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第43届中国控制会议

作者： Xiang Gu Dewei Li Aoyun Ma Yaru Yu Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

In the practical application of model predictive control in power electronics, both online computational burden and model accuracy are crucial. This paper presents an explicit model predictive control method based on input-mapping *** address the issue of parameter drift in the forward DC-DC converter system, the input-mapping method is introduced to compensate for model deviations using historical data. Firstly, the average model of the forward DC-DC converter system is introduced. For the control objective of voltage tracking, an explicit predictive control using the incremental model is ***, input-mapping method is integrated with explicit predictive control. During offline computation, analytical forms of the input-mapping combination coefficients and the optimal solution function of explicit model predictive control are *** computation of combination coefficients is conducted to obtain the optimal solution rapidly. The effectiveness of the proposed method is verified through simulations in MATLAB.

关键词： Forward DC-DC converter explicit model predictive control input-mapping method

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Encrypted Finite-Horizon Energy-to-Peak State Estimation for Time-Varying Systems Under Eavesdropping Attacks: Tackling Secrecy Capacity

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 985-996页

作者： Lei Zou Zidong Wang Bo Shen Hongli Dong Guoping Lu College of Information Science and Technology Donghua UniversityShanghai 201620 Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of EducationShanghai 201620China College of Electrical Engineering and Automation Shandong University of Science and TechnologyQingdao 266590China Department of Computer Science Brunel University LondonUxbridgeMiddlesex UB83PHUK Intelligence Energy Research Institute Northeast Petroleum UniversityDaqing 163318 Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum UniversityDaqing 163318 Sanya Offshore Oil&Gas Research Institute Northeast Petroleum UniversitySanya 572024China School of Electrical Engineering Nantong UniversityNantong 226019China

This paper is concerned with the problem of finitehorizon energy-to-peak state estimation for a class of networked linear time-varying *** to the inherent vulnerability of network-based communication,the measurement signals transmitted over a communication network might be intercepted by potential *** avoid information leakage,by resorting to an artificial-noise-assisted method,we develop a novel encryption-decryption scheme to ensure that the transmitted signal is composed of the raw measurement and an artificial-noise term.A special evaluation index named secrecy capacity is employed to assess the information security of signal transmissions under the developed encryption-decryption *** purpose of the addressed problem is to design an encryptiondecryption scheme and a state estimator such that:1)the desired secrecy capacity is ensured;and 2)the required finite-horizon–l_(2)-l_(∞)performance is *** conditions are established on the existence of the encryption-decryption mechanism and the finite-horizon state ***,simulation results are proposed to show the effectiveness of our proposed encryption-decryption-based state estimation scheme.

关键词： Artificial-noise-assisted technique eavesdropping encryption-decryption scheme energy-to-peak state estimation finitehorizon state estimation

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Evaluating the Influence of Object Detection Models and Dataset Selection on Traffic Accident Prediction Performance

Evaluating the Influence of Object Detection Models and Data...

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2025 IEEE International Conference on Consumer Electronics, ICCE 2025

作者： Chen, Wen-Hui Huang, Yu-Hung Lin, Yu-Chen Graduate Institute of Automation Technology National Taipei University of Technology Taipei Taiwan Department of Automatic Control Engineering Feng Chia University Taichung Taiwan

ISBN: (纸本)9798331521165

Traffic accidents pose significant social and economic challenges, making effective accident prediction systems essential. Traditional machine learning methods often struggle to capture the complex, nonlinear patterns in visual accident data. Recent advancements suggest that deep learning offers a promising solution to this challenge. These vision-based systems rely on object detection as a foundational step, identifying key entities in traffic scenes captured by cameras to improve prediction accuracy. Despite its importance, the impact of object detection accuracy on overall accident prediction effectiveness remains underexamined. This study investigates this relationship through cross-dataset analysis. Experimental results show that object detection accuracy directly impacts accident prediction performance, with training dataset choice playing a critical role. Enhancing model generalization is essential to stabilizing accident prediction systems. © 2025 IEEE.

关键词： Highway accidents

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Comparative analysis of bioinspired algorithms for tuning a flatness-based controller: A ball and beam case study

Comparative analysis of bioinspired algorithms for tuning a ...

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Latin America Congress on Computational Intelligence (LA-CCI)

作者： M. A. Pastrana José Oniram de A. Limaverde Filho Luiz Henrique Oliveira Jaider Bautista Eugênio Fortaleza Daniel M. Muñoz Department of Mechanical Engineering Automation and Control Group (GRACO) University of Brasília Brasília Brazil Department of Electrical Engineering University of Brasília Brasília Brazil Faculty of Engineering Systems Undergraduate Program University of the Amazonia Florencia Colombia

ISBN: (数字)9798350374575

ISBN: (纸本)9798350374582

This paper provides a comprehensive comparative analysis of the performance of four bioinspired algorithms (Differential Evolution, Grasshopper Optimization Algorithm, Moth-flame Optimization, and Particle Swarm Optimization) in designing a flatness-based controller for a ball and beam system simulated in MATLAB/Simulink environment. The assessment involves the tuning of feedback gains utilizing four distinct fitness functions: Integral Square Error, Integral Absolute Error, Integral Time Absolute Error, and an ad-hoc cost function. Hypothesis tests are employed to choose the optimal controllers from each combination for every bioinspired algorithm and a fitness function. Subsequently, a control performance analysis of these controllers for the ball and beam system is conducted, focusing on critical parameters such as overshoot, settling time, and steady-state error. This analysis demonstrates that all the controllers achieve a zero steady-state error. Noteworthy is the flatness-based controller tuned with the bioinspired Grasshopper Optimization Algorithm and utilizing the Integral Time Absolute Error fitness function, which stands out for achieving the fastest response with the lowest overshoot. This particular controller emerges as the most recommended choice for the specified application.

关键词： Particle beams Focusing Cost function MIMO Steady-state Performance analysis Particle swarm optimization MATLAB Tuning Computational intelligence

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A Transfer Gated Recurrent Unit Model for Battery Health Monitoring Under Cross-Domain Conditions

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Tian, Jilun Xie, Jiale Zhang, Jiusi Huang, Congsheng Jiang, Yuchen Luo, Hao Chow, Mo-Yuen Yin, Shen Harbin Institute of Technology School of Astronautics Department of Control Science and Engineering Harbin150001 China North China Electric Power University Department of Automation Baoding071003 China University of Electronic Science and Technology of China School of Automation Engineering Chengdu611731 China National Taipei University of Technology Department of Electrical Engineering Taipei10608 Taiwan University of Michigan-Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China Norwegian University of Science and Technology Faculty of Engineering Department of Mechanical and Industrial Engineering Trondheim7034 Norway

Battery health monitoring is crucial for ensuring maintenance reliability and safety, with broad applications in various industrial systems. Data-driven state-of-health (SOH) estimation methods can perform excellently using massive historical data without prior physical knowledge. In the battery aging process, this article extracts the essential health indicators to construct the model and adopts a suitable data preprocessing method to reduce the influence of noise. There is still a limitation for data-driven methods regarding data quality, and the domain shift caused by different operating conditions will damage estimation performance. To tackle the issue, this article proposes a transfer feature transformation (TFT) based on mean maximum discrepancy (MMD) to get a new feature space to get domain-invariant features with sufficient information. We propose a multilayer gated recurrent unit (GRU) neural network with fully connection (FC) layers to uncover hidden relationships in degraded data. Fusing TFT and GRU-FCs methods can realize an end-to-end SOH estimation under cross-domain conditions. We apply real-world public Center of Advanced Life Cycle engineering (CALCE) and NASA battery datasets and lab testing-based accelerated aging data to validate the performance of algorithms. By comparison, our proposed TFT-GRU-FCs method can get the best performance of all algorithms, and we have also given sufficient results as support. © 1963-2012 IEEE.

关键词： Electronic health record

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Effect of External Biases on Opinion Formation in a Cooperative Network

Effect of External Biases on Opinion Formation in a Cooperat...

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control Conference (ICC), 2019 Sixth Indian

作者： Vishnudatta Thota Akshay Nagesh Kamthe Twinkle Tripathy The Control and Automation specialisation of the Department of Electrical Engineering Indian Institute of Technology Kanpur Kanpur Uttar Pradesh India

In this paper, we study the effect of external biases on opinion formation in a group of $n$ agents. To do so, we propose a biased Laplacian model. The proposed model shows that clustering and polarization of opinions are possible outcomes in the cooperative framework, even in the presence of an external bias. We also determine the conditions necessary for the stability of the system in the given framework. Numerical simulations are also presented to illustrate the theoretical results.

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Competitive Meta-Learning

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IEEE/CAA Journal of Automatica Sinica 2023年第9期10卷 1902-1904页

作者： Boxi Weng Jian Sun Gao Huang Fang Deng Gang Wang Jie Chen National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081 Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China School of Automation Tsinghua UniversityBeijing 100084China Department of Control Science and Engineering Tongji UniversityShanghai 201804 National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081China IEEE

Dear Editor,This letter is concerned with developing meta-learning models for fast,stable,and effective few-shot learning across tasks over a few training ***,deep and reinforcement learning(RL)is widely used in auton... 详细信息

关键词： robot autonomous concerned

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Robust controller Design with Two-Degree-of-Freedom Feedback Loop Factorization for Oscillating Plant with Uncertain Time Delay*

Robust Controller Design with Two-Degree-of-Freedom Feedback...

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International Conference on control, automation and Diagnosis (ICCAD)

作者： Marek Dlapa Department of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlin Zlin Czech Republic

Application of Robust control Toolbox for Time Delay Systems implemented in the Matlab system to the oscillating plant with uncertain time delay using the D-K iteration and algebraic approach. The algebraic approach combines the structured singular value, algebraic theory and algorithm of global optimization solving remaining issues in structured singular value framework. The algorithm of global optimization can be alternated with direct search methods such as Nelder-Mead simplex method giving solutions for problems with one local extreme. As a global optimization method, Differential Migration is used proved to be reliable in solving this type of problems. The D-K iteration represents a standard method in the structured singular value theory. The results obtained from the D-K iteration are compared with the algebraic approach.

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A K-Means Clustering-Based Optimization of IT2FL for Improved Regenerative Braking Performance 1

A K-Means Clustering-Based Optimization of IT2FL for Improve...

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1st International Conference on Smart Mechatronics, ICSMech 2024

作者： Wahid, Muhammad Rizalul Joelianto, Endra Budiman, Bentang Arief Tongroon, Manida Pratama, Mulia Gianti, Mahmudah Salwa Hernadi, Muhammad Fauzan Mechatronics and Artificial Intelligence Universitas Pendidikan Indonesia Bandung Indonesia Instrumentation Control and Automation Research Group Institut Teknologi Bandung Bandung Indonesia Institut Teknologi Bandung Faculty of Mechanical and Aerospace Engineering Bandung Indonesia Kasetsart University Atae Research Unit Department of Mechanical Engineering Sriracha Thailand Pusat Riset Mekatronika Cerdas Organisasi Riset Elektronika dan Informatika-BRIN Bandung Indonesia

ISBN: (纸本)9798350368918

Optimizing regenerative braking systems in electric vehicles presents a complex challenge requiring precise and adaptable control. This research proposes employing K-Means Clustering to the Interval Type-2 Fuzzy Logic (IT2FL) membership functions, thereby improving overall regenerative braking efficiency and enhancing driving range. This research demonstrates that implementing a K-Means in the IT2FL control system in electric vehicles effectively recovers 35.84% of energy. By incorporating a K-means-based approach, the IT2FL controller further enhances vehicle range by 43 kilometers, achieving a total range of 108 kilometers. In comparison, an IT2FL system without K-means recovered only 26.67% of energy and achieved a total range of 93 kilometers. Notably, the IT2FL controller with K-means enabled the electric vehicle to attain an energy efficiency of 22 kilometers per kilowatt-hour. These findings underscore the significant improvement in maximum range offered by the IT2FL controller with K-means compared to alternative methods. © 2024 IEEE.

关键词： Regenerative braking

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Modeling and Calculation of Core Loss and Heat Distribution in Ultra-Thin Wound Core Reactor Based on Electromagnetic and Fluid-Thermal Coupling

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IEEE Transactions on Magnetics 2025年

作者： Yuan, Jiaxin Li, Xuzhe Zhou, Hang Muramatsu, Kazuhiro State Key Laboratory of Power Grid Environmental Protection School of Electrical Engineering and Automation Wuhan University Wuhan430072 China School of Electrical Engineering and Automation Wuhan University Wuhan430072 China Laboratory of Hydro-Wind-Solar Multi-Energy Control Coordination Wuhan University Wuhan China Department of Electrical and Electronic Engineering Saga University Saga840-8502 Japan

The anode saturable reactor (ASR) is a critical component in converter valves for protecting thyristors. In recent years, fault issues caused by abnormal heating have received widespread attention. However, the complex structure of the ASR presents a significant challenge for accurate temperature rise calculations. This study focuses on an ETT-type ASR and establishes a comprehensive electromagnetic-thermal-flow simulation model. The improved Bertotti loss separation model is applied to calculate core losses, and time-averaged losses are used as the heat source coupled to the temperature field to address the mismatch between the time scales of losses and temperature rise. The temperature distribution of multiple core pairs in the ASR is solved based on a fluid-thermal coupling method and compared with three other methods. Experimental results show that under normal operating conditions, the core temperature of the ASR is approximately 75°C, with slight temperature differences observed across the cores. The proposed heat calculation model provides more accurate results than other models. © 2015 IEEE.

关键词： Saturable core reactors

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