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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41-50 订阅

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ADHDP-Based Housing Energy Management For Two Housing Units With Mobile Storage 9

ADHDP-Based Housing Energy Management For Two Housing Units ...

引用

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

作者： Xue, Jiguang Yan, Chunsheng Liu, Lu Wang, Jiahan Zhao, Xuliang Wang, Xin State Grid Liaoning Elect Power Co Ltd Elect Power Res Inst Shenyang 110006 Peoples R China LiaoNing Elect Power Dev Stock Co LTD Shenyang 110006 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

ISBN: (纸本)9781728159225

In this paper, a new optimal learning control scheme for discrete-time nonlinear systems using iterative adaptive dynamic programming (ADP) approach is developed to obtain the optimal control law for two-house energy systems. First, the operation modes of the battery are analyzed, and the problem statement is carried out. Next, according to the data of the users, action dependent heuristic dynamic programming (ADHDP) is developed to obtain the optimal control law. Numerical results are given to illustrate the performance of the present method.

关键词： Battery electric vehicle optimal control adaptive dynamic programming battery management

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Formation tracking for discrete-time multi-agent system with unknown dynamics by using adaptive finite rational orthogonal basis functions 9

Formation tracking for discrete-time multi-agent system with...

引用

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

作者： Ge, Yu Fang, Yong Sheng, Zhichao Shanghai Univ Shanghai Inst Adv Commun & Data Sci Key Lab Specialty Fiber Opt & Opt Access Networks Joint Int Res Lab Specialty Fiber Opt & Adv Commu Shanghai 200444 Peoples R China

ISBN: (纸本)9781728159225

this paper considers iterative learning control (ILC) for formation tracking problem of discrete-time multi-agent system with unknown system dynamics. It is assumed that each agent has its own system dynamics. thus, the unknown system dynamics and information interaction between multi-agent make formation tracking difficult to achieve. In this paper, we utilize the adaptive Fourier decomposition (AFD) algorithm to approximate the system parameters only with input and output data. then a learning control scheme is proposed with estimated system dynamics. Simulations show trajectories of multi-agent are tracked precisely after a certain number of iterations.

关键词： ILC multi-agent unknown system dynamics adaptive Fourier decomposition

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learning rule with fractional-order average momentum based on Tustin generating function for convolution neural networks 9

Learning rule with fractional-order average momentum based o...

引用

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

作者： Jian, Jing Gao, Zhe Kan, Tao Liaoning Univ Sch Math Shenyang 110036 Peoples R China Liaoning Univ Coll Light Ind Shenyang 110036 Peoples R China

ISBN: (纸本)9781728159225

In this paper, we propose a fractional-order average momentum (FOAM) method based on Tustin generating function to train parameters in convolution neural networks. Taking the classical data set MNIST as the training and testing data, the effectiveness of the FOAM for CNNs is verified. the experimental results show that the stochastic gradient descent method based on FOAM can improve the recognition accuracy and learning convergence speed of convolution neural networks.

关键词： Convolutional neural networks fractional-order average momentum parameter updating stochastic gradient descent method

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Optimal Predictive Delay Compensation for Robot Networked control System 9

Optimal Predictive Delay Compensation for Robot Networked Co...

引用

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

作者： Chen, Dihan Liu, Xia Xihua Univ Sch Elect Engn & Elect Informat Chengdu 610039 Peoples R China

ISBN: (纸本)9781728159225

In order to solve the problem of random delay in robot networked control system, an optimal predictive compensation control method is designed. the state observer is used to observe the joint position information of the robot at the current time, and it is sent to the control predictive generator. the predictive generator forecasts and calculates the control input at the later time, and optimizes the predictive result of the control input by rolling optimization. Finally, simulations are conducted on a two-joint robot networked control system. the simulation results show that the method can effectively compensate for the influence of random delay and packet disorder on the position tracking performance of the system.

关键词： robot networked control system random delay state observer predictive compensation rolling optimization

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A Simplified data-driven Optimal Iterative learning control based on Iterative Extended State Observer 9

A Simplified Data-driven Optimal Iterative Learning Control ...

引用

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

作者： Ai, Wei Lin, Peilin Li, Xiangyang South China Univ Technol Sch Automat Sci & Engn Guangzhou 510641 Peoples R China

ISBN: (纸本)9781728159225

Inspired by Active Disturbance Rejection based Iterative learning control (ADR-ILC) and data-driven Optimal Iterative learning control (DDOILC), this paper proposes a simplified data-driven optimal iterative control method based on iterative extended state observer (IESO). Accurate estimation of the system uncertainties is observed by IESO during the iterative process. though considering the uncertainties on iterative dynamic linearization method, it is not needed to deduce a new form of the original iterative pseudo partial derivative (PPD). IESO, undertaking as the tool to estimate the whole uncertainties, is added into the DDOILC control law as a separate part. the whole control law is more intuitive and concise than other IESO based DDOILC method which has modified PPD updating law and control law. At the same time the variable gain control mechanism makes the proposed method demonstrate superiority over ADR-ILC in the case of strong nonlinearity. Simulation shows it that can achieve better performance than DDOILC and the other IESO based DDOILC.

关键词： Active disturbance rejection control Iterative extended state observer data-driven control Iterative learning control

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Closed-Loop Pitch Attitude control of Biomimetic Robotic Fish 9

Closed-Loop Pitch Attitude Control of Biomimetic Robotic Fis...

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

作者： Zhang, Yujie Li, Zonggang Du, Yajiang Lanzhou Jiaotong Univ Sch Mech Engn Lanzhou Peoples R China Lanzhou Jiaotong Univ Robot Inst Lanzhou Peoples R China

ISBN: (纸本)9781728159225

this paper considers the pitch control of a robotic fish with three degree-of-freedom(DOF) pectoral fins, wire-driven flexible body and a passive caudal fin. the linear model with undetermined parameters is first suggested to describe the dynamics of the pitch angles, which are the control parameters to adjust the posture of robotic fish. then, a control network based on Central Pattern Generators(CPGs) is proposed to separately adjust the state of each DOF. Finally, a compound controller is designed to adjust the amplitudes of pectoral Fins such that the desired pitch angle is tracked, in which an adaptive law combined with RBF neural network is proposed to estimate the undetermined parameters. the stability of the proposed algorithm is proved and then the validity is investigated by the simulation results.

关键词： Biomimetic robotic fish CPG pitch attitude control adaptive control RBF neural network

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data driven control for a Class of Nonlinear systems with Stochastic Fading Channels 9

Data Driven Control for a Class of Nonlinear Systems with St...

引用

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

作者： Yu, Wei Bu, Xuhui Yin, Yanling Liang, Jiaqi Henan Polytech Univ Sch Elect Engn Jiaozuo 454000 Henan Peoples R China

ISBN: (纸本)9781728159225

this paper investigates the data driven model free adaptive control (MFAC) problem for a class of non-affine nonlinear systems with stochastic fading channels. Firstly, the phenomenon of signal fading is regarded as an independent stochastic process occurring at the output side, which has known mathematical expectations. Using an innovative linearization method, the considered non-affine system is converted into a linear model with a time-varying parameter called PPD and the MFAC controller is redesigned by utilizing the faded outputs. the stability of the system is analyzed rigorously and the influence of incomplete signal transmission on system convergence is explored. Finally, a numerical example shows the validity of the presented strategies.

关键词： data driven model free adaptive control fading channels stability analysis

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A Pattern-moving-Based data-driven control Method for a Kind of Industrial Production Processes 9

A Pattern-moving-Based Data-driven Control Method for a Kind...

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

作者： Li, Xiangquan Xu, Zhengguang Wang, Mushu Cui, Jiarui Yang, Xu Univ Sci & Technol Beijing Sch Automat & Elect Engn Beijing 100083 Peoples R China Minist Educ Key Lab Knowledge Automat Ind Proc Beijing 100083 Peoples R China Shandong Jiaotong Univ Sch Informat Sci & Elect Engn Jinan 250357 Peoples R China

ISBN: (纸本)9781728159225

Due to the existence of a kind of industrial production process which is too complex to determine the model structure and identify the system parameters, a data-driven control method is proposed based on pattern moving. First of all, the way of system dynamics description based on pattern moving is introduced. then, according to the mentioned way a pattern-moving-based model free adaptive control (PMFAC) algorithm is put forward, and pseudo orders of the PMFAC algorithm are identified by using the conditional entropy of output classes. At last, simulation results demonstrate the feasibility and effectiveness of proposed data-driven control method.

关键词： Pattern moving data-driven control pseudo orders identification model free adaptive control

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On the Cumulative Number of Confirmed Cases of 2019-nCoV which Based on data-driven Concepts 9

On the Cumulative Number of Confirmed Cases of 2019-nCoV whi...

引用

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

作者： Wang, Xuan Yang, Zhihui Anhui Univ Finance & Econ Bengbu 233000 Peoples R China

On the basis of data-driven, this paper fitted two models of different states which according to the initial data of China9;s fight against COVID-19 epidemic. Depending on the stage of the outbreak, we applied the ... 详细信息

ISBN: (纸本)9781728159225

On the basis of data-driven, this paper fitted two models of different states which according to the initial data of China's fight against COVID-19 epidemic. Depending on the stage of the outbreak, we applied the two models to predict the cumulative number of confirmed covid-19 cases in the United States and Italy in the early stages of the outbreak. In the early days of the outbreak, the number of confirmed cases in the United States is expected to reach 250000 to 300,000. And if the control measures are effective, there is a high probability that the number of confirmed diagnoses in Italy will not exceed 210,000. Unity can put the difficult away. We should believe that only when countries respect each other and strengthen cooperation can they finally defeat the epidemic.

关键词： data driven Philosophy 2019-nCoV Non-linear Fitting Logistic Function

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data Analysis and Practical Strategies on Opioid Crisis 9

Data Analysis and Practical Strategies on Opioid Crisis

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

作者： Yang, Donghao Yang, Zhihui Huaibei Normal Univ Sch Math Sci Huaibei 235000 Peoples R China Anhui Univ Finance & Econ Sch Stat & Appl Math Bengbu 233030 Peoples R China

ISBN: (纸本)9781728159225

In view of the time-dependent spread and characteristics of synthetic opioids and heroin reported between five states and their counties in the US, aiming at the correlation analysis between opioid-like use and the social and economic data of the US census, the optimal C5.0 algorithm and data flow network model are used to model the decision tree, and the quantitative results of the related factors of opioid-like use are obtained. We try to simplify the model, making the whole process clear, easy to understand. the practices described herein provide one set of practical strategies and tools for potential use.

关键词： Opioid community discovery algorithm priori algorithm Python

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