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Multisensor fusion estimation of nonlinear systems with intermittent observations and heavy-tailed noises

Science China(Information Sciences) 2022年第09期65卷 173-190页

作者： Bo XIAO Q.M.Jonathan WU Liping YAN School of Artificial Intelligence Beijing University of Posts and Telecommunications Department of Electrical and Computer Engineering University of Windsor Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology

Inspired by the robust student t-distribution based nonlinear filter(RSTNF), a student tdistribution and unscented transform(UT) based filter for state estimation of heavy-tailed nonlinear dynamic systems, a modified RSTNF for intermittent observations is derived. The fusion estimation for nonlinear multisensor systems with intermittent observations and heavy-tailed measurement and process noises is *** this work, the centralized fusion, the sequential fusion, and the na¨?ve distributed fusion algorithms are presented, respectively. Theoretical analysis shows that the presented algorithms are effective, which are the efficient extension of the classical unscented Kalman filter(UKF) or the cubature Kalman filter(CKF) based algorithms with Gaussian noises. Simulation results show that the presented algorithms are effective and feasible.

关键词： state fusion estimation nonlinear systems heavy-tailed noise intermittent observations multivariate t-distribution

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Wearable ubiquitous energy system

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Science China(Information Sciences) 2021年第2期64卷 237-239页

作者： Fang DENG Ning DING Ziman YE Yeyun CAI Jie CHEN School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

In recent years, owing to the growing maturity of Internet of Things technology and mobile communication technology, intelligent wearable devices have developed *** have been widely applied in aviation, medicine, military, entertainment and other fields. Through intelligent wearable devices, people can communicate efficiently, dynamically perceive external environments, and monitor the body's vital signs.

关键词： Information systems and Communication Service

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Stability and Bifurcation control of Fractional BAM Neural Networks with Diffusion and Time Delays

Stability and Bifurcation control of Fractional BAM Neural N...

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Chinese control Conference (CCC)

作者： Feng Liu Wei Wang Gang Cai Feifan Zhou Hua O Wang Xiuqin Yang School of Automation China University of Geosciences Wuhan China Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Department of Mechanical Engineering Boston University Boston MA USA School of Education Minzu University of China Beijing China

Based on fractional calculus theory and reaction-diffusion equation theory, a fractional-order time-delay reaction-diffusion neural network with Neumann boundary conditions is investigated. By constructing the phase space basis based on the Laplace operator eigenvector, the system equation is linearized to obtain the characteristic equation. Then, the characteristic equation is analyzed, and the local stability of the system at the equilibrium point is discussed. And taking the time delay as the bifurcation parameter, the stability changes of the system at the equilibrium point and the generation conditions of the Hopf bifurcation are studied when the time delay changes. Moreover, a state feedback controller is designed to control the bifurcation of the system. Finally, the theoretical derivation is verified by numerical simulation.

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Parallel-Data-Based Social Evolution Modeling

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Tsinghua Science and Technology 2021年第6期26卷 878-885页

作者： Weishan Zhang Zhaoxiang Hou Xiao Wang Zhidong Xu Xin Liu Fei-Yue Wang China University of Petroleum Qingdao 266580China Qingdao Academy of Intelligent Industry Qingdao 266111China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100049China Institute of National Security National Defense UniversityBeijing 100081China

Abnormal or drastic changes in the natural environment may lead to unexpected events,such as tsunamis and earthquakes,which are becoming a major threat to national ***,no effective assessment approach can deduce a situation and determine the optimal response strategy when a natural disaster *** this study,we propose a social evolution modeling approach and construct a deduction model for self-playing,self-learning,and self-upgrading on the basis of the idea of parallel data and reinforcement *** proposed approach can evaluate the impact of an event,deduce the situation,and provide optimal strategies for *** the breakage of a submarine cable caused by earthquake as an example,we find that the proposed modeling approach can obtain a higher reward compared with other existing methods.

关键词： paral el data reinforcement learning decision-making

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Explainable Deep Learning for Semg-Based Similar Gesture Recognition: A Shapley-Value-Based Solution

SSRN

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SSRN 2023年

作者： Wang, Feng Ao, Xiaohu Wu, Min Kawata, Seiichi She, Jinhua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Engineering Tokyo University of Technology Hachioji Tokyo192-0982 Japan

Surface electromyography (sEMG) based gesture recognition shows promise in enhancing human-robot interaction. However, accurately recognizing similar gestures is a challenging task, and the underlying mechanisms of gesture recognition are not well understood. To address these issues, we developed a new solution called the Shapley-value-based similar gesture recognition (SV-SGR) method. Our solution combines deep learning and game theory to achieve high recognition accuracy and interpretability. First, we devised a data preprocessing method that converts sEMG signals into sEMG color images, which can be more effectively utilized by deep learning techniques. Next, we established a deep-neural-network-based model for gesture recognition using the processed sEMG color images. Then, we designed a global explanation approach based on Shapley values to quantify the contribution of each channel to recognizing similar gestures. Finally, we carried out an explanation analysis, which provides feedback on the recognition model to enhance the precision of gesture recognition. Extensive comparisons and interpretable analyses have been conducted on real-world datasets, and the results demonstrate that the SV-SGR method outperforms other baselines under various experimental conditions. The interpretable analysis method based on Shapley values effectively enhances the performance of recognizing similar gestures and provides valuable insights into the decision-making process of recognition models. © 2023, The Authors. All rights reserved.

关键词： Gesture recognition

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Dynamic Analysis and control of Fractional Order Memristor Hopfield Neural Network

Dynamic Analysis and Control of Fractional Order Memristor H...

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Chinese control Conference (CCC)

作者： Feng Liu Gang Cai Feifan Zhou Wei Wang Hua Wang Xiuqin Yang School of Automation China University of Geosciences Wuhan China Engineering Research Center of Ministry of education for intelligent technology of earth exploration Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Department of Mechanical Engineering Boston University Boston MA USA School of Education Minzu University of China Beijing China

In this paper, a novel smooth magnetron is introduced to construct a fractional memristor Hopfield neural network (fractional order M-HNN). The local stability of equilibrium point are analyzed theoretically. Taking the memristor coupling strength coefficient and the fractional order as bifurcation parameters, the phase trajectory diagram, the bifurcation diagram of the system are drawn to analyze the influence on the dynamic behavior of the neural network. When the system parameters are fixed, the hyperchaos phenomenon of the fractional order M-HNN model is revealed. Finally, the PD controller is applied to the model to enhance the stability of the system.

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automation 5.0: The key to systems Intelligence and Industry 5.0

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1723-1727页

作者： Ljubo Vlacic Hailong Huang Mariagrazia Dotoli Yutong Wang Petros A.Ioannou Lili Fan Xingxia Wang Raffaele Carli Chen Lv Lingxi Li Xiaoxiang Na Qing-Long Han Fei-Yue Wang Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith UniversityNathanQLD 4111Australia Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the Qingdao Academy of Intelligent IndustriesQingdao 266114China Department of Electrical Engineering-Systems University of Southern CaliforniaLos AngelesCA 90007 USA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 Beijing Huairou Academy of Parallel Sensing Beijing 101499China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndianapolisIN 46202 USA Department of Engineering University of CambridgeCB21TN CambridgeU.K. School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Dazhou Artificial Intelligence Institute Dazhouand the Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

automation has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with *** rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:***,***,***,***,***,***,***,***,***,***,***,Q.-***,and F.-***,“automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA ***,vol.11,no.8,pp.1723-1727,Aug.2024.

关键词： automation machinery intelligence

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Study on Disturbance Propagation Characteristics of Power Grid and Evaluation of Temporal and Spatial Correlation Characteristics of Voltage Phase Trajectory 41

Study on Disturbance Propagation Characteristics of Power Gr...

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第41届中国控制会议

作者： Yibo Kong Changyou Feng Hongying Yang Liping Yan Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology Xinjiang Electric Power Research Institute of State Grid Xinjiang Electric Power Co. Ltd. National Electric Power Dispatching and Control Center of State Grid Corporation of China China Electric Power Research Institute

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

With the access of large-scale new energy and power electronic equipment,as well as the influence of various random uncertain factors,the analysis and control of dynamic security of large power grids become particularly difficult,so it is of great practical significance to study the disturbance propagation characteristics of complex power *** is an important parameter that affects the security of power systems,and the voltage phase trajectory contains abundant power grid ***,based on the measured data,this paper quantitatively describes the characteristics of dynamic space-time distribution of the voltage,and numerically reveals the different influences of disturbance on different nodes and the characteristics of disturbance ***,the geometric characteristics of the measured voltage phase trajectory are mined,the new trajectory distance is defined,the characteristic trajectory plane is constructed,and the spatio-temporal evolution law of voltage phase trajectory is *** the sequel,through the density-based DBSCAN clustering method,the characteristic tracks of voltage movement are clustered and analyzed,and the temporal and spatial correlation characteristics of voltage movement trends of each node are measured,and the law of disturbance propagation is ***,based on the measured data of IEEE 39-bus system,the simulation analysis is carried out,and the effectiveness of the presented algorithm is verified.

关键词： Disturbance propagation Voltage phase trajectory Temporal and spatial correlation characteristics Trajectory clustering

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A New Total Variation Denoising Algorithm for Piecewise Constant Signals Based on Non-convex Penalty 1

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2nd International Conference on Neural Computing for advanced Applications, NCAA 2021

作者： Lv, Donghao Cao, Weihua Hu, Wenkai Wu, Min School of Automation China University of Geosciences Wuhan430074 China School of Information Engineering Inner Mongolia University of Science and Technology Baotou014010 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China

ISBN: (数字)9789811651885

ISBN: (纸本)9789811651878

Total variation signal denoising is an effective nonlinear filtering method, which is suitable for the restoration of piecewise constant signals disturbed by white Gaussian noises. Towards efficient denoising of piecewise constant signals, a new total variation denoising algorithm based on an improved non-convex penalty function is proposed in this paper. While ensuring the objective function is convex, a new non-convex penalty is designed. The denoising efficiency is improved by updating the dynamic total variational adjustment in the penalty function to the static adjustment. Experimental results demonstrated that the proposed denoising algorithm improved the denoising efficiency without affecting the denoising effect. The overall performance was shown better than the current excellent denoising algorithm. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Efficiency

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An Enhanced Fuzzy Repetitive-control Design and Optimisation Method based on 2D Performance Index 10

An Enhanced Fuzzy Repetitive-Control Design and Optimisation...

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10th IEEE Data Driven control and Learning systems Conference, DDCLS 2021

作者： Zhang, Manli Wu, Min Tian, Shengnan She, Jinhua School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Engineering Tokyo University of Technology Hachioji192-0982 Japan

ISBN: (纸本)9781665424233

This paper concerns the design and optimisation of two-dimensional (2D) repetitive control of nonlinear systems based on the Takagi-Sugeno (T-S) fuzzy model. First, a continuous-discrete 2D model of nonlinear repetitive-control systems based on T-S fuzzy model is constructed by utilizing the 2D characteristics of continuous control and discrete learning actions in the repetitive-control process. Next, a fuzzy Lyapunov-Krasovskii functional derives the linear-matrix-inequality-based stability condition with a low conservatism. Two positive and two nonzero parameters in the fuzzy Lyapunov-Krasovskii functional tune the control and learning actions. Then the particle swarm optimisation algorithm based on a 2D performance index searches for the best parameter combination, resulting in the optimal 2D controller gains. A numerical example is given to demonstrate the effectiveness of the method. © 2021 IEEE.

关键词： Linear matrix inequalities

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