检索结果-内蒙古大学图书馆

2017 International Conference on automation, control and Robots, ICACR 2017

作者： Sarhan, Mohammad Abu Ding, Min Chen, Xin Ou, Yingxiong Wu, Min School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

ISBN: (纸本)9781450363501

This paper presents a maximum power point tracking controller for a PV solar system. The PV solar system is connected to the load through a DC-DC boost converter which is controlled by Adaptive Neuro-Fuzzy Inference System (ANFIS) MPPT controller. The ANFIS controller is modeled by selecting the irradiation and temperature as an input for the controller while the duty cycle is the output of the controller. To demonstrate that the performance of ANFIS MPPT controller gives more accurate results and more efficiency with respect to the measured results, it is compared with Fuzzy Logic (FL) MPPT controller and Neural Network (NN) MPPT controller. The analyzed results and the comparison have been obtained through MATLAB/Simulink Environment. © 2017 Copyright is held by the owner/author(s).

关键词： controllers

来源：评论

学校读者我要写书评

暂无评论

A CUDA-based iterative segmentary parallel Gaussian-kernel function adaptive dynamic programming algorithm 5

A CUDA-based iterative segmentary parallel Gaussian-kernel f...

引用

5th International Workshop on advanced Computational Intelligence and intelligent Informatics, IWACIII 2017

作者： Li, Lu Chen, Xin School of Automation China University of Geosciences Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

Adaptive Dynamic Programming (ADP) with critic-actor structure is a useful way to achieve online learning control. The Gaussian-Kernel Function Adaptive Dynamic Programming (GK-ADP) algorithm does not need to preset the value function model which greatly enhances the applicability of ADP method in continuous space. However, when the complexity of the system increases in practice, the scale of sample set will increase which will induce a high computation cost. In order to speed up computation, a CUDA-Based Iterative Segmentary Gaussian-Kernel Function Adaptive Dynamic Programming algorithm( cuISGK-ADP) is presented in this paper. The algorithm uses singular value decomposition to decompose the large-scale matrix and uses CUDA with multi-threaded structure in order to enhance the performance. The comparison result illustrates that the computation burden which hinders the GK-ADP's application is reduced when the cuISGK-ADP algorithm is introduced. The proposed approach enhances the efficiency of the computation to a large extent.

关键词： Singular value decomposition

来源：评论

学校读者我要写书评

暂无评论

A NSGA-Ⅱ based Peak Load Shifting Optimization Method for Customers with Distributed Generators Considering Time-of-use Price

A NSGA-Ⅱ based Peak Load Shifting Optimization Method for C...

引用

第37届中国控制会议

作者： Hao Zhou Min Ding Bo Hu Qingyi Wang Zhili Tan Danyun li School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System State Grid Energy Research Institute Co. LTD.

With the extensive use of distributed generation, the traditional demand response analysis cannot meet the current *** paper proposes a NSGA-II based peak load shifting optimization method for customers with distributed generators considering time-of-use price. Firstly, a fuzzy classification method divides the daily power into three time segments,peak hours, flat hours and valley hours. Secondly, on the basis of the time-of-use price, a peak load shifting optimization model is built with constraints and the objectives of minimizing the peak load, maximizing the valley load, and minimizing the peakvalley difference. Then, a NSGA-II based optimization method solves the optimal model and obtains the optimal electricity prices of different time segments to shift the peak load and the valley load. Finally, the simulation results shows the effectiveness of the proposed method.

关键词： Distributed Generation Demand Respond Time-of-use Price Multi-objective Genetic Algorithm

来源：评论

学校读者我要写书评

暂无评论

Sinter Product Rate forecasting Based on T-S Fuzzy Model 36

Sinter Product Rate Forecasting Based on T-S Fuzzy Model

引用

第36届中国控制会议

作者： Qi Lei GaiWen Zhao Xin Chen Min Wu School of Information Science and Engineering Central South University School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems

ISBN: (纸本)9781538629185

Through the analysis of sintering process and the relationship between sintering thermal state and sinter product rate, this paper determines the key factors influencing the sinter product rate, and proposes a method of sinter product rate forecasting based on T-S fuzzy model. Based on the extraction of the characteristic parameters of the thermal state of sintering process, the input of the model is determined. Then, the antecedent and the consequent parameters of the forecasting model are identified by the fuzzy c-means(FCM) clustering algorithm and the recursive least squares method(RLS). Finally, the T-S fuzzy model for sinter product rate forecasting is obtained. The proposed forecasting method is of value through the analysis of the forecast ing results. The forecasting results are also compared with the support vector machine(SVM) and the back propagation neural network(BPNN) methods. The results show that the proposed T-S fuzzy model can effectively improve the precision of the sinter product rate forecasting.

关键词： Sinter Product Rate forecasting T-S Fuzzy Model Fuzzy c-means Recursive Least Squares(RLS)

来源：评论

学校读者我要写书评

暂无评论

Street Object Detection Based on Faster R-CNN

Street Object Detection Based on Faster R-CNN

引用

Chinese control Conference

作者： Wendi Cai Jiadie Li Zhongzhao Xie Tao Zhao Kang Lu Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. china The Library of Wuhan University of Technology Wuhan P. R. China

With the increased number of traffic accidents, the research and development of smart cars have been promoted. The detection of street objects has become one of the important research topics. Generic Model detection algorithm based on Convolution Neural Network(CNN) need to design the training model, while the training and testing of the model will take a lot of time. Transfer Learning is used to fine-tune the pre-trained models, using the Image task datasets of COCO, transferring a generic deep learning model to specific one with different weights and outputs. Furthermore, the CNN structure is adjusted to improve overall performance, and the street environment is trained to the special scene. We compare the results of experiments, and the results showed that the network which is fine-tuned is effective.

关键词： Object detection Computer vision Training Proposals Machine learning Automobiles Convolution

来源：评论

学校读者我要写书评

暂无评论

Stability and Neimark-Sacker bifurcation analysis for single gene discrete system with delay

Stability and Neimark-Sacker bifurcation analysis for single...

引用

第37届中国控制会议

作者： Feng Liu Qicheng Mei Fenglan Sun Xinmei Wang Hua O Wang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Research Center of System Theory and Application Chongqing University of Posts and Telecommunications Department of Mechanical Engineering Boston University

The network structure and functional properties of gene regulatory system and their relationships are an important research field in systems *** this paper,a new improved model is proposed based on the study of gene expression *** model takes into account the effect of protein concentration on the gene expression,so as to obtain a new bifurcation point and improve the performance of the *** validity of the model is verified by theoretical analysis and data simulation.

关键词： Stability Neimark-Sacker bifurcation single gene discrete system delay

来源：评论

学校读者我要写书评

暂无评论

Optimal Consensus control of Unknown Nonlinear Multi-Agent systems Using Adaptive Dynamic Programming via MRAC

Optimal Consensus Control of Unknown Nonlinear Multi-Agent S...

引用

Chinese control Conference (CCC)

作者： Hao Fu Xin Chen Wei Wang Jinbin Li Yaodong Zhang Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China State Grid Hubei Electric Power Research Institute Wuhan P. R. China

This paper introduces an optimal consensus control scheme for nonlinear multi-agent systems with completely unknown dynamics. In general, it is difficult to solve the coupled Hamilton-Jacobi-Bellman (HJB) equations, which the optimal consensus control relies on in multi-agent systems, especially unknown nonlinear systems. for the purpose of solving the problem, we propose an optimal consensus control approach based on the model reference adaptive control (MRAC) and adaptive dynamic programming (ADP). Using the structure of the diagonal recurrent neural network, the identifier and controller are devised to achieve MRAC for every plant of the unknown nonlinear systems, i.e. the reference model serves as a dynamic model of each individual agent. Then, according to reference models of distributed agents, an adaptive dynamic programming (ADP) is introduced to approximate the solution of the coupled HJB equations.

关键词： Multi-agent systems Mathematical model Adaptation models Heuristic algorithms Recurrent neural networks Dynamic programming

来源：评论

学校读者我要写书评

暂无评论

intelligent coordinating control between burn-through point and mixture bunker level in an iron ore sintering process

Intelligent coordinating control between burn-through point ...

引用

作者： Du, Sheng Wu, Min Chen, Xin Lai, Xuzhi Cao, Weihua School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems No. 388 Lumo Road Hongshan District Wuhan Hubei430074 China

Sintering is a process that involves complex physical and chemical reactions. An intelligent coordinating control strategy is proposed for the strong coupling between the burn-through point (BTP) and the mixture bunker level (MBL). First, an intelligent integrated controller is established for the BTP by fusing the neural network, expert rules, and fuzzy logic. Moreover, an expert controller is designed for the MBL based on expert rules using the analysis of the main factors that affect the MBL. Furthermore, by employing the soft switching control algorithm, an intelligent coordinating controller for the BTP and the MBL is designed. The optimal operation parameters are obtained from the algorithm, which realize the multi-objective control of the sintering process. Finally, a simulation and an experiment of the intelligent coordinating control between the BTP and the MBL are carried out, where the models of the BTP and the MBL are the Takagi-Sugeno (T-S) fuzzy model and the linear model, respectively. And the results show that the proposed approach is feasible and effective.

关键词： Mixtures

来源：评论

学校读者我要写书评

暂无评论

A threshold segmentation method for non-uniform illumination image based on brightness equalization

引用

IOP Conference Series: Materials Science and Engineering 2019年第5期569卷

作者： Hui Guo Peng Chen Shun Huang Cong Hu Lijun Zhang School of Automation China University of Geosciences Wuhan 430074 China Hubei key laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan 430074 China

In the process of image acquisition, non-uniform illumination images are common due to poor lighting, surface reflection, or a combination of these two factors. In order to improve the quality of image segmentation, an image threshold segmentation method is proposed for non-uniform illumination images. First, the brightness of different regions in the image is compensated to make the brightness background of the whole image consistent. Second, the gradation histogram of the processed image is obtained and simulated into Gaussian distribution curve, then the inflection points of the curve are calculated. Finally, the two inflection points are set as thresholds to segment the image after brightness equalization. This method eliminates the influence of non-uniform illumination to a certain extent and gets a better segmentation effect. Experiments were carried out on images containing several different types of non-uniform illumination. The results demonstrate that the proposed method outperforms the compared enhancement algorithms in threshold segmentation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Research on Image Denoising Method Based on Wavelet Transform

Research on Image Denoising Method Based on Wavelet Transfor...

引用

Chinese control Conference

作者： JunLei Song MeiJuan Chen Chang Jiang YanXia Huang Qi Liu Yuan Meng WenQin Mo KaiFeng Dong Fang Jin China University of Geosciences Wuhan Hubei CN School of Automation China University of Geosciences Wuhan P. R. China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan P. R. China

In the process of image acquisition and transmission, the image always generates noise due to internal and external interference. Noise reduces the quality of the image, and makes it difficult for subsequent image processing. Therefore, image denoising is very important in image processing. Wavelet denoising can effectively filter out noise and retain high-frequency information of the image, this method has the characteristics of fast operation speed and has become an important branch of image denoising. Threshold functions commonly used in wavelet threshold denoising include hard threshold function and soft threshold function. The hard threshold function is not continuous as a whole. Although the soft threshold function has good continuity, there is always a constant deviation between the processed coefficient and the original coefficient when the wavelet coefficient is large. In response to these deficiencies, this paper establishes a new improved threshold function based on traditional soft and hard threshold functions. By processing the thresholds of wavelet coefficients, a reasonable balance between smoothing and edge oscillations can be achieved after image denoising. The improved threshold function not only overcomes the shortcomings of the soft and hard threshold functions, but also provides more flexibility in the processing of image noise. Through MATLAB simulation, the denoising effects of the soft, hard threshold functions and the threshold function constructed in this paper are compared in terms of signal-to-noise ratio (SNR) and root mean square error (MSE). The MATLAB simulation results show that compared with the traditional threshold function, the improved threshold function has a higher signal-to-noise ratio (SNR = 26.27709) and a smaller mean square error (MSE = 153.4579), and it has a good noise reduction effect.

关键词： Wavelet coefficients Noise reduction Image denoising Correlation Signal to noise ratio

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：