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检索条件"任意字段=2023 6th International Conference on Advanced Algorithms and Control Engineering, ICAACE 2023"

共 292 条记录，以下是241-250 订阅

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A Model-Predictive-Enabled Equivalent-Input-Disturbance Approach for Disturbance Rejection

A Model-Predictive-Enabled Equivalent-Input-Disturbance Appr...

引用

Industrial Cyber-Physical Systems (ICPS)

作者： Yujian Zhou Jinhua She Feng Wang Makoto Iwasaki 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 School of Engineering Tokyo University of Technology Tokyo Japan Department of Electrical and Mechanical Engineering Nagoya Institute of Technology Nagoya Japan

this paper presents a model-predictive-enabled equivalent-input-disturbance (MPEID) method for disturbance rejection. An EID estimator with a state observer estimates the effect of disturbances in a system. the disturbance estimation will not be directly added to the input channel for disturbance rejection. A cost function that considers the disturbance estimation is designed. An MPC controller calculates an optimal control input by minimizing the cost function. the stability condition of the closed-loop system is analyzed based on the Lyapunov stability theory. Simulation results show that our method has better disturbance-rejection performance than an MPC method when the control input is similar.

关键词： Simulation Estimation Optimal control Predictive models Observers Cyber-physical systems Cost function

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Lightweight and Heterogeneous Conversion of Power Transmission Model Based on CATIA V6

Lightweight and Heterogeneous Conversion of Power Transmissi...

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IEEE international conference on Automation, Electronics and Electrical engineering (AUTEEE)

作者： Shan Lin Zhou Zheng Yan Yang Qian Jian Jianye Huang Linting Wu Fujian Power Co. Ltd. Electric Power Research Institute Fujian Fuzhou China

CATIA V6 (Computer-Aided three-Dimensional Interactive Application), as an advanced computer-aided design software, can help engineers quickly realize the design and optimization of power transmission models. this article aims to conduct research on lightweight and heterogeneous conversion of power transmission models based on CATIA V6. this article constructed a control group and two experimental groups, and conducted 10 tests each. the control group used the original CATIA V6 power transmission model as a comparison group. the experimental group 1 lightweighted the model to simplify the structural elements and ensure that accuracy requirements were met. the experimental group 2 used heterogeneous transformation to replace some structural elements with an adaptation framework or chip that adapts to a specific environment. then, the article determined the input parameters and keeps them consistent to ensure the accuracy of the comparison. the results showed that experimental group 1 and experimental group 2 had positive impact on model accuracy, computational efficiency and performance evaluation compared with the control group. this shows that lightweight and heterogeneous conversion have a positive impact on the model, providing useful suggestions and guidance for improving the CATIA V6 power transmission model.

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Analysis of Risk Factors of Railway Trespassing Accidents Based on Multinomial Logit Model 6th

Analysis of Risk Factors of Railway Trespassing Accidents Ba...

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6th international conference on Electrical engineering and Information Technologies for Rail Transportation, EITRT 2023

作者： Wang, Xu Ma, Xiaoping Zhang, Hanqing Chen, Fei State Key Laboratory of Advanced Rail Autonomous Operation Beijing Jiaotong University Beijing100044 China School of Traffic and Transportation Beijing Jiaotong University Beijing100044 China Key Laboratory of Railway Industry of Proactive Safety and Risk Control Beijing Jiaotong University Beijing100044 China

ISBN: (纸本)9789819993109

In order to solve the problem of imprecise alarm of foreign objects in railway encroachment, realize foreign object risk stratification and early warning. the main purpose of this paper is to analyze the trespasser factors, environmental factors and track factors associated with the severity of injuries in railway trespassing accidents from the perspective of trespasser, so as to identify features that rail monitoring needed, and propose optimization measures for accident prevention. this paper uses the Multinomial logit model to identify the factors and characteristics of trespasser injury severity based on Federal Railroad Administration accident record data. the pre-accident acts and location are the most important factors influencing the severity of the accident. Driving is the most common acts in trespassing incidents, while lying, standing and walking have a significant relationship with fatality outcomes. Combinations of some different behaviors and orbital locations can lead to polarization of accident risk with a higher risk of death, and it should be pay more attention when monitoring these features. this paper can be used to determine the relative level of risk for of each feature of illegal trespassing accidents and infer the severity of accident casualties, so as to construct an evaluation index system for foreign body characteristics. this paper helps to improve the detection and early warning accuracy of intrusion accidents by considering trespassers’ acts, weather and track scene types in the framework of railway foreign object video detection, which has practical significance. © Beijing Paike Culture Commu. Co., Ltd. 2024.

关键词： Railroads

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Sound Field control by Using Equivalent Input Disturbance method

Sound Field Control by Using Equivalent Input Disturbance me...

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Industrial Cyber-Physical Systems (ICPS)

作者： Toshiki Watanabe Jinhua She Zewen Wang Department of Sustainable Engineering Tokyo university of technology Japan 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 Laboratory for Future Interdisciplinary Research of Science and Technology (FIRST) Tokyo Institute of Technology Yokohama Kanagawa Japan

Low-frequency noise, such as road noise from automobiles and interior noise from bullet train cars, is detrimental to passenger comfort. Active noise control provides us with a way of suppressing low-frequency noise. It generates a sound of the same amplitude and opposite phase as noise and uses it to cancel the noise. Conventional active noise control is complicated to apply. thus, the objective of this study is to establish a sound field control system by using the equivalent-input-disturbance method. System identification was performed to obtain an ideal plant of a duct. the control system is constructed based on the equivalent-input-disturbance approach with a low-order controller. the experimental results showed a suppression effect of about 50% of the sound field.

关键词： Roads Noise reduction Ducts Channel estimation Auditory system Cyber-physical systems control systems

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control Strategy of Direct-Driven PMSM Wind Turbines Participating in Fast Frequency Response of Power Grid

Control Strategy of Direct-Driven PMSM Wind Turbines Partici...

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Energy, Electrical and Power engineering (CEEPE), international conference on

作者： Heming Yan Feng Ji Hui Pang Wenxuan Jia Chang Lin Xiangyu Pei State Key Laboratory of Advanced Power Transmission Technology State Grid Smart Grid Research Institute Co. Ltd. Beijing China The college of Electrical and Electronic Engineering North China Electric Power University Beijing China Beijing Key Laboratory of DC Grid Technology and Simulation State Grid Smart Grid Research Institute Co. Ltd. Beijing China

the large-scale grid connection of wind power brings challenges to the frequency stability of the power system, the system inertia decreases, the frequency regulation capability deteriorates, and the traditional wind turbine is difficult to meet the frequency regulation demand of the system. To address the problem of slow response of existing wind turbines participating in frequency regulation, this paper proposes a control method for permanent magnet direct-driven wind turbines participating in fast frequency response of the grid, based on power electronic converters equipped with electromagnetic level control speed to rapidly change the electromagnetic torque of the wind turbine rotor according to the system frequency change, increase or decrease the wind turbine speed to fully utilize the stored or released rotational inertia and achieve fast power regulation of the wind turbine. the results of the frequency step simulation of the permanent magnet direct-driven synchronous wind power system show that the fast frequency regulation response time of the control method proposed in this paper can reach the millisecond level.

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Dynamic Sensing Modeling of Dielectric Elastomer Sensors Based on GRU Neural Network

Dynamic Sensing Modeling of Dielectric Elastomer Sensors Bas...

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IEEE international conference of Intelligent Robotic and control engineering (IRCE)

作者： Mingyi Zhang Peng Huang Yawu Wang School of Automation China University of Geosciences Wuhan Hubei China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan Hubei China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan Hubei China

Dielectric elastomer sensor (DES) is a flexible sensor that can perform free bending deformation, thus it has broad application prospects in the fields of medical electronics, wearable devices, soft robots, etc. Previous studies have mostly focused on exploring the static sensing characteristics of the DES. Considering that the DES may be used in dynamic conditions, it is very meaningful to study its dynamic sensing characteristics to broaden its application ranges. In this paper, a dynamic sensing model of the DES is established based on the gate recurrent unit (GRU) neural network. Firstly, the structure of the DES and the construction of the experimental system are introduced. In addition, the dynamic sensing characteristics of the DES are analyzed by conducting several sets of experiments, which shows that the DES has significant rate-dependent hysteresis nonlinearities, multivalued mapping and memory characteristics. After that, the dynamic sensing model of the DES is built based on the GRU neural network to describe the above dynamic sensing characteristics. Next, the dynamic displacement and force sensing models of the DES are trained according to the dynamic displacement-capacitance and dynamic force-capacitance experimental data, respectively. Finally, several experiments are performed to verify the effectiveness and generalization ability of the established dynamic sensing model.

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Prediction model of photovoltaic output power based on VMD-EMD-BiLSTM

Prediction model of photovoltaic output power based on VMD-E...

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Industrial Cyber-Physical Systems (ICPS)

作者： Shaolong Zheng 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 Wuhan China

the accuracy of photovoltaic (PV) power prediction is significantly influenced by the high complexity and volatility of the PV sequence. the existing methods for predicting photoelectric power are difficult to effectively mine and analyze the internal variation law of data. To improve the accuracy of PV power prediction, a new method is proposed that first performs variational mode decomposition (VMD) and empirical mode decomposition (EMD), and then establishes a bi-directional long and short-term memory neural network (BiLSTM) for PV output power prediction. the proposed method extracts the amplitude and frequency characteristics of the PV output power series through VMD. After that, the residual term with strong non-stationarity is generated, which still has more sequence characteristics. the residual term is then decomposed by EMD for the second time to extract more features. Finally, the BiLSTM model is established to conduct bidirectional mining for PV power data and predict PV output power. the actual PV data is used to test the experimental results, which show that the proposed VMD-EMD-BiLSTM prediction model has better prediction performance.

关键词： Photovoltaic systems Empirical mode decomposition Simulation Neural networks Predictive models Cyber-physical systems Prediction algorithms

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Research on Multilevel Degradater Model under Unsupervised Learning

Research on Multilevel Degradater Model under Unsupervised L...

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international conference on Computer Network, Electronic and Automation (ICCNEA)

作者： Jieyi Lv Zhongsheng Wang School of Computer Science and Engineering Xi'an Technological University Xi'an China State and Provincial Joint Engineering Lab. of Advanced Network Monitoring and Control Xi'an Technological University Xi'an China

In most super-resolution experiments, because the data set in the real scene cannot meet the quantity requirements, it is necessary to downsample the high-resolution images using the degradation method to obtain the same proportion of low-resolution images. However, because the same degradation method is used to process images, the processing process of low-resolution images is relatively simple, which is easy to cause model solidification in the subsequent training process. After the training is completed, the generalization ability will be generally low due to the single underlying degradation method. this paper uses the SRMD method to build an unsupervised multilevel degradation, and takes advantage of the adduction network generated in unsupervised learning. After extracting image features, it adopts anisotropic Gaussian fuzzy kernel, bi-cubic subsampling and additive Gaussian noise to compose the degradation training data set. Compared with the traditional bi-cubic PNSR, the performance is improved by 5%. the SSIM value is increased by 3%, and the running speed is increased by 7% on average.

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$H_{\infty}$ control against mixed DoS attacks for cyber-physical systems

$H_{\infty}$ control against mixed DoS attacks for cyber-phy...

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Industrial Cyber-Physical Systems (ICPS)

作者： Hui-Ting Wang Chuan-Ke Zhang Yong He 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 Wuhan China

this article focuses on the $H_{\infty}$ control against mixed denial of service (DoS) attacks for cyber-physical systems (CPSs), where attacks are under zero-input and hold-input strategies. By introducing a unified model describing the simultaneous existence of the two attacks, the CPS can be converted to a switched system with one delay. To ensure control performance, the type-dependent average dwell time (ADT) is applied for the first time to pose constraints on the occurrence frequency of DoS attacks. In the meantime, multiple discontinuous Lyapunov functions (MDLFs) are employed. Upon this, the global uniform exponential stability (GUES) and $H_{\infty}$ performance of the closed-loop system are guaranteed. Finally, the effectiveness of our theoretical results is verified by a numerical example.

关键词： Switched systems Time-frequency analysis Stability Cyber-physical systems Delays control theory Closed loop systems

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Resilient Predictive control of Constrained Connected and Automated Vehicles under Malicious Attacks

Resilient Predictive Control of Constrained Connected and Au...

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Industrial Cyber-Physical Systems (ICPS)

作者： Henglai Wei Yan Wang Jicheng Chen Hui Zhang Centre of Excellence for Testing Research of Autonomous Vehicles NTU (CETRAN) and School of Mechanical and Aerospace Engineering Nangyang Technological University Singapore School of Mechanical and Aerospace Engineering Nangyang Technological University Singapore School of Transportation Science and Engineering Beihang University Beijing China

In this paper, we present a novel resilient distributed model predictive control (RDMPC) framework for the con-strained Connected and Automated Vehicles (CAV) in the pres-ence of $F$ -local malicious attacks. the proposed framework aims to ensure constraint satisfaction and identify malicious attacks using previously broadcast information and a convex set, referred to as the ”resilience set.“ Compared to the well-known Mean Subsequence Reduced (MSR) algorithms that require (2F + 1)-robust graphs, the proposed approach significantly reduces the required robustness level to (F + 1)-robust graph. Our simulation results demonstrate the effectiveness of the proposed approach in mitigating the impact of malicious attacks on constrained CAVs while ensuring constraint satisfaction. Overall, the proposed RDMPC framework contributes to the field of resilient platoon control for CAVs and has potential implications for improving the reliability and security of CAVs in real-world scenarios.

关键词： Uncertainty Simulation Predictive models Cyber-physical systems Robustness Security Communication networks

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