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Distributed Resilient Fusion Filtering for Nonlinear systems with Random Sensor Delays:Optimized Algorithm Design and Boundedness Analysis

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Journal of systems Science & complexity 2023年第4期36卷 1423-1442页

作者： HU Jun HU Zhibin DONG Hongli LIU Hongjian School of Automation Harbin University of Science and TechnologyHarbin 150080China Department of Mathematics Harbin University of Science and TechnologyHarbin 150080China Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin University of Science and TechnologyHarbin 150080China Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum UniversityDaqing 163318China School of Mathematics-Physics and Finance Anhui Polytechnic UniversityWuhu 241000China

This paper is concerned with the distributed resilient fusion filtering(DRFF)problem for a class of time-varying multi-sensor nonlinear stochastic systems(MNSSs)with random sensor delays(RSDs).The phenomenon of the RSDs is modeled by a set of random variables with certain statistical *** addition,the nonlinear function is handled via Taylor expansion in order to deal with the nonlinear fusion filtering *** aim of the addressed issue is to propose a DRFF scheme for MNSSs such that,for both RSDs and estimator gain perturbations,certain upper bounds of estimation error covariance(EEC)are given and locally minimized at every sample *** the light of the obtained local filters,a new DRFF algorithm is developed via the matrix-weighted fusion ***,a sufficient condition is presented,which can guarantee that the local upper bound of the EEC is ***,a numerical example is provided,which can show the usefulness of the developed DRFF approach.

关键词： Distributed resilient fusion filtering matrix-weighted fusion nonlinear time-varying systems random sensor delays

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Conservative-Progressive Collaborative Learning for Semi-Supervised Semantic Segmentation

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IEEE Transactions on Image Processing 2023年 32卷 6183-6194页

作者： Fan, Siqi Zhu, Fenghua Feng, Zunlei Lv, Yisheng Song, Mingli Wang, Fei-Yue Institute of Automation State Key Laboratory of Management and Control of Complex Systems Chinese Academy of Sciences Beijing100190 China Tsinghua University Beijing100190 China Zhejiang University College of Computer Science and Technology Hangzhou310027 China

Pseudo supervision is regarded as the core idea in semi-supervised learning for semantic segmentation, and there is always a tradeoff between utilizing only the high-quality pseudo labels and leveraging all the pseudo labels. Addressing that, we propose a novel learning approach, called Conservative-Progressive Collaborative Learning (CPCL), among which two predictive networks are trained in parallel, and the pseudo supervision is implemented based on both the agreement and disagreement of the two predictions. One network seeks common ground via intersection supervision and is supervised by the high-quality labels to ensure a more reliable supervision, while the other network reserves differences via union supervision and is supervised by all the pseudo labels to keep exploring with curiosity. Thus, the collaboration of conservative evolution and progressive exploration can be achieved. To reduce the influences of the suspicious pseudo labels, the loss is dynamic re-weighted according to the prediction confidence. Extensive experiments demonstrate that CPCL achieves state-of-the-art performance for semi-supervised semantic segmentation. © 1992-2012 IEEE.

关键词： Semantic Segmentation

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Large Language Models as Few-Shot Defect Detectors for Additive Manufacturing

Large Language Models as Few-Shot Defect Detectors for Addit...

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2024 China Automation Congress, CAC 2024

作者： Fang, Qihang Xiong, Gang Wang, Fang Shen, Zhen Dong, Xisong Wang, Fei-Yue State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9798350368604

Additive manufacturing (AM) is a promising technology to tailor complex structures in a layer-by-layer fashion. Its wide adoption, however, is hampered by occurrence of defects that deteriorates product quality. Defect detection methods have therefore been developed to address quality issues, primarily utilizing deep learning models. Despite achieving appreciable results, these models require a substantial amount of labeled data and extensive training, which are costly and time-consuming. Thus, it is worth developing a new approach that can perform defect detection (1) with minimal labeled data, and (2) without the necessity for model updating. Recently, the large language model (LLM) has demonstrated remarkable generalization capability across various fields. It features an in-context learning (ICL) capability that allows it to learn from a context without any retraining. This study explores the potential of applying an LLM for AM defect detection based on ICL. To this end, a dataset pertaining to the resin deposition status in vat photopolymerization, as a field where prevailing LLMs have limited exposure, is collected. Two contributions are made to achieve more accurate defect detection by prompting. First, a multimodal context that includes both image-label pairs and expert knowledge is tailored, which contains comprehensive information about deposition status. Second, a repeated query and voting (RQV) technique is proposed to mitigate occasional misjudgements, thus enhancing the reliability of the defect detection. Comprehensive ablation studies verify the effectiveness of both the multimodal context and RQV technique. As a result, 96.2% classification accuracy is achieved in such a challenging few-shot setting, obviating the need of model updating. © 2024 IEEE.

关键词： Labeled data

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Pattern transition and regulation in a subthalamopallidal network under electromagnetic effect

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Chinese Physics B 2022年第11期31卷 626-637页

作者： Zilu Cao Lin Du Honghui Zhang Yuzhi Zhao Zhuan Shen Zichen Deng School of Mathematics and Statistics Northwestern Polytechnical UniversityXi'an 710129China School of Aeronautics Northwestern Polytechnical UniversityXi'an 710072China MIIT Key Laboratory of Dynamics and Control of Complex Systems Xi'an 710129China

Although the significant roles of magnetic induction and electromagnetic radiation in the neural system have been widely studied,their influence on Parkinson’s disease(PD)has yet to be well *** virtue of the magnetic flux variable,this paper studies the transition of firing patterns induced by magnetic induction and the regulation effect of external magnetic radiation on the firing activities of the subthalamopallidal network in basal *** find:(i)The network reproduces five typical waveforms corresponding to the severity of symptoms:weak cluster,episodic,continuous cluster,episodic,and continuous wave.(ii)Magnetic induction is a double-edged sword for the treatment of *** the increase of magnetic coefficient may lead the physiological firing activity to transfer to pathological firing activity,it also can regulate the pathological intensity firing activity with excessiveβ-band power transferring to the physiological firing pattern with weakβ-band power.(iii)External magnetic radiation could inhibit continuous tremulous firing andβ-band power of subthalamic nucleus(STN),which means the severity of symptoms ***,the bi-parameter plane of the regulation region shows that a short pulse period of magnetic radiation and a medium level of pulse percentage can well regulate pathological *** work helps to understand the firing activity of the subthalamopallidal network under electromagnetic *** may also provide insights into the mechanisms behind the electromagnetic therapy of PD-related firing activity.

关键词： subthalamopallidal network magnetic induction and radiation pattern transition regulation of pathological oscillation

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A Secure Clock Synchronization Scheme for Wireless Sensor Networks Against Malicious Attacks

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Journal of systems Science & complexity 2021年第6期34卷 2125-2138页

作者： ZHANG Xuxin LIU Yanzhang ZHANG Ya School of Automation Southeast UniversityNanjing 210096China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of EducationNanjing 210096China China Electric Power Research Institute Nanjing 210003China

This paper studies the secure and accurate clock synchronization problem for sensor networks with time-varying delays and malicious attacks.A novel clock synchronization scheme based on the attack detection mechanism,attack compensation,and maximum consensus protocol is *** proposed scheme starts with the detection of the malicious attacks and the clock data under attacks is *** the basis,software clock parameters are updated so that all the nodes in the network can have the same software skew and offset,so the clock synchronization can be ***,it is theoretically proved that the proposed scheme can achieve the attack detection correctly,and further can guarantee a secure and accurate clock *** addition,extensive simulations are also conducted to validate the effectiveness of the proposed scheme.

关键词： Clock synchronization communication delays consensus malicious attacks wireless sensor networks

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Nonrigid Object Contact Estimation With Regional Unwrapping Transformer

arXiv

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arXiv 2023年

作者： Xie, Wei Zhao, Zimeng Li, Shiying Zuo, Binghui Wang, Yangang Southeast University China The Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

Acquiring contact patterns between hands and nonrigid objects is a common concern in the vision and robotics community. However, existing learning-based methods focus more on contact with rigid ones from monocular images. When adopting them for nonrigid contact, a major problem is that the existing contact representation is restricted by the geometry of the object. Consequently, contact neighborhoods are stored in an unordered manner and contact features are difficult to align with image cues. At the core of our approach lies a novel hand-object contact representation called RUPs (Region Unwrapping Profiles), which unwrap the roughly estimated hand-object surfaces as multiple high-resolution 2D regional profiles. The region grouping strategy is consistent with the hand kinematic bone division because they are the primitive initiators for a composite contact pattern. Based on this representation, our Regional Unwrapping Transformer (RUFormer) learns the correlation priors across regions from monocular inputs and predicts corresponding contact and deformed transformations. Our experiments demonstrate that the proposed framework can robustly estimate the deformed degrees and deformed transformations, which makes it suitable for both nonrigid and rigid contact. © 2023, CC BY-NC-SA.

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Symplectic analysis for regulating wave propagation in a one-dimensional nonlinear graded metamaterial

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Applied Mathematics and Mechanics(English Edition) 2023年第5期44卷 745-758页

作者： Yunping ZHAO Xiuhui HOU Kai ZHANG Zichen DENG Department of Applied Mathematics Northwestern Polytechnical UniversityXi’an 710072China School of Mechanics Civil Engineering and ArchitectureNorthwestern Polytechnical UniversityXi’an 710072China Ministry of Industry and Information Technology Key Laboratory of Dynamics and Control of Complex SystemsNorthwestern Polytechnical UniversityXi’an 710072China State Key Laboratory of Structural Analysis for Industrial Equipment Dalian University of TechnologyDalian 116024China

An analytical method,called the symplectic mathematical method,is proposed to study the wave propagation in a spring-mass chain with gradient arranged local resonators and nonlinear ground *** with the linearized perturbation approach,the symplectic transform matrix for a unit cell of the weakly nonlinear graded metamaterial is derived,which only relies on the state *** results of the dispersion relation obtained with the symplectic mathematical method agree well with those achieved by the Bloch *** is shown that wider and lower frequency bandgaps are formed when the hardening nonlinearity and incident wave intensity ***,the displacement response and transmission performance of nonlinear graded metamaterials with finite length are *** dual tunable effects of nonlinearity and gradation on the wave propagation are explored under different excitation *** small excitation frequencies,the gradient parameter plays a dominant role compared with the *** reason is that the gradient tuning aims at the gradient arrangement of local resonators,which is limited by the critical value of the local resonator *** contrast,for larger excitation frequencies,the hardening nonlinearity is dominant and will contribute to the formation of a new bandgap.

关键词： symplectic mathematical method nonlinear graded metamaterial tunable bandgap

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General Simultaneous Localization and Mapping Scheme for mmWave Communication systems

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IEEE Internet of Things Journal 2024年第12期11卷 22521-22536页

作者： Du, Tao Yang, Jie Wen, Chao-Kai Xia, Shuqiang Jin, Shi Southeast University National Mobile Communications Research Laboratory Nanjing210096 China Southeast University Key Laboratory Of Measurement And Control Of Complex Systems Of Engineering Ministry Of Education The Frontiers Science Center For Mobile Information Communication And Security Nanjing210096 China Institute Of Communications Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan Zte Corporation The State Key Laboratory Of Mobile Network And Mobile Multimedia Technology Shenzhen518055 China Southeast University National Mobile Communications Research Laboratory The Frontiers Science Center For Mobile Information Communication And Security Nanjing210096 China

Utilizing high-resolution antenna arrays and wide bandwidth of the millimeter-wave (mmWave) spectrum in 5G new radio (NR) mmWave communication systems holds the potential for high-throughput data transmission while enabling user localization and environmental mapping. However, the majority of existing simultaneous localization and mapping (SLAM) algorithms rely on methods akin to the extended Kalman filter for generating initial map features. These methods prove ineffective when the measurement dimension is insufficient. Furthermore, there is a notable absence of research exploring mmWave prototype systems to evaluate and compare the performance and viability of various SLAM algorithms. To address these challenges, we propose an innovative probability hypothesis density (PHD) generation scheme for birth events and have developed a prototype system. Our approach, referred to as PHD-SLAM, exhibits remarkable effectiveness even in scenarios where the measurement dimension falls short of map features. This means it can function seamlessly with only delay or angle information available. Additionally, we have designed a 28GHz mmWave beam scanning prototype system that leverages the 5G NR frame for accomplishing SLAM algorithms. Following this, we conducted extensive simulations and experimental evaluations to gauge the performance of several leading-edge SLAM algorithms under diverse mmWave circumstances, encompassing PHD-based and belief propagation (BP) SLAM algorithms. Our analysis reveals that both PHD and BP SLAM can achieve agent localization precision within a decimeter and mapping precision within a meter, capitalizing on the angle parameters of mmWave signals. While BP SLAM showcases reduced computational demand, its estimation precision is marginally inferior to that of PHD-SLAM. © 2014 IEEE.

关键词： Belief propagation

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Effectiveness of Koopman Autoencoder Predicting Nonlinear System States: Effect of Latent Layer Neuron Number

Effectiveness of Koopman Autoencoder Predicting Nonlinear Sy...

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2022 Chinese Automation Congress, CAC 2022

作者： Zhou, Jun Jia, Yubin Liu, Zhimin Yong, Panxiao Guo, Jun The School of Automation Southeast University Jiangsu Nanjing210096 China The Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing210096 China

ISBN: (纸本)9781665465335

Researchers have always been popular with analyzing and controlling nonlinear systems, yet most methods are based on local linearized models. As an alternative, Koopman theory was introduced to solve global linearization problems. Koopman operator is infinite-dimensional and has the ability to globally linearize nonlinear systems without information loss. In this work, a Koopman autoencoder, which combines the Koopman operator and autoencoder network, is used for predicting nonlinear systems. The autoencoder network is designed to find an approximate finite-dimensional Koopman operator. An inverted pendulum dynamic system is used to evaluate the effectiveness of the Koopman autoencoder, and accurate prediction results have been achieved. Furthermore, we discussed the effect of latent layer neuron number in the Koopman autoencoder, prediction results are given, and the best number of latent layer neurons for this system is found. © 2022 IEEE.

关键词： Nonlinear systems

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Comparison of Three Data-Driven Networked Predictive control Methods for a Class of Nonlinear systems

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1714-1716页

作者： Zhong-Hua Pang Xue-Ying Zhao Jian Sun Yuntao Shi Guo-Ping Liu the Key Laboratory of Fieldbus Technology and Automation of Beijing North China University of TechnologyBeijing 100144China the State Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of TechnologyBeijing 100081China the Center for Control Science and Technology Southern University of Science and TechnologyShenzhen 518055China

Dear Editor,In this letter,in order to deal with random network delays and packet losses in a class of networked nonlinear systems,three data-driven networked predictive control methods are *** closed-loop systems and... 详细信息

关键词： letter Nonlinear nonlinear

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