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检索条件"机构=School of Control and Computer Engineering"

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Data-driven-based control Performance Degradation Online Recovery for Voltage Source Inverter: A PnP strategy 48

Data-driven-based Control Performance Degradation Online Rec...

引用

48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Zhang, Shufeng Liu, Changan Shi, Yuntao Yin, Xiang North China Electric Power University School of Control and Computer Engineering Beijing China North China University of Technology School of Information Beijing China North China University of Technology School of Electrical and Control Engineering Beijing China

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

This paper presents a primary control strategy that can recover control performance online for the voltage source inverter (VSI) with inductor-capacitor (LC) filter. The control strategy contains a droop-based feedforward controller, an LQR-based state feedback controller and a data-driven residual compensation controller (FFR). An event-triggered mechanism based on stability margin is used to implement the plug-and-play (PnP) function of the residual compensation controller. Simulations show that FFR can realize uncertainty control and disturbance suppression and improve the dynamic performance, robustness and power distribution ability of the VSI system. © 2022 IEEE.

关键词： controllers

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Process-Model-Free Design of MPC via a Reference-Model-Based PI controller for the Gas Turbine 9

Process-Model-Free Design of MPC via a Reference-Model-Based...

引用

9th International Conference on Electrical engineering, control and Robotics, EECR 2023

作者： Shi, Gengjin Dai, Chengbo Ma, Miaomiao Li, Donghai Ding, Yanjun Tsinghua University State Key Lab of Power Systems Dept. of Energy & Power Engineering Beijing China North China Electric Power University School of Control & Computer Engineering Beijing China

ISBN: (纸本)9781665491204

Model predictive control (MPC) is a modern advanced control strategy which has great reputation because of its excellent reference tracking performance and the ability to deal with process constraints, time delay and multivariable problems. However, the gas turbine is difficult to model accurately and unmeasurable disturbances are unavoidable, which limits the application of MPC to the gas turbine. To solve these problems, a process-model-free design method for MPC via a reference-model (RM)-based proportional-integral (PI) controller-desired dynamic equational (DDE)-PI controller (MPC-DDE) is proposed in this paper. The DDE-PI provides the design model for the MPC and handle with unmeasurable disturbances while MPC provides a rolling optimized set point for DDE-PI. Simulation results illustrate the superiorities of the proposed hierarchical control strategy in reference tracking, disturbance rejection and robustness, which indicates the promising prospect of practical application of MPC-DDE to the gas turbine. © 2023 IEEE.

关键词： Model predictive control

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DV-Hop Localization Strategy Based on Beacon Node Confidence Analysis 6

DV-Hop Localization Strategy Based on Beacon Node Confidence...

引用

6th International Conference on computer Network, Electronic and Automation, ICCNEA 2023

作者： Shen, Han Wang, Zhongsheng Xi'an Technological University School of Computer Science and Engineering Xi'an710021 China Xi'an Technological University State and Provincial Joint Engineering Lab. of Advanced Network Monitoring and Control Xi'an China

ISBN: (纸本)9798350305388

To address the problem that the DV-Hop localization model for wireless sensor networks can no longer meet the current localization accuracy requirements, this paper proposes the concept of beacon node trustworthiness to provide ideas and basis for improving the optimization model. Based on the principle of least squares in the localization model, weighted least squares is introduced to present the trustworthiness for beacon nodes with different characteristics. To analyze the characteristics of the trustworthiness of beacon nodes, 18 functions are designed in terms of function instrumentality and decrement able, hierarchical faultiness, etc. Finally, the conclusions obtained from the credibility test are tested with weighted matrix and average hop distance weighting, and the localization error is reduced from 32.68% to 31.78%, with a role rate of 100%. The credibility characteristics of beacon nodes discussed in this paper provide ideas for subsequent optimization of the localization model. © 2023 IEEE.

关键词： Sensor nodes

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Complex Permeability Determination for EE Core Based on Flexible PCB Fixture and Magnetic Flux Path Length Analysis 2

Complex Permeability Determination for EE Core Based on Flex...

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2nd China Power Supply Society Electromagnetic Compatibility Conference, CPEMC 2024

作者： Jie, Huamin Zhao, Zhenyu Chang, Yongqi Wang, Changdong Jiang, Shiqi Gao, Richard Xian-Ke See, Kye Yak School of Electrical and Electronic Engineering Nanyang Technological University Singapore Singapore Department of Electrical and Computer Engineering National Univeristy of Singapore Singapore Singapore Department of Control Science and Engineering Harbin Institute of Technology Harbin China School of Electronics and Information Engineering Harbin Institute of Technology Harbin China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China Institute of High Performance Computing A*STAR Singapore Singapore

ISBN: (纸本)9798331509552

The complex permeability of magnetic cores acts as a vital factor in electromagnetic interference (EMI) filtering choke design and optimization. Many efforts have been reported for toroid cores, but fewer target those with other shapes, such as EE, EI, UU, and UI cores. Owing to their commonly used in planar EMI filters, determining the complex permeability of them is of significance. Targeting EE cores, this paper presents a flexible printed circuit board (PCB)-based fixture adapter tailored designed for performing the measurement, while the corresponding core permeability can be calculated through magnetic flux path length analysis. The experiments validate the effectiveness and accuracy of the proposed methods, spanning a wide frequency range up to 120 MHz. ©2024 IEEE.

关键词： Magnetic flux

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ICEEMDAN-IWOA-BiLSTM Hybrid Algorithm-based Model for Short-term Load Forecasting 2

ICEEMDAN-IWOA-BiLSTM Hybrid Algorithm-based Model for Short-...

引用

2023 2nd International Conference on Energy Internet and Power Systems, ICEIPS 2023

作者： Dong, Enchong Luan, Wenting School of Control and Computer Engineering North China Electric Power University Beijing China College of Intelligence Science and Technology National University of Defense Technology Changsha China

Given the uncertain, random, and volatile characteristics of power load, accurate forecasting of power load becomes challenging. To address this issue, this paper proposes an optimized prediction model by using a modified Adaptive White Noise Complete Integrated Empirical Modal Decomposition Algorithm (ICEEMDAN) and the improved Whale Optimization Algorithm (IWOA) for bidirectional short-term and long-term memory networks (BiLSTM). First of all, Australian power load data is preprocessed in this study. Then, the load data is decomposed into a series of sequences by using ICEEMDAN. After that, the improved whale algorithm is employed to analyze the BiLSTM super parameter optimization. Finally, each decomposed component is input into the IWOA-BiLSTM model for load forecasting. The results demonstrate that the proposed algorithm achieves higher accuracy in power load forecasting, compared to individual benchmark models and most portfolio models, indicating its applicability and practical value. © 2023 Published under licence by IOP Publishing Ltd.

关键词： Forecasting

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Decentralised Collaborative Iterative Learning control for Multi-Agent Systems Point-to-Point Channel Tracking

Decentralised Collaborative Iterative Learning Control for M...

引用

American control Conference (ACC)

作者： Shangcheng Chen Christopher T. Freeman School of Automatic Control and Systems Engineering University of Sheffield School of Electronics and Computer Science University of Southampton

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

Application of learning to collaborative tracking control of multi-agent systems has addressed a wealth of problems across transportation, manufacturing, rescue, aerospace and medical care areas. Iterative learning control algorithms have been proposed to address synergistic objectives in general optimization problems, achieving a transparent balance between convergence speed, tracking error and robustness. This paper builds on this framework by formulating a point-to-point strategy that allows each subsystem to track only a portion of the trajectory, thereby providing a more flexible design framework with broad utility. Moreover, a channel tracking strategy is developed to ensure that the total output during untracked intervals is limited to an a specified range. The practicality of this novel control framework is illustrated through derivation, simulation and evaluation of three new iterative learning laws: inverse, gradient and norm-optimal. Convergence analysis for the proposed framework is also given.

关键词： Collaboration Transportation Medical services Robustness Trajectory Manufacturing Optimization

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Bipolar Picture Fuzzy Graph Based Multiple Attribute Decision Making Approach–Part I 1

引用

4th International Conference on Machine Learning for Cyber Security, ML4CS 2022

作者： Gong, Shu Hua, Gang Department of Computer Science Guangdong University of Science and Technology Dongguan523083 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China

ISBN: (数字)9783031200991

ISBN: (纸本)9783031200984

The multiple attribute decision making (MADM) is a one of most crucial topic in decision making and computer science. The key technology for MADM is to learn the correlation between different attributes, and the graph model is an appropriate tool to analyze it. In this work, the MADM problem is formulated in the bipolar picture fuzzy graph framework, and decision making algorithms are designed to characterize the relationships among attributes. The numerical example is introduced in this paper to show how to handle the MADM problem in terms of bipolar picture graph model. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Fuzzy sets

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Dust-Mamba: An Efficient Dust Storm Detection Network with Multiple Data Sources 39

Dust-Mamba: An Efficient Dust Storm Detection Network with M...

引用

39th Annual AAAI Conference on Artificial Intelligence, AAAI 2025

作者： Bai, Cong Lin, Zhonghao Zhang, Jinglin Chen, Shengyong College of Computer Science Zhejiang University of Technology China School of Control Science and Engineering Shangdong University China School of Computer Science and Engineering Tianjin University of Technology China

ISBN: (纸本)157735897X

Accurate detection of dust storms is challenging due to complex meteorological interactions. With the development of deep learning, deep neural networks have been increasingly applied to dust storm detection, offering better learning and generalization capabilities compared to traditional physical modeling. However, existing methods face some limitations, leading to performance bottlenecks in dust storm detection. From the task perspective, existing research focuses on occurrence detection while neglecting intensity detection. From the data perspective, existing research fails to explore the utilization of multi-source data. From the model perspective, most models are built on convolutional neural networks, which have an inherent limitation in capturing long-range dependencies. To address the challenges mentioned, this study proposes Dust-Mamba. To the best of our knowledge, this study is the first attempt to accomplish both the occurrence and intensity detection of dust storms with advanced deep learning technology. In Dust-Mamba, multi-source data is introduced to provide a comprehensive perspective, Mamba and attention are applied to boost feature selection while maintaining long-range modeling capability. Additionally, this study proposes Structure Sharing Transfer Learning Strategies for intensity detection, which further enhances the performance of Dust-Mamba with minimal time cost. As shown by experiments, Dust-Mamba achieves Dice scores of 0.963 for occurrence detection and 0.560 for intensity detection, surpassing several baseline models. In conclusion, this study offers valuable baselines for dust storm detection, with significant reference value and promising application potential. Copyright © 2025, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Deep neural networks

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Dissolved Gas Analysis for Transformer Fault Diagnosis Based on Capsule Network

Dissolved Gas Analysis for Transformer Fault Diagnosis Based...

引用

2023 China Automation Congress, CAC 2023

作者： Li, Tong Shi, Xin Teng, Jing Fang, Fang Wang, Tingting Luo, Bing School of Control and Computer Engineering North China Electric Power University Beijing China Electric Power Research Institute China Southern Power Grid Guangzhou China

ISBN: (纸本)9798350303759

To solve the limitations of current dissolved gas analysis based transformer fault diagnosis methods and further improve the diagnostic accuracy, this paper develops a novel transformer fault diagnosis approach based on the Capsule Network (CapsNet). By combining the unique capability of CapsNet to handle vectors and the characteristics of dissolved gases in transformer oil, our approach is able to accurately model the intricate nonlinear relationship between dissolved gases and fault types, realizing the automatic extraction of key features. The dynamic routing technique and backpropagation algorithm are used for training the diagnostic model. Case studies on the real DGA data from a power grid validate that our approach outperforms both SVM and DBN across three performance metrics, demonstrating its advantages in real-world transformer fault diagnosis applications. © 2023 IEEE.

关键词： Dissolution

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Joint Optimization of Wind Farm Layout Considering Yaw control 8th

Joint Optimization of Wind Farm Layout Considering Yaw Cont...

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8th International Conference on Life System Modeling and Simulation, LSMS 2024 and 8th International Conference on Intelligent Computing for Sustainable Energy and Environment, ICSEE 2024

作者： Wang, Yiqun Jiang, Ruolin Chen, Yuanye Fang, Fang School of Control and Computer Engineering North China Electric Power University Beijing102206 China

ISBN: (纸本)9789819602247

As wind farms continue to grow in size, minimizing wake losses between turbines in layout design becomes increasingly important. Current wind farm layout strategies often focus on the performance of individual turbines without considering wake interactions. This study introduces a coordinated control approach that considers wake effects and demonstrates an improved yaw control results to reduce the impact of wake interactions. By implementing cooperative yaw control among turbines and using the NSGA-II algorithm, the study establishes a dual optimization problem of minimizing turbine spacing and maximizing power output, ultimately yielding the optimal layout for wind turbines. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Wind turbines

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