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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Lu, Xuanzhao Xu, Qimin Zhang, Jinglong Chen, Cailian Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

To improve the performance of industrial cyber-physical systems (ICPS), the joint design of control and transmission has been shown to be an effective mechanism. However, the existing joint design work lack completeness and accuracy, which brings challenges to improving the stability and network resource utilization of ICPS. In this paper, we propose a control and transmission joint design architecture for integrated multi-subsystem ICPS for multi-hop networks. We consider the timeliness of information through state delays, input delays, and event-triggered states in ICPS. To avoid the instability caused by input delay, we design an LQR-based controller and derive the feasible region of delay to guarantee the stability of the control system. Finally, we propose an event-triggered strategy that represents control and transmission costs to minimize the amount of data transfer while ensuring system stability. The evaluation results show that our strategy improves the stability of the control system while reducing the network burden compared with the traditional joint design method. © 2022 IEEE.

关键词： Cyber Physical system

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Fault Diagnosis and Prognosis in Partially-Observed Discrete Event systems with Delayed Observations 63

Fault Diagnosis and Prognosis in Partially-Observed Discrete...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Wang, Jiwei Baldi, Simone Yu, Wenwu Yin, Xiang Southeast University School of Cyber Science and Engineering Nanjing210096 China Southeast University School of Mathematics Nanjing210096 China Shanghai Jiao Tong University Department of Automation Key Laboratory of System Control and Information Processing Shanghai200240 China

ISBN: (纸本)9798350316339

Fault diagnosis and prognosis in discrete event systems are studied in the scenario where the observations are possibly received with delay. To address this scenario, two conditions for diagnosis and prognosis with delayed observations are proposed, where we show that the state-of-the-art notion of prognosability must be revised to avoid conservativeness. Diagnosability and prognosability conditions are then verified by introducing a delay observer and a new verification function. Theoretical analysis indicates the effectiveness of the verification method for fault diagnosis and prognosis in the system. © 2024 IEEE.

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Integrated Framework for Test and Evaluation of Autonomous Vehicles

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Journal of Shanghai Jiaotong university(Science) 2021年第5期26卷 699-712页

作者： SU Yimin WANG Lin Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China

Autonomous vehicles must pass effective standard tests to verify their reliability and ***-ingly,it is very important to establish a complete scientific test and evaluation system for autonomous vehicles.A comprehensive framework incorporating the design of test scenarios,selection of evaluation indexes,and estab-lishment of an evaluation system is proposed in this *** aims of the system are to obtain an objective and quantitative score regarding the intelligence of autonomous vehicles,and to form an automated process in the future *** proposed framework is built on a simulation platform to ensure the feasibility of the design and implementation of the test *** design principle for the test scenarios is also *** reduce subjective influences,the proposed framework selects objective indexes from four aspects:safety,comfort,driving performance,and standard *** order relation analysis method is adopted to formulate the index weights,and fuzzy comprehensive evaluation is used to quantify the ***,a numerical example is provided to visually demonstrate the evaluation results for the autonomous vehicles scored by the proposed framework.

关键词： test and evaluation scenario construction evaluation index autonomous vehicles

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Real-Time Trajectory Planning for On-road Autonomous Tractor-Trailer Vehicles

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Journal of Shanghai Jiaotong university(Science) 2021年第5期26卷 722-730页

作者： SHEN Qiyue WANG Bing WANG Chunxiang Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationShanghai Jiao Tong UniversityShanghai 200240China

Tractor-trailer vehicles,which are composed of a car-like tractor towing a passive trailer,have been widely deployed in the transportation industry,and trajectory planning is a critical step in enabling such a system to drive *** to the properties of being highly nonlinear and nonholonomic with complex dynamics,the tractor-trailer system poses great challenges to the development of motion-planning *** this study,an indirect trajectory planning framework for a tractor-trailer vehicle under on-road driving is presented to deal with the problem that the traditional planning framework cannot consider the feasibility and quality simultaneously in real-time trajectory generation of the tractor-trailer *** indirect planning framework can easily handle complicated tractor-trailer dynamics and generate high-quality,obstacle-free trajectory using quintic polynomial spline,speed profile optimization,forward simulation,and properly designed cost *** under different driving scenarios and trajectories with different driving requirements are conducted to validate the performance of the proposed framework.

关键词： trajectory planning tractor-trailer vehicle forward simulation on-road driving

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Semantic Coherence Guided Multiview Similarity for Image Classification with Varied Supervision

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第6期5卷 3072-3082页

作者： Zhang, Chunjie Cao, Ping Bai, Huihui Zheng, Xiaolong Beijing Jiaotong University Institute of Information Science Beijing100044 China Beijing Jiaotong University Beijing Key Laboratory of Advanced Information Science and Network Technology Beijing100044 China University of Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems The State of Key Laboratory of Management and Control for Complex System Institute of Automation Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100190 China

Pairwise similarity has been widely used for image classification by propagating the class information from labeled images to unlabeled images and predicting the classes of unlabeled images accordingly. Although widely used, pairwise similarity based classification methods have two drawbacks. On one hand, visual-semantic similarity consistency does not always hold due to semantic gap. On the other hand, the reliability of pairwise similarity is also influenced by the number and underlying distribution of labeled images. A well-designed classification model cannot be easily generalized to few-shot classification tasks. To solve these two problems, in this article, we propose a semantic coherence guided multiview similarity (SCG-MV) for image classification method with varied supervision levels. We measure the semantic coherence between image pairs for classifier learning. This is achieved by first conducting line search along the line segment between each image pair, and then measure the semantics of each interval. The similarity of one image pair can then be obtained by aggregating the semantic coherence of all the intervals. In this way, we can model image similarities more finely and discriminatively. To make use of multiview information, we also use the semantic coherence guided image similarities to learn multiview classifiers. The proposed semantic coherence guided method can be combined with other similarity based methods for image classification with various levels of supervision. We conduct both few-shot and fully supervised classification experiments on four datasets with the results well prove the discriminative power and generalization ability of the proposed method. © 2020 IEEE.

关键词： Semantics

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Discussion on application of FLIC-Fluent coupled simulation technology on medium-scale and large-scale municipal solid waste incinerators 6

Discussion on application of FLIC-Fluent coupled simulation ...

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6th International Conference on Intelligent Computing, Communication, and Devices, ICCD 2023

作者： Zhang, Hongze Guangxi Key Laboratory of Machine Vision and Intelligent Control Guangxi Wuzhou China Guangxi Colleges and Universities Key Lab. of Image Processing and Intelligent Information System Guangxi Wuzhou China School of Electronics and Information Engineering Wuzhou University Guangxi Wuzhou China

ISBN: (数字)9781510666269

ISBN: (纸本)9781510666252

Today, the world economy is in the stage of rapid development, followed by the rising quantity, the decreasing moisture content, and the increasing heat value of Municipal Solid Waste (MSW). Since waste incineration has the advantages of excellent volume reduction effect, high resource utilization efficiency, and less secondary pollution to the environment, waste incineration disposal technology has received extensive attention worldwide. With the continuous increase of the urban population, the amount of sewage sludge is growing year by year. The process of the sludge incineration system is highly complicated, and the cost of construction and operation is high. The waste incinerator can process not only MSW but also sewage sludge. Therefore, the co-incineration of sewage sludge with MSW in the existing waste incinerator is a safe and effective way to dispose of sewage sludge. In this paper, the simulation results of Computational Fluid Dynamics (CFD) are analyzed for medium-scale and large-scale waste incinerators, characterized by high moisture content, high ash content, low heat value of sewage sludge, and incomplete combustion and high pollutant emissions in waste incinerators. With FLIC-Fluent coupled simulation method, the critical information such as temperature field, velocity field, concentration field of principal components, and the pollutant emissions can be predicted. Based on the CFD simulation results, the performance and structure of waste incinerators can be optimized, and the new products can be designed and developed. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Waste incineration

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3D measurement of scattering media based on self-supervised fringe domain transformation

3D measurement of scattering media based on self-supervised ...

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2024 International Conference on Optical and Photonic Engineering, icOPEN 2024

作者： Tan, Ji Niu, Haipeng Luo, Suofan Liu, Jia He, Zhaoshui School of Automation Guangdong University of Technology Guangzhou510006 China Guangdong University of Technology Key Laboratory for IoT Intelligent Information Processing and System Integration Ministry of Education Guangzhou510006 China

ISBN: (数字)9781510688117

ISBN: (纸本)9781510688100

The scattering media measurement for structured light techniques remains challenging due to the subsurface scattering that destroys fringe patterns and introduces phase error. Recently, deep learning has been successfully applied to fringe analysis. Unfortunately, collecting a large scale of labeled data is difficult, especially in scattering media measurement scenarios. Inspired by image style transfer, we proposed a high-precision scattering medium measurement method based on self-supervised fringe domain transformation. Specifically, by treating degraded fringe and ideal fringe as two pattern styles, a cycle generation strategy is developed to achieve fringe enhancement by translating between two fringe domains. Two generators and two discriminators are used to form cycle-consistency constraints for self-supervised learning with unpaired dataset. Additionally, we combine numerical and physical constraints to jointly optimize network parameters, effectively suppressing phase-shift errors and improving phase quality. Since the proposed approach eliminates the need for label data, it exhibits great potential for applying deep learning to scattering medium measurement. Experiments verify that our method can obtain high-quality 3D morphology of translucent objects. © 2025 SPIE.

关键词： Velocity measurement

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Network Intrusion Detection Model Based on Space-time Fusion Features and Attention Mechanism 33

Network Intrusion Detection Model Based on Space-time Fusion...

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第33届中国控制与决策会议

作者： Yali Wu Liting Huang Jinjin Qi Xiaoxiao Quan School of Automation and Information Engineering Xi'an University of Technology Shaanxi ProvinceKeyLaboratory of Complex System Control and Intelligent Information Processing Shaanxi Province Key Laboratory of Complex System Control and Intelligent Information Processing

ISBN: (纸本)9781665431293

To solve the problem of low performance of network intrusion detection,a deep learning intrusion detection model based on space-time fusion features and attention mechanism—CLT-net is *** this model,space-time fusion features are obtained by integrating convolutional neural network and long short-time memory network,and attention module is added to calculate the importance of the input features,and softmax function is used for *** a large number of simulation experiments on NSL-KDD data sets,CLT-net has significantly improved the convergence of the training set and the accuracy of the test *** with the traditional CNN model with similar structure and the space-time fusion CLSTM the accuracy of the model increased by 11.8% and 10.9%*** shows that this model has great potential in the application field of network intrusion detection.

关键词： Network Intrusion Detection Convolution Neural Network Long Short-term Memory Network Attention Mechanism CLT-net

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Improved Double Deep Q Network Algorithm Based on Average Q-Value Estimation and Reward Redistribution for Robot Path Planning

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Computers, Materials & Continua 2024年第11期81卷 2769-2790页

作者： Yameng Yin Lieping Zhang Xiaoxu Shi Yilin Wang Jiansheng Peng Jianchu Zou Key Laboratory of Advanced Manufacturing and Automation Technology Guilin University of TechnologyEducation Department of Guangxi Zhuang Autonomous RegionGuilin541006China Guangxi Key Laboratory of Special Engineering Equipment and Control Guilin University of Aerospace TechnologyGuilin541004China Guilin Mingfu Robot Technology Company Limited Guilin541199China Key Laboratory of AI and Information Processing Education Department of Guangxi Zhuang Autonomous RegionHechi UniversityYizhou546300China

By integrating deep neural networks with reinforcement learning,the Double Deep Q Network(DDQN)algorithm overcomes the limitations of Q-learning in handling continuous spaces and is widely applied in the path planning of mobile ***,the traditional DDQN algorithm suffers from sparse rewards and inefficient utilization of high-quality *** those problems,an improved DDQN algorithm based on average Q-value estimation and reward redistribution was ***,to enhance the precision of the target Q-value,the average of multiple previously learned Q-values from the target Q network is used to replace the single Q-value from the current target Q ***,a reward redistribution mechanism is designed to overcome the sparse reward problem by adjusting the final reward of each action using the round reward from trajectory ***,a reward-prioritized experience selection method is introduced,which ranks experience samples according to reward values to ensure frequent utilization of high-quality ***,simulation experiments are conducted to verify the effectiveness of the proposed algorithm in fixed-position scenario and random *** experimental results show that compared to the traditional DDQN algorithm,the proposed algorithm achieves shorter average running time,higher average return and fewer average *** performance of the proposed algorithm is improved by 11.43%in the fixed scenario and 8.33%in random *** not only plans economic and safe paths but also significantly improves efficiency and generalization in path planning,making it suitable for widespread application in autonomous navigation and industrial automation.

关键词： Double Deep Q Network path planning average Q-value estimation reward redistribution mechanism reward-prioritized experience selection method

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Toward Cable-Driven Continuum Robots: Micro-Motion Augmentation Using Eccentrically Arranged Fibres with Eccentric Lumens

Toward Cable-Driven Continuum Robots: Micro-Motion Augmentat...

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2024 IEEE International Conference on Robotics and Biomimetics, ROBIO 2024

作者： Lin, Zecai Zhou, Cheng Zou, Yun Gao, Anzhu Shanghai Jiao Tong University Institute of Medical Robotics Department of Automation China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781665481090

Micro-motion augmentation of macro-motion continuum robot can largely enhance its micro-operation capability during surgery. However, most existing micro-motion continuum robots have non-compact mechanical structure or non-smooth micro tip motion, which leads to complicated control in micro lumens. This paper proposes a micro-motion augmentation method by rotating eccentrically arranged fibres with eccentric lumens for cable-driven continuum robots. Two thermal drawn polymer fibres with an eccentric lumen on each are inserted into its eccentric lumens of the continuum robot. The micro-motion mechanism relies on small changes in the neutral axis of the continuum robot due to the rotation of the eccentrically arranged fibres. A kinematic model considering variable neural axis is built to describe the micro motion, and a simulation is conducted to investigate the deformation characteristics. The resolution and micro motion with respect to different structural parameters are also analysed. Detailed experiments are performed to validate the effectiveness of the proposed method, and results indicate that the repeatability of micro-motion is 10.1 μm (4.0 %). © 2024 IEEE.

关键词： Robotic surgery

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