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2021 4th International Conference on computer Information Science and Application Technology, CISAT 2021

作者： Sun, Shimin Zhang, Xinchao Huang, Wentian Xu, Aixin Wang, Xiaofan Han, Li Tianjin Key Laboratory of Autonomous Intelligent Technology and System School of Computer Science and Technology Tiangong University Tianjin300387 China National Engineering Laboratory for Computer Virus Prevention and Control Technology School of Computer Science and Engineering Tianjin University of Technology Tianjin300384 China

Most of the detection methods against DDoS attacks are based on periodic detection, which leads to high communication overhead, untimely detection, and slow attack response. This paper proposes a passive abnormality detection approach. First, we record the two flow-table characteristics of the regular switches. Then, based on dynamic threshold method and Grubbs outlier test method, we make a determination of abnormal switches. This method reduces the amount of data duplication and regular traffic collection. Moreover, we use Support Vector Machine (SVM) algorithm to evaluate the performance of the passive anomaly detection method. The experiment results show a better performance than active period DDoS attack detection approaches. © Content from this work may be used under the terms of the Creative Commons Attribution 3.0 Licence.

关键词： Support vector machines

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Gesture Recognition of sEMG Based on Res-LSTM 17th

Gesture Recognition of sEMG Based on Res-LSTM

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17th International Conference on Intelligent Robotics and Applications, ICIRA 2024

作者： Zhao, Yujia Zou, Chunlong Yun, Juntong Jiang, Du Huang, Li Liu, Ying Jiang, Guozhang Xie, Yuanmin Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education Wuhan University of Science and Technology Wuhan430081 China College of Mechanical Engineering Hubei University of Automotive Technology Shiyan442000 China Research Center for Biomimetic Robot and Intelligent Measurement and Control Wuhan University of Science and Technology Wuhan430081 China Hubei Key Laboratory of Mechanical Transmission and Manufacturing Engineering Wuhan University of Science and Technology Wuhan430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan University of Science and Technology Wuhan430081 China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan430081 China School of Mechanical Engineering Hubei Engineering University Xiaogan432000 China

ISBN: (纸本)9789819607761

sEMG (surface electromyography) signal control of bionic prostheses has been widely studied over the past few years. In particular, sparse sEMG signals are rapidly developing in the field of gesture recognition for their convenience, noninvasiveness, and ease of access. However, compared with high-density EMG signals, sparse EMG signals lack rich feature information, which in turn affects gesture recognition accuracy. In order to reduce the loss of feature information of sparse EMG signals in the spatio-temporal dimension, this paper proposes a hybrid neural network Res-LSTM combining residual network and long short-term memory network. The ordinary convolutional blocks in the CNN network are replaced with residual blocks, and the final fully connected layer is removed and a constant mapping layer is added to adequate extraction of spatial feature information of the data. The Res layer’s output is utilized as the input for the long and short-term memory (LSTM) network, which further extracts the features of the data in the temporal dimension, and finally completes the categorization output through a fully connected layer. The average accuracy of 91.11% for gesture-motion classification was verified by training on a homebrew dataset;and tested on a public dataset, NinaPro DB1, with an average accuracy of 91.03%. The experimental findings indicate that the proposed Res-LSTM network framework contributes to solving the problem of lack of feature information of sparse sEMG signals and improves the pattern recognition accuracy. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Gesture recognition

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Modeling Method of Aircraft Simulation Based on Formal Description of Petri Net 18th

Modeling Method of Aircraft Simulation Based on Formal Des...

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18th Chinese Intelligent systems Conference, CISC 2022

作者： Zhan, Tianming Huang, Yu Geng, Huapin Tong, Jiahui TAIJI Computer Co. Ltd Beijing100102 China Peking University Beijing100871 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100190 China Beijing Electro-Mechanical Engineering Institute Beijing102299 China

ISBN: (纸本)9789811962028

The simulation of aircraft guidance and control system has characteristics such as multiple model classification, large parameter influence,complex information interaction and so on. The traditional code-level model development method has many limitations, such as time consuming, low reusability, low modeling efficiency, and model quality can not be guaranteed. Based on the concurrency, graphic representation, mathematics and simulation characteristics of Petri net, this paper studies the aircraft simulation modeling method of formal description based on Petri net, constructs a general modeling development and integration software tool that can carry out component, parametric and graphical modeling, solves the problems of multi granularity model modeling and automatic generation of real-time simulation model code, and realizes the visual graphic modeling and comprehensive integration of different granularity models such as components, modules and meta models. The research method has been successfully applied in the simulation modeling of an aircraft. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Petri nets

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Physics-Informed Learning Using Hamiltonian Neural Networks with Output Error Noise Models

arXiv

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arXiv 2023年

作者： Moradi, Sarvin Jaensson, Nick Tóth, Roland Schoukens, Maarten Control System group Eindhoven University of Technology Eindhoven Netherlands Eindhoven Artificial Intelligence Systems Institute Eindhoven Netherlands Processing and Performance of Materials Group Eindhoven University of Technology Eindhoven Netherlands Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary

In order to make data-driven models of physical systems interpretable and reliable, it is essential to include prior physical knowledge in the modeling framework. Hamiltonian Neural Networks (HNNs) implement Hamiltonian theory in deep learning and form a comprehensive framework for modeling autonomous energy-conservative systems. Despite being suitable to estimate a wide range of physical system behavior from data, classical HNNs are restricted to systems without inputs and require noiseless state measurements and information on the derivative of the state to be available. To address these challenges, this paper introduces an Output Error Hamiltonian Neural Network (OE-HNN) modeling approach to address the modeling of physical systems with inputs and noisy state measurements. Furthermore, it does not require the state derivatives to be known. Instead, the OE-HNN utilizes an ODE-solver embedded in the training process, which enables the OE-HNN to learn the dynamics from noisy state measurements. In addition, extending HNNs based on the generalized Hamiltonian theory enables to include external inputs into the framework which are important for engineering applications. We demonstrate via simulation examples that the proposed OE-HNNs results in superior modeling performance compared to classical HNNs. © 2023, CC BY-NC-SA.

关键词： Hamiltonians

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Time series generator adversarial network with stochastic process for the degradation generation and prediction

Time series generator adversarial network with stochastic pr...

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Data Driven control and Learning systems (DDCLS)

作者： Anqi Shangguan Nan Feng Lingxia Mu Rong Fei Xinhong Hei Guo Xie Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China School of computer science and Engineering Xi'an University of Technology Xi'an China

Since the cumbersome collection process and high cost, the collected degradation of the product is basically small samples, which will affect the accuracy of reliability evaluation. It is necessary to expand the degradation to improve the accuracy of later reliability assessment. Therefore, a degradation generation and prediction method is proposed combining the time series generator adversarial network (TimeGAN) and stochastic process. Firstly, the input degradation is expanded by the sliding window to improve the later training accuracy; Then, the construction of the generator in TimeGAN is linked with the stochastic process to make the generation data more realistic. Finally, the results of degradation prediction by the Gated Recurrent Unit (GRU) can be obtained. Two datasets and different generation methods are adopted to evaluate the effectiveness of the proposed method. The results shows that the Kullback-Leibler(KL) divergence is the smallest, and the prediction error is the smallest compared with the other methods. So, the proposed method is proved that it is valid in the degradation generation and prediction, and can be used for the further reliability assessment of the product in the industrial system.

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An online sparse least square support vector regression and particle filter for remaining useful life prediction of capacitive-type pressure transducer 3

An online sparse least square support vector regression and ...

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2024 3rd International Conference on Aerospace and control Engineering, ICoACE 2024

作者： Wang, Senlin Dai, Lingfeng Guo, Mingzhe Lu, Yikang Fujian Institute of Research on the Structure of Matter Chinese Academy of Sciences Fujian Fuzhou362200 China Fujian Provincial Key Laboratory of Intelligent Identification and Control of Complex Dynamic System Quanzhou362200 China Fujian College University of Chinese Academy of Sciences Fujian Fuzhou350002 China School of Advanced Manufacturing Fuzhou University Fujian Quanzhou350108 China School of College of Computer and Cyberspace Security Fujian Normal University Fujian350007 China

This paper proposes a novel online sparse least square support vector regression without bias for forecasting capacitive type pressure transducer remaining useful life prediction (RUL). The proposed approach is based on mechanism and statistical knowledge. The impedance variables are applied to calibrate the correlation between pressure capacitance capacity degradation and the resistance value to improve the prediction precision. Furthermore, a particle filter algorithm is proposed to estimate the pressure capacitance impedance fade parameters, and then the probability density function of the predicted RUL value is obtained by Gaussian. Lastly, experimental results consider #5 and #6. The pressure capacitance data set verifies the hybrid RUL prognostics strategy with high accuracy and robust stability. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Support vector regression

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A Novel Switching Asynchronous Sampled-Data Scheme: Implementations in Interconnected Feedback systems

A Novel Switching Asynchronous Sampled-Data Scheme: Implemen...

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American control Conference (ACC)

作者： Xiaoyu Wang Feng Xiao Qian Feng State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

Sampled-data control is continually under research exploration and development to optimally coordinate the limited communication resources in networked control systems. In this paper, a novel switching asynchronous sampleddata framework with double-checking consisting of two distinct sampling schemes is proposed. An established method involves designing the switching sampling scheme with event-triggered and time-triggered mechanisms. We also introduce the concept of switching event-triggered control (SETC), by which a positive minimum sampling interval can be guaranteed effectively. By an integral method and Barbalat's Lemma, sufficient conditions that ensure the stability of interconnected linear systems are derived under the SETC. Numerical examples are presented to demonstrate the effectiveness of the proposed methodology.

关键词： Linear systems Sufficient conditions Networked control systems Delay effects Switches Trajectory Numerical stability

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Approximate state estimation with large-scale sensor networks under event-based sensor scheduling strategy

Approximate state estimation with large-scale sensor network...

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IEEE Conference on Decision and control

作者： Xinhui Liu Meiqi Cheng Dawei Shi Ling Shi MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing Institute of Technology Beijing China Department of Electronic and Computer Engineering Hong Kong University of Science and Technology Kowloon Hong Kong China

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

In this paper, we investigate the issues of real-time sensor scheduling and state estimator design within large-scale sensor network systems. Specifically, data redundancy sometimes occurs in large-scale sensor arrays due to the excessive proximity of sensing units in the spatial domain, leading to high similarity in their measurement data. Currently, it is difficult to account for such redundancy in sensor scheduling algorithms found in existing literature, where the optimal subset of sensors is generally selected by optimizing objective functions formulated from certain performance criteria. To tackle this problem, we introduce an event-based sensor scheduling strategy, the triggering condition of which is designed founded on the similarity of sensor data, so as to identify the most informative subset of sensors for state estimation. To evaluate the impact of the sensor scheduling protocol on system observability, we propose a new notion of $\mathscr{E}(\varepsilon)$-observability, based on which an observability criterion is derived. In addition, we have designed a set-valued state estimation algorithm, which takes into account the intricate measurement information structure inherent within the sensor selection mechanism. The performance enhancement of the proposed estimator is also investigated. Finally, numerical experiments are conducted to validate the effectiveness of the proposed estimation algorithm and to verify the performance improvement.

关键词： Protocols Event detection Scheduling algorithms Redundancy Approximation algorithms Real-time systems Sensors State estimation Observability Sensor arrays

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Data-driven traffic dynamic understanding and safety monitoring applications 4

Data-driven traffic dynamic understanding and safety monitor...

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4th IEEE International Conference on Civil Aviation Safety and Information Technology, ICCASIT 2022

作者： Zhou, Shizhong Hu, Yi Guo, Dongyue Lin, Yi Yang, Bo Sichuan University National Key Laboratory of Fundamental Science on Synthetic Vision Chengdu China Southwest Air Traffic Management Bureau CAAC Chengdu China Nanjing University of Aeronautics and Astronautics Nanjing China National Key Laboratory of Air Traffic Control Automation System Technology College of Computer Science Sichuan University Chengdu China

ISBN: (数字)9781665467667

ISBN: (纸本)9781665467667

In this work, a novel framework is proposed to improve air traffic safety from the perspective of human factors by detecting possible risks from air-ground speech communication. In the proposed framework, the automatic speech recognition and the spoken instruction understanding techniques serve as an interface to sense real-time traffic dynamics of airspace, which are achieved by deep learning-based data-driven models. Based on the obtained dynamics, several applications are designed to detect safety-critical risks of air-ground communication, including the normative instruction check, readback confirmation, trajectory conformance, and potential aircraft conflict detection. A prototype is developed to implement the proposed framework. To validate the proposed framework and prototype, we deploy them in the Chengdu area control center, Changsha aerodrome and approach, China. The data statistics collected from the real-world environment demonstrate that the proposed framework has the ability to improve air traffic safety and reduce the workload of air traffic controllers by understanding the traffic dynamics automatically. In addition, the performance of the core techniques is also confirmed by extensive data investigation. © 2022 IEEE.

关键词： Speech communication

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Reduced-Order Consensus Protocols with Pure Relative Output: Design, Existence, and Dual Results

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IEEE Transactions on Automatic control 2025年

作者： Ma, Yuwen Li, Xianwei Li, Shaoyuan Lin, Zongli Shanghai Jiao Tong University Department of Automation Shanghai200240 China State Key Laboratory of Submarine Geoscience China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China University of Virginia Charles L. Brown Department of Electrical and Computer Engineering CharlottesvilleVA22904 United States

This paper studies reduced-order dynamic consensus protocols for homogeneous linear multi-agent systems using pure relative output information. By applying H∞ control theory, a separation principle-like method with an additional small-gain constraint is proposed for designing an (nx-nu)th order protocol, where nx and nu are the numbers of states and inputs of each agent, respectively. Existence conditions for the protocol are then systematically discussed from the graph, low gain and high gain perspectives, respectively. It is revealed that the protocol always exists and can be found by the proposed design method for three cases: 1) directed acyclic networks, 2) agents with all eigenvalues in the closed left-half complex plane and 3) agents of minimum phase. Another reduced-order protocol of (nx - ny)th order is further discussed through duality. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method. © 1963-2012 IEEE.

关键词： Robust control

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