executor, an adaptive control method is designed to maintain the altitude and posture of the UAV without the attack diagnostic mechanism. Adaptive event trigger control methods also consider the mechanism of event triggering. The main impact of attacks on UAVs is the loss of thrust from UAVs. The attack-tolerant method designed in this paper can ensure that the tracking error of multi-acting device can maintain altitude and attitude when attacked is gradually convergent. At the same time, the event trigger method reduces the use of communication resources. Simulation proves the validity of the method.

关键词： Adaptive control attack-tolerant method event-triggered quadrotor UAV

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Design of a prediction and optimization system for plate shape in roller quenching process

Design of a prediction and optimization system for plate sha...

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第40届中国控制会议

作者： Wen Zhang Min Wu Cong Chen Sheng Du Luefeng Chen 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

Plate shape is one of the key quality indices of steel plates after *** is of great significance to realize the prediction and optimization of plate shape for obtaining high quality steel *** paper designs a prediction and optimization system for plate shape in roller quenching ***,the roller quenching process is described in detail,the design objectives are analyzed,and the architecture of the system is ***,the system is designed from four parts:the prediction model of plate shape,the comprehensive evaluation model of plate shape,the intelligent optimization model of operating parameters and the case ***,the prediction and optimization system is applied to the industrial *** results of preliminary tests show that the system improves the quality of plate shape.

关键词： Roller quenching process Plate shape prediction Intelligent optimization Case matching

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Deep learning-based spatial modeling method for 3D formation drillability field

Deep learning-based spatial modeling method for 3D formation...

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第40届中国控制会议

作者： Lei Peng Chao Gan Weihua Cao 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

3D formation drillability field is crucial for drilling optimization and control due to its vital role in describing the spatial formation environment. Conventional geostatistical and machine learning methods are introduced to establish the ***, the modeling accuracy should be further improved to meet the high-level requirement of drilling engineering. In this paper, a novel deep learning-based spatial modeling method is proposed for 3D formation drillability field. First of all, the drilling process and its characteristics are described and analyzed. After that, long short-term memory（LSTM）, a deep learning method is proposed to establish the 3D formation drillability field model. The inputs of the model are the ground and depth coordinates and the output of the model is the formation drillability. Finally, 3D modeling and final test experiments are executed and the drilling data are from Xujiawei area, Northeast China. The results show the effectiveness of proposed method in modeling accuracy compared with four conventional methods（Random forest, Support vector regression, Scattered Interpolation, and Kriging）.

关键词： Spatial modeling Formation drillability LSTM 3D field Drilling process

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A Few-Shot Learning Approach for Fault Diagnosis Based on Event Sequences of Alarm Floods

A Few-Shot Learning Approach for Fault Diagnosis Based on Ev...

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第32届中国过程控制会议(CPCC2021)

作者： Guang Yang Wenkai Hu Weihua Cao Min Wu 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

Alarm systems are commonly deployed in modern industrial facilities for monitoring of process ***,due to the presence of nuisance alarms and alarm floods,the efficiency of many real alarm systems is much *** that problems,such as chattering alarms,redundant alarms,and false alarms,can be well solved,alarm floods are still difficult to *** an alarm flood situation,a number of alarms appear and overwhelm the plant operators;as a result,the operator may overlook the critical alarms and thus the situation may get *** paper studies the root cause analysis of alarm floods,and proposes a Few-Shot Learning(FSL) approach to diagnose faults under alarm flood situations based on alarm event sequences extracted from alarm and event(A&E) *** with the existing methods based on continuous-valued process data,the proposed method does not need to conduct feature selection or dimension reduction,and thus is more straightforward and computationally *** addition,the proposed method only requires a few shots of faulty data to train a fault diagnosis model,and thus shows better applicability in *** experimental results on the Vinyl Acetate Monomer(VAM) benchmark dataset showed the superiority of the proposed model against the state-of-the-art approaches.

关键词： Fault diagnosis alarm flood few-shot learning alarm and event data

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Adaptive Event-Triggered control of Virtual Player for Social Motor Coordination in Joint actions

Adaptive Event-Triggered Control of Virtual Player for Socia...

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第40届中国控制会议

作者： Bowen Guo Chao Zhai 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

In this work,an adaptive event-triggered control approach is developed for a virtual player(VP) to generate the human-like trajectories in the mirror game,a simple yet effective paradigm for studying interpersonal *** taking into account individual motor signature,an online control algorithm is designed to produce joint improvised motions with a human player or another virtual player while exhibiting some desired kinematic *** the proposed control algorithm,the control actions can be adaptively switched according to the movement status of ***,stability analysis of the VP model driven by the feedback controller is ***,the proposed control approach is validated by matching the experimental data.

关键词： adaptive event-triggered control virtual player motor coordination joint action

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A long short-term memory based wind power prediction method

A long short-term memory based wind power prediction method

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第40届中国控制会议

作者： Yufeng Huang Min Ding Zhijian Fang Qingyi Wang Zhili Tan Danyun Li 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

Wind power prediction is the basis of power grid energy dispatching. However, wind instability increases the difficulty of wind power prediction. The paper proposes a wind power prediction method based on long and short-term memory network to improve the accuracy of wind power prediction. First, wind power sequence is decomposed by empirical mode decomposition(EMD) method, and the noise in the original sequence was removed by effective component reconstruction. Then, long shortterm memory(LSTM) with the ability of information memory predicts model of wind power sequence. The improved particle swarm optimization algorithm(IPSO) optimized the parameters of LSTM to solve the problem that the parameters of LSTM, such as the number of neurons, the learning rate and the number of iterations, are difficult to determine and thus affect the prediction accuracy of the model. Finally, the proposed EMD-IPSO-LSTM method makes rolling prediction of wind power series of actual wind farm, and the prediction results are compared with other prediction models. The results show that the prediction model has higher accuracy.

关键词： Wind power prediction Long short-term memory Improved particle swarm optimization

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A dulcimer keys positioning method based on improved Roberts operator

A dulcimer keys positioning method based on improved Roberts...

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2021 China automation Congress, CAC 2021

作者： Tang, De Zhang, Ziying Chen, Xin Xiao, Zhe Qin, Mengxi School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan430074 China School of Arts and Communication China University of Geosciences Wuhan430074 China

ISBN: (纸本)9781665426473

It is important for the dulcimer robot to obtain the spatial coordinates of the dulcimer phonemes. However, the traditional manual positioning method is both inefficient and does not meet the intelligence requirements of modern robot. A visual positioning method based on improved Roberts operator is proposed in this paper on account of solving these problems, which can obtain the 3D coordinates of the dulcimer keys in a short time. First, an improved Roberts edge detection operator is designed, which fully detects the edge information of the target by transforming the scale. Further, this paper proposes a dulcimer keys positioning method by fusing RGB and depth image information. This method has a better positioning effect for dulcimer keys with complex background and small size. The experimental results show that the visual positioning method proposed in this paper can effectively identify and locate the dulcimer keys, and it has better robustness to the lighting environment. © 2021 IEEE

关键词： Binocular vision

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Electroencephalogram Emotion Recognition Using Variational Modal Decomposition Based Dispersion Entropy Feature Extraction

Electroencephalogram Emotion Recognition Using Variational M...

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第40届中国控制会议

作者： Si-Jun Hu Zhen-Tao Liu Xue-Wen Ding 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

Electroencephalogram（EEG） emotion recognition has gained considerable attention due to its ability to reflect people’s inner emotional states objectively and *** extraction is a critical step in EEG emotion recognition because of non-stationarity and irregularity of EEG signals.A feature extraction method using Variational Modal Decomposition（VMD）to extract Dispersion Entropy（DispEn） is proposed in this *** EEG signal is decomposed into several components,and DispEn of each component is extracted in eight emotion-related *** method was tested on DEAP dataset in which the EEG emotional states are accessed in Valence-Arousal emotional *** emotional states（i.e.,HVHA,HVLA,LVHA,LVLA） are classified by Support Vector Machine（SVM）.The experimental results show that the accuracy of emotion recognition is 77.87%,which demonstrates its effectiveness.

关键词： EEG Emotion recognition VMD Dispersion Entropy Feature Extraction SVM

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A New Dynamic Event-Triggered Mechanism Based Model Predictive control for systems with Polytopic Uncertainties

A New Dynamic Event-Triggered Mechanism Based Model Predicti...

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第40届中国控制会议

作者： Fan Wei Xiongbo Wan 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

This paper investigates the problem of model predictive control（MPC） for systems with polytopic uncertainties under the event-triggered communication mechanism. To save network resources, a new dynamic event-triggered mechanism（DETM） is proposed, which contains an adaptive internal dynamic variable（IDV） and a time-varying parameter. A "min-max"optimization problem is put forward to dealing with the MPC problem for systems with polytopic uncertainties. With the aid of a Lyapunov-like function dependent on the IDV of the DETM, an auxiliary optimization problem is devised with constraints in terms of linear matrix inequalities. By solving such an auxiliary optimization problem, sub-optimal feedback gains are obtained which ensure the input-to-state practical stability of the closed-loop system. A numerical example is provided to demonstrate the effectiveness of the devised MPC algorithm.

关键词： Model predictive control dynamic event-triggered mechanism networked systems input-to-state practical stability

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