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34th Chinese control Conference, CCC 2015

作者： Wei, Jing Qiao, Junfei Qinchao, Meng College of Electronic Information and Control Engineering Beijing University of Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

ISBN: (纸本)9789881563897

This paper proposes an improved non-dominated sorting genetic algorithm (NSGA2)-DNSGA2, with the aim of preserving diversity of obtained optimal solution and avoiding the original NSGA2 algorithm falling into local optimal. The proposed DNSGA2 algorithm which introduces a differential mutation operator to replace the original polynomial mutation because the method of differential local search is helpful to the uniformity of Pareto optimal solution set. The performance of the proposed DNSGA2, NSGA2 and W-LRCD-NSGA2 (Based on left-right crowding distance non-dominated sorting genetic algorithm) are compared via four benchmark functions. Simulation results indicate that the diversity and uniformity of Pareto optimal solution obtained by DNSGA2 are better than the other two algorithms. © 2015 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Differential mutation Multi-objective NSGA2 Pareto optimal solution

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An Improved NSGA2 Algorithm with the Adaptive Differential Mutation Operator

An Improved NSGA2 Algorithm with the Adaptive Differential M...

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第三十四届中国控制会议

作者： WEI Jing QIAO Junfei Meng Qinchao College of Electronic Information and Control Engineering Beijing University of TechnologyBeijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781467374439

This paper proposes an improved non-dominated sorting genetic algorithm(NSGA2)-DNSGA2, with the aim of preserving diversity of obtained optimal solution and avoiding the original NSGA2 algorithm falling into local optimal. The proposed DNSGA2 algorithm which introduces a differential mutation operator to replace the original polynomial mutation because the method of differential local search is helpful to the uniformity of Pareto optimal solution set. The performance of the proposed DNSGA2, NSGA2 and W-LRCD-NSGA2(Based on left-right crowding distance non-dominated sorting genetic algorithm) are compared via four benchmark functions. Simulation results indicate that the diversity and uniformity of Pareto optimal solution obtained by DNSGA2 are better than the other two algorithms.

关键词： Multi-objective,NSGA2,Differential mutation,Pareto optimal solution

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A Human Motion Prediction Algorithm Based on HSMM for SIAT's Exoskeleton

A Human Motion Prediction Algorithm Based on HSMM for SIAT's...

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第35届中国控制会议

作者： Min Wang Xinyu Wu Du-Xin Liu Can Wang Key Laboratory of Human-Machine-Intelligence Synergic Systems Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institutes of Advanced TechnologyChinese Academy of Sciences Department of Mechanical and Automation The Chinese University of Hong Kong

ISBN: (纸本)9781509009107

Getting the exoskeleton pilot's motion intent is very important for exoskeleton *** this paper,a new approach to predict human motion is *** prediction method is based on Hidden Semi-Markov *** orientation of the pilot's segment is collected by the Inertial Measurement *** Adaptive Boosting algorithm is adopted to classify the orientation data into *** sequence of motion labels is inputted into Hidden Semi-Markov Models for motion *** experimental data validate the proposed method.

关键词： Adaptive Boosting Hidden Semi-Markov Model Human Motion Prediction Exoskeleton

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Multiple feature sample classification via joint sparse representation

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Journal of Computational Information systems 2015年第14期11卷 5125-5133页

作者： Zha, Changjun Xu, Tailong Key Laboratory of Machine Vision and Intelligence Control Technology Hefei University Hefei China

Based on the characteristics of wireless monitoring networks and profiling sensors, we present a method of acquiring the profile of moving objects. First, principal component analysis is used to extract profile sample features, and then a sink node collects all of the nodes' sample features to give a signal fusion model. This model enables a novel algorithm to be proposed that identifies test signals containing multiple sample features. Using profile feature information, the algorithm constructs a dictionary from which test samples can be sparsely represented. Then, according to the error in the sparse reconstruction, the algorithm identifies the class of profile samples acquired by the monitoring node. Unlike traditional classification algorithms, which rely on single feature samples, our approach can identify test samples consisting of multiple sample features. A numerical simulation and experimental results demonstrate that the proposed algorithm is superior to traditional methods. ©, 2015, Journal of Computational Information systems. All right reserved.

关键词： Classification (of information)

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A Fast Growing Cascade Neural Network for BOD Estimation

A Fast Growing Cascade Neural Network for BOD Estimation

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第三十四届中国控制会议

作者： LI Fanjun QIAO Junfei ZHANG Wei College of Electronic Information and Control Engineering Beijing University of Technology School of Mathematical Science University of Jinan Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781467374439

In this paper, a fast growing cascade neural network(FGCNN) is proposed, as a software sensor, to rapidly estimate the biochemical oxygen demand(BOD) in wastewater treatment plants(WWTPs). Firstly, a novel method, based on the orthogonal least squares(OLS), is put forward to add input and hidden units to the existing network one by one. Every unit added to the network affords the maximal reduction of the sum of squared errors(SSE). Then, the FGCNN incrementally updates its output weights by iterations without gradients and generalized inverses, while the other weights remain unchanged during the growth of the network. The simple and effective training method make the FGCNN learn extremely fast. Finally, the proposed FGCNN is applied to estimate the BOD in WWTPs using other easy-to-measure or secondary variables. The experiment results show that the FGCNN has better performance on real-time estimation of BOD than other similar methods.

关键词： Artificial neural network,biochemical oxygen demand,wastewater treatment plant,software sensor

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Distributed simultaneous localization and mapping algorithm based on partition of space-region

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Xi Tong Gong Cheng Yu Dian Zi Ji Shu/systems Engineering and Electronics 2015年第3期37卷 639-645页

作者： Pei, Fu-Jun Cheng, Yu-Hang Li, Hao-Yang Ju, He-Hua School of Electronic Information & Control Engineering Beijing University of Technology Beijing100124 China Beijing Key Laboratory of Computational Intelligence and Intelligence System Beijing100124 China

To solve the problem of the simultaneous localization and mapping (SLAM) under the complex circumstance, a distributed algorithm of the SLAM based on partition of space-region is proposed considering the respective advantages of centralized configuration and distributed structure. The region is formed according to the angle between two landmarks and the robot, which is designed in case of the collinearity between two landmarks. The landmarks in each region are combined to establish the corresponding observation model. Besides, the position of the robot is obtained by applying the distributed unscented particle filter and the positions of the landmarks are estimated simultaneously by employing the Kalman filter. Meanwhile, the accuracy and the stability are improved through constructing the adjustment of particle distribution during the dynamic reconfiguration process. Eventually, the better real-time capability and filter accuracy of the proposed SLAM algorithm are proved through simulation experiments which are supported by actual data. ©, 2015, Chinese Institute of Electronics. All right reserved.

关键词： Kalman filters

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A fast growing cascade neural network for BOD estimation 34

A fast growing cascade neural network for BOD estimation

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34th Chinese control Conference, CCC 2015

作者： Fanjun, Li Junfei, Qiao Wei, Zhang College of Electronic Information and Control Engineering Beijing University of Technology Beijing China School of Mathematical Science University of Jinan Shandong China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

ISBN: (纸本)9789881563897

In this paper, a fast growing cascade neural network (FGCNN) is proposed, as a software sensor, to rapidly estimate the biochemical oxygen demand (BOD) in wastewater treatment plants (WWTPs). Firstly, a novel method, based on the orthogonal least squares (OLS), is put forward to add input and hidden units to the existing network one by one. Every unit added to the network affords the maximal reduction of the sum of squared errors (SSE). Then, the FGCNN incrementally updates its output weights by iterations without gradients and generalized inverses, while the other weights remain unchanged during the growth of the network. The simple and effective training method make the FGCNN learn extremely fast. Finally, the proposed FGCNN is applied to estimate the BOD in WWTPs using other easy-to-measure or secondary variables. The experiment results show that the FGCNN has better performance on real-time estimation of BOD than other similar methods. © 2015 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Artificial neural network biochemical oxygen demand software sensor wastewater treatment plant

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Fan Fault Diagnosis Based on Wavelet Spectral Analysis

Fan Fault Diagnosis Based on Wavelet Spectral Analysis

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第三十四届中国控制会议

作者： Wen Zheng Wang Pu Gao Xuejin Zhang Yachao College of Electronic and Control Engineering Beijing University of Technology Engineering Research Center of Digital Community Ministry of Education Beijing Laboratory For Urban Mass Transit Beijing Key Laboratory of Computational Intelligence and Intelligent System

ISBN: (纸本)9781467374439

Fan plays an irreplaceable role in the ventilation of underground environment. It will cause serious consequences once the fan fails. So it is essential to do fault diagnosis of fan to prevent the emergence of break down. Spectral analysis method is a simple and effective method for signal analysis and it has been widely used in fault diagnosis of rotating machinery. This paper has researched the bearing fault of fan on the base of in-depth study of the frequency characteristics of typical faults fan. High-frequency noise of vibration signal has been removed through wavelet soft thresholding method. Get its spectrum characteristic of the reconstructed signal, and then the failure category of signal is discriminated by comparing its characteristic frequency to typical faults frequency in theory. Combining the advantage of Lab VIEW and MATLAB, we implement the algorithm through two of them, accomplishing denoising and spectral analysis of vibration signals, completing fault diagnosis of fan.

关键词： Fan Fault Diagnosis,Wavelet Denoising,Spectral Analysis

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A comparative study on D converter based on control schemes of maximum extracted power

A comparative study on D converter based on control schemes ...

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Conference Record of the IEEE Industry Applications Society Annual Meeting (IAS)

作者： Ahmad El Khateb M.N. Uddin N. A. Rahim Barry W. Williams Automatic Control and Human-Machine Systems LAMIH UMR/CNRS Valenciennes France Electronic Engineering Department Tsinghua University Tsinghua National Laboratory for Information Science and Technology (TNList) Beijing P. R. China Shenzhen City Key Laboratory of Digital TV System Valeo Powertrain Systems Amiens France National Engineering Lab. for DTV(Beijing) Beijing P. R. China

ISBN: (纸本)9781479983988

This paper presents analysis and control of D converter, which has continuous input and output current to obtain maximum power transfer from a photovoltaic (PV) system. Examining the maximum power involves optimization and control techniques that ensure maximum power extraction enhancement. Traditional converters have rather high input ripple current that originates considerable loss of power extraction when linked to photovoltaic panels. Operating with zero input ripple current enlarges the power obtained from the PV panel without employing electrolytic capacitor. Experiment and simulation of the converter performance support and extol the system concept and establish a balanced view among several types of used controllers as well.

关键词： Inverters Capacitors Photovoltaic systems Radiation effects control systems Fuel cells

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Fan fault diagnosis based on wavelet spectral analysis 34

Fan fault diagnosis based on wavelet spectral analysis

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34th Chinese control Conference, CCC 2015

作者： Zheng, Wen Pu, Wang Xuejin, Gao Yachao, Zhang College of Electronic and Control Engineering Beijing University of Technology Beijing China Engineering Research Center of Digital Community Ministry of Education Beijing China Beijing Laboratory for Urban Mass Transit Beijing China Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing China

ISBN: (纸本)9789881563897

Fan plays an irreplaceable role in the ventilation of underground environment. It will cause serious consequences once the fan fails. So it is essential to do fault diagnosis of fan to prevent the emergence of break down. Spectral analysis method is a simple and effective method for signal analysis and it has been widely used in fault diagnosis of rotating machinery. This paper has researched the bearing fault of fan on the base of in-depth study of the frequency characteristics of typical faults fan. High-frequency noise of vibration signal has been removed through wavelet soft thresholding method. Get its spectrum characteristic of the reconstructed signal, and then the failure category of signal is discriminated by comparing its characteristic frequency to typical faults frequency in theory. Combining the advantage of LabVIEW and MATLAB, we implement the algorithm through two of them, accomplishing denoising and spectral analysis of vibration signals, completing fault diagnosis of fan. © 2015 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Fan Fault Diagnosis Spectral Analysis Wavelet Denoising

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