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H∞ State Estimation for Time-Delayed Static Neural Networks Using an Improved Delay-Product-Type LKF

H∞ State Estimation for Time-Delayed Static Neural Networks...

引用

第42届中国控制会议

作者： Yong-He Lao Yu-Long Fan Liang-Tong Luo Chuan-Ke Zhang 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

This paper is concerned with H performance state estimation of static neural networks with a time-varying ***, a PI estimator with exponential term is used to estimate neuron states based on output measurement. Second, an augmented Lyapunov-Krasovskii functional（LKF） containing delay-product-type non-integral terms and single integral terms is constructed by introducing negative definite terms. After that, a criterion with less conservatism is derived based on extended reciprocally convex matrix inequality. Finally, a numerical example is provided to reveal the effectiveness of the proposed approach.

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Hot Spot Detection of Photovoltaic Module Infrared Near-field Image based on Convolutional Neural Network 4

Hot Spot Detection of Photovoltaic Module Infrared Near-fiel...

引用

2022 4th International Conference on Energy systems and Electrical Power, ICESEP 2022

作者： Fan, Fu Na, ZhiXiong Zhang, ChangZhi Li, HaoRan Tong, ChaoLiu School of Computer Science and Technology Beijing Institute of Technology Beijing100081 China State Grid e-commerce Co. Ltd Beijing100053 China State Grid Tianjin Electric Power Company Tianjin300010 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China

With the installation and use of large-scale photovoltaic systems around the world, the detection of photovoltaic system operation and maintenance has become increasingly important. This research uses a convolutional neural network training model to detect and classify the infrared near-field images of photovoltaic modules from small-scale photovoltaic plants in the laboratory. This model classifies the images into two categories: with and without hot spots, with a classification accuracy of 96.58%. The experimental results show that the convolutional neural network training model has a good classification result. © 2022 Institute of Physics Publishing. All rights reserved.

关键词： Convolutional neural networks

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The 110kV Live-maintaining Robot control system Design For Substation Equipment in complex Working Conditions

The 110kV Live-maintaining Robot Control System Design For S...

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第42届中国控制会议

作者： Chenyu Hu Xin Chen Chengyu Li Guangxian Huang Cheng Zhou Xu Jian 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

Live-maintaining work is essential for continuous power supply to the *** improve the safety and efficiency of live-maintaining work,this paper proposes an equipotential live-maintaining robot system suitable for 110 kV voltage *** the narrow space,complex working conditions and strong electromagnetic interference in substations,binocular vision technology,manipulator trajectory planning algorithm based on timeenergy optimization,high voltage electromagnetic shielding technology are utilized to develop the system,and the live-maintaining robot is successfully applied in actual *** accurately identifying and locating the joint bolts and insulator,the robot system can achieve equipotential live-disassemble,live-assemble the joint bolts within18 minutes and live-clean insulator within 5 minutes,demonstrating its the effectiveness and practicability.

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Trajectory Optimization for Multi-Lane Platoon Formation with Undefined Configurations

Trajectory Optimization for Multi-Lane Platoon Formation wit...

引用

International Conference on Intelligent Transportation

作者： Siwen Yang Yunwen Xu Dewei Li Chen Zhang School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China

Many studies have demonstrated the potential benefits of connected and autonomous vehicles (CAVs) platooning to energy consumption and traffic efficiency. However, how to implement platoon formation, which assigns and regulates vehicles scattered in different lanes to platoons, while reducing vehicle delay and time consumption remains an open issue. Besides, most existing studies require a predetermined platoon configuration, which decreases maneuverability. This paper proposes a multilane platoon formation strategy with undefined configurations. The vehicle sequence in newly formed platoons along with the longitudinal trajectories of all vehicles before changing lanes is optimized in a nonlinear programming model. The multi-objective function considers the average velocity of all CAVs and the time consumption of formation. A Fibonacci search algorithm with an embedded mixed integer linear programming (MILP) model is developed to obtain solutions efficiently. The numerical experiments indicate the superiority of the proposed method in optimizing the vehicles' trajectories and improving multi-lane platoon formation efficiency.

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Delay-Dependent Stability Analysis of Multi-Area Load Frequency control systems with Multiple Renewable Energy Structures

Delay-Dependent Stability Analysis of Multi-Area Load Freque...

引用

第42届中国控制会议

作者： Qian-Long Pan Li Jin Yong He Zhou-Zhou Liu 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

This paper investigates the delay-dependent stability of time-delayed load frequency control(LFC) systems with multiple energy structures based on Lyapunov theory and linear matrix inequality(LMI) ***,a multi-area delayed LFC model considering multiple renewable energy structures is ***,in order to improve the computation efficiency of stability analysis of large scale LFC systems,a new reconstruction technique for system model is ***,the improved delay-dependent stability criteria are established based on reconstructed model by using the Lyapunov stability ***,case studies are based on two-area LFC *** with the criterion based on the original model without reconstruction,the calculation efficiency of proposed stability criteria has been greatly improved with the cost of small accuracy,and the calculation accuracy is better than the previous methods.

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Image Segmentation Based on Improved Wavelet Transform

Image Segmentation Based on Improved Wavelet Transform

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第35届中国控制与决策会议

作者： Guowu Zhu Lixiang Ma Bingyou Liu Pan Yang College of Electrical Engineering Anhui Polytechnic University Key Laboratory of Advanced Perception and Intelligent Control of High-End Equipment Ministry of Education Anhui Institute of Information Technology College of Electrical Engineering Anhui Polytechnic University Key Laboratory of Advanced Perception and Intelligent Control of High-End EquipmentMinistry of Education Anhui Dar Intelligent Control System Stock Co. Ltd

In order to preserve the effective information of the image and segment it better,an image segmentation method based on improved wavelet transform is ***,the image is decomposed based on wavelet transform to obtain the horizontal,vertical and diagonal information of the ***,the peak and valley points are determined by the decomposed wavelet coefficients,and the segmentation threshold is ***,the experimental results show that the improved wavelet transform segmentation method proposed in this paper has better segmentation effect than the traditional segmentation method.

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Stability Analysis of a New Constant Current to Constant Voltage Power Supply system

Stability Analysis of a New Constant Current to Constant Vol...

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第42届中国控制会议

作者： Xiaoxian Song Zhijian Fang Yuangeng Xia Jie Cai Zihao Wei 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

A high-reliability constant current to constant voltage power supply system has the advantages of small volume of switching power supply,high power density,high efficiency was propos *** paper use two controllers to control the shunt regulator (SR) circuit and single-end flyback converter part,and separate the two parts for small signal modeling and give the parameters to stabilize the closed *** state space average modeling idea was used to solve the state equ ations for th e modes of the converters in a switching *** order to ensure the stability of cascade system,this paper collaborative optimization of hardware filter parameters and the appropriate PI parameter *** experimentals verify the correctness of our theory,and the system has good stability under closed-loop conditions.

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CrossNet: Computing-Friendly Lightweight Anchor-Free Detector 4

CrossNet: Computing-Friendly Lightweight Anchor-Free Detecto...

引用

4th International Conference on Artificial Intelligence and Big Data, ICAIBD 2021

作者： Yao, Yuncong Wang, Qiang Mai, Jiren Yang, Wankou Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjin210096 China School of Automation Southeast University Nanjin210096 China Jiangsu Automation Research Institute Lianyungang221116 China

ISBN: (纸本)9780738131702

Many scenarios such as edge and mobile scenarios are very sensitive to computing complexity and parameter size. Most object detection models cannot be directly deployed without specific modifications. In this paper, we introduce CrossNet, a compute-friendly lightweight anchor-free detector based on CenterNet. We abandon DCN module and design the network structure according to lightweight design principles. A new sample matching strategy based on neighbor points is adopted for improving its performance greatly. Weighted Focal Loss and Balanced L1 Loss further reduce the performance gap between CrossNet and CenterNet. CrossNet possesses a model size of 4.3MB (12.8× smaller than original CenterNet, respectively) and requires 1.51B operations for inference (11.7× smaller than original CenterNet, respectively) while still achieving mAP of 74.2% on VOC dataset. We hope our work could provide some inspiration for lightweight detector design. © 2021 IEEE.

关键词： Object detection

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Context-aware Emotion Recognition Based on Vision-Language Pre-trained Model

Context-aware Emotion Recognition Based on Vision-Language P...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： XingLin Li Xinde Li Chuanfei Hu Huaping Liu School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China Nanjing Center for Applied Mathematics Nanjing China Southeast University Shenzhen Research Institute Shenzhen China Department of Computer Science and Technology Tsinghua University Beijing China

ISBN: (数字)9798350385724

ISBN: (纸本)9798350385731

Given the difficulty of recognizing ambiguous emotions in facial expression recognition tasks, we propose a visual-language model named CAER-CLIP to address this challenge. The proposed CAER-CLIP standed for Context-Aware Emotion Recognition (CAER), and were incorporated structure of the Contrastive Language–Image Pre-training (CLIP) model as promising alternative to classifier. There are two parts in CAER-CLIP model. In the visual part, facial expressions and contextual information of the image are simultaneously extracted to obtain the final feature embeddings, which are then used as a learnable “class” token for text-image pairing with desired module. In the textual part, we use text labels for emotion recognition classes as input. The outputs were merged to participate the comparative study to generated parameters of the model. The experiments demonstrate the effectiveness of the proposed method and show that our CAER-CLIP outperforms the state-of-the-art results on the CAER benchmark. The ablation experiment verified the effectiveness of both the classifier-based and text-based (ours without classifier) models, demonstrating that our method with the CAER-CLIP structure performed better, and the incorporation of a text encoder in the deep network model architecture effectively enhancing recognition accuracy.

关键词： Training Emotion recognition Visualization Accuracy Text recognition Face recognition Benchmark testing Feature extraction Data mining Context modeling

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Model Predictive Load Frequency control for Power systems Under New Event-triggered Mechanism

Model Predictive Load Frequency Control for Power Systems Un...

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第42届中国控制会议

作者： Ziqian Wang Fan Wei Xiongbo Wan 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

In this article, we pay attention to event-based model predictive control(MPC) for load frequency control of multiarea power system. Considering the practical issues, the inputs are subject to hard constraints. A novel dynamic event-triggered mechanism(DETM) which contains an additive internal dynamic variable and an adjusting variable is designed to reduce data transmission burden. The MPC problem is expressed as a "min-max" optimisation problem. By considering the effects of load disturbances and the DETM, we give the design approach for the controller which integrates H2 and H∞ performance indexes through an auxiliary optimization problem. A simulation example is provided to verify the effectiveness of the proposed algorithm.

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