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21st IEEE International Conference on Sciences and Techniques of Automatic control and Computer engineering, STA 2022

作者： Arichi, Fayssal Cherki, Brahim Djemai, Mohamed Engin, Seref Naci Ecole Supérieure en Sciences Appliquées Tlemcen Algeria Algeria LAMIH CNRS Umr 8201 UVHC ValenciennesF-59313 France QUARTZ Laboratory Cergy95000 France Yildiz Technical University Faculty of Electrical and Electronics Engineering Department of Control and Automation Engineering Istanbul Turkey

ISBN: (纸本)9781665482615

This paper investigates the problem of diagnosing discrete faults for a class of hybrid dynamical systems, where the evolution of the discrete state is led by a set of discrete modes governed by a partially observed Petri net which means that we can know the activation of some discrete modes and the firing of some switching conditions. The considered class may have several modes evolving simultaneously. The modes can be associated with normal or faulty operating conditions. Therefore, the knowledge of the current mode represents the coeur part of the proposed diagnosis approach. We present at first an asymptotic observer to detect both the activation of discrete modes and the switching conditions. Then, we propose an algorithm to diagnose faults using the estimated discrete states provided by the observer. Simulation results show the effectiveness of the proposed approach. © 2022 IEEE.

关键词： Petri nets

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Actuator Faults Tolerance for Stochastic High-Order Fully Actuated Systems

Actuator Faults Tolerance for Stochastic High-Order Fully Ac...

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Fully Actuated System Theory and Applications (CFASTA), Conference on

作者： Xueqing Liu Sheng Li Donghua Zhou Department of Automation Tsinghua University Beijing P. R. China College of Control Science and Engineering China University of Petroleum (East China) Qingdao P. R. China College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao P. R. China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

This article investigates the problem of fault-tolerant control (FTC) for stochastic high-order fully actuated (SHOFA) systems with actuator faults. Different from the majority of existing studies focusing on deterministic high-order fully actuated (HOFA) systems, this work accounts for stochastic disturbances. Employing the generalized martingale technique, a novel fault-tolerant equivalent controller is formulated. Additionally, an adaptive compensation law is devised to address time-varying faults promptly. The designed pre-closed-loop strategy advocates the advantage of HOFA methodology in the meantime and guarantees performance by ensuring that all signals are bounded in probability. Finally, a numerical example is presented to demonstrate the efficacy of the proposed method.

关键词： Actuators Fault tolerance State feedback Fault tolerant systems Stochastic processes Focusing control systems

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Skin-like cryogel electronics from suppressed-freezing tuned polymer amorphization

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Nature Communications 2023年第1期14卷 1-10页

作者： Zhang, Xiansheng Yan, Hongwei Xu, Chongzhi Dong, Xia Wang, Yu Fu, Aiping Li, Hao Lee, Jin Yong Zhang, Sheng Ni, Jiahua Gao, Min Wang, Jing Yu, Jinpeng Ge, Shuzhi Sam Jin, Ming Liang Wang, Lili Xia, Yanzhi State Key Laboratory of Bio-Fibers and Eco-Textiles College of Textiles and Clothing Qingdao University Qingdao 266071 China Institute for Future Shandong Key Laboratory of Industrial Control Technology School of Automation Qingdao University Qingdao 266071 China College of Materials Science and Engineering Qingdao University Qingdao 266071 China CAS Key Laboratory of Engineering Plastics Institute of Chemistry Chinese Academy of Sciences Beijing 100190 China Department of Chemistry SungKyunKwan University Suwon 16419 South Korea State Key Laboratory of Fluid Power and Mechatronic Systems College of Mechanical Engineering Zhejiang University Hangzhou 310027 China College of Biological Science and Medical Engineering Donghua University Shanghai 201620 China Institute of Environmental Engineering ETH Zürich Zürich 8093 Switzerland Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Singapore

The sole situation of semi-crystalline structure induced single performance remarkably limits the green cryogels in the application of soft devices due to uncontrolled freezing field. Here, a facile strategy for achieving multifunctionality of cryogels is proposed using total amorphization of polymer. Through precisely lowering the freezing point of precursor solutions with an antifreezing salt, the suppressed growth of ice is achieved, creating an unusually weak and homogenous aggregation of polymer chains upon freezing, thereby realizing the tunable amorphization of polymer and the coexistence of free and hydrogen bonding hydroxyl groups. Such multi-scale microstructures trigger the integrated properties of tissue-like ultrasoftness (Young’s modulus <10 kPa) yet stretchability, high transparency (~92%), self-adhesion, and instantaneous self-healing (<0.3 s) for cryogels, along with superior ionic-conductivity, antifreezing (−58 °C) and water-retention abilities, pushing the development of skin-like cryogel electronics. These concepts open an attractive branch for cryogels that adopt regulated crystallization behavior for on-demand functionalities. © 2023, Springer Nature Limited.

关键词： Gels and hydrogels Polymers

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Robust controller Design for an Active Hexapod Platform with Prescribed Performance

Robust Controller Design for an Active Hexapod Platform with...

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International Conference on Advanced Robotics and Mechatronics (ICARM)

作者： Rongji Yin Yi Shi Wei Xie Jinhui Lu Yu Wen Weixing Cheng Weidong Zhang Department of Automation Shanghai Jiao Tong University Shanghai China National Engineering Research Center of Ship & Shipping Control System School of Mechanical Engineering Shanghai Jiao Tong University Shanghai China

In this paper, we use a robust controller with prescribed performance for the Stewart-Gangway system, achieving motion compensation under unknown time-varying disturbances. The designed controller is able to drive the Stewart top platform towards an arbitrarily small neighborhood of a desired trajectory, with convergence speed no less than a prespecified value, and a maximum overshoot less than a sufficiently small preseted constant. To demonstrate the effictiveness of the designed control strategy, simulation results are given.

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LiDAR Point Cloud Map Coding Framework Based on Quadric Surface Fitting and Scene Construction

LiDAR Point Cloud Map Coding Framework Based on Quadric Surf...

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Pattern Recognition and Machine Learning (PRML), IEEE International Conference on

作者： Xuebin Sun Jinxi Wang Xiaofei Yang School of Electrical Automation and Information Engineering Tianjin University Tianjin China School of Information and Control Engineering China University of Mining and Technology Xuzhou China Department of Aerospace Laser Technology and System Shanghai Institute of Optics and Fine Mechanics Shanghai China

ISBN: (数字)9798350355925

ISBN: (纸本)9798350355932

Due to rapid 3D acquisition advancements, LiDAR point clouds are prevalent in emerging applications like heritage preservation, mobile robotics, and remote sensing. Yet, the sheer data volume poses challenges for transmission and storage, especially in autonomous driving. This paper introduces an efficient coding framework for compressing large dense LiDAR point cloud maps. By recording timestamps and quaternion matrices during map construction, we reduce map compression to sequence compression. The scans are segregated into intra-frames and inter-frames. For intra-frames, a quadric surface fitting intra-prediction technique eliminates spatial redundancy. For inter-frames, by constructing the 3D scene using encoded intra-frames, the inter-frame can be simulated according to its posture and LiDAR intrinsic parameters. Coding focuses on the difference between actual and predicted point cloud data. Decoding reverses this process, reconstructing the point cloud map from the decoded sequence and quaternion matrices. KITTI dataset experiments show the point cloud map can be averagely compressed to 3.43% of its original size while maintaining centimeter-level precision. This outperforms both octree and Google Draco methods.

关键词： Point cloud compression Surface reconstruction Laser radar Three-dimensional displays Quaternions Fitting Robot sensing systems Surface fitting Encoding Surface treatment

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An Insulator Missing Defect Detection Method Based on Unmanned Aerial Vehicles

An Insulator Missing Defect Detection Method Based on Unmann...

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International Conference on control and automation (ICCA)

作者： Yulong Zhang Zhongxian Zhou Lingxia Mu Xianghong Xue Jing Xin Youmin Zhang School of Automation and Information Engineering Xi'an University of Technology Xi'an Shaanxi China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an China Department of Mechanical Industrial and Aerospace Engineering Concordia University Montreal Quebec Canada

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

In this paper, an insulator missing defect detection method is proposed based on unmanned aerial vehicles to solve the problem of glass insulator burst fault detection in high-voltage transmission lines. Firstly, the proposed method utilizes the improved Mask R-CNN (region-based convolutional neural network) algorithm to segment insulator strings in aerial images. Then, the constructed encoder-decoder network is used to extract and reconstruct features of the insulators, resulting in residual images. Finally, the residual images preserve the location information of the fault and obtains the result of missing insulators. The experiment shows that the proposed algorithm has high segmentation accuracy for insulators and high recognition accuracy for insulator missing faults.

关键词： Image segmentation Accuracy Power transmission lines Fault detection High-voltage techniques Insulators Feature extraction

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Sliding Mode-based Two-Dimensional Iterative Learning control for Systems with Uncertainties and External Disturbances

Sliding Mode-based Two-Dimensional Iterative Learning Contro...

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International Conference on control and automation (ICCA)

作者： Y. Yaru L. Dewei M. Aoyun Furong Gao Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University Shanghai Department of Chemical and Biological Engineering Hong Kong University of Science and Technology HongKong

ISBN: (数字)9798350354409

ISBN: (纸本)9798350354416

This paper proposes a sliding mode-based two-dimensional (2D) iterative learning control (ILC) strategy for discrete- time batch process systems challenged by uncertainties and external disturbances. Considering the repetitive nature of batch process systems, the ILC method shows significant advantages. Given the presence of non-repetitive uncertainties and external disturbances in practical systems, this paper integrates the sliding mode control (SMC) scheme into the ILC design framework to ensure system robustness. A novel aspect of this study is the development of an augmented 2D model that captures the dynamic evolution in both batch and sampling time directions. Based on this 2D model, a corresponding 2D sliding mode surface and a 2D iterative learning sliding mode controller are designed, preserving the learning capabilities of ILC and the robustness of SMC against uncertainties and external disturbances. The method proposed in this paper enables the controlled system to maintain a high tracking capability in the face of non-repetitive uncertainties and external disturbances. Particularly, the stability conditions derived from this 2D model provide a broad feasible solution space, which improves the applicability. Furthermore, the correctness of the proposed method is proven and its effectiveness is validated through a simulation example.

关键词： Uncertainty System dynamics Two-dimensional displays Simulation Batch production systems Robustness Stability analysis

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A Real-time Framework of Multi-Camera Vehicle Tracking System

A Real-time Framework of Multi-Camera Vehicle Tracking Syste...

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2024 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2024

作者： Zhuang, Hanyang Chen, Xingyuan Lan, Jianglin Wang, Ying Lu, Zhaoxuan Wang, Chunxiang Yang, Ming University of Michigan Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China University of Glasgow James Watt School of Engineering GlasgowG12 8QQ United Kingdom Shanghai Jiao Tong University School of Mechanical Engineering Shanghai200040 China Shanghai Intelligent and Connected Vehicle R and D Center Co. LTD Shanghai201400 China 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)9798350372601

Multi-camera vehicle tracking (MCVT) system is a key technology to build an intelligent city and intelligent transportation system. The MCVT system utilizes roadside monitoring devices and computing platforms to achieve city-level road traffic perception at a finer scale by tracking each vehicle on the road to obtain the trajectory. The existing MCVT system mainly focuses on dealing with the algorithm modules separately, without studying the real-time performance and system architecture of the entire pipeline. However, in real-world applications, many of the tricks in improving evaluation metrics are not applicable since there is endless traffic flow running all the time. Therefore, this paper proposes a real-time framework of the MCVT system to streamline all the algorithm modules with proper data flow. Firstly, a multi-threaded multi-vehicle tracking (MVT) module is developed to detect vehicles in each camera. Re-identification is implemented during MVT to provide the feature for tracking in the same camera and across different cameras. Then, after the vehicle leaves the camera field of view, the feature of vehicle trajectory is calculated by averaging the feature at each frame. Meanwhile, a background thread runs continuously to match the incoming feature of vehicle trajectory with past features by conducting a topology searching method. In the end, the vehicle trajectories with well-matched features are considered to be the same vehicle. The entire pipeline has been validated on two different datasets, the precision is 0.64 in the CityFlow dataset which uses 6 cameras simultaneously. In the customized dataset, the same method can still reach real-time when using 16 cameras at the same time with smaller network modules. © 2024 IEEE.

关键词： Vehicle locating systems

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Improved ELBO-assisted Transformer for Skeleton-Based Action Recognition

Improved ELBO-assisted Transformer for Skeleton-Based Action...

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International Conference on Intelligent Transportation

作者： Arnab Bhattacharjee Wen-Hui Chen Yu-Chen Lin Kuan-Ting Lai Graduate Institute of Automation Technology National Taipei University of Technology Taipei Taiwan Department of Automatic Control Engineering Feng Chia University Taichung Taiwan Department of Electronic Engineering National Taipei University of Technology Taipei Taiwan

Recognizing human actions accurately from video data is a difficult task because of the variability in human motion, appearance, and context. A new approach to human action recognition is proposed in this study, which uses a combination of Variational Autoencoder (VAE) and Transformer models. The VAE with IWGECO optimization is utilized for acquiring a compact and discriminative representation of the input 2D skeletons from video frames along with its spatial relations. This encoded representation of 2D poses is then fed into a Transformer model for sequence modeling and classification, resulting in effective recognition of human actions. The proposed approach is evaluated on the MPOSE2021 benchmark dataset, outperforming existing methods (90.6%) with an average classification accuracy of 92.0%. The model performs well on real-life data too showcasing its generalizing potential. The study also addresses the domain shift problem occurring in real-world situations by using a pre-trained VAE and subsequently training the Transformer on the MPOSE2021 dataset. The results demonstrate the effectiveness of combining VAE and Transformer models for human action recognition.

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Particle Swarm Optimization based Trajectory Propagation for RLV Approach and Landing Phase

Particle Swarm Optimization based Trajectory Propagation for...

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2022 Chinese automation Congress, CAC 2022

作者： Yan, Han Shen, Xiaxin Wang, Xinghu Beijing Institute of Control Engineering Beijing100094 China Science and Technology on Space Intelligent Control Laboratory Beijing100094 China Beijing Sun Wise Space Technology Ltd. Beijing100094 China University of Science & Technology of China Department of Automation Hefei230027 China

ISBN: (纸本)9781665465335

The trajectory propagation is used to estimate the flight states of the RLV when landing with a designed trajectory, so as to verify that whether the trajectory is suitable or not. Most of existing results are developed based on Euler numerical integration technique, and due to the implementation of the method, the efficiency of propagation may be low if a small integration step is used for high accuracy. To handle such issue, the paper propose a particle swarm optimization (PSO) based trajectory propagation method. With the proposed method, the efficiency of propagation can be significantly improved without losing accuracy. Simulations are done to show the advantages of our method. © 2022 IEEE.

关键词： Trajectories

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