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检索条件"机构=China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex System"

共 1567 条记录，以下是231-240 订阅

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Inverse Compensation Feedforward control Strategy for a Vertical Pneumatic Artificial Muscle system 8

Inverse Compensation Feedforward Control Strategy for a Vert...

引用

8th International Conference on control Science and systems Engineering, ICCSSE 2022

作者： Xiao, Huai Meng, Qingxin Lai, Xuzhi Yan, Ze Zhao, Shiying Wu, Min School of Automation China University of Geosciences 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 Hubei Wuhan430074 China

ISBN: (纸本)9781665484138

This paper proposes an inverse compensation feed-forward control strategy for a vertical pneumatic artificial muscle (PAM) system. Firstly, we conduct a preliminary experiment on the vertical PAM system, and on this basis, we analyze the motion characteristics of the system. Moreover, we clarify the control objective of this paper. Then, we establish a model that can describe the hysteresis characteristics of the system, and we further construct an inverse compensation feedforward controller by inversing this established model. Finally, we carry out some tracking control experiments based on the vertical PAM experimental platform to verify the effectiveness and superiority of the proposed control strategy, © 2022 IEEE.

关键词： Hysteresis

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AFPN based YOLOX for Rotation Object Detection in Remote Sensing Image

AFPN based YOLOX for Rotation Object Detection in Remote Sen...

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2024 china automation Congress, CAC 2024

作者： Zhou, Wen Liu, Xiaobo Zheng, Yiting Zhang, Dongsen Xiang, Hongbo School of Automation China University of Geosciences Wuhan430074 China Hubei Key Lab of Advanced Control and Intelligent Automation China University of Geosciences Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Key Laboratory of Geological Survey and Evaluation Ministry of Education China University of Geosciences Wuhan430074 China

ISBN: (纸本)9798350368604

Rotation Object Detection in Remote Sensing Image is a big challenge, as it has different sizes and orientations. In this paper, we proposed an AFPN and YOLOX based Rotation Object Detection method, named AFPN-RYOLOX. In the AFPN-RYOLOX, an angle prediction branch added into the detection head of YOLOX and revised the loss function to incorporate Kullback-Leibler Divergence (KLD) loss firstly, which enhanced loss continuity and ensuring scale invariance. Then, the Asymptotic Feature Pyramid Network (AFPN) is integrated in the neck layer of YOLOX, which boosts the network’s capability to extract features and decreases the number of model parameters through a dual-phase adaptive spatial fusion process. Through compare with other SOTA method, the proposed AFPN-RYOLOX achieved superior performances on DOTA and HRSC2016 datasets. © 2024 IEEE.

关键词： Deep learning

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Optimal Scheduling Strategy of Limited Electricity Based on Energy Sharing of Multi-microgrid

Optimal Scheduling Strategy of Limited Electricity Based on ...

引用

2022 Chinese automation Congress, CAC 2022

作者： Zeng, Zihan Li, Danyun Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China

ISBN: (纸本)9781665465335

In the environment of limited electricity supply in distribution network, due to the limitation of its own power capacity and the uncertainty of new energy output, there will be insufficient electricity supply in microgrid, which will affect the economy and comfort of users in microgrid system. Therefore, aiming at the situation of limited electricity supply in distribution network, multi-microgrid system is taken as the research object, and the cooperative game method is adopted to realize the energy sharing of multi-microgrid system, and then the limited electricity optimal dispatching model of multi-microgrid system is constructed to realize the reasonable power distribution for different types of loads. Finally, the simulation results show that this strategy can effectively realize power sharing, reduce outage loss and improve user satisfaction. © 2022 IEEE.

关键词： Electric power distribution

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Dual-polarization Dual-mode Silicon 3dB Beam Splitter Based on Shallow Etched Multimode Interference Coupler

Dual-polarization Dual-mode Silicon 3dB Beam Splitter Based ...

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Optoelectronics Global Conference (OGC)

作者： Hong Ma Mengyuan Ye Jie Liu Duowei Zeng Yang Chen School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences Wuhan China

In this paper, we propose a dual polarization dual mode 3dB beam splitter. By utilizing the shallow etched multimode interference (MMI) coupler, the proposed device can handle TE 0 , TE 1 , TM 0 and TM 1 modes simul...

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An accurate tuning model of spintronic memristor with different switching thresholds by logic judgment of domain wall motion 41

An accurate tuning model of spintronic memristor with differ...

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第41届中国控制会议

作者： Kun Wang Yajuan Hui Zhong Yang Xiangshui Miao 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 National Lab for Optoelectronics Huazhong University of Science and Technology

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Spintronic memristor possessing extraordinary advantages such as high-speed,low-power,highly scalable,and capable of constructing dynamic complex systems,which is a potential candidate for the next-generation memory *** many excellent models of spintronic memristor have been proposed,nonlinear model is not suitable for application analysis because of its complex *** this paper,an accurate tuning model of spintronic memristor with different switching thresholds by logic judgment of domain-wall motion is *** switching thresholds of current density are introduced to drive the domain-wall movement by judging the position of state value and real-time current density,which solves the general problems of boundary ***,by the simulation and verification via PSpice modeling,an accurate regulation of the resistance by voltage excitation is *** results pave the way for the applications of diversified circuit design for spintronic memristor.

关键词： Spintronic memristor Different switching thresholds SPICE model

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Research on Dynamic Labels in Network Pruning

Research on Dynamic Labels in Network Pruning

引用

Industrial Cyber-Physical systems (ICPS)

作者： Lijun Zhang Yaomin Luo Shiqi Xie Xiucheng Wu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation China University of Geosciences Wuhan China

Convolutional neural network compression technology plays an extremely important role in model transplantation and deployment, especially in mobile and embedded hardware platforms with small memory and low computing power, compression technology is even more critical. Convolutional neural network channel pruning technology has developed rapidly in recent years, and a number of excellent pruning algorithms have emerged. The channel pruning technology has gradually developed from the earliest static pruning to dynamic pruning, which adopts different pruning schemes for different inputs. However, the current dynamic pruning scheme needs to introduce multiple modules to predict the mask to prune the feature maps, and some schemes also introduce multiple hyperparameters in the loss function to balance the model accuracy and pruning rate, which leads to The model has difficulty converging during training. We propose a dynamic pruning method, each convolution structure configures a simple prediction module, and generating dynamic labels through the input's norm and similarity to guide the prediction module training, which will not bring new parameters to the loss function. We conducted related experiments on multiple models on the Cifar10 datasets. The experiments on ResNet56 show that our scheme is 1.3% higher than the most advanced scheme in terms of compression rate under the premise of the same accuracy.

关键词： Training Convolution Heuristic algorithms Computational modeling Predictive models Cyber-physical systems Prediction algorithms

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Correction of Images Projected on Non-White Surfaces Based on Deep Neural Network 14

Correction of Images Projected on Non-White Surfaces Based o...

引用

14th International Conference on Digital Image Processing, ICDIP 2022

作者： Wang, Zewei Zhang, Jingjing Du, Xingzhuo Cao, Sihua Wei, Wenxuan School of Automation China University of Geosciences 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 China

ISBN: (纸本)9781510657564

When projecting onto a non-white surface, the projected image is distorted or color mixing by complex luminance and chrominance information, which makes the projection result different from the visual perception of the human eye. The purpose of projection image correction is to remove these effects, and traditional solutions usually estimate parameters from the collected projection samples, compute an inverse model of the projection imaging process, and try to fit a correction function. In this paper, a deep neural network-based projection image correction network (PICN) is designed to implicitly learn complex correction functions. PICN consists of a U-shaped backbone network, a convolutional neural network that extracts projected surface features, and a perceptual loss network that optimizes the correction results. Such a structure can not only extract the deep features and surface interference features of the projected image, but also make the corrected projected image more in line with human visual perception. In addition, we built a projector-camera system under the condition of a fixed global illumination environment for verification experiment, and proved the effectiveness of the proposed method by calculating the evaluation metrics of projected images before and after correction. © 2022 SPIE.

关键词： Deep neural networks

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Polarization-independent Dual Mode Silicon Spot Size Converter Using Gradual Index Distributed Subwavelength Gratings

Polarization-independent Dual Mode Silicon Spot Size Convert...

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Optoelectronics Global Conference (OGC)

作者： Jie Liu Mengyuan Ye Hong Ma Duowei Zeng Yang Chen School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

We propose and demonstrate a polarization-independent dual mode spot size converter (SSC) on silicon integrated platform. By utilizing gradual index distributed subwavelength gratings (GRIN-SWG). The proposed device c...

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Drug-target interaction prediction using high order nonlinear features via neural factorization machines 4

Drug-target interaction prediction using high order nonlinea...

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2022 4th International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2022

作者： Qian, Quan Zhu, Yuan School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

Medication design and repositioning are sped up by the prediction of drug-target interactions (DTIs). Two main kinds of prediction methods are commonly used, which are based on chemical structure feature extraction and deep learning methods. However, on the one hand, the DTI prediction approaches based on chemical structural feature extraction may not wholly explore the possible network characteristics in the data. On the other hand, many deep learning methods call for numerous layers of neural networks to be layered to learn higher-order feature interaction information. To sum up, the existing computation methods often have the limitations of gradient disappearance and overfitting. This study presents a novel method (JRD-NFM) by calculating Jaccard similarities, getting an eigenvector through Restarted random walk (RWR), and generating low-dimensional feature vectors by Disposition Component Analysis (DCA). Besides decoding the topological features and similarity information of target and drug node, it can also get the context information of a single network. Considering the advantages of Neural Factorization Machines (NFM) in extracting high-order nonlinear features and processing sparse data, this study use NFM to classifier the collection data to integrate drug and target biochemical structure information. The experimental results demonstrate that JRD-NFM can outperform widely used deep learning methods and conventional chemical structure approaches. It could provide fresh ideas for combining molecular structure and heterogeneous network data to predict DTIs. © Published under licence by IOP Publishing Ltd.

关键词： Feature extraction

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Wavelength Selective Mode Converter Using Grating Assisted Anti-reflection Contra-asymmetric Directional Couplers

Wavelength Selective Mode Converter Using Grating Assisted A...

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Optoelectronics Global Conference (OGC)

作者： Duowei Zeng Mengyuan Ye Yang Chen Hong Ma Jie Liu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

We propose and demonstrate a wavelength selective mode converter on silicon integrated platform. By utilizing grating assisted anti-reflection contra-asymmetric directional couplers (CADCs), wavelength selective TE 0 -TE 1 mode conversion could be achieved. Simulation results show that the operation wavelength is 1544.8 nm and 3 dB bandwidth is 8.3 nm. Insertion loss of the proposed device is simulated to be 0.29dB and the crosstalk is less than -50dB. The proposed device can be used in mode division multiplexing (MDM) wavelength division multiplexing (WDM) communication network.

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