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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111-120 订阅

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ILC for a Class of Linear Parabolic DPSs with Moving Boundaries 9

ILC for a Class of Linear Parabolic DPSs with Moving Boundar...

引用

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

作者： Zhang, Hai Dai, Xisheng Aslam, Muhammad Shamrooz Wang, Su Guangxi Univ Sci & Technol Sch Elect & Informat Engn Liuzhou 545006 Peoples R China

ISBN: (纸本)9781728159225

this article focuses on the iterative learning control problem of a class of linear parabolic distributed parameter systems, which has the characteristic that the boundaries of the spatial domain change continuously with time. then, the open-loop P-type iterative learning method is used to study the system output tracking problem. through rigorous theoretical analysis, some methods such as the contraction mapping approach and Bellman-Gronwall inequality are used to prove the convergence of the tracking error. Finally, the effectiveness of the algorithm is verified by numerical simulation.

关键词： Distributed parameter systems Moving boundary Iterative learning control Convergence

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On Simulation control System of Automatic Production Line Based on PLC data Drive 9

On Simulation Control System of Automatic Production Line Ba...

引用

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

作者： Yang, Xiaojia Han, Cunwu Liu, Lei Zhang, Xiaoping North China Univ Technol Beijing Key Lab Fieldbus Technol & Automat Beijing 100144 Peoples R China

ISBN: (纸本)9781728159225

With the development of science and technology and the expansion of intelligent manufacturing technology, there are more and more automatic production lines in China, but the overall structure of the automatic production line is complex and the R & D investment cycle is long, resulting in low production efficiency. From the point of view of automatic production line structure and data virtual simulation, this paper studies the simulation control debugging system of automatic production line driven by PLC data. According to PLC data, the developer can carry out virtual commissioning of automatic production line and verify the timing of production line.

关键词： PLC data drive automatic production line simulation control system virtual commissioning

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Comparing the Effectiveness of Two Convolutional Neural Networks Methods on Fault Diagnosis 9

Comparing the Effectiveness of Two Convolutional Neural Netw...

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

作者： Liu, Yinping Li, Junmin Xidian Univ Sch Math & Stat Xian 710071 Peoples R China

ISBN: (纸本)9781728159225

Fault diagnosis is an important branch of modern control system and plays an important role in industrial production. Researchers keep pursuing more convenient and practical methods for fault diagnosis. As data collection becoming more convenient, data-driven methods develops rapidly for their excellent performance, especially the deep learning methods have been a popularity way to fault diagnosis. this paper tries to use two data-driven methods (ResNet-50 and SE-ResNet-50) on fault diagnosis without transfer learning. More uniquely, training data and testing data are collected under different conditions. SE-ResNet-50 achieves the highest accuracy 99.1%, which is better than ResNet-50 obviously. this experiment shows that SE-ResNet-50 achieves good performance without large training samples in fault diagnosis.

关键词： Fault diagnosis data-driven Deep learning Convolutional Neural Networks ResNet-50 SE-ResNet-50

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DNN-based Implementation of data-driven Iterative learning control for Unknown System Dynamics 9

DNN-based Implementation of Data-Driven Iterative Learning C...

引用

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

作者： Li, Junkang Fang, Yong Ge, Yu Wu, Yuzhou 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

As the condition of iterative learning control, it is usually necessary to estimate the parameters of the system model to determine whether the system satisfies the global Lipschitz condition and estimate the upper and lower bounds of the rate of change of the system. However, for systems with unknown dynamics, the data-driven iterative learning control based on system input and output cannot be realized fully. In this paper, using the nonlinear mapping and feature extraction ability of deep learning, only input / output data is used to determine whether the uncertain system satisfies the global Lipschitz condition and estimate the upper and lower bounds of the system's rate of change, so as to realize the iterative learning control of the system. the simulation results verify the validity of estimating whether the system satisfies the ILC condition only based on the input / output data of the system.

关键词： data-driven control iterative learning control deep learning

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data-driven Backstepping control of Chemical Process 9

Data-Driven Backstepping Control of Chemical Process

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

作者： Gao, Jiawen Huang, Jingwen Beijing Univ Chem Technol Beijing 100029 Peoples R China

ISBN: (纸本)9781728159225

Modeling and control design of complex chemical processes are challenge tasks because of their multi-variable, time-delay and non-linear features. On the other hand, the plant dynamics are hard to characterize precisely on line when facing uncertain disturbance. In the light of this, this paper presents a data-driven backstepping control scheme for the nonlinear chemical process. Compared with other regular chemical process control schemes, the proposed scheme is independent of specific mathematical models, and free of decoupling operation, linearization, or off-line recognition and modeling. By constructing Lyapunov function and feedback control rate based on real-time data, the integral stability is guaranteed. Williams-Otto reactor example is provided to demonstrate the effectiveness and applicability of the scheme.

关键词： data-driven Backstepping control Chemical Process Williams-Otto Reactor

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Adaptive learning control for Nonparametric systems with Bouc-Wen Hysteresis Input 9

Adaptive Learning Control for Nonparametric Systems with Bou...

引用

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

作者： Huang, Weigang Cheng, Leiyu Yan, Qiuzhen Cai, Jianping Guan, Xiaohui Zhejiang Univ Water Resources & Elect Power Coll Informat Engn Hangzhou 310018 Peoples R China

ISBN: (纸本)9781728159225

In this paper, an adaptive iterative learning control scheme is propsed for a class of nonparametric systems with hysteresis input described by Bouc-Wen model. First, based on analyzing the property of Bouc-Wen model, the adaptive learning controller is designed by using Lyapunov synthesis. In the control design, the nonparametric uncertainty and hysteresis nonlinearity is compensated by robust strategy and iterative learning strategy together, according to the property of Bouc-Wen model. As the iteration increases, the system state can track its reference signal accurately over the whole period. Numerical results demonstrate the effectiveness of the adaptive learning control scheme.

关键词： Hysteresis Bouc-Wen model adaptive learning control nonparametric uncertainties

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High-order Model-free Adaptive Iterative learning control for Velocity Tracking of Wheeled Mobile Robots 9

High-order Model-free Adaptive Iterative Learning Control fo...

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

作者： Li, Jiawei Chi, Ronghu Yang, Dejing Qingdao Univ Sci & Technol Sch Automat & Elect Engn Qingdao 266061 Peoples R China Shandong JinKaiFeng Machinery Technol Co Ltd Yishui 276400 Peoples R China

ISBN: (纸本)9781728159225

In this paper, a data-driven high-order model-free adaptive iterative learning control (HMFAILC) is developed by a wheeled mobile robots (WMR) for trajectory tracking in the repetitive systems. the design and analysis of the controller only uses the I/O of the system and in the absence of any explicit model information. control performance is improved by using higher-order learning control methods to obtain more control information in the iterative process. the control performance of the control scheme is proved by mathematical analysis and simulation.

关键词： Wheeled mobile robot data-driven method High-order algorithm Iterative learning control

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Hierarchical least squares based iterative algorithms for two-input single-output Hammerstein finite impulse response systems 9

Hierarchical least squares based iterative algorithms for tw...

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

作者： Sha, Liangbin Ji, Yan Qingdao Univ Sci & Technol Sch Automat & Elect Engn Qingdao 266061 Peoples R China

ISBN: (纸本)9781728159225

this paper focuses on the identification problem for finite impulse response systems through using the hierarchical identification principle. Based on the hierarchical identification principle, the hierarchical based least squares iterative algorithm is proposed to estimate the parameters of the two-input single-output Hammerstein finite impulse response systems. Finally, a simulation example is given to test the effectiveness of the proposed algorithm.

关键词： Hammerstein system Iterative method Least squares Parameter estimation

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Iterative learning control algorithm of consensus for discrete-time heterogeneous multi-agent systems with independent topologies 9

Iterative learning control algorithm of consensus for discre...

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

作者： Liu, Xinxin Li, Junmin He, Chao Xidian Univ Sch Math & Stat Xian 710071 Peoples R China

ISBN: (纸本)9781728159225

In this paper, leader-follower consensus problems of a kind of discrete-time heterogeneous multi-agent systems(MASs) with independent topologies are studied by using iterative learning control(ILC) in a repeatable control environment. the heterogeneous multi-agent systems are composed of second-order and first-order dynamic systems, and independent topology refers to the topological structure of velocity and position is different. An iterative learning control algorithm is proposed to solve the exact consensus of discrete-time heterogeneous multi-agent systems with independent topology. A necessary and sufficient condition of the consensus is also given for the MASs. Finally, the simulation example proves the effectiveness of the iterative learning control algorithm.

关键词： multi-agent systems heterogeneous system independent topology iterative control algorithm

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Event-triggered based consensus control for a type of multi-agent systems 9

Event-triggered based consensus control for a type of multi-...

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

作者： Shi, Jiantao Nanjing Res Inst Elect Technol Nanjing 210039 Peoples R China CETC Key Lab Intellisense Technol Nanjing 210039 Peoples R China

ISBN: (纸本)9781728159225

In this note, the consensus control problem has been researched for a type of leader-follower multi-agent systems by using the event-triggered strategy. In order to eliminate continuous information transmission between the neighboring agents or nodes, the consensus controller is constructed by using the estimated state information of neighboring agents instead of their real states. the communication instants are determined by the developed event-triggered strategy to minimize the amount of communication between neighboring agents. A type of error convergence analysis based on Lyapunov function has been provided to prove the bounded convergence of the proposed consensus scheme. Finally, a simulation case is given to verify the effectiveness of the given event-based consensus control strategy.

关键词： multi-agent system leader-follower agents event-triggered strategy

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