检索结果-内蒙古大学图书馆

Cooperative Output Regulation of Heterogeneous systems over Directed Graphs:A Dynamic Adaptive Event-Triggered Strategy

引用

Journal of systems Science & complexity 2023年第3期36卷 909-921页

作者： SU Hang CHENG Bin LI Zhongkui State Key Laboratory for Turbulence and Complex Systems and Department of Mechanics and Engineering Science College of EngineeringPeking UniversityBeijing 100871China Department of Control Science and Engineering College of Electronics and Information EngineeringTongji UniversityShanghai 201804China Frontiers Science Center for Intelligent Autonomous Systems Shanghai 201210China

This paper investigates the cooperative output regulation problem of heterogeneous linear multi-agent systems over directed graphs with the constraint of communication *** that there exists an exosystem whose state information is not available to all agents,the authors develop distributed adaptive event-triggered observers for the followers based on relative information between neighboring *** should be pointed out that,two kinds of time-varying gains are introduced to avoid relying on any global information associated with the network,and dynamic triggering conditions are designed to get rid of continuous *** the basis of the designed observers,the authors devise a local controller for each *** with the existing related works,the main contribution of the current paper is that the cooperative output regulation problem for general directed graphs is solved requiring neither global information nor continuous communications.

关键词： Adaptive control consensus cooperative output regulation directed graph event-triggered control multi-agent systems

来源：评论

学校读者我要写书评

暂无评论

Self-supervised Depth Completion with Adaptive Online Adaptation 23

Self-supervised Depth Completion with Adaptive Online Adapta...

引用

7th International Conference on Machine Learning and Soft Computing, ICMLSC 2023

作者： Chen, Yang Tan, Yang Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of Education School of Automation Southeast University Nanjing210096 China

ISBN: (纸本)9781450398633

Although depth completion has achieved remarkable performance relying on deep learning in recent years, these models tend to suffer a performance degradation when exposed to new environments. Online adaptation, where the model is trained in a self-supervised manner during testing, seems a promising technique to alleviate the drop. However, continuous online adaptation may cause the model to over-adapt and miss the optimal parameters, resulting in oscillation or even degradation of the model performance, in addition to wasting computational resources. Therefore, this paper proposes an adaptive online adaptation framework to make model adaptively trigger online adaptation when encountering novel environments and stop adaptation when model has adapted to the current environment. In detail, we design a trigger to detect the familiarity of model to the current scenario based on image similarity and then launch online adaptation when the scenario is novel. Besides, we elaborate a stopper to monitor the error between prediction and depth input and convert online adaptation to inference when online adaptation does not bring improvement for model. Experimental results demonstrate that our method improves the accuracy of model prediction and increases average running speed of the model on each frame in online adaptation. © 2023 ACM.

关键词： Deep learning

来源：评论

学校读者我要写书评

暂无评论

Inverse Reinforcement Learning Integrated Reinforcement Learning for Single Intersection Traffic Signal control 5

Inverse Reinforcement Learning Integrated Reinforcement Lear...

引用

5th International Conference on Industrial Artificial Intelligence, IAI 2023

作者： Gu, Shiyi Zhang, Tingting Zhang, Ya Southeast University School of Automation Nanjing210096 China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Nanjing China Army Engineering University College of Command and Control Engineering Nanjing210017 China

ISBN: (纸本)9798350325294

Traffic Signal control (TSC) optimization is vital for efficient traffic flow in urban intersections. Recent research has explored the application of Reinforcement Learning (RL) agents to tackle TSC challenges. However, the selection of an appropriate reward function in RL agent training still relies on subjective judgment and experience. To address this issue, an Inverse Reinforcement Learning (IRL) integrated RL algorithm is proposed. In the IRL learning section, expert trajectory data are collected and analyzed by Relative Entropy IRL (REIRL). The latent reward of expert policy is reconstructed and utilized in RL agent training process. In the RL control section, a Double Dueling Deep Q Network is applied under a cycle control framework. As verified in simulations, the introduction of expert experience improves the performance of the RL agent to the expert level and concurrently enables robustness to expert policy noises. © 2023 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Urban Traffic control Meets Decision Recommendation System:A Survey and Perspective

引用

IEEE/CAA Journal of Automatica Sinica 2024年第10期11卷 2043-2058页

作者： Qingyuan Ji Xiaoyue Wen Junchen Jin Yongdong Zhu Yisheng Lv Zhejiang Lab Hangzhou 311121China College of Engineering and Architecture Zhejiang UniversityHangzhou 310013China College of Electrical Engineering Zhejiang UniversityHangzhou 310013China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China IEEE

Urban traffic control is a multifaceted and demanding task that necessitates extensive decision-making to ensure the safety and efficiency of urban transportation *** approaches require traffic signal professionals to manually intervene on traffic control devices at the intersection level,utilizing their knowledge and ***,this process is cumbersome,labor-intensive,and cannot be applied on a large network *** studies have begun to explore the applicability of recommendation system for urban traffic control,which offer increased control efficiency and *** a decision recommendation system is complex,with various interdependent components,but a systematic literature review has not yet been *** this work,we present an up-to-date survey that elucidates all the detailed components of a recommendation system for urban traffic control,demonstrates the utility and efficacy of such a system in the real world using data and knowledgedriven approaches,and discusses the current challenges and potential future directions of this field.

关键词： Recommendation system traffic control traffic perception traffic prediction

来源：评论

学校读者我要写书评

暂无评论

The TAO of Blockchain Intelligence for Intelligent Web 3.0

引用

IEEE/CAA Journal of Automatica Sinica 2023年第12期10卷 2183-2186页

作者： Juanjuan Li Fei-Yue Wang IEEE the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China

WE are in an exciting new intelligent era where various Web 3.0 systems emerge and flourish.[1]–[3].In this new epoch,the collaboration of data and knowledge,humans and machines,actual and virtual worlds is undergoing an unprecedented diversification and community-driven transformation,unveiling an open future full of boundless ***,the value of dispersed data extends far beyond passive storage and application.

关键词： Web TAO knowledge

来源：评论

学校读者我要写书评

暂无评论

Optimal Strategy for Aircraft Pursuit-evasion Games via Self-play Iteration

引用

Machine Intelligence Research 2024年第3期21卷 585-596页

作者： Xin Wang Qing-Lai Wei Tao Li Jie Zhang State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing100049China Institute of Systems Engineering Macao University of Science and TechnologyMacao999078China

In this paper,the pursuit-evasion game with state and control constraints is solved to achieve the Nash equilibrium of both the pursuer and the evader with an iterative self-play *** the condition where the Hamiltonian formed by means of Pontryagin’s maximum principle has the unique solution,it can be proven that the iterative control law converges to the Nash equilibrium ***,the strong nonlinearity of the ordinary differential equations formulated by Pontryagin’s maximum principle makes the control policy difficult to figured *** the system dynamics employed in this manuscript contains a high dimensional state vector with *** practical applications,such as the control of aircraft,the provided overload is ***,in this paper,we consider the optimal strategy of pursuit-evasion games with constant constraint on the control,while some state vectors are restricted by the function of the *** address the challenges,the optimal control problems are transformed into nonlinear programming problems through the direct collocation ***,two numerical cases of the aircraft pursuit-evasion scenario are given to demonstrate the effectiveness of the presented method to obtain the optimal control of both the pursuer and the evader.

关键词： Differential games pursuit-evasion games nonlinear control optimal control Nash equilibrium solution

来源：评论

学校读者我要写书评

暂无评论

Online Estimation of State of Healh for Lithium-ion Batteries Based on Attention-LSTM Netwrok Using Partial Charging Features 6

Online Estimation of State of Healh for Lithium-ion Batterie...

引用

6th International Conference on Energy, Electrical and Power engineering, CEEPE 2023

作者： Yao, Yue Wang, Ying Zhang, Jiangfeng Zhang, Kaifeng Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China State Grid Zhejiang Electric Power Research Institute Zhejiang China

ISBN: (纸本)9798350348279

Accurate estimation for state-of-health (SOH) of lithium-ion batteries is critical to ensure the security and durability of battery operation. Accordingly, this paper proposes a SOH estimation method based on Attention-LSTM neural network using the partial charging features. First, features are extracted from partial constant-current charging curves. Second, Pearson coefficient analysis is employed to analysis the mapping relationship between extracted features and SOH. Third, an Attention-LSTM network is utilized to realize the SOH estimation. The attention mechanism can adaptively assign weights to the input features and time steps, thereby improving the estimation accuracy. Validation experiments are conducted on public dataset from NASA Ames Prognostics Center of Excellence. The experimental results highlight that the proposed method has higher accuracy and robustness compared with other approaches. © 2023 IEEE.

关键词： Lithium-ion batteries

来源：评论

学校读者我要写书评

暂无评论

Solving the Collaborative Problem in the Process of Dual-Arm Robot Assembly Based on Fully Constrained Synchronous Collaboration Mode

Solving the Collaborative Problem in the Process of Dual-Arm...

引用

2022 Chinese Automation Congress, CAC 2022

作者： Sui, Shunfan Gan, Yahui Dai, Xianzhong Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Nanjing China

ISBN: (纸本)9781665465335

In this paper, a fully constrained collaboration synchronization model is proposed to solve the cooperative problem in the dual-arm assembly process. Compared with the single-arm robot, the dual-arm robot has higher flexibility and larger working space, but it is more difficult to control. It has its inherent constraint relationship during movement. The dual-arm cooperation constraint is the basis of the dual-arm motion planning. The paper first analyzes the constraint relationship between the two arms when the rigid body is transported by the two arms and the assembly of the shaft hole respectively. The study finds that there are many common points between the two movements: during the movement process, the two manipulators always maintain a constraint relationship with the object. On this basis, the full constraint is proposed to solve the position and pose constraints of the tool hands when the arms are moved. Finally, the simulation experiment of dual-arm handling rigid body and shaft-hole assembly is carried out to verify that the proposed dual-arm cooperation mode can effectively realize the dual-arm cooperative motion. © 2022 IEEE.

关键词： Motion planning

来源：评论

学校读者我要写书评

暂无评论

Missing Small Bolt Detection on High-speed Train Using Improved Yolov5 8

Missing Small Bolt Detection on High-speed Train Using Impro...

引用

8th International Conference on systems and Informatics, ICSAI 2022

作者： Wei, Yiming Lu, Xiaobo Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Nanjing China

ISBN: (纸本)9781665474481

Tiny bolts are widely used on high-speed trains, playing an important role in fixing train components. However, because of the complex running environment of trains, missing bolts occur from time to time and may cause traffic accidents, resulting in property damage and, in serious cases, endangering the lives of the occupants. Therefore, it is essential to detect missing bolts on high-speed trains. The bolts discussed in this paper are generally located on the underside of high-speed trains and their small size makes detection more difficult. In this paper, we first expand the dataset, and then add the Attention module and Transformer based on YOLOv5, and change the FPN of YOLOv5 to BiFPN, fuse the features of different layers using different weights, and crop the high-resolution original image during training and testing, and finally return to the original image. Our method eventually achieves 95.3% AP, effectively improving the detection accuracy. © 2022 IEEE.

关键词： Statistical tests

来源：评论

学校读者我要写书评

暂无评论

A Trajectory Tracking Algorithm Based on Interior Point Method for A Class of Mobile Manipulators

A Trajectory Tracking Algorithm Based on Interior Point Meth...

引用

2022 Chinese Automation Congress, CAC 2022

作者： Rao, Xuechen Gan, Yahui Wang, Xiaoteng Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation NanJing China

ISBN: (纸本)9781665465335

At present, due to the high redundancy and strong coupling characteristics of mobile manipulator systems, there are few and in-depth studies on coordinated motion planning. Aiming at the above problems, this paper proposes a coordinated control algorithm that can track the desired trajectory of the end-effector based on a class of 5-DOF mobile manipulators. The algorithm takes the power consumption and trajectory stability of the entire system as the optimization objectives, and sets the function of the selected optimization objective on the desired trajectory, and performs optimization based on the interior point method of convex optimization to converge to the optimal solution faster. Finally, the system is simulated to verify the correctness and effectiveness of the control algorithm. © 2022 IEEE.

关键词： Convex optimization

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：