检索结果-内蒙古大学图书馆

第40届中国控制会议

作者： Chi Zhan 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 paper, the dynamic event-triggered fault detection（FD） problem is revisited for networked singularly perturbed systems. A new dynamic event-triggered mechanism（DETM） is devised, which contains some existing triggering mechanisms as special cases. Our aim is to design a fault detection filter（FDF）, which ensures that the resulting filtering error dynamics of FD under the new DETM is asymptotically stable and satisfies an H∞ performance requirement. By constructing a new Lyapunov function dependent on both the singular perturbation parameter and two flexible variables in the DETM, a sufficient condition ensuring the existence of the desired FDF is obtained in terms of linear matrix inequalities（LMIs）. The parameters of the FDF are explicitly given based on the feasible solutions of these LMIs. A numerical example is provided to demonstrate the effectiveness of the DETM-based FD method.

关键词： Fault detection dynamic event-triggered mechanism singularly perturbed systems networked systems

来源：评论

学校读者我要写书评

暂无评论

Load Prediction Model of Gas Boiler Generator Set Based on CNN-LSTM 11th

Load Prediction Model of Gas Boiler Generator Set Based on...

引用

11th International Symposium on Computational Intelligence and Industrial Applications, ISCIIA 2024

作者： Xu, Yan Wu, Min Hu, Jie Peng, Fu-Sheng Zhang, Wen Song, Wen-Shuo Li, Hui-Hang 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 Wuhan430074 China

ISBN: (纸本)9789819647521

With the proposal of carbon peak and carbon neutrality targets and the construction of a new power system, improving energy efficiency and reducing carbon emissions have become the key to the sustainable development of industrial boiler generator sets. However, the current load scheduling of gas boiler power plants is mainly based on manual experience, which limits achieving more efficient and stable operation. Accurate short-term load forecasting can help dispatchers to make reasonable production schedules. Therefore, this paper proposes a hybrid load forecasting model for generator sets based on convolutional neural networks combined with long short-term memory networks. First, the Isolation Forest algorithm eliminates anomalies in the historical data set. Then, variables related to unit load are selected by combining mechanistic analysis with the Spearman algorithm. Considering the multiple operating conditions and high complexity of unit loads, the CNN-LSTM network is used to fully extract the spatial and temporal characteristics to build the load prediction model. Finally, experiments are conducted using actual production data, showing that the proposed method is effectiveness. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Electric load dispatching

来源：评论

学校读者我要写书评

暂无评论

Multi-task Safe Reinforcement Learning for Navigating Intersections in Dense Traffic

arXiv

引用

arXiv 2022年

作者： Liu, Yuqi Gao, Yinfeng Zhang, Qichao Ding, Dawei Zhao, Dongbin The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China College of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing1000839 China

Multi-task intersection navigation including the unprotected turning left, turning right, and going straight in dense traffic is still a challenging task for autonomous driving. For the human driver, the negotiation skill with other interactive vehicles is the key to guarantee safety and efficiency. However, it is hard to balance the safety and efficiency of the autonomous vehicle for multi-task intersection navigation. In this paper, we formulate a multi-task safe reinforcement learning with social attention to improve the safety and efficiency when interacting with other traffic participants. Specifically, the social attention module is used to focus on the states of negotiation vehicles. In addition, a safety layer is added to the multi-task reinforcement learning framework to guarantee safe negotiation. We compare the experiments in the simulator SUMO with abundant traffic flows and CARLA with high-fidelity vehicle models, which both show that the proposed algorithm can improve safety with consistent traffic efficiency for multi-task intersection navigation. Copyright © 2022, The Authors. All rights reserved.

关键词： Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

Multimodal Emotion Recognition Based on Multi-Scale Facial Features and Cross-Modal Attention 26

Multimodal Emotion Recognition Based on Multi-Scale Facial F...

引用

26th International Conference on Industrial Technology, ICIT 2025

作者： Bao, Chengao Chen, Luefeng Li, Min Wu, Min Pedrycz, Witold Hirota, Kaoru School of Automation China University of Geosciences Wuhan430074 China School of Automation Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6R 2G7 Canada Tokyo Institute of Technology Yokohama226-8502 Japan Tokyo Institute of Technology Tokyo226-8502 Japan

ISBN: (纸本)9798331521950

A multi-modal emotion recognition method based on facial multi-scale features and cross-modal attention (MS-FCA) network is proposed. The MSFCA model improves the traditional single-branch ViT network into a two-branch ViT architecture by using classification tokens in each branch to interact with picture embeddings in the other branch, which facilitates effective interactions between different scales of information. Subsequently, audio features are extracted using ResNet18 network. The cross-modal attention mechanism is used to obtain the weight matrices between different modal features, making full use of inter-modal correlation and effectively fusing visual and audio features for more accurate emotion recognition. Two datasets are used for the experiments: eNTERFACE'05 and REDVESS dataset. The experimental results show that the accuracy of the proposed method on the eNTERFACE'05 and REDVESS datasets is 85.42% and 83.84% respectively, which proves the effectiveness of the proposed method. © 2025 IEEE.

关键词： Modal analysis

来源：评论

学校读者我要写书评

暂无评论

Base-Acid Relay Catalytic Upgrading of Coal Pyrolysis Volatiles Over Cao and Hzsm-5 Catalysts

SSRN

引用

SSRN 2022年

作者： Yang, Hang Zhang, Jiehan Chen, Zhaohui Wan, Lifeng Li, Changming Zhang, Xinyu Li, Jianling Tian, Ruoxuan Yu, Jian Gao, Shiqiu State Key Laboratory of Multi-phase Complex Systems Institute of Process Engineering Chinese Academy of Sciences Beijing100190 China School of Chemical Engineering University of Chinese Academy of Sciences Beijing100049 China State Environmental Protection Key Laboratory of Food Chain Pollution Control School of Ecology and Environment Beijing Technology and Business University Beijing100048 China China Huanqiu Contracting & Engineering Co. Ltd Beijing100012 China

The relay catalytic upgrading of coal pyrolysis volatiles employing different layouts of basic CaO and acidic HZSM-5 zeolite was proposed to improve the tar quality as well as alleviate catalyst deactivation. The synergistic effect is found in relay catalytic upgrading of coal pyrolysis volatiles over dual CaO and HZSM-5 catalysts system. The relay CaO-HZSM-5 layout is better compared to layouts of relay HZSM-5-CaO, mixed CaO/HZSM-5, and their independent employments. The relay CaO-HZSM-5 layout ensures the highest light fraction in tar with 70.1% and the minimized carbon deposition over HZSM-5 while remaining a relatively high tar yield (7.8 wt.%). Meanwhile, the contents of aromatics and phenols in tar increase by 221% and 164% compared with the blank test (without catalyst), respectively. In this scenario, CaO promotes the cracking of large molecules in tar to form more olefins and small molecules firstly, which subsequently diffuses into micropores of HZSM-5 zeolite to produce more aromatics by dehydrocyclization. In addition, the roles of pre-cracking and pre-deoxidation of volatiles over CaO reduce the possibility of the polycondensation reactions of large molecules over acidity sites of HZSM-5 zeolite, thus lowering the carbon deposition over zeolite. These findings suggest that the base-acid relay catalytic upgrading of volatiles during coal pyrolysis will be a promising strategy to increase the tar quality and slow down catalyst deactivation. © 2022, The Authors. All rights reserved.

关键词： Catalyst deactivation

来源：评论

学校读者我要写书评

暂无评论

AirVista-II: An Agentic System for Embodied UAVs Toward Dynamic Scene Semantic Understanding

arXiv

引用

arXiv 2025年

作者： Lin, Fei Tian, Yonglin Zhang, Tengchao Huang, Jun Guan, Sangtian Wang, Fei-Yue Department of Engineering Science Faculty of Innovation Engineering Macau University of Science and Technology 999078 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

Unmanned Aerial Vehicles (UAVs) are increasingly important in dynamic environments such as logistics transportation and disaster response. However, current tasks often rely on human operators to monitor aerial videos and make operational decisions. This mode of human-machine collaboration suffers from significant limitations in efficiency and adaptability. In this paper, we present AirVista-II—an end-to-end agentic system for embodied UAVs, designed to enable general-purpose semantic understanding and reasoning in dynamic scenes. The system integrates agent-based task identification and scheduling, multimodal perception mechanisms, and differentiated keyframe extraction strategies tailored for various temporal scenarios, enabling the efficient capture of critical scene information. Experimental results demonstrate that the proposed system achieves high-quality semantic understanding across diverse UAV-based dynamic scenarios under a zero-shot setting. Copyright © 2025, The Authors. All rights reserved.

关键词： Drones

来源：评论

学校读者我要写书评

暂无评论

Spiking Neuron Networks based Energy-Efficient Object Detection for Mobile Robot

Spiking Neuron Networks based Energy-Efficient Object Detect...

引用

2021 China Automation Congress, CAC 2021

作者： Liu, Bo-Chao Yu, Qian Gao, Jing-Wen Zhao, Shuang Liu, Xiong-Chang Lu, Yan-Feng Beijing Information Science and Technology University Beijing China Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China School of Instrument Science and Optoelectronic Engineering Beijing Information Science and Technology University Beijing China The State Key Laboratory of Management and Control for Complex Systems CASIA Beijing China Science and Technology on Underwater Vehicle Technology Laboratory Harbin Engineering University Harbin China

ISBN: (纸本)9781665426473

This paper focuses on the highly energy-efficient visual detection method, which first apples spiking neuron networks based object detection method in mobile robot. Visual perception is an important part of mobile robot, but the real-time visual perception is with high energy consumption that limits the battery running time of the robotic platform. In this paper, we bring in a Spiking-YOLO algorithm for the visual detection of the mobile robot, which combines the YOLO algorithm with the third generation artificial neural network-Spiking Neural Network (SNN). The Spiking-YOLO integrates the characteristics in real-time and high precision of the YOLO, and event-driven and low-powered nature of the SNN. We introduce the Spiking-YOLO model to the Robotnik's SUMMIT-XL mobile robot to perform the task of visual detection and the experimental verification is carried out on data sets. The experimental results show that this method has excellent energy-efficient and precision on the detection task of the robot. © 2021 IEEE

关键词： Neural networks

来源：评论

学校读者我要写书评

暂无评论

Digital Twin-based Automatic Train Regulation for Integration of Dispatching and control

Digital Twin-based Automatic Train Regulation for Integratio...

引用

Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Min Zhou Zhuopu Hou Jun Liu Clive Reborts Hairong Dong State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences CRSC Research & Design Institute Group Co. Ltd. School of Electronic Electrical and Systems Engineering University of Birmingham United Kingdom

This paper proposes a framework of digital twin-based integration of train regulation and control for metro systems. We study the integration of train regulation and train control by using deep learning and hybrid search methods. Specifically, a well-trained convolutional neural network is adopted to fit the nonlinear function mapping relationship between the input set (the line conditions and running time of the train in each section) and the output set (the energy consumption of the optimal speed profile and the switching points), which greatly reduces the calculation time of the optimal recommended speed profile in the process of train regulation. An integrated optimization model is proposed with the aim to minimize the total train delay and energy consumption, a hybrid search algorithm based on particle swarm optimization and a genetic algorithm was developed to solve the problem. The effectiveness of the proposed method is verified based on the actual operating data of a Beijing subway line.

关键词： Energy consumption Neural networks Switches Search problems Regulation Delays Particle swarm optimization

来源：评论

学校读者我要写书评

暂无评论

Parallel Planning:A New Motion Planning Framework for Autonomous Driving

引用

IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 236-246页

作者： Long Chen Xuemin Hu Wei Tian Hong Wang Dongpu Cao Fei-Yue Wang IEEE School of Data and Computer Science Sun Yat-sen University the School of Computer Science and Information Engineering Hubei University Institute of Measurement and Control Systems Karlsruhe Institute of Technology Department of Mechanical and Mechatronics Engineering University of Waterloo the State Key Laboratory of Management and Control for Complex Systems.Institute of Automation Chinese Academy of Sciences the Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology

Motion planning is one of the most significant technologies for autonomous driving. To make motion planning models able to learn from the environment and to deal with emergency situations, a new motion planning framework called as"parallel planning" is proposed in this paper. In order to generate sufficient and various training samples, artificial traffic scenes are firstly constructed based on the knowledge from the reality.A deep planning model which combines a convolutional neural network(CNN) with the Long Short-Term Memory module(LSTM) is developed to make planning decisions in an end-toend mode. This model can learn from both real and artificial traffic scenes and imitate the driving style of human ***, a parallel deep reinforcement learning approach is also presented to improve the robustness of planning model and reduce the error rate. To handle emergency situations, a hybrid generative model including a variational auto-encoder(VAE) and a generative adversarial network(GAN) is utilized to learn from virtual emergencies generated in artificial traffic scenes. While an autonomous vehicle is moving, the hybrid generative model generates multiple video clips in parallel, which correspond to different potential emergency scenarios. Simultaneously, the deep planning model makes planning decisions for both virtual and current real scenes. The final planning decision is determined by analysis of real observations. Leveraging the parallel planning approach, the planner is able to make rational decisions without heavy calculation burden when an emergency occurs.

关键词： Autonomous driving artificial traffic scene deep learning emergencies motion planning parallel planning

来源：评论

学校读者我要写书评

暂无评论

Fast control Strategy of Grid-forming Inverter Based on Power Feedforward

Fast Control Strategy of Grid-forming Inverter Based on Powe...

引用

第42届中国控制会议

作者： Sheng Zhang Zhijian Fang Qine Liu Muchao Xiang Dingbang Huang 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 State Grid Hubei Electric Power Co. LtdXiangyang Power Supply Company Electric Power Scientific Research Institute of State Grid Hubei Electric Power Co. Ltd

Grid-forming inverter is widely used in grid-connected systems of distributed generation because of its frequency and voltage support capacity and good stability in microgrid,but its large inertia will affect the dynamic response speed of grid-forming *** order to solve this problem,this paper introduces the loop that affects the dynamic response of grid-forming inverter,and carries out small signal modeling for active loop,analyzes the dynamic performance indicators and determinants of typical second-order ***,a method of adding power feedforward coefficient to the forward channel of the power loop is designed,and the response speed of the system with or without feedforward coefficient under the unit step response is ***,the simulation results show that adding the power feedforward coefficient can improve the response speed of the grid-forming inverter during startup and power switching,then achieves the effect of fast control.

关键词：

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：