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Review of Frequency Response Analysis of Power Electronics-Dominated Power systems

Review of Frequency Response Analysis of Power Electronics-D...

引用

2024 ieee international conference on Electrical Energy Conversion systems and control, IEECSC 2024

作者： Zhao, Xiongguang Ling, Xu Jin, Weigang Wang, Ying Yu, Xiaodong Chen, Lei You, Xiaoyan Chen, Hongkun Central China Branch of State Grid Corporation of China Wuhan430077 China School of Electrical Engineering and Automation Wuhan University China

ISBN: (纸本)9798350389357

The growing integration of power electronic devices in power systems has brought attention to frequency stability issues due to low inertia as well as inadequate frequency regulation. In this regard, the paper defines frequency stability and introduces the frequency response process. It then outlines the current research progress in frequency response analysis methods from three perspectives: mathematical analytic algorithm, time domain simulation, and intelligent algorithms based on data-driven. The features of these modeling methods are compared in detail. Furthermore, the paper suggests future research directions and technical improvements by reviewing the frequency stability issues in power electronics-dominated power systems (PEDPSs). It is hoped that future efforts will deepen the understanding of frequency stability in PEDPSs, contributing to developing power systems with improved safety, stability, and efficiency. © 2024 ieee.

关键词： Frequency stability

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Modeling Method for cyber-Physical Power systems Considering Multiple Coupling Characteristics 3

Modeling Method for Cyber-Physical Power Systems Considering...

引用

3rd international conference on Energy, Power and Electrical technology, ICEPET 2024

作者： Zhao, Yulong Fu, Qingyu Wu, Yuhan Wang, Ying Li, Xinyu Liu, Chunming North China Electric Power University School of Electrical and Electronic Engineering Beijing China

ISBN: (纸本)9798350352658

With the wide application of intelligent devices, the operational efficiency of power grids has been improved, but it also brings new security challenges. In order to solve this problem, this paper proposes a modeling method for cyber-Physical Power System considering multiple coupling characteristics from the perspective of information-physical convergence and by comprehensively considering the correlation relationship and coupling characteristics of the power grid and cyber network. Firstly, a three-layer modeling framework of power information physics considering multi-layer coupling characteristics is proposed. Secondly, based on the steady state trend equation of the power grid, the power network operation model and the cyber network operation model are established considering the information transmission process and the information decision process, respectively. On this basis, a coupling relationship model containing structural coupling and functional coupling is established to form an integrated cyber-Physical Power System model. Finally, the validity of the model is verified by simulation analysis based on the ieee 24-node system. © 2024 ieee.

关键词： Power grids

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Enhancing Intrusion Detection systems in IoT Networks: A Hybrid Approach using CNN, ANN, LSTM, GRU for Improved Security 8

Enhancing Intrusion Detection Systems in IoT Networks: A Hyb...

引用

8th international conference on Inventive systems and control, ICISC 202

作者： Pradeep, M. Gopalakrishnan, S. Hindustan Institute of Technology and Science Department of Information Technology TamilNadu Kelambakkam603103 India

ISBN: (纸本)9798350386578

The automation of daily tasks via the Internet of Things (IoT) has drastically changed people's lives in the last few years. By connecting different physical devices with various functionalities, this is accomplished. As a result, as IoT networks grow, so does the rate of cyber threats, risking the stability and integrity of data. Numerous intrusion detection systems (IDS s) are currently developed to identify harmful actions based on predefined attacks patterns, thereby safeguarding data against misuse and abnormal attempts. The current IDS have to be improved due to the sharp rise in these types of attacks. The key to enhancing intrusion detection systems is now machining learning. A proposed intrusion detection methodology in this study is hybrid approach. After evaluating the model's performance using a number of popular, advanced methods currently in use, the suggested model uses CNN, ANN, LSTM and GRU model. The model gives better trade -off compared to other approaches. © 2024 ieee.

关键词： Network intrusion

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Sampled-Data Based Robust Multi-Objective Path-Following control of Autonomous Vehicles 6

Sampled-Data Based Robust Multi-Objective Path-Following Con...

引用

6th international conference on Electronic Engineering and Informatics, EEI 2024

作者： Yang, Xinduan Weng, Zhixiang Lin, Kunsong Li, Panshuo School of Automation Guangdong University of Technology Guangdong Provincial Key Laboratory of Intelligent Decision and Collaborative Control China

ISBN: (纸本)9798350353594

This paper proposes a sampled-data multi-objective path-following control method for autonomous vehicles based on the polytopic linear parameter varying (LPV) approach. Combining the active front-wheel steering (AFS) and the direct yaw moment control (DYC) strategies, an LPV path-following model is established subject to time-varying longitudinal velocity and uncertain cornering stiffness. Based on it, a sampled-data H∞/GH2 controller is obtained by solving linear matrix inequalities (LMIs), which guarantees the path-following performance and the lateral stability of the vehicle. The effectiveness of the proposed controller is verified in the simulation. © 2024 ieee.

关键词： Sampled data control systems

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SKD-Net: Spectral-based Knowledge Distillation in Low-Light Thermal Imagery for robotic perception

SKD-Net: Spectral-based Knowledge Distillation in Low-Light ...

引用

ieee international conference on Robotics and automation (ICRA)

作者： Sikdar, Aniruddh Teotia, Jayant Sundaram, Suresh Indian Inst Sci Robert Bosch Ctr Cyber Phys Syst Bangalore Karnataka India Indian Inst Sci Dept Aerosp Engn Bangalore Karnataka India

ISBN: (纸本)9798350384581;9798350384574

Enhancing the generalization capacity for semantic segmentation of aerial perception systems for safety-critical applications is vital, especially for environments with low-light and adverse conditions. Multi-spectral fusion techniques aim to maintain the merits of electro-optical (EO) and infrared (IR) images, e.g., retaining low-level features and capturing detailed textures from both modalities. However, these techniques encounter limitations when faced with scenarios involving missing modalities, especially during inference when only IR images are available. In this paper, we propose a novel spectralbased knowledge distillation architecture known as SKD-Net to improve the performance of deep learning models for missing modality scenarios for semantic segmentation tasks. In this architecture, we make use of Gated Spectral Unit to combine information from both modalities. SKD-Net aims to extract valuable semantic information from EO images while preserving spectral knowledge from the IR images within the feature space. The model retains the style information in the shallow layers while simultaneously fusing the high-level semantic context obtained from EO and IR images to improve the feature generation capacity when dealing with only IR images during inference. SKD-Net outperforms state-of-the-art multi-modal fusion and distillation models by 2.8% on average in scenarios with missing modalities when using only IR data during inference in two public benchmarking datasets. This performance increase is achieved without additional computational costs compared to the baseline segmentation models.

关键词： Semantic Segmentation

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A Robust Seabed Terrain Contour Aid Navigation Method Facing the Smooth Terrain 12

A Robust Seabed Terrain Contour Aid Navigation Method Facing...

引用

12th international conference on cyber technology in automation, control, and intelligent systems, cyber 2022

作者： Zhang, Wenjun Ma, Dong Gao, Jingxuan Ma, Teng Ben, Yueyang Science and Technology on Underwater Vehicles Laboratory Harbin Engineering University Heilongjiang Harbin150001 China College of Nautical and Naval Engineering Dalian Ocean University Liaoning Dalian116000 China College of Intelligent Systems Science and Engineering Harbin Engineering University Heilongjiang Harbin150001 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

The underwater terrain-aid navigation (TAN) method using a single-beam sonar has demonstrated its potential for autonomous underwater vehicles (AUVs) long-range accurate navigation without the aid of acoustics arrays and satellites. This paper proposed a robust terrain contour aid navigation(TCAN) method using a single-beam sonar in the smooth terrain areas, which considered the error characteristics of an inertial navigation system(INS), can realize long-range underwater navigation. As for the measurement error of a single-beam sonar and the influence of the smooth terrain areas, this paper proposed a measurement confidence interval calculation method, which can reduce the influence of the measurement error on the navigational result, improving the accuracy and robustness of the TCAN method. The influence of algorithm parameters on the result of the navigation method are researched by simulation experiments. The results show that the navigation method can realize long-range underwater navigation in the smooth terrain areas on making full use of an INS error characteristics, and has a good application prospect. © 2022 ieee.

关键词： Sonar

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Asynchronous Microphone Array Calibration using Hybrid TDOA Information

Asynchronous Microphone Array Calibration using Hybrid TDOA ...

引用

2024 international conference on intelligent Robots and systems

作者： Zhang, Chengjie Wang, Jiang Kong, He Southern Univ Sci & Technol Shenzhen Key Lab Control Theory & Intelligent Sys Shenzhen 518055 Peoples R China

ISBN: (纸本)9798350377712;9798350377705

Asynchronous microphone array calibration is a prerequisite for many audition robot applications. A popular solution to the above calibration problem is the batch form of Simultaneous Localisation and Mapping (SLAM), using the time difference of arrival measurements between two microphones (TDOA-M), and the robot (which serves as a moving sound source during calibration) odometry information. In this paper, we introduce a new form of measurement for microphone array calibration, i.e. the time difference of arrival between adjacent sound events (TDOA-S) with respect to the microphone channels. We propose to use TDOA-S and TDOA-M, called hybrid TDOA, together with odometry measurements for bath SLAM-based calibration of asynchronous microphone arrays. Extensive simulation and real-world experiments show that our method is more independent of microphone number, less sensitive to initial values (when using off-the-shelf algorithms such as Gauss-Newton iterations), and has better calibration accuracy and robustness under various TDOA noises. Simulation results also demonstrate that our method has a lower Cramer-Rao lower bound (CRLB) for microphone parameters. To benefit the community, we open-source our code and data at https://***/AISLAB-sustech/Hybrid-TDOA-Calib.

关键词： Calibration

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Adaptive Fuzzy Optimal control of Modular Robot Manipulators systems via Integral Reinforcement Learning-Based Value Iteration Algorithm

Adaptive Fuzzy Optimal Control of Modular Robot Manipulators...

引用

ieee international conference on cyber technology in automation, control, and intelligent systems

作者： Hucheng Jiang Tianjiao An Zhenguo Zhang Mingchao Zhu Yuanchun Li Bo Dong Department of Control Science and Engineering Changchun University of Technology Changchun China Changchun Institute of Optics Fine Mechanics and Physics Changchun China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

A novel adaptive fuzzy optimal compensation control approach is developed for modular robot manipulator (MRM). By incorporating integral reinforcement learning (IRL) to value iteration (VI), the adaptive fuzzy optimal control approach effectively addresses the trajectory tracking problem without accurate dynamic model information, and break the limitation of traditional policy iteration (PI). Moreover, this article approximate cost function with fuzzy logic system (FLS), which simplify the solution of the optimal control policy and better capture the important features of the cost function.

关键词： Fuzzy logic Adaptation models Adaptive systems Trajectory tracking Heuristic algorithms Optimal control Reinforcement learning Cost function intelligent systems Manipulator dynamics

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Remote Operation Human-Machine Interaction System for a Robotic Arm in Deep Ground Environments

Remote Operation Human-Machine Interaction System for a Robo...

引用

ieee international conference on cyber technology in automation, control, and intelligent systems

作者： Zhenming Zheng Junkai Huang Xinyi Wu Xinyao Wang Fei Wang Faculty of robot Northeastern University Bussiness School Liaoning University Department of Engineering Northeastern University

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

Developing deep underground energy resources is crucial for addressing our country's energy imbalance. To tackle unsafe conditions and high communication latency, we designed a Remote control Human-Machine Interaction System for Robotic Arms. Using dual MYO armbands to collect human arm joint data, Quaternion data is converted into Euler Angles for the robotic arm joints. This study focuses on Motion Mapping in the Joint Space from the master arm to the slave arm. Integrating Model Predictive control technology predicts the motion of the slave arm joints, achieving effective Remote control and significantly reducing latency.

关键词： Human computer interaction Energy resources Quaternions Arms Manipulators Main-secondary Hazards intelligent systems Remote control Predictive control

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Deterministic Learning-Based Robust Practical Output Regulation for Second-Order Nonlinear systems

Deterministic Learning-Based Robust Practical Output Regulat...

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2024 international Annual conference on Complex systems and intelligent Science, CSIS-IAC 2024

作者： Hu, Qingxi Liu, Wei Key Laboratory of Autonomous Systems and Networked Control of Ministry of Education School of Automation Science and Engineering South China University of Technology Guangzhou510641 China

ISBN: (纸本)9798331504755

This article intends to investigate the semi-global robust practical output regulation problem for a class of second-order nonlinear systems with parametric and non-parametric uncertainties based on deterministic learning method. First, by constructing the internal models, the robust output regulation problem is transformed into the semi-global robust practical stabilization problem. Second, we propose an adaptive neural control (ANC) strategy to solve the stabilization problem and utilize the radial basis function neural networks (RBF NNs) to identify unknown dynamic. Moreover, under the persistently exciting (PE) property, the unknown dynamics can be identified and the learned knowledge is saved as some constant NN weights. Finally, we design an deterministic learning-based adaptive neural control (DLANC) law with the learned knowledge to solve the output regulation problem and improve control performance. © 2024 ieee.

关键词： Contrastive Learning

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