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42nd Chinese control Conference, CCC 2023

作者： Li, Zexin Liu, Guoqiang Zhao, Wei Li, Xi School of Artificial Intelligence and Automation Huazhong University of Science & Technology Key Laboratory of Image Processing and Intelligent Control of Education Ministry Hubei Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute Guangdong Shenzhen518055 China

ISBN: (纸本)9789887581543

The multi-stack fuel cell system (MFCS) is an important basis for the application of solid oxide fuel cell (SOFC) technology to large-scale power generation systems. MFCS can provide higher power, longer lifetime and better reliability. Different from the single-stack fuel cell system (SFCS), there may be some inconsistencies among the stacks in the MFCS. If the inconsistencies are ignored, they will significantly affect the lifetime of the MFCS. This study focuses on the lifetime extension of multi-stack SOFC power generation systems with inconsistent stacks. Since the multi-stack system of SOFC generally cannot control the flow rate of each stack respectively, it brings a difficulty to the control of the MFCS with inconsistencies among the stacks. In order to overcome this difficulty, this paper built a multi-stack SOFC system model, which can characterize the degradation and inconsistencies among SOFC stacks. And then designed a power distribution strategy based on fuzzy control to extend the lifetime of the MFCS. The strategy was verified by simulations. The simulation results show that the strategy can effectively control the inconsistencies among the stacks and significantly extend the lifetime of the MFCS. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Fuzzy control

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Nested Saturated control of Uncertain Complex Cascade Systems Using Mixed Saturation Levels

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IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1163-1174页

作者： Meng Li Zhigang Zeng Wuhan National Laboratory for Optoelectronics Wuhan 430074 School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074 Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074China

This study addresses the problem of global asymptotic stability for uncertain complex cascade systems composed of multiple integrator systems and non-strict feedforward nonlinear systems. To tackle the complexity inherent in such structures, a novel nested saturated control design is proposed that incorporates both constant saturation levels and state-dependent saturation levels. Specifically, a modified differentiable saturation function is proposed to facilitate the saturation reduction analysis of the uncertain complex cascade systems under the presence of mixed saturation levels. In addition, the design of modified differentiable saturation function will help to construct a hierarchical global convergence strategy to improve the robustness of control design scheme. Through calculation of relevant inequalities, time derivative of boundary surface and simple Lyapunov function,saturation reduction analysis and convergence analysis are carried out, and then a set of explicit parameter conditions are provided to ensure global asymptotic stability in the closed-loop systems. Finally, a simplified system of the mechanical model is presented to validate the effectiveness of the proposed method.

关键词： method saturation differentiable

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Retinex-based Illumination feature fusion network for low-light image enhancement 4

Retinex-based Illumination feature fusion network for low-li...

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4th International Conference on Artificial Intelligence and Computer Engineering, ICAICE 2023

作者： He, Tiange Liang, Yuqi Lanzhou Jiaotong University Key Laboratory of Optoelectronic Technology and Intelligent Control Ministry of Education Gansu Lanzhou730000 China

ISBN: (纸本)9798400708831

Vision is the main means for human beings to acquire external information, and with the arrival of the wave of informationization, digital images have become an important carrier of information dissemination. Due to the complexity of the imaging environment, as well as the lack of hardware conditions of the imaging equipment, the directly acquired images are often of poor quality, limiting their application in actual scenes, while the lack of light during the image acquisition process will greatly reduce the visibility of the image. Existing low-light image enhancement techniques are difficult to balance quality and efficiency, and are ineffective in complex scenes. In this paper, an image decomposition model is constructed based on Retinex theory to reduce the uncertainty of decomposition. In order to recover the degradation process existing in the reflection image, a light feature map is introduced to serve as a guide, and an image enhancement network module is constructed by using a light feature fusion module, and at the same time, a light tuning network is designed to adaptively adjust the lighting conditions of the light map. Experiments on a benchmark dataset show the effectiveness and rationality test of the method. © 2023 ACM.

关键词： image enhancement

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A Point Cloud Segmentation Method Based on Ground Point Cloud Removal and Multi-Scale Twin Range image 42

A Point Cloud Segmentation Method Based on Ground Point Clou...

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42nd Chinese control Conference, CCC 2023

作者： Zhou, Yicheng Peng, Gang Duan, Hangqi Wu, Zhangang Zhu, Xukang School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Ministry of Education Wuhan430074 China Shantui Construction Machinery Co. Ltd. Jining272073 China

ISBN: (纸本)9789887581543

Aiming at the shortcomings of traditional point cloud segmentation algorithms, this paper proposes a 3D lidar point cloud segmentation method combining ground filtering and multi-scale twin range image construction. This method fully considers the geometric space distribution characteristics of the point cloud and the randomness of the positions between objects. Based on the assumption of multi plane model, the point cloud is divided into sectors. The ground points are removed through region ground plane fitting and growth, and then the multi-scale twin range image is constructed according to non-ground points. On the basis of the twin range image, the Breadth First Search algorithm is improved, the depth-breadth joint search strategy is proposed, all the points to be clustered are traversed, and the adaptive clustering threshold is used for point cloud clustering, which realizes a point cloud segmentation method with higher accuracy and robustness. Through the experimental analysis of KITTI dataset and collected campus outdoor scene dataset, compared with the traditional point cloud segmentation algorithm, the method proposed in this paper can effectively improve the point cloud segmentation accuracy and robustness of mobile robots in complex environments. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： image enhancement

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MultiJSQ:Direct joint segmentation and quantification of left ventricle with deep multitask-derived regression network

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CAAI Transactions on Intelligence Technology 2025年第1期10卷 175-192页

作者： Xiuquan Du Zheng Pei Ying Liu Xinzhi Cao Lei Li Shuo Li Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education Anhui UniversityHefeiChina School of Computer Science and Technology Anhui UniversityHefeiChina Department of Neurology Shuyang Affiliated Hospital of Nanjing University of Traditional Chinese MedicineSuqianChina Department of Biomedical Engineering Case Western Reserve UniversityClevelandOhioUSA

Quantitative analysis of clinical function parameters from MRI images is crucial for diagnosing and assessing cardiovascular ***,the manual calculation of these parameters is challenging due to the high variability among patients and the time-consuming nature of the *** this study,the authors introduce a framework named MultiJSQ,comprising the feature presentation network(FRN)and the indicator prediction network(IEN),which is designed for simultaneous joint segmentation and *** FRN is tailored for representing global image features,facilitating the direct acquisition of left ventricle(LV)contour images through pixel ***,the IEN incorporates specifically designed modules to extract relevant clinical *** authors’method considers the interdependence of different tasks,demonstrating the validity of these relationships and yielding favourable *** extensive experiments on cardiac MR images from 145 patients,MultiJSQ achieves impressive outcomes,with low mean absolute errors of 124 mm^(2),1.72 mm,and 1.21 mm for areas,dimensions,and regional wall thicknesses,respectively,along with a Dice metric score of *** experimental findings underscore the excellent performance of our framework in LV segmentation and quantification,highlighting its promising clinical application prospects.

关键词： global image features joint segmentation and quantification left ventricle(LV) multitask-derived regression network

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State-of-Charge Balancing control for Battery Energy Storage Systems of Near-Space Vehicles with an Electric-Thermal-Aging Coupling Model 42

State-of-Charge Balancing Control for Battery Energy Storage...

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42nd Chinese control Conference, CCC 2023

作者： Zuo, Zhiqiang Du, Yunhao Wang, Yijing Zhang, Zhicheng Li, Peng School of Electrical and Information Engineering Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Tianjin University Tianjin300072 China Ministry of Education Key Laboratory of System Control and Information Processing Shanghai200240 China

ISBN: (纸本)9789887581543

State-of-charge (SoC) balancing is crucial for improving the efficiency and lifetime of the battery energy storage system in near-space vehicles. In this paper, the SoC balancing control problem is investigated by a coupling battery model with electric-thermal-aging dynamics. Firstly, a system identification experiment is carried out to obtain the internal parameters of the battery. Secondly, a weight optimization index is designed by integrating the balancing speed and battery state-of-health (SoH). Then, a receding horizon control algorithm is proposed to realize multi-unit battery SoC balancing with partial swarm optimization (PSO). Finally, the effectiveness of the proposed strategy is verified by simulation results. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Battery management systems

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Online Identification of Boost Converter Components with Multiple Updating RLS Algorithm 42

Online Identification of Boost Converter Components with Mul...

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42nd Chinese control Conference, CCC 2023

作者： Zhou, Tong Zhang, Zhicheng Zuo, Zhiqiang Wang, Yijing Li, Peng School of Electrical and Information Engineering Tianjin Key Laboratory of Intelligent Unmanned Swarm Technology and System Tianjin University Tianjin300072 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China

ISBN: (纸本)9789887581543

In this paper, component parameters of the boost converter are identified online using a multiple updating recursive least squares (MURLS) algorithm. The component parameters, such as resistance, inductor inductance and capacitor capacitance, are obtained directly through the identification procedure rather than transfer function coefficients. The MURLS algorithm is applied to improve the rapidity of system identification compared to the traditional recursive least squares (RLS) algorithm, which is verified by a comparative simulation between MURLS and RLS and the simulation of a load-switching scenario. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Parameter estimation

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Economic Scheduling of Multi-microgrid Systems Based on Distributed Event-triggered Consensus Strategy 8

Economic Scheduling of Multi-microgrid Systems Based on Dist...

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8th International Conference on Power and Renewable Energy, ICPRE 2023

作者： Xu, Tingting Fang, Xiaohan Fan, Yuan Anhui University Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Electrical Engineering and Automation Hefei230601 China

ISBN: (纸本)9798350328813

Multi-microgrid (MMG) systems offer notable advantages in terms of power sharing and mutual support when compared to individual microgrids (MGs). This paper presents a based on distributed event-triggered consensus strategy for optimizing the economic dispatch of multiple microgrids. The incorporation of the event-triggered mechanism into the multi-microgrid framework significantly reduces unnecessary communication among microgrids in contrast to the conventional time-triggered approach. For the multi-microgrid setup, a two-layer control strategy consisting of inter-microgrid and intra-microgrid layers is employed to achieve coherence by regulating the micro-incremental rates of distributed generation (DG) units. Leaderless event-triggered consistency is utilized for inter-microgrid coordination, while leader event-triggered consistency is implemented for intra-microgrid coordination, ultimately realizing the economic objective of minimizing the operational costs of the multi-microgrid system. Simulation results validate the efficacy of introducing the event-triggered mechanism and its impact on the economic dispatch of the multi-microgrid system. © 2023 IEEE.

关键词： Consensus Event-triggered Micro-incremental rates Multi-microgrid

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Subsampling Decomposition based k-Space Refinement for Accelerated MRI Reconstruction

Subsampling Decomposition based k-Space Refinement for Accel...

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2025 IEEE International Conference on Acoustics, Speech, and Signal processing, ICASSP 2025

作者： Qiao, Xiaoyu Li, Weisheng Xiao, Bin Huang, Yuping Yang, Lijian Chongqing Key Laboratory of Image Cognition Chongqing University of Posts and Telecommunications Chongqing China Key Laboratory of Cyberspace Big Data Intelligent Security Chongqing University of Posts and Telecommunications Ministry of Education Chongqing China

ISBN: (纸本)9798350368741

In accelerated MRI reconstruction problem, directly recovering all the missing k-space data from undersampled measurements is highly ill-posed and often leads to suboptimal performance. To address the problem, we propose a novel deep unfolding network (DUN) with subsampling decomposition (SD) based k-space refinement to mitigate the ill-posedness. Our method employs a parallel network architecture with a primary branch unfolded by gradient descent-inspired optimization process (GD-PB) for reconstruction. Additionally, we introduce an SD-based auxiliary branch (SD-AB) that decompose the inverse problem into moderately corrupted subproblems. We design a novel subsampling mask predictor that captures both global and local spatial correlations in k-space, ensuring the SD-AB effectively preserves the most well-reconstructed subsets as reliable region (RR). The RR in SD-AB is used to periodically refine the intermediate outputs of the GD-PB, achieving improved accuracy. Experimental results reveal that our method significantly outperforms conventional and SD-based DUN techniques, achieving superior PSNR and SSIM results compared with cutting-edge methods. © 2025 IEEE.

关键词： compressed sensing deep unfolded network MRI reconstruction parallel imaging subsampling decomposition

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Research and significance of DC switch acquisition board in railway signal training system

Research and significance of DC switch acquisition board in ...

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2022 International Conference on Signal processing and Communication Technology, SPCT 2022

作者： Gao, Shuai He, Tao Key Laboratory of Optoelectronic Technology and Intelligent Control Ministry of Education Lanzhou Jiaotong University China Institute of Automatic Control Lanzhou Jiaotong University China

ISBN: (纸本)9781510664333

With the vigorous promotion of railway infrastructure construction in china, higher requirements have been put forward for railway running safety. Railway signal monitoring equipment, as the key equipment to ensure driving safety, find and solve the fault, has a broad development prospect in the process of railway system modernization[1]. By analyzing the practical significance of railway signal training system and referring to the technical conditions of railway signal centralized monitoring system, the DC switch acquisition module of railway signal training system is developed and designed based on the microcontroller of Cortex-M4 kernel. The acquisition board has unique advantages in power consumption, acquisition speed and scalability, high integration, good reliability, its accuracy and stability meet the requirements of railway signal training, has a broad space for development, and is of great significance for the pre-job training of railway related majors and the improvement of teaching quality. © 2023 SPIE.

关键词： Railroads

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