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检索条件"任意字段=8th IEEE Data Driven Control and Learning Systems Conference, DDCLS 2019"

共 336 条记录，以下是81-90 订阅

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An incremental conductance method based on fuzzy control 8

An incremental conductance method based on fuzzy control

引用

8th ieee data driven control and learning systems conference, ddcls 2019

作者： Qin, Guangjian Che, Xiaofei College of Information Science and Engineering Northeastern University Shenyang110819 China

ISBN: (纸本)9781728114545

In order to make full use of solar energy in photovoltaic power generation system, maximum power point tracking (MPPT) is usually required. However, traditional incremental conductance method (INC) with fixed step size can't balance both tracking speed and tracking accuracy, and misjudgment may occur when the environment changes abruptly. To solve the above problems, this paper proposes an incremental conductance method based on fuzzy control. In this method, to track the maximum power point quickly and accurately, the fuzzy controller can adjust the step size automatically according to the information of voltage and power. In addition, we make full use of the fuzzy control rules to improve the anti-interference ability of the system. Finally, a simulation is carried out in Matlab/Simulink. the results show that this method can achieve MPPT quickly and accurately, which has a strong anti-interference ability. © 2019 ieee.

关键词： Fuzzy control

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PID-compensated ANN inverse control with application in superheated steam temperature control of supercritical boiler unit 8

PID-compensated ANN inverse control with application in supe...

引用

8th ieee data driven control and learning systems conference, ddcls 2019

作者： Ma, Liangyu Yan, Meng Wang, Yongjun School of Control and Computer Engineering North China Electric Power University Baoding071003 China

ISBN: (纸本)9781728114545

Considering the nonlinearity, large inertia and large time delay of superheated steam temperature system of the supercritical boiler unit, the nonlinear dynamic neural network inverse models of superheated steam temperature water-spray desuperheating system were established, and the historical operation data of the unit were used to train and verify the models. Based on the trained models, neural network inverse controllers with PID compensation links were constructed, and a real-time control program was programmed in MATLAB. With the full-scope simulation system of the 600MW supercritical unit, the superheated steam temperature control simulation tests were carried out under setpoint value disturbance and continuous variable load disturbances. the results show that the neural network inverse control scheme with PID compensation can effectively reduce the control deviation of superheated steam temperature and greatly shorten the process stabilization time. © 2019 ieee.

关键词： Real time control

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Iterative learning control with optimal learning gain for recharging of Lithium-ion battery 8

Iterative learning control with optimal learning gain for re...

引用

8th ieee data driven control and learning systems conference, ddcls 2019

作者： Wang, Chaolun Xiao, Tengfei Li, Xiao-Dong School of Electronics and Information Technology Sun Yet-Sen University Guangzhou510275 China School of Data and Computer Science Sun Yet-Sen University Guangzhou510275 China

ISBN: (纸本)9781728114545

Lithium-ion battery has been widely used by the virtue of its high energy density and longevity. It is required that the lithium-ion battery ought to be recharged and discharged with the guarantee of safety and reliability in the applications. In this paper, a P-type iterative learning control (ILC) algorithm is introduced to manage the charging process of lithium-ion battery described by the equivalent circuit model as a special case of non-linear distributed parameter system. For practical implementations, the monotone convergence is analyzed and guaranteed in the sense of Lebesgue-p norm. Furthermore, an optimal learning gain is selected in order to achieve rapid convergence speed. A practical simulation using parameters identified by real lithium-ion battery is built up to verify the effectiveness of proposed control scheme. © 2019 ieee.

关键词： Lithium-ion batteries

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Performance assessment of non-Gaussian systems based on double error entropy minimization 8

Performance assessment of non-Gaussian systems based on doub...

引用

8th ieee data driven control and learning systems conference, ddcls 2019

作者： Zhang, Han Zhou, Jinglin Wang, Jing College of Information Science Technology Beijing University of Chemical Technology Beijing100029 China

ISBN: (纸本)9781728114545

Due to the existence of non-Gaussian interference in practical industry, more and more people are studying the parameter identification of non-Gaussian systems. Some results have been achieved. In this paper, a new double error entropy minimization algorithm is proposed for parameter identification of non-Gaussian systems. the algorithm is improved on the basis of the EDA algorithm and the Fixed-Point MEE algorithm. the simulation results show that the proposed algorithm can not only improve the accuracy of parameter identification but also estimate the required interference distribution. the algorithm has been successfully applied to the performance assessment of non-Gaussian systems and achieved good results. © 2019 ieee.

关键词： Errors

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Nonlinear variational bayesian factor regression for inferential sensor modeling 8

Nonlinear variational bayesian factor regression for inferen...

引用

8th ieee data driven control and learning systems conference, ddcls 2019

作者： Yang, Zeyu Ge, Zhiqiang Shao, Weiming Yao, Le College of Control Science and Engineering Zhejiang University Hangzhou310027 China

ISBN: (纸本)9781728114545

Inferential sensors are mathematical methods to describe the dependence of quality-related variables called primary variables on those easy-to-measure variables called secondary variables. For majority complex cases in biological and chemical industrial processes with especially nonlinear characteristics, traditional VBFR-based inferential sensor method may not function well because of its linearity assumption on the process data. To tackle the issue that nonlinear relationships exist between input and output variables, an enhanced nonlinear variational Bayesian factor regression (NVBFR) approach is proposed for inferential sensing. On the basis of the probabilistic modeling method, with incorporation of nonlinear mapping, this paper aims to extend the linear probabilistic inferential sensor into the nonlinear form. To evaluate the feasibility and efficiency of the developed Inferential sensors, a real industrail process example is demonstrated. © 2019 ieee.

关键词： Regression analysis

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Design of internal model control oriented PID for typical thermal processes in combined cycle unit 8

Design of internal model control oriented PID for typical th...

引用

8th ieee data driven control and learning systems conference, ddcls 2019

作者： Yang, Hongqiang Zeng, Fanfei Jiangsu Electric Power Co. Ltd. China Energy Investment Corporation Nanjing China Beijing Guodian Zhishen Control Technology Co. Ltd. Beijing Engineering Technology Research Center of Power Station Automation Beijing102200 China

ISBN: (纸本)9781728114545

the internal model control oriented PID control law was proposed for typical thermal processes in the combined cycle unit, and the corresponding parameters tuning approach is also put forward. First of all, the internal model control law is employed to derive a PID parameters tuning approach for the typical thermal processes in the combined cycle unit. Secondly, three different parameters tuning approaches of the PID controller are derived by approximating the pure delay element of the controlled process in three different ways. In addition, the robustness of the closed loop system with the proposed approaches is theoretically analyzed and compared in detail. then, extensive simulation examples are presented to validate the effectiveness of the proposed approaches. Finally, conclusions are given and future research directions are also pointed out. © 2019 ieee.

关键词： Closed loop systems

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Vehicles detection of traffic flow video using deep learning 8

Vehicles detection of traffic flow video using deep learning

引用

8th ieee data driven control and learning systems conference, ddcls 2019

作者： Lou, Lu Zhang, Qi Liu, Chunfang Sheng, Minglan Zheng, Yu Liu, Xuan College of Information Science and Engineering Chongqing Jiaotong University Chongqing400074 China Chongqing Vocational College of Transportation Department of Rail Transit Engineering Chongqing402247 China

ISBN: (纸本)9781728114545

the vehicle detection and tracking are important tasks in intelligent transportation system. the traditional methods of vehicle detection often cause the coarse-grained results due to suffering from the complex environments. YOLO is a pragmatic approach to multi-target detection with a simple and effective algorithm. this paper use YOLO to detect the moving vehicles and use a modified Kalman filter algorithm to dynamically track the detected vehicles, achieving overall competitive performance in day or night. the experimental results show the method is robust to occluding vehicles or congested roads and can obtain 92.11% average accuracy of vehicle counting at 2.55 fps speed. © 2019 ieee.

关键词： Kalman filters

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SocialRT: A recommendation method based on social trust 8

SocialRT: A recommendation method based on social trust

引用

8th ieee data driven control and learning systems conference, ddcls 2019

作者： Xing, Xing Meng, Zhixin Chu, Hanting Luo, Jianyan Qu, Tiansheng Jia, Zhichun Key Laboratory of Digital Publishing Big Data Mining Governance and Presentation Technology Standard Bohai University Jinzhou121013 China School of Information Science and Technology Bohai University Jinzhou121013 China

ISBN: (纸本)9781728114545

With the advent of online social networks, the approach of recommendation based on social network has emerged. However, some recommendation algorithms based on the trust network do not fully mine the information of user's trust relationships. To alleviate such problems, we propose a socialRT method, which is a social recommendation trust method based on joint matrix decomposition. the proposed socialRT method collective factorizes the following relationship matrix and the social trust relationship matrix to obtain the recommendation model. We have conducted experiments on Sina Weibo dataset, the experimental results demonstrate that the proposed recommendation method leads to a substantial increase in recommendation quality. © 2019 ieee.

关键词： Social networking (online)

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Active disturbance rejection control of ship course based on deep belief network 8

Active disturbance rejection control of ship course based on...

引用

8th ieee data driven control and learning systems conference, ddcls 2019

作者： Qin, Beibei Chen, Zengqiang Sun, Mingwei Sun, Qinglin College of Artificial Intelligence Nankai University Tianjin300350 China Key Laboratory of Intelligent Robotics of Tianjin Tianjin300350 China

ISBN: (纸本)9781728114545

All ships are inherently under the influence of various uncertainty and disturbances during the voyage. It is unavoidable for ships to exhibit nonlinearity due to the variation of parameters caused by disturbances such as wind, wave and current. Besides, the changes of loading, speed and draft depth also change the parameters, which performs internal uncertainty. Both nonlinearity and uncertainty of the ship model make it difficult to design a controller. To solve this problem, an adaptive active disturbance rejection controller (ADRC) based on deep belief network (DBN) is proposed. the controller takes advantage of DBN's effective deep learning ability to learn the main control parameters of ADRC online. the simulation results show that the adaptive ADRC controller has better tracking performance, better control effect and stronger robustness than traditional linear ADRC controller. © 2019 ieee.

关键词： controllers

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Adaptive neural control for a class of uncertain nonlinear systems with input delay 8

Adaptive neural control for a class of uncertain nonlinear s...

引用

8th ieee data driven control and learning systems conference, ddcls 2019

作者： Liu, Siwen Wang, Huanqing Kang, Shijia School of Mathematics and Physics Bohai University Jinzhou121000 China

ISBN: (纸本)9781728114545

this paper proposes a control scheme for a class of non-strict-feedback systems with input delay based on adaptive neural network technology. An appropriate auxiliary system is utilized to cope with the difficulties appeared in input delay. through the utilization of backstepping, a controller based on adaptive neural network technique is proposed in this paper. the controller design enables the states in the system to be bounded. the main significance of this research is that an intelligent control scheme is extended to a class of nonlinear systems with non-strict-feedback form and input delay. Finally, an example is given to prove the effectiveness of the control method. © 2019 ieee.

关键词： Backstepping

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