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检索条件"任意字段=9th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2020"

共 506 条记录，以下是201-210 订阅

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Observer-Based Adaptive Multi-dimensional Taylor Network control for Nonlinear systems with Time-Delay 9

Observer-Based Adaptive Multi-dimensional Taylor Network Con...

引用

9th ieee data driven control and learning systems conference (ddcls)

作者： Chu, Lei Zhang, Shuhua Wang, Mingxin Zhu, Shanliang Han, Yuqun Qingdao Univ Sci & Technol Sch Math & Phys Qingdao 266061 Peoples R China Qingdao Univ Sci & Technol Coll Electromech Engn Qingdao 266061 Peoples R China Minist Educ Key Lab Measurement & Control Complex Syst Engn Nanjing 210096 Peoples R China Qingdao Univ Sci & Technol Res Inst Math & Interdisciplinary Sci Qingdao 266061 Peoples R China

ISBN: (纸本)9781728159225

In this paper, an observer-based adaptive Multi-dimensional Taylor network (MTN) controller is proposed for strictly feedback nonlinear systems with time-delay and unmeasurable states. MTNs are utilized to approximate the unknown and desired control input signals directly instead of the unknown nonlinear functions. Moreover, a linear state observer is designed for estimating the unmeasured states. Based on the backstepping technique, a novel adaptive MTN control strategy with simple structure and good real time property is proposed. the designed controller can guarantee all the signals of the closed-loop system are bounded and the tracking error converges to a small neighborhood of the origin. Simulation results are given to demonstrate the effectiveness of the proposed method.

关键词： Multi-dimensional Taylor network Nonlinear systems Adaptive control Output-feedback Backstepping

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A data Reconstruction Method based on Adversarial Conditional Variational Autoencoder 9

A Data Reconstruction Method based on Adversarial Conditiona...

引用

9th ieee data driven control and learning systems conference (ddcls)

作者： Ren, Yifu Liu, Jinhai Zhang, Jianan Jiang, Lin Luo, Yanhong Northeastern Univ Sch Informat Sci & Engn Shenyang 110004 Peoples R China

ISBN: (纸本)9781728159225

Aiming at the problem of sample missing for magnetic flux leakage (MFL), a data reconstruction method based on conditional autoencoder (CVAE) and generative adversarial networks (GAN) is proposed. this method combines the advantages of CVAE and GAN, and generates high-quality samples steadily. the proposed CVAE-GAN method can not only reconstruct the missing MFL samples, but also generate a large amount of real and diverse defect sample, which solves the problem of low accuracy of the defect detection model due to insufficient samples and lack of diversity of samples. the defect sample are collected from the domestic in-service oil pipelines in experiments. the experimental results illustrate that the proposed method can effectively generate high-quality samples.

关键词： Magnetic Flux Leakage data Reconstructing Generative Adversarial Networks Conditional AutoEncoder

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Generative Independent Component thermography for Improved Defect Detection of Carbon Fiber Composites 9

Generative Independent Component Thermography for Improved D...

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9th ieee data driven control and learning systems conference (ddcls)

作者： Liu, Kaixin Chen, Meili Wang, Zhiwen Yao, Yuan Yang, Jianguo Liu, Yi Zhejiang Univ Technol Inst Proc Equipment & Control Engn Hangzhou 310023 Peoples R China Hangzhou Arcvideo Technol Co Ltd Hangzhou 310012 Peoples R China Liming Vocat Univ Coll Mat & Chem Engn Quanzhou 362000 Peoples R China Natl Tsing Hua Univ Dept Chem Engn Hsinchu 30013 Taiwan

ISBN: (纸本)9781728159225

As one of the popular techniques for non-destructive evaluation, infrared thermography often requires the assistance of data analysis models to help defect detection and identification. A novel generative independent component thermography (GICT) framework for defect detection in polymer composites is proposed. It utilizes a deep convolutional generative adversarial network to generate more informative images, which enhances the diversity of thermography data. the defect detection performance of sequential ICT-based thermographic data analysis can be enhanced. the feasibility of GICT is illustrated with its application to the defect detection of a carbon fiber reinforced polymer specimen.

关键词： non-destructive evaluation deep learning generative adversarial network independent component thermography carbon fiber reinforced polymer

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An Edge-Cloud Synergy Integrated Security Decision-Making Method for Industrial Cyber-Physical systems 9

An Edge-Cloud Synergy Integrated Security Decision-Making Me...

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9th ieee data driven control and learning systems conference (ddcls)

作者： Xing, Hang Zhou, Chunjie Ye, Xinhao Zhu, Meipan Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan Peoples R China

ISBN: (纸本)9781728159225

With the introduction of new technologies such as cloud computing and big data, the security issues of industrial cyber-physical systems (ICPSs) have become more complicated. Meanwhile, a lot of current security research lacks adaptation to industrial system upgrades. In this paper, an edge-cloud synergy framework for security decision-making is proposed, which takes advantage of the huge convenience and advantages brought by cloud computing and edge computing, and can make security decisions on a global perspective. Under this framework, a combination of Bayesian network-based risk assessment and stochastic game model-based security decision-making is proposed to generate an optimal defense strategy to minimize system losses. this method trains models in the clouds and infers at the edge computing nodes to achieve rapid defense strategy generation. Finally, a case study on the hardware-in-the-loop simulation platform proves the feasibility of the approach.

关键词： industrial cyber-physical system (ICPS) edge-cloud synergy decision-making game theory security

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Bipartite Consensus of Second-order Multi-agent systems with Multiple Input Delays 9

Bipartite Consensus of Second-order Multi-agent Systems with...

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9th ieee data driven control and learning systems conference (ddcls)

作者： Chen, Zhongqiu Ye, Hongtao Guo, Junzheng Luo, Wenguang Li, Kene Guangxi Univ Sci & Technol Sch Elect & Informat Engn Liuzhou 545036 Peoples R China Guilin Univ Elect Technol Guangxi Key Lab Automat Detecting Technol & Instr Guilin 541004 Peoples R China Guangxi Univ Sci & Technol Guangxi Key Lab Automobile Components & Vehicle T Liuzhou 545036 Peoples R China

ISBN: (纸本)9781728159225

this study deals with the bipartite consensus problem of second-order multi-agent systems (MASs) with multiple input delays. the main mission is to seek out the maximum permissible time delay of MASs under the condition that each agent has different input delay. Using mathematical analysis methods, the maximum allowable delay of the system is obtained through calculation, which is determined by the maximum eigenvalue of Laplace matrix and control parameters. Simulation shows the validity of the proposed control protocols.

关键词： MASs multiple input delays bipartite consensus

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data-driven Distributed Consensus Filter for a Discrete-time Nonlinear Sensor Network 9

Data-driven Distributed Consensus Filter for a Discrete-time...

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9th ieee data driven control and learning systems conference (ddcls)

作者： Bai, Chuandong Ji, Honghai Wei, Yuzhou Pang, Zhonghua Hou, Zhongsheng North China Univ Technol Sch Elect & Control Engn Beijing 100144 Peoples R China Qingdao Univ Sch Automat Qingdao 266071 Peoples R China

ISBN: (纸本)9781728159225

In this work, a novel data-driven distributed consensus filter (DD-DCF) is proposed based on the dynamic linearization technique (DLT) for a discrete-time nonlinear sensor network. Compared with conventional model-based consensus filters, the proposed method is data-driven merely depending on the input and output (I/O) data from measurements. Both the data-driven system identification (DD-SI) algorithm and the distributed consensus filter state estimation (DCF-SE) algorithm are investigated for a nonlinear sensor network. the theoretical analysis shows the main result of the DD-DCF algorithm in the sensor network. the simulation results verify the effectiveness of the designed approach.

关键词： Dynamic Linearization Technique System Identification State Estimation Distributed Consensus Filter Sensor Network

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An Analytical Discretization Approach to Continuous-time System for Kalman Filter 9

An Analytical Discretization Approach to Continuous-time Sys...

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9th ieee data driven control and learning systems conference (ddcls)

作者： Zhang, Lijun Xu, Jian Li, Yonghua Zhao, Ruoyan Wu, Shenggang Pan, Mengfan Lei, Lei Liu, Jianping Lu, Yi China Xian Satellite Control Ctr Xian 710043 Peoples R China State Key Lab Astronaut Dynam Xian 710043 Peoples R China Southwest Univ Sci & Technol Mianyang 621000 Sichuan Peoples R China

ISBN: (纸本)9781728159225

this paper presents an analytical discretization approach for continuous-time systems. By using the matrix multiplying expression of the state transition matrix and the matrix quadratic form theory, the general discretized model of the system state equation in the time domain is derived. the design of the parameter N is used to ensure the accuracy and robustness of the algorithm. Compared with the traditional methods in deducing the discretization formulas, the proposed method has the advantages of generality and easiness. this method is propitious to the integrated realization of the Kalman filter process for the continuous-time system. Simulation results verify the validity and feasibility of the proposed method.

关键词： Kalman filter Continuous time system Matrix theory Quadratic form

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An adaptive unscented Kalman filter for a nonlinear fractional-order system with unknown order 9

An adaptive unscented Kalman filter for a nonlinear fraction...

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9th ieee data driven control and learning systems conference (ddcls)

作者： Miao, Yue Gao, Zhe Chen, Xiaojiao Liaoning Univ Shool Math Shenyang 110036 Peoples R China Liaoning Univ Coll Light Ind Shenyang 110036 Peoples R China

ISBN: (纸本)9781728159225

In this paper, an unscented Kalman filter (UKF) for a nonlinear fractional-order system (FOS) with the unknown order is proposed. the continuous-time nonlinear FOS is discretized by Grunwald-Letnikov difference, and the corresponding difference equation is obtained. Besides, the augmented vector is presented to establish the augmented equation with respect to the state and fractional-order, and the nonlinear functions in the nonlinear augmented equation are performed by the unscented transform. the state and unknown order are estimated by the proposed adaptive UKF to improve the accuracy of state and order estimations compare with the extended Kalman filter. Finally, two examples are given to verify the effectiveness.

关键词： Nonlinear fractional-order systems unscented Kalman filter unknown order state estimation

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Design of Spatial Repetitive controller with Fractional FIR Filter 9

Design of Spatial Repetitive Controller with Fractional FIR ...

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9th ieee data driven control and learning systems conference (ddcls)

作者： Wang, Bo Huo, Xin Xu, Lu Xu, Zimo Harbin Inst Technol Control & Simulat Ctr Harbin 150080 Peoples R China Beijing Sogou Network Technol CO LTD Beijing 100084 Peoples R China Shanghai Aerosp Control Technol Inst Shanghai 201109 Peoples R China

ISBN: (纸本)9781728159225

Rate turnable is a high precision position servo system. Due to the existence of spatially periodic disturbances, the control accuracy and riding quality of rate turnable are affected. In this paper, the spatial repetitive controller is introduced to reject spatially periodic disturbances. Spatially periodic disturbances of rate turnable system are analyzed. Traditional repetitive controller is talked about and the design method of fractional FIR filter based on window function is given. Based on these, repetitive controller design method of fractional FIR filter based on window function is proposed. However, the speed changes in systems, the period of disturbances also changes. For this problem, the spatial repetitive controller with fractional FIR filter is presented. the simulation results are made to illustrate the effectiveness of the spatial repetitive controller.

关键词： Spatially Periodic Disturbances Fractional FIR Filter Window Function Spatial Repetitive controller

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State of Charge Estimation for Lithium-ion Batteries Based on Adaptive Fractional Extended Kalman Filter 9

State of Charge Estimation for Lithium-ion Batteries Based o...

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9th ieee data driven control and learning systems conference (ddcls)

作者： Li, Shizhong Li, Yan Sun, Yue Zhao, Daduan Zhang, Chenghui Shandong Univ Sch Control Sci & Engn Jinan 250061 Peoples R China

ISBN: (纸本)9781728159225

Battery state of charge (SOC) estimation is crucial for battery management systems to ensure the reliability and safety of electric vehicles. To achieve accurate SOC estimation, the fractional-order model which can accurately describe the diffusion and polarization of batteries is established and parameterized by particle swarm optimization firstly. then, the Kalman filter method that can realize optimal estimation of systems is combined with fractional calculus by utilizing fractional state function. Consequently, the fractional extended Kalman filter (FEKF) is built up, in which an adaptive variance update algorithm is adopted to improve the convergence speed and robustness. Finally, the proposed algorithms are applied to two dynamic working conditions and the experimental results indicate that the adaptive FEKF is efficient and accurate in SOC estimation.

关键词： Lithium-ion battery state of charge fractional-order model particle swarm optimization adaptive extended Kalman filter

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