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3rd Conference on Fully Actuated system Theory and Applications, FASTA 2024

作者： Zhang, Qing-Hao Lu, Jun-Guo Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9798350373691

This paper investigates the problems of H8 consensus control for high-order fully actuated multi-agent systems (HOFAMASs) with external disturbances. By utilizing the characteristics of high-order fully actuated systems (HOFASs), the distributed control protocols are designed, eliminating all nonlinear characteristics of open loop systems while establishing new closed-loop dynamic characteristics. Then, the H8 consensus problems of HOFAMASs are addressed. The corresponding parameters to be designed in the distributed control protocols are given by using linear matrix inequalities (LMIs). A novel multi-spacecraft attitude model is proposed based on HOFASs. An illustrative example of the multi-spacecraft attitude model is given, in order to demonstrate the effectiveness and application of the results proposed in this paper. © 2024 IEEE.

关键词： Multi agent systems

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Equilibrium analysis of networked game under best-response dynamics 43

Equilibrium analysis of networked game under best-response d...

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43rd Chinese control Conference, CCC 2024

作者： Xia, Yu Su, Qi Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9789887581581

Both coordination, a behavioral pattern where individuals adopt the same behavior as the majority, and anticoordination, a behavioral pattern where individuals choose a behavior different from the majority, are prevalent in social and engineering scenarios. Examples include the spread of social norms or innovations for coordination and the division of labor and traffic congestion for anti-coordination. Exploring the large-scale interacting systems driven by coordination and anticoordination is of great significance in understanding, predicting, and optimizing the evolutionary outcomes. While existing studies have primarily focused on analyzing the convergence of networked systems and evaluating the time to reach equilibrium, our investigation delves into all possible states of a networked system and scrutinizes all equilibrium states. Notably, we observe that the number of equilibrium states increases exponentially with the network size. Accounting for network structure properties, homogeneous networks exhibit more equilibrium states than heterogeneous networks. Furthermore, for specific behavioral switching thresholds, the number of equilibrium states is surprisingly higher than at neighboring switching thresholds. Our work reveals the intricate interplay between evolutionary dynamics, system structure, and behavioral switching thresholds. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Traffic congestion

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Energy-Efficient Safety-Aware Scheduling of Real-Time control systems with Burst Tasks 22

Energy-Efficient Safety-Aware Scheduling of Real-Time Contro...

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22nd IEEE International Conference on Industrial Informatics, INDIN 2024

作者： Cheng, Ting Liang, Yonghui Xu, Qimin Zhu, Shanying Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China

ISBN: (纸本)9798331527471

In industrial sites, multiple real-time control systems often share computing resources. However, burst computing tasks may lead to the random dropping of control computing subtasks, resulting in control failures and potential hazards. To address this issue, we propose an energy-efficient safety-aware task scheduling scheme based on mixed-integer programming. When burst computing tasks are triggered, this scheduling scheme adaptively releases resources from low-criticality control computing subtasks and adjusts the processor speed based on the dynamic voltage and frequency scaling technology (DVFS), ensuring the timely completion of burst computing tasks and keeping the control system state deviation within a safe threshold. To achieve the scheduling scheme, we propose an efficient algorithm called EESASA. Simulation results show that EESASA can minimize the overall cost of control and processor energy while ensuring the safety of the control system and the timely completion of burst computing tasks. © 2024 IEEE.

关键词： Dynamic frequency scaling

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Online Multi-Object Tracking Under Moving Unmanned Aerial Vehicle Platform Based on Object Detection and Feature Extraction Network

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Journal of Shanghai Jiaotong university(Science) 2024年第3期29卷 388-399页

作者：刘增敏王申涛姚莉秀蔡云泽 Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong UniversityShanghai 200240China JD Business Growth Department Beijing 100176China Institute of Marine Equipment Shanghai Jiao Tong UniversityShanghai 200240China

In order to solve the problem of small object size and low detection accuracy under the unmanned aerial vehicle(UAV)platform,the object detection algorithm based on deep aggregation network and high-resolution fusion module is ***,a joint network of object detection and feature extraction is studied to construct a real-time multi-object tracking *** the problem of object association failure caused by UAV movement,image registration is applied to multi-object tracking and a camera motion discrimination model is proposed to improve the speed of the multi-object tracking *** simulation results show that the algorithm proposed in this study can improve the accuracy of multi-object tracking under the UAV platform,and effectively solve the problem of association failure caused by UAV movement.

关键词： moving unmanned aerial vehicle(UAV)platform small object feature extraction image registration multi-object tracking

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Extended NNs-Based Adaptive Event-Triggered Asymptotic control for Nonlinear systems Against Actuator Faults 7

Extended NNs-Based Adaptive Event-Triggered Asymptotic Contr...

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7th International Symposium on Autonomous systems, ISAS 2024

作者： Liu, Shanlin Zhang, Yingwei Zhao, Xudong Wang, Hesheng Northeastern University College of Information Science and Engineering Shenyang China Northeastern University State Laboratory of Synthesis Automation of Process Industry Shenyang China Dalian University of Technology Faculty of Electronic Information and Electrical Engineering Dalian China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9798350363173

In this article, an adaptive event-triggered asymp¬totically fault-tolerant control (FTC) issue for nonlinear systems with actuator faults is investigated. An extended neural networks (NNs) technique is introduced to estimate unknown functions of the system under consideration. Compared with traditional NNs that ignore approximation errors, the proposed extended NNs further processes approximation errors, reducing the conservatism of the proposed algorithm. Then, within the framework of backstepping method, a new adaptive control strategy is developed by combining event-triggered mechanism (ETM) and bound estimation (BE) approach, which ensures the asymptotic convergence of system states while also reducing the transmission of unnecessary information, thus improving the utilization of communication resources. At the same time, the designed controller eliminates the adverse effects of actuator failures and system nonlinear terms. Finally, a simulation example of a single-link robot system is provided to demonstrate that the developed control strategy can ensure that all signals are bounded and system states are asymptotically convergent. © 2024 IEEE.

关键词： Approximation algorithms

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Self-Supervised Learning with Min-Max Distance Approach for Few-Shot Steel Surface Defects Recognition 43

Self-Supervised Learning with Min-Max Distance Approach for ...

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43rd Chinese control Conference, CCC 2024

作者： Wang, Tianlei Chen, Xinyao Li, Zeliang Zhou, Zhencai Zhou, Zhiheng Wuyi University School of Electronic and Information Engineering Jiangmen China Jiangmen Key Laboratory of Kejie Semiconductor Bonding Technology and Control System Jiangmen China Wuyi University School of Mechanical and Automation Engineering Jiangmen China Guangdong Province Kejie Machinery Automation Company Technical Department Jiangmen China

ISBN: (纸本)9789887581581

Surface defects in steel are crucial for quality inspection in the manufacturing of industrial metal products. While deep learning methods have been extensively studied in this field, the lack of large-scale annotated defect samples imposes significant labeling pressure, making training fully supervised deep models challenging. In response to this issue, we employ self-supervised learning for few-shot recognition, effectively learning representations from limited unlabeled data and achieving defect recognition with a small amount of labeled samples. In particular, we construct Other encoder with multi-view information and Base encoder with single view information based on the distillation self-supervised learning framework through the multi-crops mechanism, and the Other encoders and Base encoders perform information share. Our main contribution is that, based on this framework, we propose a new regularization method to solve the problem of instances deviating from the center of self-supervised clustering by minimizing the maximum instance distance (MMD). In testing, fine-tuning the MMD pre-trained model with a small number of labeled data achieves superior recognition performance on the steel surface defect dataset NEU, significantly outperforming other testing methods. © 2024 Technical Committee on control Theory, Chinese Association of automation.

关键词： Self-supervised learning

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Validation of Delayed Anesthesia Model Using Identification Methods and Correlation Analysis

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IFAC-PapersOnLine 2024年第27期58卷 172-177页

作者： Bora Ayvaz Erhan Yumuk Clara M. Ionescu Ali Fuat Ergenç Control and Automation Engineering Department Istanbul Technical University Istanbul 34469 Turkey Department of Electromechanics System and Metal Engineering Ghent University 9052 Ghent Belgium

Many successful control strategies for anesthetic processes do not adequately consider time delays despite potential 30-second delays from biophase and bispectral index (BIS) monitoring. This study introduces linear delayed Pharmacokinetic-Pharmacodynamic (PK-PD) patient models that correlate more to real patient outputs than common non-delayed models. The delayed models are obtained for both effect-site concentration (Ce) and BIS outputs. The model structures are identified using autoregressive exogenous input (ARX) and delayed-ARX (DARX) polynomial models and least squares estimations (LSE) using the real surgical data of the open-access database VitalDB. Validation of delayed PK-PD patient models involves using correlation analysis. Results indicate that PK-PD patient models with output delays exhibit higher correlations with real patient data, particularly when considering BIS output.

关键词： Time Delay Models General Anesthesia system Identification Correlation Analysis Closed-Loop control

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MMC Based D-STATCOM control by Using a Modified ADRC Strategy 8

MMC Based D-STATCOM Control by Using a Modified ADRC Strateg...

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8th Southern Power Electronics Conference and the 17th Brazilian Power Electronics Conference, SPEC / COBEP 2023

作者： Neto, João A. Moor Zachi, Alessando R. Paucar, Braulio Chuco Do Brasil, Thiago Americano Mussa, Samir Ahmad CEFET-RJ Department of Electrical Engineering Rio de Janeiro Brazil CEFET-RJ Department of Control System and Automation Engineering Rio de Janeiro Brazil UFSC - Sc Dept. of Electrical and Electronic Engineering Florianopolis Brazil

ISBN: (纸本)9798350321128

This paper presents investigations of a transformerless half bridge sub-module (HBSM) modular multilevel converter based distribution static synchronous compensator (MMC D-STATCOM) performance in reactive power compensation considering the application of the modified ADRC controllers in the inner current loop and in the outer DC voltage loop using Synchronous Reference Frame control. Simulation results with the imposition of severe variations in reactive loads were obtained on a 5 km medium voltage feeder and will demonstrate that the modified ADRC controller enables superior performance for flexible operation with fast and efficient response of the MMC D-STATCOM in reactive power compensation. © 2023 IEEE.

关键词： ADRC controller D-STATCOM PI controller PSCAD/EMTDC Reactive Power Compensation

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Development of a Bio-inspired Tailless FWMAV with High-Frequency Flapping Wings Trajectory Tracking control

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Journal of Bionic engineering 2024年第5期21卷 2145-2166页

作者： Qingcheng Guo Chaofeng Wu Yichen Zhang Feng Cui Wu Liu Xiaosheng Wu Junguo Lu National Key Laboratory of Advanced Micro and Nano Manufacture Technology Shanghai Jiao Tong UniversityShanghai200240China Department of Micro/Nano Electronics School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai200240China Department of Automation Shanghai Jiao Tong UniversityShanghai200240China The Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai200240China

The development of a tailless Flapping Wing Micro Aerial Vehicle(FWMAV)inspired by the hummingbird is presented in this *** implementing mechanical simplifications,it is possible to use planar machining technology for manufacturing of the FWMAV’s body,greatly reducing assembly ***,studies on flapping wing aircraft are limited to open-loop wing kinematics *** this work,an instantaneous closed-loop wing trajectory tracking control system is introduced to minimize wings’trajectory tracking *** control system is based on Field-Oriented control(FOC)with a loop shaping compensation technique near the flapping *** frequency analysis,the loop shaping compensator ensures the satisfactory bandwidth and performance for the closed-loop flapping *** implement the proposed controller,a compact autopilot board integrated with FOC hardware is designed,weighing only 2.5 *** utilizing precise wing trajectory tracking control,the hummingbird-inspired FWMAV demonstrates superior ability to resist external disturbances and exhibits reduced attitude tracking errors during hovering flight compared to the open-loop wing motion.

关键词： Flapping Wing Micro Aerial Vehicle(FWMAV) Bio-inspired robotics Trajectory control Loop shaping compensator Field-Oriented control(FOC)

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Multi-Branch Spatial-Temporal Attention Graph Convolution Network for Skeleton-based Action Recognition 41

Multi-Branch Spatial-Temporal Attention Graph Convolution Ne...

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第41届中国控制会议

作者： Daoshuai Wang Dewei Li Yaonan Guan Gang Wang Haibin Shao Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Skeleton-based human action reco gnition has attracted considerable research interest due to its robustness to dynamic environments and complex *** based on graph neural networks have achieved great success in this ***,most of these graph neural network based methods adopt a single-branch or two-stream structure with limited input *** to the separation of space and time,many methods cannot pay attention to the critical information of human skeleton sequence,and multi-scale spatial-temporal dependent attention modeling becomes the key to *** paper proposes a novel multi-branch Spatio-temporal attention graph convolutional neural network(MB-STAGCN) to recognize human actions from skeleton *** proposed model adopts a multi-branch structure,fuses three-stream features,and then inputs them into the backbone network to extract features from multiple perspectives to a greater ***,we design a new temporal convolutional block for multi-scale extraction of information in the backbone *** also propose an attention block named Spatio-temporal Concat Attention(STCatAtt) to capture critical *** on benchmark datasets show remarkable performance for human action reco gnition,demonstrating the effectiveness of our method.

关键词： Skeleton-based human action recognition MB-STAGCN STCatAtt

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