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2024 China Automation Congress, CAC 2024

作者： Wang, Ying Lang, Xun Wu, Jiande Li, Yuzhen Li, Peng Zhang, Yufeng Department of Electronic Engineering Information School Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China

ISBN: (纸本)9798350368604

Variational mode decomposition (VMD) is extensively utilized in the field of industrial signal processing due to its superior anti-mixing and denoising capabilities. However, in practice, the performance of VMD is significantly influenced by the initial center frequency. An improper setting of can significantly reduce the stability of decomposition, resulting in the loss or masking of feature information by noise. To address the above issue, an improved VMD algorithm is proposed in this work. Our algorithm redefines based on the narrowband characteristics of intrinsic mode function (IMF). Under the new definition, can be adaptively adjusted based on the signal spectrum processed by Wiener filtering. This adjustment significantly enhances the flexibility and anti-mixing performance of the original VMD. To validate our proposed method, comparative experiments were conducted using two sets of fault data from Case Western Reserve University (CWRU). The results demonstrate that our method is more effective and superior in extracting fault features. © 2024 IEEE.

关键词： Variational mode decomposition

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A Scholar of Dignity:Remembering Peter Luh

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1895-1897页

作者： Fei-Yue Wang Macao University of Science and Technology Macao 999078China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of SciencesBeijing 100190China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China

It was a shock and disbelief to learn of Peter's death last *** me,he was so fit in his figure,so healthy in his lifestyle,so mild and mindful in his social behavior,and so devout in his religious belief,......,I ... 详细信息

关键词： religious Scholar belief

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Digital CEOs in Digital Enterprises:Automating,Augmenting,and Parallel in Metaverse/CPSS/TAOs

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IEEE/CAA Journal of Automatica Sinica 2024年第4期11卷 820-823页

作者： Juanjuan Li Rui Qin Sangtian Guan Xiao Xue Peng Zhu Fei-Yue Wang with State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the College of Intelligence and Computing Tianjin UniversityTianjin 300072China School of Economics and Management Nanjing University of Science and TechnologyNanjing 210094China the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China

BIG models or foundation models are rapidly emerging as a key force in advancing intelligent societies[1]–[3]Their significance stems not only from their exceptional ability to process complex data and simulate advan... 详细信息

关键词： exceptional Auto advancing

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A self-adaptive multi-objective harmony search based fuzzy clustering technique for image segmentation

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Journal of Ambient Intelligence and Humanized computing 2023年第11期14卷 14943-14958页

作者： Wan, Changjing Yuan, Xiaofang Dai, Xiangshan Zhang, Ting He, Qian College of Electrical and Information Engineering Hunan University Changsha410082 China Guangxi Colleges and Universities Key Laboratory of Cloud Computing and Complex Systems Guilin University of Electronic Technology Guilin541004 China

Image segmentation can be considered as a problem of clustering since the pixels in the digital image are clustered in term of some evaluation criteria. Generally, clustering technique in image segmentation employs a single objective which can not reach ideal result for various kinds of images. Moreover, fuzzy c-means (FCM) algorithms which determine the fuzzy partition matrix of the data set by solving the clustering problem with conditional constraints and obtain the clustering output, have been verified effective and efficient for image segmentation. In fact, these FCM algorithms still have some shortcomings including: being sensitive to outliers and noise, key parameters need to be adjusted with experience. In view of this, a self-adaptive multi-objective harmony search based fuzzy clustering (SAMOHSFC) technique for image segmentation is proposed in this paper. SAMOHSFC technique encodes several cluster centers in one harmony vector and optimizes multiple objectives. In addition, we consider the spatial information of the image as an attribute of the input data set besides the attribute of gray information of input image in the SAMOHSFC. Superiority of the proposed algorithm over three classic segmentation algorithms has been verified for a synthetic and two real images from quantitative and visual aspect. In the experiment, the effect of different kinds of spatial information on the segmentation performance of the SAMOHSFC is analyzed. © 2018, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Multiobjective optimization

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Structured Music Transformer: Structured conditional music generation based on stylistic clustering using Transformer 43

Structured Music Transformer: Structured conditional music g...

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43rd Chinese Control Conference, CCC 2024

作者： Zhang, Dan Chen, Xin Xiao, Zhe China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

ISBN: (纸本)9789887581581

Recent advancements in music generation research have significantly progressed the field. However, a prevalent issue among current models is their tendency to overlook music's intrinsic structure, leading to compositions that lack coherence and thematic consistency. This paper proposes a novel approach to structured music generation that addresses these challenges by considering music structure as styles of different subsegments. The approach enhances the deep structural aspects of generative music by deriving embedding vectors from pre-trained contrastive models and clustering them into discrete structured tokens for generative conditions. Furthermore, this study introduces a self-similarity-based evaluation method to assess the structural features of the generated music. Experimental results indicate that the Structured Music Transformer (SMT) significantly outperforms contemporary models in producing compositions that are stylistically coherent and structurally robust, as demonstrated across two diverse datasets. © 2024 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Contrastive Learning

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Comprehensive Gear Shift Schedule Design for 2-AMT Electric Vehicles Based on Sparrow Search Algorithm 42

Comprehensive Gear Shift Schedule Design for 2-AMT Electric ...

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42nd Chinese Control Conference, CCC 2023

作者： Wang, Tianyi Ma, Liling Wang, Junzheng School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789887581543

With the aim of 2-AMT electric vehicles, a comprehensive shift schedule that considers both power and economy is proposed. First, the objective function of the comprehensive shift schedule is constructed, which is the weighted sum of vehicle acceleration time and vehicle power consumption per unit distance. Second, Sparrow Search Algorithm is used to solve the objective function and obtain the comprehensive shift schedule. Finally, AVL Cruise simulation software is used to simulate vehicle dynamics and economy under an NEDC. The results show that the comprehensive shift schedule is similar to the optimal power shift schedule in terms of dynamic performance, and the economy is optimized by 3%. The feasibility of the comprehensive shift schedule is verified. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Electric vehicles

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Few-shot Pose-free View Synthesis with 3D Gaussian Splatting

Few-shot Pose-free View Synthesis with 3D Gaussian Splatting

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2024 China Automation Congress, CAC 2024

作者： Huang, Yuan Xu, Chi 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 Wuhan China

ISBN: (纸本)9798350368604

Recent advancements in Novel View Synthesis using neural radiance fields and 3D Gaussian splatting have demonstrated promising results. However, these methods conventionally rely on accurate initial poses and point clouds from the model of structure from motion, which poses challenges in sparse input views. To addressing these drawbacks, we introduces an novel method for view synthesis based on 3D Gaussian splatting. Our approach operates on sparse input views without the prerequisite of pose priors, achieving reconstruction and real-time rendering of novel perspectives. For the deficiency of camera poses and point cloud, we employ an end-to-end deep learning model to recover the 3D structure from a few of 2D images to initialize the 3D Gaussian point cloud. In addressing the issue with few-shot, we utilize the differentiable rasterization module to render depth map and apply regulation on it. Additionally, we incorporate supervision between input views by interpolating to generate novel perspectives during training. Experimental results demonstrate that our proposed method significantly enhances the capabilities of 3D Gaussian splatting for novel view synthesis in sparse views and without the necessity of camera pose priors. © 2024 IEEE.

关键词： 3D reconstruction

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Electric Dual Variable Pump Controlled Hydraulic Motor 42

Electric Dual Variable Pump Controlled Hydraulic Motor

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42nd Chinese Control Conference, CCC 2023

作者： Yang, Jianmin Wang, Junzheng Niu, Shanshuai School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing100081 China

ISBN: (纸本)9789887581543

The combined control of variable speed and variable displacement is a new type of volume control with high efficiency and fast response. However, due to the inherent nonlinearity of multiplication, it brings certain difficulties to the control. The electric double-variable pump[1] is a dual-input single-output system, and it is a nonlinear system[2]. It is necessary to linearize the system or use a nonlinear control method to control and solve the control problem of the system. In this paper, an intelligent control rule is proposed for the nonlinear problem of double input and single output. Through backstepping design[3], the nonlinear system is transformed into multiple linear subsystems. Then the original system is turned into two independent subsystems with single input and single output, which are controlled separately. The co-simulation platform based on AMESIM and Simulink[4] has been verified and compared with a single PID control algorithm to simulate the step response and sinusoidal tracking performance of the system. The results show that the response speed of the system has been greatly improved. © 2023 Technical Committee on Control Theory, Chinese Association of Automation.

关键词： Backstepping

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Design of Load Frequency Controller for Power System Based on Equivalent Input Disturbance Method 4

Design of Load Frequency Controller for Power System Based o...

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4th IEEE New Energy and Energy Storage System Control Summit Forum, NEESSC 2024

作者： Zhang, Jianrong Xu, Hang Wang, Hongzhang Zhang, Chuanke 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 Automation Wuhan China

ISBN: (纸本)9798350389012

In the power system, due to the instability of the external environment, safe and stable operation cannot always be guaranteed, as it frequently encounters varying degrees of external disturbances. In order to mitigate the effects of these disturbances on the system, the power system can operate safely and stably, In this paper, a power system load frequency control (LFC) based on Equivalent Input Disturbance (EID) method is proposed from the perspective of active disturbance suppression. Firstly, the disturbances present in the environment are unified as external disturbances, and then a single area the electric power system model with external disturbance was constructed. Then, a controller algorithm based on EID was designed using EID equivalent processing method and linear matrix inequality method to address the issue of external interference in the power system. Finally, a numerical example is used to validate the effectiveness and accuracy of the controller by simulating with two aspects, fixed perturbation and random perturbation, respectively. © 2024 IEEE.

关键词： Linear matrix inequalities

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DMA-Net: A Deep Multi-Attention Network for Brain Tumor Classification on MRI Images 7

DMA-Net: A Deep Multi-Attention Network for Brain Tumor Clas...

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7th International Conference on Biological Information and Biomedical Engineering, BIBE 2024

作者： Yu, Wanlong Ma, Zhaopeng Zhang, Xiang He, Bingbing Lang, Xun Zhang, Yufeng Bai, Zhengyao Lv, Wenbing School of Information Yunnan University Yunnan Kunming650504 China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Yunnan Kunming650504 China

ISBN: (纸本)9783800762910

Accurate and impartial classification of brain tumors is crucial for early diagnosis and treatment. Deep learning technology can effectively represent and utilize the visual content of images, playing a key role in more precise medical image analysis. In this study, we proposed an advanced deep multi-attention network (DMA-Net) to address the challenge of brain tumor classification on MRI images. The proposed DMA-Net employs a novel multi-layer attention mechanism, integrating efficient channel attention (ECA), spatial attention (SPA), depthwise separable convolutions with vision transformer (DWSC-ViT), and group attention (GA) to enhance the processing of complex neural imaging. Our approach is characterized by its ability to effectively balance detailed image representation and computational efficiency, maintaining excellent classification accuracy even with a substantial reduction in model parameters. With the integration of these new modules, DMA-Net outperformed other state-of-the-art (SOTA) mobile networks, achieving a classification accuracy of 96.70% and an AUC of 0.9971 in brain tumor classification. Furthermore, DMA-Net is the most compact model among the SOTA networks, demonstrating significant potential for deployment on mobile devices to enhance application efficiency. © VDE VERLAG GMBH.

关键词： Magnetic resonance imaging

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