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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21-30 订阅

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data-driven-Based Distributed Security control for Vehicle-Following Platoon 9

Data-Driven-Based Distributed Security Control for Vehicle-F...

引用

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

作者： Che, Weiwei Deng, Chao Liu, Dan Qingdao Univ Inst Complex Sci Qingdao 266071 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

ISBN: (纸本)9781728159225

this paper proposes a data-driven-based distributed security control approach for vehicle-following platoons in the presence of denial-of-service attacks. First, distributed resilient observers are designed to estimate the trajectories of the leader-vehicle. Based on the developed observers, data-driven controllers are proposed for the vehicle-followers. Specifically, a datadriven approach is introduced to identify controller parameters without relying on the knowledge of system dynamics. Finally, a vehicle-following platoon example is provided to demonstrate the effectiveness of the data-driven-based distributed security control method.

关键词： data-driven control Distributed security control Vehicle-following platoon DoS attacks

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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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Iterative learning control for Multiple Time-Delays Discrete systems in Finite Frequency Domain 9

Iterative Learning Control for Multiple Time-Delays Discrete...

引用

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

作者： Li, Xiaohui Shen, Jianqiang Tao, Hongfeng Hao, Shoulin Jiangnan Univ Minist Educ Key Lab Adv Proc Control Light Ind Wuxi 214122 Jiangsu Peoples R China

ISBN: (纸本)9781728159225

this paper developes iterative learning control scheme and the stability conditions for multiple time-delays discrete system. By formulating the problem over repetitive process form using 2D theory, sufficient stability conditions for multiple timedelays discrete system are developed along the trial, which guarantees the trial-to-trial error monotonic convergence. Moreover, the generalized Kalman-Yakubovich-Popov (KYP) lemma allows the iterative learning control scheme to develope stability conditions with LMI constraints and analyze in the finite frequency domain. A numerical simulation for multiple time-delays discrete system is given to verify the proposed method.

关键词： Multiple Time-Delays Repetitive Process KYP Lemma Iterative learning control

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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...

引用

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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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...

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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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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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Model Free Adaptive Pitch control of a Flapping Wing Micro Aerial Vehicle with Input Saturation 9

Model Free Adaptive Pitch Control of a Flapping Wing Micro A...

引用

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

作者： Wang, Tianhe Jin, Shangtai Hou, Zhongsheng Beijing Jiaotong Univ Sch Elect & Informat Engn Beijing 100044 Peoples R China Qingdao Univ Sch Automat Qingdao 266071 Peoples R China

ISBN: (纸本)9781728159225

In this paper, the dynamics of a flapping wing micro aerial vehicle is analyzed. Aiming at the difficulty of controller design caused by the nonlinearity, time-varying and strong coupling characteristics of the micro aerial vehicle, a full form dynamic linearization based model free adaptive control scheme (FFDL-MFAC) is presented to realize the pitch control of the controlled vehicle. In addition, a compensator is introduced to overcome the control input saturation caused by the limitation of the actuator. Simulation results are provided to demonstrate the effectiveness of the proposed MFAC.

关键词： Model free adaptive control flapping wing micro aerial vehicle pitch angle control input saturation

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Event-Triggered Consensus Output Tracking Strategy for Multiagent systems Utilizing Model-Free Adaptive control 9

Event-Triggered Consensus Output Tracking Strategy for Multi...

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

作者： Song, Weizhao Feng, Jian Northeastern Univ Coll Informat Sci & Engn Shenyang 110819 Liaoning Peoples R China

ISBN: (纸本)9781728159225

In this article, a model-free-adaptive-control-based (MFAC-based) event-triggered (ET) consensus output tracking problem for multiagent systems (MASs) is investigated. the dynamic models of agents are unknown, and only a subset of agents can acquire the reference trajectory. the consensus tracking algorithm is designed by the real-time input/output data and pseudo-partial-derivative (PPD), which is an important parameter of MFAC approach. An output observer is built to design the centralized ET mechanism. then, the boundedness analysis that the tracking error is uniformly ultimately bounded (UUB) is given. Finally, a simulation experiment is provided to verify the feasibility of the ET consensus output tracking strategy for MASs.

关键词： Model free adaptive control (MFAC) Multiagent systems (MASs) Event-triggered (ET) Consensus output tracking

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Bagging-ELM Model for Heating Furnace thermal Efficiency Prediction 9

Bagging-ELM Model for Heating Furnace Thermal Efficiency Pre...

引用

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

作者： Shang, Kai Zeng, Xianglong Dong, Xiaorui Shengli Coll China Univ Petr Qingdao 257061 Shandong Peoples R China China Huanqiu Contracting & Engn Beijing Co Ltd Beijing 100012 Peoples R China

ISBN: (纸本)9781728159225

thermal efficiency is a very important index for heating furnace in chemical industry. In order to predict the complicated variables, the Bagging-ELM network based on ensemble learning and Extreme learning Machine is adopted. the proposed model is applied to predicting the net hourly electrical energy output in Combined Cycle Power Plant data set and the thermal efficiency of the heating furnace. there is a comparison between the results generated by Bagging-ELM model and those generated by BP model, RBF model, ELM model. Compared with other models, the Bagging-ELM can obtain higher accuracy and stability.

关键词： ELM Ensemble learning Heating furnace thermal efficiency

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