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Design of Robotic Visual Servo control Based on Neural Network and Genetic Algorithm

International Journal of Automation and computing 2012年第1期9卷 24-29页

作者： Hong-Bin Wang Mian Liu Key Lab of Industrial Computer Control Engineering of Hebei Province Institute of Electrical EngineeringYanshan UniversityQinhuangdao 066004PRC

A new visual servo control scheme for a robotic manipulator is presented in this paper, where a back propagation （BP） neural network is used to make a direct transition from image feature to joint angles without requiring robot kinematics and camera calibration. To speed up the convergence and avoid local minimum of the neural network, this paper uses a genetic algorithm to find the optimal initial weights and thresholds and then uses the BP Mgorithm to train the neural network according to the data given. The proposed method can effectively combine the good global searching ability of genetic algorithms with the accurate local searching feature of BP neural network. The Simulink model for PUMA560 robot visual servo system based on the improved BP neural network is built with the Robotics Toolbox of Matlab. The simulation results indicate that the proposed method can accelerate convergence of the image errors and provide a simple and effective way of robot control.

关键词： Visual servo image Jacobian back propagation （BP） neural network genetic algorithm robot control

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Dynamic Consensus of High-order Multi-agent Systems and Its Application in the Motion control of Multiple Mobile Robots

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International Journal of Automation and computing 2012年第1期9卷 54-62页

作者： Zhong-Qiang Wu Yang Wang Key Laboratory of Industrial Computer Control Engineering Yanshan UniversityQiuhuangdao 066004PRC

In this paper, the leader-following consensus problem for multi-agent linear dynamic systems is considered. All agents and leader have identical multi-input multi-output （MIMO） linear dynamics that can be of any order, and only the output information of each agent is delivered throughout the communication network. When the interaction topology is fixed, the leader-following consensus is attained by Ho~ dynamic output feedback control, and the sufficient condition of robust controllers is equal to the solvability of linear matrix inequality （LMI）. The whole analysis is based on spectral decomposition and an equivalent decoupled structure achieved, and the stability of the system is proved. Finally, we extended the theoretical results to the case that the interaction topology is switching. The simulation results for multiple mobile robots show the effectiveness of the devised methods.

关键词： Multi-agent systems consensus problem dynamic output feedback linear matrix inequality （LMI） multiple mobile robots.

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New methodology for creating probit models to assess the domino effect caused by overpressure

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Dongbei Daxue Xuebao/Journal of Northeastern University 2013年第SUPPL.1期34卷 265-272页

作者： Sun, Dong-Liang Huang, Guang-Tuan Jiang, Jun-Cheng Zhang, Ming-Guang Wang, Zhi-Rong State Environ Protection Key Lab of Environmental Risk Assessment and Control on Chemical Process School of Resources and Environmental Engineering East China University of Science and Technology Shanghai 200237 China Jiangsu Key Laboratory of Urban and Industrial Safety School of Urban Construction and Safety Engineering Nanjing University of Technology Nanjing 210009 China

Chemical process equipment and the damage phenomenon were categorized. Data were collected and unnecessary overpressure values together with the corresponding damage phenomenon in which the domino effect did not appear were deleted. The entire range of damage probability was divided into three categories according to degree of damage, by two segmentation points of random variables, and the model of damage probability following a uniform distribution in each degree of damage was proposed, in order to establish more detailed and realistic probit models. The influence of the two random separation points on the mean square errors was investigated and the average of the errors was regarded as the criterion for integral accuracy of the created models. The results showed that the mean square errors of different equipment and their average decreased according to the smaller separation point, and decreased initially and then increased with the larger separation point. The prediction model with high reliability was obtained by data fitting to calculate the average of the mean square errors, which reached a minimum when the values of both break points were 0.3363. These probit models of the four equipment categories with lower mean square errors and better consistency between predicted and observed data were proposed after correcting the few and unnecessary observed data used in curve regression and oversimplification in the probability arrangement in a previous study. The threshold value for damage of 33.63% was 19, 37, 26 and 31 kPa for atmospheric, pressurized, elongated and small equipment, respectively.

关键词： Mean square error

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Incentive-Driven and Freshness-Aware Content Dissemination in Selfish Opportunistic Mobile Networks

Incentive-Driven and Freshness-Aware Content Dissemination i...

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IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems (MASS)

作者： Huan Zhou Jie Wu Hongyang Zhao Shaojie Tang Canfeng Chen Jiming Chen State Key Lab. of Industrial Control Technology Zhejiang University China Department of Computer and Information Sciences Temple University USA Nokia Research Center Beijing China

Recently, the content-based publish/subscribe (pub/sub) paradigm is gaining popularity in opportunistic mobile networks (OppNets) for its flexibility and adaptability. Since nodes in OppNets is controlled by humans, they often behave selfishly with an aim to maximize their own revenues without considering the performance of others. Therefore, stimulating nodes in OppNets to collect, store, and share content efficiently is one of the key challenges under this scheme. Meanwhile, guaranteeing the freshness of content is also a big problem for content dissemination in OppNets. In this paper, in order to solve these problems, we propose an incentive-driven and freshness-aware pub/sub content dissemination scheme, called ConDis (Content Dissemination), for selfish OppNets. In ConDis, the Tit-For-Tat (TFT) scheme is employed to deal with selfish behaviors of nodes in OppNets. ConDis also implements a novel content exchange protocol when nodes are in contact. Specifically, during each contact, the exchange order is determined by the content utility, which is calculated by the direct subscribed value and the indirect subscribed value, and the objective of nodes is to maximize the utility of the content inventory stored in their buffer. Extensive realistic trace-driven simulation results show that ConDis is superior to other existing schemes in terms of total freshness value, total delivered contents, and total transmission cost.

关键词： Peer-to-peer computing Buffer storage Delays Thin film transistors Incentive schemes Exponential distribution Mobile computing

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Compressed sensing ensemble classifier for human detection

Compressed sensing ensemble classifier for human detection

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4th International Conference on Intelligence Science and Big Data engineering, IScIDE 2013

作者： Zhang, Baochang Liu, Juan Gao, Yongsheng Liu, Jianzhuang Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering BeiHang University Beijing 100191 China School of Engineering Griffith University Australia Shenzhen Key Lab for Computer Vision and Pattern Recognition Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China Department of Information Engineering Chinese University of Hong Kong Hong Kong Hong Kong

ISBN: (纸本)9783642420566

This paper proposes a novel Compressed Sensing Ensemble Classifier (CSEC) for human detection. The proposed CSEC employs the compressed sensing technique to get a more sparse model with a more reasonable selection of base classifiers. The major contributions of this paper are: 1) a novel principled framework for ensemble classifier design based on compressed sensing;2) a new concept of considering both the simplicity of ensemble classifier and irrelevance of base classifiers towards optimal classifier design;and 3) a quadratic function for CSEC optimization which includes a new optimizable positive semi-definite relevance matrix to simultaneously select appropriate base classifiers with minimized relevance. Experimental results on INRIA and SDL databases show that the performance of CSEC is better than two most popular classifiers SVM and AdaBoost, as well as a most recent method CLML. © 2013 Springer-Verlag Berlin Heidelberg.

关键词： Compressed sensing

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Performance analysis for high-speed railway communication network using stochastic network calculus

Performance analysis for high-speed railway communication ne...

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5th IET International Conference on Wireless, Mobile and Multimedia Networks, ICWMMN 2013

作者： Li, Ying Lei, Lei Zhong, Zhangdui Lin, Siyu School of Electronics and Information Engineering Beijing Jiaotong University Beijing 100044 China State Key Lab. of Rail Traffic Control and Safety Beijing Jiaotong University Beijing 100044 China Dept. of Electrical and Computer Engineering University of Victoria Victoria BC V8P 5C2 Canada

ISBN: (纸本)9781849197267

High-speed railway (HSR) wireless communication network has won a great development in recent years. However, due to its unique characteristics, such as high speed, fixed mobility track, special traffic, frequent handover and bandwidth constraints, it is quite a challenge to carry out the performance analysis on HSR. In this paper, we derive the backlog and delay bounds for HSR communication network by using stochastic network calculus (SNC) with moment generating functions (MGFs). SNC is a highly useful tool in packet switched network performance analysis since 1990s. Different from the previous studies about SNC which mostly concentrate on general low-speed, traditional public communication network, we take the varying small-scale fading and large-scale fading into consideration by means of a novel multi-dimension finite-state Markov channel (FSMC) model. We elaborate the differences in packet-level channel model, traffic model of train control information and performance metrics in HSR communication network. Particularly, the backlog and delay bounds of HSR with different packet arrival rates and violation probabilities are derived when train travels from the cell center to the cell edge. What is more, the numerical results can help to provide a guideline for designing the proper violation probabilities and arrival rates to different types of traffic in HSR communication network.

关键词： Calculations

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Energy-efficient area coverage in bistatic radar sensor networks

Energy-efficient area coverage in bistatic radar sensor netw...

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2013 IEEE Global Communications Conference (GLOBECOM)

作者： Qianqian Yang Shibo He Jiming Chen State Key Lab. of Indnsrrial Control Technology Zhejiang University China School of Electrical Computer and Energy Engineering Arizona State University USA

ISBN: (纸本)9781479913510

In this paper we study area coverage in bistatic radar sensor networks (BRSN), which is composed of a collection of transmitters and receivers. Coverage in BRSN is much more difficult than that in traditional sensor networks as the sensing area of a bistatic radar depends on the positions of its component transmitter and receiver, and is in general of an elliptical shape. We first investigate the geometrical relationship between the c-coverage area of a bistatic radar and the distance between its component transmitter and receiver, based on which we reduce the number of candidate bistatic radars from all transmitter-receiver pairs. Then we reduce the problem dimension by transforming the area coverage problem to point coverage problem by employing intersection point concept. Finally we propose an efficient algorithm to solve the Point Coverage Problem, which thus solves the area coverage problem. We perform extensive simulations to validate our analysis and the performance of the proposed algorithm.

关键词： Bistatic radar Receivers Algorithm design and analysis Radio transmitters Sensors

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Direct Localization of Multiple Sources in Sensor Array Networks: A Joint Sparse Representation of Array Covariance Matrices Approach

Direct Localization of Multiple Sources in Sensor Array Netw...

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IEEE Internatonal Conference on Mobile Adhoc and Sensor Systems (MASS)

作者： Ji-An Luo Zhi Wang Yu-Hen Hu Hangzhou Dianzi University Institute of Information and Control China Zhejiang University The State Key Laboratory of Industrial Control Technology China Dept. Electrical and Computer Engineering University of Wisconsin-Madison WI U. S. A

A novel sparse representation based multi-source localization method is presented in this work. We envision a wireless network infrastructure containing multiple phase arrays of acoustic sensors. With multiple arrays, direct estimation of a set of source locations is achieved using a new joint sparse representation of array covariance matrices (JSRACM). This representation transforms the source location estimation problem into a spatial sparse signal representation (SSSR) optimization problem. To mitigate the high computation complexity of JSRACM, a novel binary sparse indicative vector (SIV) is introduced to represent the support of joint SSSR of array covariance matrices. As such, the multiple source locations may be estimated by solving an unconstrained optimization problem of the SIV vector using existing FOCUSS-like algorithms. The resulting SIVR-JSRACM algorithm does not require prior information of the number of sources nor initial source location estimates. It promises super-resolution, robustness to noise, and low computing complexity which is independent of the number of sensor phase arrays. Simulation results demonstrate superior performance of the proposed algorithm.

关键词： Arrays Vectors Covariance matrices Noise Signal processing algorithms Joints Dictionaries

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Sparse signal analysis using Ramanujan sums 1

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9th International Conference on Intelligent Computing, ICIC 2013

作者： Chen, Guangyi Krishnan, Sridhar Liu, Weihua Xie, Wenfang Department of Computer Science and Software Engineering Concordia University Montreal QC H3G 1M8 Canada Department of Computer and Electrical Engineering Ryerson University Toronto ON Canada State Key Lab. of Virtual Reality Technology and Systems Beihang University No 37 Xueyuan Rd. Haidian District 100191 Beijing China Department of Mechanical and Industrial Engineering Concordia University Montreal QC H3G 1M8 Canada

ISBN: (数字)9783642394829

ISBN: (纸本)9783642394812

In this paper, we perform sparse signal analysis by using the Ramanujan Sums (RS). The RS are orthogonal in nature and therefore offer excellent energy conservation. Our analysis shows that the RS can compress the energy of a periodic impulse chain signal into fewer number of RS coefficients than the Fourier transform (FT). In addition, the RS are faster than the FT in computation time because we can calculate the RS basis functions only once and save them to a file. We can retrieve these RS basis functions for our calculation instead of computing them online. To process a signal of 128 samples, we spend 1.0 millisecond for the RS and 5.82 milliseconds for the FT by using our unoptimized Matlab code. © 2013 Springer-Verlag.

关键词： Signal analysis

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Canonical correlation analysis based on Hilbert-Schmidt independence criterion and centered Kernel target alignment

Canonical correlation analysis based on Hilbert-Schmidt inde...

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30th International Conference on Machine Learning, ICML 2013

作者： Chang, Billy Kruger, Uwe Kustra, Rafal Zhang, Junping Dalla Lana School of Public Health University of Toronto Toronto ON M5T 3M7 Canada Dept. Mechanical and Industrial Engineering Sultan Qaboos University Al Khoud Oman Shanghai Key Lab of Intelligent Information Processing and School of Computer Science Fudan University China

ISBN: (纸本)9781629933061

Canonical correlation analysis (CCA) is a well established technique for identifying linear relationships among two variable sets. Kernel CCA (KCCA) is the most notable nonlinear extension but it lacks interpretability and robustness against irrelevant features. The aim of this article is to introduce two nonlinear CCA extensions that rely on the recently proposed Hilbert-Schmidt independence criterion and the centered kernel target alignment. These extensions determine linear projections that provide maximally dependent projected data pairs. The paper demonstrates that the use of linear projections allows removing irrelevant features, whilst extracting combinations of strongly associated features. This is exemplified through a simulation and the analysis of recorded data that are available in the literature. Copyright 2013 by the author(s).

关键词： Correlation methods

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