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第41届中国控制会议

作者： Yujie Cao Sheng Du Chengda Lu Min Wu Jinhua She School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Engineering Tokyo University of Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Safe and efficient deep-sea drilling is inseparable from accurate and timely recognition of the ocean and geological *** refers to ocean dynamics,meteorology,hydrology,ecology,chemistry,ocean sound,light physical characteristics,ocean geology and geography.A complex ocean environment is one of the challenges facing ocean engineering at *** is difficult to establish an independent ocean or geological model for controller of the deep-sea drilling *** the face of complex and changeable ocean environment,modeling and analysis of wave environmental factors alone is not suitable for the control of deep-sea drilling *** paper analyzes the influence of various marine environmental factors on the offshore drilling platform and studies the internal relationship between each ***,the models of ocean breeze,wave and ocean current were designed to realize the simulation of ocean environment and parameterized description of ocean environment for deep-sea drilling *** has laid the foundation for the design of a deep-sea drilling control system.

关键词： Marine environment model Offshore drilling process Multi-model coupled

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Deep learning-based distributionally robust joint chance constrained distribution networks PV hosting capacity assessment

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Applied Energy 2025年 394卷

作者： Wang, Zihui Jia, Yanbing Han, Xiaoqing Wang, Peng Liu, Jiajie Key Laboratory of Cleaner Intelligent Control on Coal & Electricity Ministry of EducationShanxi Key Laboratory of Power System Operation and Control Taiyuan University of Technology Taiyuan China Department of Electrical and Electronic Engineering Nanyang Technology University Singapore

As distributed photovoltaic (PV) penetration in distribution networks (DNs) is increasing, it is essential to assess the PV hosting capacity (PVHC) to ensure the safe operation of DNs. This paper proposes a data-driven distributionally robust joint chance constrained (DRJCC) distribution networks PVHC assessment framework. Firstly, the spatiotemporal attention, projection, supervision, and Transformer architecture-based generative adversarial blocks are introduced to develop an augmented time series generative adversarial network (ATS-GAN), which, by integrating both supervised and unsupervised learning during the joint training process, better captures the spatiotemporal characteristics of PV and load power. Subsequently, leveraging the ATS-GAN, a Wasserstein metrics-based ambiguity set of PV and load power probability distributions is constructed, centered on the distributions induced by the generator neural network. Secondly, the DRJCC PVHC assessment model is proposed. A combination of the Bonferroni inequality and conditional value-at-risk approximation is adopted to transform the multivariate DRJCC model into a tractable conic formulation for efficient computation. Numerical results demonstrate that the proposed method effectively captures the spatiotemporal characteristics and uncertainties of multivariate distributions under multiple constraints, significantly reducing the conservatism typically associated with distributionally robust individual chance constraints. © 2025

关键词： Normal distribution

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Research on Synthetic Data Generation and Multi-modal Target Detection

Research on Synthetic Data Generation and Multi-modal Target...

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第34届中国控制与决策会议

作者： Jiexi Liu Chenyu Wang Lei Xu Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision

Target Detection is one of the most important tasks in Computer Vision,which has broad application prospects in many *** the past few years,great progress has been made in this field with the rapid development of deep learning ***,it's still a big challenge at complex scenarios such as dim environment for traditional single-modal visible *** address this problem,researchers introduce thermal images as additional modal in consideration of that thermal cameras are less susceptible to interference and explore how to fuse the two modalities information ***,the lack of large labeled and high-quality visible-thermal datasets hampers the usage of convolutional neural networks for ***,we propose to use image-to-image translation model combined with a differentiable data augmentation method to generate fake thermal images from labeled visible images and use multi-modal target detection model to prove the validity of the *** experiment results show that our method can provide us a large labeled dataset of synthetic visible-thermal image pairs with better generalization and the introduction of thermal modality can obtain a better performance than single modality.

关键词： Image-to-image translation Multi-modal target detection Deep learning

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Energy management of solid oxide fuel cell/lithium battery hybrid system

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CSEE Journal of Power and Energy systems 2022年 1-14页

作者： Li, Dong Zhong, Xiao Bo Xu, Yuan Wu Wei, Chong Yang Zhao, Song Jiang, Jianhua Deng, Zhonghua Fu, Xiaowei Li, Xi School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Hubei Wuhan430074 China College of Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Hubei Wuhan430081 China

The research of fuel cell and lithium battery hybrid system has attracted more and more researchers because of its advantages of low emission. However, the lower efficiency of energy management has been a critical factor that obstruct the commercialization of hybrid system. In this work, based on finite element ideas, a solid oxide full cell node model is developed to accurately estimate the operating status of the fuel cell. As for lithium battery, previous energy management studies generally only focused on state of charge, however, state of health is also a key parameter for lithium battery. In this paper, considering the strong coupling between variables we use particle filter algorithm to jointly estimate the state of charge and state of health. To reasonably distribute and manage the energy in the hybrid system, a T-S fuzzy controller for the hybrid system is designed by controlling the state variables in the SOFC model and the state of lithium battery. Finally, our algorithm is verified by DSPACE simulation platform. The result shows that the hybrid system with the energy management strategy not only meets the real-time sharply changing demand but also ensures the hybrid system working efficiently and safely. © 2022 China Electric Power Research Institute. All rights reserved.

关键词： Hybrid systems

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Wearable multichannel pulse condition monitoring system based on flexible pressure sensor arrays

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Microsystems & Nanoengineering 2022年第1期8卷 249-258页

作者： Jie Wang Yirun Zhu Zhiyong Wu Yunlin Zhang Jian Lin Tao Chen Huicong Liu Fengxia Wang Lining Sun Jiangsu Provincial Key Laboratory of Advanced Robotics School of Mechanical and Electric EngineeringSoochow UniversitySuzhou 215123China Micro Nano System Research Center Key Laboratory of Advanced Transducers and Intelligent Control System of Ministry of Education and Shanxi Province&College of Information EngineeringTaiyuan University of TechnologyTaiyuan 030024China Suzhou Institute of Nano-tech and Nanobionics Chinese Academy of SciencesSuzhou 215123China

Pulse diagnosis is an irreplaceable part of traditional Chinese medical ***,application of the traditional pulse monitoring method was restricted in the modernization of Chinese medical science since it was difficult to capture real signals and integrate obscure feelings with a modern data ***,a novel multichannel pulse monitoring platform based on traditional Chinese medical science pulse theory and wearable electronics was *** pulse sensing platform simultaneously detected pulse conditions at three pulse positions(Chi,Cun,and Guan).These signals were fitted to smooth surfaces to enable 3-dimensional pulse mapping,which vividly revealed the shape of the pulse length and width and compensated for the shortcomings of traditional single-point pulse ***,the pulse sensing system could measure the pulse signals from different individuals with different conditions and distinguish the differences in pulse *** addition,this system could provide full information on the temporal and spatial dimensions of a person’s pulse waveform,which is similar to the true feelings of doctors’*** innovative,cost-effective,easily designed pulse monitoring platform based on flexible pressure sensor arrays may provide novel applications in modernization of Chinese medical science or intelligent health care.

关键词： multichannel system replace

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Analysis and State Feedback control Bifurcation of Fractional-Order Cyclic Gene Regulatory Networks with Time Delay 41

Analysis and State Feedback Control Bifurcation of Fractiona...

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第41届中国控制会议

作者： Feng Liu Shujiang Sun Juan Zhao Feiyue Zhuo Hua O Wang School of Automation China University of Geosciences Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Mechanical Engineering Boston University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,a fractional-order cyclic gene regulatory network model with time delay is ***,the total time delay of the system is selected as the bifurcation parameter,and the condition for the existence of Hopf bifurcation is derived by analyzing its characteristic *** is found that the time delay affects the stability of the system,and the order affects the position of the bifurcation *** the time delay is greater than the critical time delay,the system loses ***,a state feedback controller is designed for the unstable *** is proved that the control method has good control effect for the system instability caused by Hopf ***,the correctness of the theoretical derivation is verified by simulation.

关键词： Fractional-order cyclic gene regulatory network Hopf bifurcation feedback control time delay

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Hardware-in-the-loop Simulation and Experimental system for Process control of Marine Resources Exploration 43

Hardware-in-the-loop Simulation and Experimental System for ...

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43rd Chinese control Conference, CCC 2024

作者： Wang, Zeyi Wang, Chenxuan Ma, Zhejiaqi Zeng, Kanghui Lu, Chengda Wang, Yawu Wu, Min China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China China University of Geosciences School of Future Technology Wuhan430074 China

ISBN: (纸本)9789887581581

Effective control techniques are essential for offshore platform systems to suppress disturbances caused by the complex marine environment and ensure the stable operation of the systems during the exploration of marine resources. This paper establishes a hardware-in-the-loop based marine resource exploration process control simulation and experiment system to simulate the effects of marine environmental factors on the offshore platform. The marine environment is simulated using JONSWAP spectra and real marine environment data. The dynamics of offshore platform is modeled using Lagrange's equation method. And the control effect is demonstrated using virtual reality technology. Ultimately, the dynamic positioning system control experiment, which uses the equivalent input disturbance method, validates the experimental system. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Hardware-in-the-loop simulation

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RBP-Former: Joint Prediction of RNA-protein Binding Sites on Full-length RNA Transcripts for Multiple RBPs

RBP-Former: Joint Prediction of RNA-protein Binding Sites on...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Li, Yichong Liu, Xiaojian Cheng, Fan Pan, Xiaoyong Yang, Yang Shanghai Jiao Tong University Department of Computer Science and Engineering Shanghai200240 China Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai200240 China

ISBN: (纸本)9798350386226

RNA-binding proteins (RBPs) are essential for gene expression, and the complex RNA-protein interaction mechanisms require analysis of global RNA information. Therefore, accurate prediction of RBP binding sites on full-length RNA transcripts is crucial for understanding these mechanisms and their roles in diseases. While machine learning methods can predict RBP binding to RNA fragments, extending this to full-length transcripts presents challenges due to sequence length and data imbalance. In this paper, we introduce RBP-Former, a binding site joint prediction model designed specifically for full-length RNA transcripts that can be used for multiple RBPs. This model processes information at both coarse and fine-grained levels to fully exploit sequence data and its interactions with multiple RBPs. We develop multi-level imbalance learning strategies, achieving favorable results on imbalanced data. Our method outperforms existing methods in predicting binding sites on full-length RNA transcripts for multiple RBPs, demonstrating its effectiveness in handling imbalanced label and sample distributions. © 2024 IEEE.

关键词： Binding sites

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Data-driven Fault Diagnosis Method Based on Fusion of Multi-direction and Multi-source Signals 5

Data-driven Fault Diagnosis Method Based on Fusion of Multi-...

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5th International Conference on intelligent Autonomous systems, ICoIAS 2022

作者： Yang, Yang Wang, Junda Li, Ning Shanghai Jiaotong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Department of Automation Shanghai China

ISBN: (数字)9781665498388

ISBN: (纸本)9781665498388

As a pivotal mechanical component of turbine drive-chain, gearbox suffers from various accidents and fault diagnosis could remarkably enhance its reliability and maintain running safety and lifetime. Vibration-based analysis on single-channel is mainly adopted in previous diagnostic, which cannot catch full vibration inner information in gearbox sensors and bring model performance down. In this paper, a novel method based on the fusion of multi-direction and multi-source signals and the convolutional neural network (MDMS-CNN) is presented. This method can obtain multi-dimensional feature maps from MDMS and preserve the time correlation among different signal sequences. First, features from MDMS are extracted via a corrosion conversion method that converts signals into two-dimensional (2-D) gray images. Then, homologous images are spliced into same channels, while heterogeneous images are superimposed to different channels. Finally, fusion features are input into CNN for fault classification. In experiments, the method is validated on a gearbox diagnosis case. Results have shown that the proposed method achieves 99.86% recognition accuracy and faster convergence speed compared to others. © 2022 IEEE.

关键词： Failure analysis

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Distributed Real-time State Estimation for Combined Heat and Power systems

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Journal of Modern Power systems and Clean Energy 2021年第2期9卷 316-327页

作者： Tingting Zhang Wen Zhang Qi Zhao Yaxin Du Jian Chen Junbo Zhao the Key Laboratory of Power System Intelligent Dispatch and Control Ministry of EducationShandong UniversityJinan 250061China the Department of Electrical and Computer Engineering Mississippi State UniversityStarkvilleMS 39762USA

This paper proposes a distributed real-time state estimation(RTSE)method for the combined heat and power systems(CHPSs).First,a difference-based model for the heat system is established considering the dynamics of heat *** heat system model is further used along with the power system steady-state model for holistic CHPS state estimation.A cubature Kalman filter(CKF)-based RTSE is developed to deal with the system nonlinearity while integrating both the historical and present measurement ***,a multi-timescale asynchronous distributed computation scheme is designed to enhance the scalability of the proposed method for largescale *** distributed implementation requires only a small amount of information exchange and thus protects the privacy of different energy *** carried out on two CHPSs show that the proposed method can significantly improve the estimation efficiency of CHPS without loss of accuracy compared with other existing models and methods.

关键词： Combined heat and power system(CHPS) cubature Kalman filter(CKF) heat dynamics multi-time-scale asynchronous distributed scheme real-time state estimation(RTSE)

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