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On non-von Neumann flexible neuromorphic vision sensors

npj Flexible Electronics 2024年第1期8卷 638-663页

作者： Hao Wang Bin Sun Shuzhi Sam Ge Jie Su Ming Liang Jin Institute for Future Shandong Key Laboratory of Industrial Control TechnologySchool of AutomationQingdao UniversityQingdao 266071China College of Electronic and Information Engineering Qingdao UniversityQingdao 266071China Department of Electrical and Computer Engineering and Institute for Functional Intelligent MaterialsNational University of SingaporeSingapore 117583Singapore

The structure andmechanismof thehuman visual system contain rich treasures,and surprising effects can be achieved by simulating the human visual *** this article,starting from the human visual system,we compare and discuss the discrepancies between the human visual system and traditional machine vision *** the wide variety and large volume of visual information,the use of nonvon Neumann structured,flexible neuromorphic vision sensors can effectively compensate for the limitations of traditional machine vision systems based on the von Neumann ***,this article addresses the emulation of retinal functionality and provides an overview of the principles and circuit implementation methods of non-von Neumann computing ***,in terms of mimicking the retinal surface structure,this article introduces the fabrication approach for flexible sensor ***,this article analyzes the challenges currently faced by non-von Neumann flexible neuromorphic vision sensors and offers a perspective on their future development.

关键词： Neumann system starting

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Fractional core-based collapse mechanism and structural optimization in complex systems

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Science China(Information Sciences) 2023年第9期66卷 168-183页

作者： Shubin SI Changchun LV Zhiqiang CAI Dongli DUAN Jurgen KURTHS Zhen WANG School of Mechanical Engineering Northwestern Polytechnical University Key Laboratory of Industrial Engineering and Intelligent Manufacturing(Ministry of Industry and Information Technology) School of Information and Control Engineering Xi'an University of Architecture and Technology Instiute of Physics Humboldt-University Potsdam Institute for Climate Impact Research

Catastrophic and major disasters in real-world systems ranging from financial markets and ecosystems, often show generic early-warning signals that may indicate a collapse. Hence, understanding the collapse mechanism of a complex network and predicting its process are of uttermost importance. However, these challenges are often hindered by the extremely high dimensionality of the underlying *** present here the concept of the fractional core(F-core) that considers the contribution of the network topology and dynamics to systematically analyze the collapse process in such networks, and encompass a broad range of dynamical systems, from mutualistic ecosystems to regulatory dynamics. We offer testable predictions on the tipping point, and, in particular, prove that the extinction of the maximum F-core of a network is an efficient indicator of whether a system completely collapses. The results show that the death of species or cells in a low-order F-core may improve the average density and have little influence on the tipping point. Generally, the principle of the F-core demonstrates how complex systems collapse and opens an innovative optimization strategy to uncover the optimal structure of systems.

关键词： collapse mechanism tipping point structural optimization complex systems phase transition

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Active Disturbance Rejection control of Dense Medium Separation Process Based on Improved PI-GPC

Active Disturbance Rejection Control of Dense Medium Separat...

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2024 China Automation Congress, CAC 2024

作者： Zhao, Xiaoyao Zhou, Fan Zhao, Jun Wang, Wei Key Laboratory of Intelligent Control and Optimization for Industrial Equipment Ministry of Education Dalian China School of Control Science and Engineering Dalian University of Technology Dalian China

ISBN: (纸本)9798350368604

Aiming at the complex field environment of dense medium separation process and the large amount of matrix inversion calculation in the traditional PI-GPC solution process, an adaptive stepped generalized predictive control method with proportional-integral structure (PI-ASGPC-LESO) based on active disturbance rejection strategy is proposed. Considering the large amount of calculation when PI-GPC solves the optimal control rate, an adaptive step factor dependent on the system adjustment error is introduced to constrain the change of the control amount, which reduces the amount of calculation in the solution process. In view of the complex on-site environment of dense medium separation and the large interference in the system, LESO is added to the loop to suppress external disturbances and compensate the unmodeled error of the system. In order to verify the effectiveness of the proposed method, a comparative experiment with traditional PI-GPC and PI-GPC-LESO was designed with the dense medium separation system of a coal preparation plant as the control object. The experimental results show that the proposed method effectively improves the dynamic performance of the system, with shorter adjustment time, smaller overshoot, and stronger anti-interference ability. © 2024 IEEE.

关键词： Disturbance rejection

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A Novel Evaluation Strategy to Artificial Neural Network Model Based on Bionics

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Journal of Bionic engineering 2022年第1期19卷 224-239页

作者： Sen Tian Jin Zhang Xuanyu Shu Lingyu Chen Xin Niu You Wang School of Mathematics and Statistics Hunan Normal UniversityChangsha410081China College of Information Science and Engineering Hunan Normal UniversityChangsha410081China School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China Key Laboratory of Industrial Control Technology Zhejiang UniversityHangzhou310058China Science and Technology on Parallel and Distributed Laboratory College of ComputerNational University of Defense TechnologyChangsha410199China Key Laboratory of Industrial Control Technology Institute of Cyber Systems and ControlZhejiang UniversityHangzhou310027China

With the continuous deepening of Artificial Neural Network(ANN)research,ANN model structure and function are improving towards diversification and ***,the model is more evaluated from the pros and cons of the problem-solving results and the lack of evaluation from the biomimetic aspect of imitating neural networks is not inclusive ***,a new ANN models evaluation strategy is proposed from the perspective of bionics in response to this problem in the ***,four classical neural network models are illustrated:Back Propagation(BP)network,Deep Belief Network(DBN),LeNet5 network,and olfactory bionic model(KIII model),and the neuron transmission mode and equation,network structure,and weight updating principle of the models are analyzed *** analysis results show that the KIII model comes closer to the actual biological nervous system compared with other models,and the LeNet5 network simulates the nervous system in ***,evaluation indexes of ANN are constructed from the perspective of bionics in this paper:small-world,synchronous,and chaotic ***,the network model is quantitatively analyzed by evaluation indexes from the perspective of *** experimental results show that the DBN network,LeNet5 network,and BP network have synchronous *** the DBN network and LeNet5 network have certain chaotic characteristics,but there is still a certain distance between the three classical neural networks and actual biological neural *** KIII model has certain small-world characteristics in structure,and its network also exhibits synchronization characteristics and chaotic *** with the DBN network,LeNet5 network,and the BP network,the KIII model is closer to the real biological neural network.

关键词： Artificial neural network(ANN) Back Propagation(BP)network Deep Belief Network(DBN) LeNet5 network Olfactory bionic model(KIII model) Small world Chaos Synchronous

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Adaptive Attitude control for a Coaxial Tilt-Rotor UAV via Immersion and Invariance Methodology

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1710-1713页

作者： Longlong Chen Zongyang Lv Xiangyu Shen Yuhu Wu Xi-Ming Sun the Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education and the School of Control Science and EngineeringDalian University of TechnologyDalian 116024China

Dear Editor,This letter is concerned with the attitude control for a novel tiltrotor unmanned aerial vehicle with two pairs of tiltable coaxial rotors and one rear *** immersion and invariance-based adaptive attitude controller for the tilt-rotor unmanned aerial vehicle is *** the proposed control strategy,an adaptive update law is specially designed to compensate for the uncertainties of damping *** stability of the resulting closed-loop coaxial tiltrotor unmanned aerial vehicle(CTRUAV)system is proved by the Lyapunov methodology and LaSalle’s invariance ***。

关键词： theory. invariance letter

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A stacking-based model for the spread of Botryosphaeria laricina

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Journal of Forestry Research 2025年第1期36卷 427-443页

作者： Hongwei Zhou Shibo Zhang Meng Xie Xiaodong Li Yifan Chen Wenhao Dai College of Computer and Control Engineering Northeast Forestry UniversityHarbin 150040People’s Republic of China Key Laboratory of National Forestry and Grassland Administration On Forest and Grassland Pest Monitoring and Warning Center for Biological Disaster Prevention and ControlNational Forestry and Grassland AdministrationShenyang 110034People’s Republic of China

Botryosphaeria laricina(larch shoot blight)was first identified in 1973 in Jilin Province,*** disease spread rapidly and caused considerable damage because its pathogenesis was unknown at the time and there were no effective controls or quarantine *** present,it shows a spreading trend,but most research can only conduct physiological analyses within a relatively short period,combining individual influencing ***,methods such as neural network models,ensemble learning algorithms,and Markov models are used in pest and disease prediction and ***,there may be fitting issues or inherent limitations associated with these *** study obtained *** data at the county level from 2003 to *** dataset was augmented using the SMOTE algorithm,and then algorithms such as XGBoost were used to select the significant features from a combined set of 12 features.A new stacking fusion model has been proposed to predict the status of *** model is based on random forest,gradient boosted decision tree,CatBoost and logistic regression *** accuracy,recall,specificity,precision,F_(1) value and AUC of the model reached 90.9%,91.6%,90.4%,88.8%,90.2%and 96.2%.The results provide evidence of the strong performance and stability of the *** is mainly found in the northeast and this study indicates that it is spreading *** means should be used promptly to prevent further damage and spread.

关键词： Botryosphaeria laricina Data augmentation Feature selection Stacking Status of spread

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Object Helps U-Net Based Change Detectors

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 548-550页

作者： Lan Yan Qiang Li Kenli Li College of Computer Science and Electronic Engineering Hunan UniversityChangsha 410082China State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,This letter focuses on leveraging the object information in images to improve the performance of the U-Net based change *** detection is fundamental to many computer vision *** existing solutions based on ... 详细信息

关键词： Net computer networks

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Mesoporous molecular sieve-based materials for catalytic oxidation of VOC: A review

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Journal of Environmental Sciences 2023年第3期125卷 112-134页

作者： Wei Gao Xiaolong Tang Honghong Yi Shanxue Jiang Qingjun Yu Xizhou Xie Ruijie Zhuang Department of Environmental Science and Engineering School of Energy and Environmental EngineeringUniversity of Science and Technology BeijingBeijing 100083China State Environmental Protection Key Laboratory of Food Chain Pollution Control Beijing Technology and Business UniversityBeijing 100048China Beijing Key Laboratory of Resource-oriented Treatment of Industrial Pollutants Beijing 100083China

As the main contributor of the formation of particulate matter as well as ozone, volatile organic compounds(VOCs) greatly affect human health and the environmental quality. Catalytic combustion/oxidation has been viewed as an efficient, economically feasible and environmentally friendly way for the elimination of VOCs. Supported metal catalyst is the preferred type of catalysts applied for VOCs catalytic combustion because of the synergy between active components and support as well as its flexibility in the composition. The presence of support not only plays the role of keeping the catalyst with good stability and mechanical strength, but also provides a large specific surface for the good dispersion of active components, which could effectively improve the performance of catalyst as well as decrease the usage of active components, especially the noble metal amount. Mesoporous molecular sieves, owing to their large surface area, unique porous structures, large pore size as well as uniform pore-size distribution, were viewed as superior support for dispersing active components. This review focuses on the recent development of mesoporous molecular sieve supported metal catalysts and their application in catalytic oxidation of VOCs. The effect of active component types, support structure, preparation method, precursors, etc. on the valence state, dispersion as well as the loading of active species were also discussed and summarized. Moreover, the corresponding conversion route of VOCs was also *** review aims to provide some enlightment for designing the supported metal catalysts with superior activity and stability for VOCs removal.

关键词： Volatile organic compound Mesoporous molecular sieves Supported catalyst Catalytic oxidation Reaction mechanism Influencing factors

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Distributed model-free adaptive predictive control of traffic lights for multiple interconnected intersections

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Science China(Information Sciences) 2023年第9期66卷 98-99页

作者： Xinfeng RU Chenyi MEI Weiguo XIA Peng SHI Key Laboratory of Intelligent Control and Optimization for Industrial Equipment(Dalian University of Technology) Ministry of Education School of Electrical and Electronic Engineering The University of Adelaide Research and Innovation Centre Obuda University

Over the last few decades, urban traffic congestion has been an out-of-control issue globally. Several well-known micromodeling traffic control strategies have been developed for traffic light control. Previous work [... 详细信息

关键词： Fuel economy

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Learning-Based Predictive control of Switched Nonlinear Systems via Koopman Modeling Approach

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Journal of Systems Science & Complexity 2025年第2期38卷 691-716页

作者： NING Zepeng FANG Xu LI Yibei XIE Lihua School of Electrical and Electronic Engineering Nanyang Technological University Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences

This paper proposes a data-driven learning-based approach to predictive control for switched nonlinear systems subject to state and control constraints and external stochastic disturbances. A switched Koopman modeling framework is developed, where a multi-mode neural network for state lifting is trained simultaneously with Koopman operators and state reconstruction matrices for all *** framework facilitates the construction of the switched linear Koopman model in a transformed space and effectively captures the dynamics of the original nonlinear system. A switched predictive control strategy is then designed to regulate the switched Koopman model with constrained states and control inputs against both the stochastic disturbances and the uncertainties introduced by the lifting neural network. The proposed control scheme ensures mean-square stability and guarantees boundedness during the online phase. Furthermore, boundedness analysis is performed to determine the bounded set of the original system state across all admissible switching sequences. The effectiveness of the proposed methodology is demonstrated through a case study of a gene regulatory network.

关键词： Data-driven machine learning model predictive control stochastic systems switched Koopman model switched nonlinear systems

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