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Outlier-resistant distributed fusion filtering for nonlinear discrete-time singular systems under a dynamic event-triggered scheme

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Frontiers of Information Technology & Electronic Engineering 2024年第2期25卷 237-249页

作者： Zhibin HU Jun HU Cai CHEN Hongjian LIU Xiaojian YI Department of Applied Mathematics Harbin University of Science and TechnologyHarbin150080China Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and TechnologyHarbin150080China School of Automation Harbin University of Science and TechnologyHarbin150080China School of Mathematics and Physics Anhui Polytechnic UniversityWuhu241000China School of Mechatronical Engineering Beijing Institute of TechnologyBeijing100081China Yangtze Delta Region Academy of Beijing Institute of Technology Jiaxing314003China Tangshan Research Institute Beijing Institute of TechnologyTangshan063099China

This paper investigates the problem of outlier-resistant distributed fusion filtering(DFF)for a class of multi-sensor nonlinear singular systems(MSNSSs)under a dynamic event-triggered scheme(DETS).To relieve the effect of measurement outliers in data transmission,a self-adaptive saturation function is ***,to further reduce the energy consumption of each sensor node and improve the efficiency of resource utilization,a DETS is adopted to regulate the frequency of data *** the addressed MSNSSs,our purpose is to construct the local outlier-resistant filter under the effects of the measurement outliers and the DETS;the local upper bound(UB)on the filtering error covariance(FEC)is derived by solving the difference equations and minimized by designing proper filter ***,according to the local filters and their UBs,a DFF algorithm is presented in terms of the inverse covariance intersection fusion *** such,the proposed DFF algorithm has the advantages of reducing the frequency of data transmission and the impact of measurement outliers,thereby improving the estimation ***,the uniform boundedness of the filtering error is discussed and a corresponding sufficient condition is ***,the validity of the developed algorithm is checked using a simulation example.

关键词： Distributed fusion filtering Multi-sensor nonlinear singular systems Dynamic event-triggered scheme Outlier-resistant filter Uniform boundedness

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Investigation of pressure drop in flexible ventilation ducts under different compression ratios and bending angles

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Building Simulation 2021年第4期14卷 1251-1261页

作者： Ho Kam Dai Wenjie Huang Liye Fu Chao-Hsin Lin Daniel Wei Zhongzhe Dong Ruoyu You Chun Chen Department of Mechanical and Automation Engineering The Chinese University of Hong KongShatinN.T.999077Hong KongChina Department of Building Services Engineering The Hong Kong Polytechnic UniversityKowloon999077Hong KongChina Environmental Control Systems Boeing Commercial AirplanesEverettWA98203USA Boeing Research&Technology Beijing100027China Shenzhen Research Institute The Chinese University of Hong KongShenzhen518057China

Due to the large degree of freedom in terms of design and installation, flexible ventilation ducts are commonly used in ventilation systems. However, excessive use of flexible ducts may lead to greater pressure drop and higher energy consumption. This study conducted experimental measurements to characterize the pressure drop in flexible ventilation ducts with different compression ratios and bending angles. This investigation first measured the pressure drop in straight flexible ducts with four compression ratios under various airflow rates. The calculated friction factor for the straight flexible ducts was negatively associated with the compression ratio. Next, the pressure drops in single-bend flexible ducts with various bending angles from 30° to 150° were measured under various airflow rates. The calculated loss coefficient of the bend increased with the bending angle for single-bend flexible ducts. Finally, the influence of the intermediate duct length on the pressure drop across two bends was experimentally investigated. When the length of the intermediate duct was greater than eight times the inner diameter, the pressure drop across a double-bend flexible duct could be calculated from the friction factors and loss coefficients with a relative error less than 1%. The data obtained in this study can be used to calculate the total pressure loss in flexible ventilation ducting systems in buildings.

关键词： ventilation pressure loss flex duct fan energy friction factor loss coefficient

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A lightweight pedestrian detection model for edge computing systems 17th

A lightweight pedestrian detection model for edge computing ...

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17th International Symposium on Distributed Computing and Artificial Intelligence, DCAI 2020

作者： Chen, Wen-Hui Kuo, Han-Yang Lin, Yu-Chen Tsai, Cheng-Han Graduate Institute of Automation Technology National Taipei University of Technology Taipei Taiwan Department of Automatic Control Engineering Feng Chia University Taichung Taiwan Mechanical and Mechatronics Systems Laboratories Industrial Technology Research Institute Hsinchu Taiwan

ISBN: (纸本)9783030530358

Most vision-based pedestrian detection systems adopted deep learning approaches with the framework of convolutional neural networks (CNNs) to reach the state-of-the-art detection accuracy. As CNN-based approaches are computationally intensive, the deployment of those systems to a resource-limited edge device is a challenging task, especially for a real-time application such as intelligent vehicles. In this study, we proposed a lightweight high-performance edge computing solution to achieve rapid and accurate performance in pedestrian detection. Experimental results showed that the proposed framework can effectively reduce the miss rate of the YOLO-tiny detection model from 48.8% to 26.2% while achieving an inference speed of 31 frames per second (FPS) tested on the Caltech pedestrian dataset. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Edge computing

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Partially Occluded Face Expression Recognition with CBAM-Based Residual Network for Teaching Scene

Partially Occluded Face Expression Recognition with CBAM-Bas...

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Chinese automation Congress (CAC)

作者： Yanxing Bai Luefeng Chen Min Li Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration School of Automation Ministry of Education China University of Geosciences Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada Systems Research Institute Polish Academy of Sciences Warsaw Poland Department of Computer Engineering Istinye University Sariyer/Istanbul Turkey Tokyo Institute of Technology Yokohama Japan

In this paper, a deep residual network based on convolutional block attention module (CBAM) is proposed, which is utilized for feature extraction of partially occluded face expression data. The proposed method overcomes the problem of localized occlusion face feature extraction by focusing on the regions and channels containing important information in the occluded face data through CBAM. Multi-task cascaded convolutional networks (MTCNN) are firstly utilized to localize the key regions of face emotion, and then deep emotion features are extracted by CBAM-ResNet network. The final emotion labels are generated. The effectiveness of this paper's method is verified on the RAF-DB dataset and the occluded CK+ dataset. The experimental accuracy in the RAF-DB dataset is 76.3%, which is 3.74% and 1.64% higher than the accuracy produced by the method of RGBT, and the WLS-RF, respectively. Application experiments are carried out in the real teaching scenario, which verifies the applicability of the algorithm in the real teaching scene.

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Skeleton-Based Multi-Stream Adaptive Graph Convolutional Network for Indoor Scene Action Recognition

Skeleton-Based Multi-Stream Adaptive Graph Convolutional Net...

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Chinese automation Congress (CAC)

作者： Jiazhuo Li Luefeng Chen Min Li Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems and the Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation China University of Geosciences Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada Polish Academy of Sciences Systems Research Institute Warsaw Poland Department of Computer Engineering Istinye University Sariyer/Istanbul Turkey Tokyo Institute of Technology Yokohama Japan Tokyo Institute of Technology Tokyo Japan

With the rapid advances in computer vision, human action recognition has gradually received attention, but the current methods still exhibit some problems in indoor environments. The human skeleton, as the framework of human motion, contains high-quality actional feature information, and the skeleton-based action recognition method effectively avoid the interference of interior background noise and has advantages in indoor action recognition. The outstanding effect of graph convolutional networks on graph structure data processing has led to its rapid development and wide application in skeleton-based action recognition. Second-order skeletal information also contains a large number of actional features but is not effectively utilized. The artificial predefined topology of the human skeleton map has limitations, and cannot reflect the interaction between limbs. To solve the above problems, this article designs an adaptive weighted multi-stream graph convolutional network (AM-GCN) based on skeletal information, using an attention mechanism to enhance the network's ability to extract actional features, and an adaptive layer to make the construction graph more flexible, incorporating second-order skeletal features through a dual-stream architecture. In this article, the NTU-RGB+D dataset has been used for the experiments, the results show that the method in this article has good results.

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Plate Shape Prediction Based on Data-Driven in Roll Quenching Process

Plate Shape Prediction Based on Data-Driven in Roll Quenchin...

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Chinese automation Congress (CAC)

作者： Liu Hu Luefeng Chen Jie Hu Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems and the Engineering Research Center of Intelligent Technology for Geo-Exploration School of Automation Ministry of Education China University of Geosciences Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Systems Research Institute Polish Academy of Sciences Warsaw Poland The Department of Computer Engineering Istinye University Sariyer/Istanbul Turkey Tokyo Institute of Technology Yokohama Japan The Tokyo Institute of Technology Tokyo Japan

In the process of steel plate production, predicting the plate shape is of great significance for producing high-quality and consistently stable plate shapes. This paper presents a model that predicts both the defect types and flatness of the plate, providing theoretical support for setting process parameters in roller quenching production. First, the parameters of the quenching process are analyzed to identify their characteristics. Then, the K-Means clustering algorithm and correlation analysis are employed to process the quenching process parameters. A gradient boosting decision tree (GBDT) model is used to predict the defect types and flatness of the steel plates. Finally, industrial production data is utilized for experimental validation. The obtained experimental results verify the reliability of the proposed method.

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Methods of Reducing the Energy Consumption of Digital-Analog Converters and Increasing Their Metrological Reliability

Methods of Reducing the Energy Consumption of Digital-Analog...

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International Conference on Modern Problems of Radio Engineering, Telecommunications and Computer Science

作者： Oleg Zastavnyy Orest Kochan Pavlo Bykovyy Anatoliy Sachenko Roman Kochan Volodymyr Kochan Department of Specialized Computer Systems West Ukrainian National University Termopil Ukraine Department of Information and Measurement Technologies Automation and Metrology Lviv Polytechnic National University Lviv Ukraine Department of Information Computer Systems and Control West Ukrainian National University Termopil Ukraine Research Institute for Intelligent Computer Systems of West Ukrainian National University Termopil Ukraine Department of Teleinformatics Kazimierz Pulaski University of Radom Radom Poland Department of Specialized Computer Systems Lviv Polytechnic National University Lviv Ukraine

ISBN: (数字)9798331520564

ISBN: (纸本)9798331520571

This work analyzes the possibility of reducing the energy consumption of digital-to-analog converters by minimizing the energy consumption of the elements that ensure their operation. Due to the fact that such decisions can lead to an increase in the temperature and time drift of the output voltage of the digital-to-analog converter, a method of its in-situ calibration during operation is proposed. The method also allows carrying out calibration of high-speed analog-digital converters.

关键词： Energy consumption Power demand Digital-analog conversion Voltage Reliability engineering Market research Calibration Telecommunications Integrated circuit reliability Analog-digital conversion

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AGV Semantic Attack Detection Based on Hidden Markov Model

AGV Semantic Attack Detection Based on Hidden Markov Model

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2022 IEEE International Conference on Industrial Technology, ICIT 2022

作者： Zhang, Sichao Liang, Wei Zhang, Yinlong Pang, Zhibo State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China University of Chinese Academy of Sciences Beijing100049 China Technology Abb Corporate Research Sweden Department of Automation Vasteras72178 Sweden

ISBN: (纸本)9781728119489

Automatic Guided Vehicle (AGV) semantic attack is now becoming an important research topic in digital workshops. Unfortunately, the conventional attack detections could trigger the wrong attack detection alarms, because of the unexpected wireless radio frequency interference. This paper investigates a new method for AGV semantic attack detection based on Hidden Markov Model (HMM). Our method is able to discriminate the typical wireless retransmission in presence of environment interference or in the context of AGV semantic attack by comparing the hidden state transition probability with the predefined threshold. Our model has been evaluated on our developed platform. The extensive experimental results and analysis prove the effectiveness of our method. © 2022 IEEE.

关键词： Semantics

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Discretizing Continuous Action Space With Unimodal Probability Distributions for On-Policy Reinforcement Learning

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IEEE Transactions on Neural Networks and Learning systems 2024年第6期36卷 11285-11297页

作者： Yuanyang Zhu Zhi Wang Yuanheng Zhu Chunlin Chen Dongbin Zhao Department of Control Science and Intelligence Engineering School of Management and Engineering and the Laboratory of Data Intelligence and Interdisciplinary Innovation Nanjing University Nanjing China Department of Control Science and Intelligence Engineering School of Management and Engineering and the Research Center for Novel Technology of Intelligent Equipment Nanjing University Nanjing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

For on-policy reinforcement learning (RL), discretizing action space for continuous control can easily express multiple modes and is straightforward to optimize. However, without considering the inherent ordering between the discrete atomic actions, the explosion in the number of discrete actions can possess undesired properties and induce a higher variance for the policy gradient (PG) estimator. In this article, we introduce a straightforward architecture that addresses this issue by constraining the discrete policy to be unimodal using Poisson probability distributions. This unimodal architecture can better leverage the continuity in the underlying continuous action space using explicit unimodal probability distributions. We conduct extensive experiments to show that the discrete policy with the unimodal probability distribution provides significantly faster convergence and higher performance for on-policy RL algorithms in challenging control tasks, especially in highly complex tasks such as Humanoid. We provide theoretical analysis on the variance of the PG estimator, which suggests that our attentively designed unimodal discrete policy can retain a lower variance and yield a stable learning process.

关键词： Task analysis Probability distribution Aerospace electronics Reinforcement learning Gaussian distribution Technological innovation Learning systems

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DC-DC Converters Optimization in Case of Large Variation in the Load

arXiv

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arXiv 2024年

作者： Domyshev, Alexander Chistyakova, Elena Dreglea, Aliona Sidorov, Denis Liu, Fang Melentiev Energy Systems Institute Siberian Branch Russian Academy Sciences Irkutsk Russia Harbin Institute of Technology Harbin China Irkutsk National Research Technical University Irkutsk Russia Institute for System Dynamics and Control Theory Siberian Branch Russian Academy Sciences Irkutsk Russia Department of Automation Central South University Changsha China

The method for controlling a DC-DC converter is proposed to ensures the high quality control at large fluctuations in load currents by using differential gain control coefficients and second derivative control. Various implementations of balancing the currents of a multiphase DC-DC converter are discussed, with a focus on achieving accurate current regulation without introducing additional delay in the control system. Stochastic particle swarm optimization method is used to find optimal values of the PID controller parameters. An automatic constraint-handling in optimization are also discussed as relevant techniques in the *** Codes 34H05 34A09 © 2024, CC BY.

关键词： Stochastic systems

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