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2014 International Conference on Manufacturing Technology and Electronics Applications, ICMTEA 2014

作者： Peng, Pei-Zhen Yu, Yi Wang, Zhao-Jia Jiang, Min Key Laboratory of Measurement and Control of Complex Engineering of Ministry of Education School of Automation Southeast University NanjingJiangsu China

ISBN: (纸本)9783038353287

Artificial Fish Swarm Algorithm (AFSA) since 2002 has been proposed by Dr. Li Xiao-lei more than ten years, and has been widely used in various engineering fields. However, since a lot of comprehensive standard running tests has not yet been made with the algorithm, it has not yet been unanimously recognized by the international academic community. By 34 Benchmark Functions tested with AFSA, the result evaluation for functions that are applicable and not applicable by AFSA is summarized. Also in order to overcome the drawbacks of Global Artificial Fish Swarm Algorithm (GAFSA) such as slow convergence and low precision, a modified GAFSA(MS_GAFSA) is proposed. Combined with GAFSA and Modified Simplex, the algorithm can improve the convergence speed and precision of optimization. When GAFSA converges to the global optimum nearby, a simplex is constructed and the algorithm switches to Modified Simplex method which will continue to optimize until a certain stop condition is satisfied. Take the best point of simplex vertex at this time as the optimal value. The computational results on 34 Benchmark functions show that MS_GAFSA does improve in optimizing accuracy and convergence speed. © (2014) Trans Tech Publications, Switzerland.

关键词： Global optimization

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The Design of Robust MIMO Neural Network Disturbance Observer for Multi-variable system 33

The Design of Robust MIMO Neural Network Disturbance Observe...

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第三十三届中国控制会议

作者： LI Juan LI Shihua LI Shengquan School of Automation Southeast UniversityKey Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Hydraulic Energy and Power Engineering Yangzhou University

ISBN: (纸本)9781479947249

Multi-variable systems widely exist in the practical engineering control systems whose performances are always severely interrupted by strong disturbances including unmodeled dynamics, parameter variations, couplings and external disturbances. Disturbance observer(DOB) is known as an effective technique to estimate disturbances and has been extensively applied for feed-forward compensation design in the presence of disturbances. Yet many disturbance observer techniques in previous literature are just used for single-input-single-output(SISO) systems or the DOBs can be applied in the multi-variable systems, but the DOBs are still SISO DOBs. A decoupled robust multi-input-multi-output neural network disturbance observer(MNNDOB) is designed for the multi-input-multi-output(MIMO) systems. Simulation results on the mixing tank show that the proposed method has better disturbance estimation performance when there are severe model mismatches compared with the MIMO linear disturbance observer.

关键词： Multi-variable system,Model mismatches,MIMO neural network disturbance observer,Disturbance estimation

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An improved dense matching algorithm for face based on region growing

An improved dense matching algorithm for face based on regio...

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3rd International Conference on Computer engineering and Network, CENet 2013

作者： Xia, Xin Gai, Shaoyan School of Automation Southeast University Nanjing 210096 China Key Laboratory of Measurement and Control for Complex System School of Automation Southeast University Nanjing 210096 China

ISBN: (纸本)9783319017655

Traditional dense matching algorithms for face based on region growing have a lot of flaws. To generate a better disparity map, a novel improved method is proposed in this paper. Firstly, scale invariant feature (SIFT) algorithm is adopted to detect feature points for a pair of images, which are taken from two different angles. Secondly, this paper uses normalized cross correlation (NCC) to get match points and uses random sampling consensus (RANSAC) algorithm to eliminate mismatches. Several robust seeds are generated after this step. At last, by using an improved strategy of region growing, in which seeds are evaluated to help determine the locations and sizes of the search windows dynamically, the matching relations of seeds propagate to other parts of images. Experiments show that this method can obtain a good disparity map and has high computation speed. © 2014 Springer International Publishing Switzerland.

关键词： Image enhancement

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An adaptive method based on QRCP decomposition for single sample problem

An adaptive method based on QRCP decomposition for single sa...

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Chinese control Conference (CCC)

作者： Changhui Hu Xiaobo Lu Yijun Du Key Laboratory of Measurement and Control of Complex System of Engineering Southeast University Nanjing China

In this paper, an adaptive approximation image reconstruction method based on orthogonal triangular with column pivoting (QRCP) decomposition algorithm is proposed for single sample problem in face recognition. By using QRCP the single sample and its transpose are decomposed to two sets of basis images. Then an adaptive approximation image reconstruction method is proposed to reconstruct two approximation images from the two basis image sets respectively. The single training sample and its two approximation images of each object form a new training set, which can make the fisher linear discriminant analysis (FLDA) be applied to single sample problem in face recognition. The performance of the proposed method is verified on Yale, FERET, and ORL face databases. The experimental results indicate that the proposed method is efficient and outperforms some existing methods which are proposed to overcome the single sample problem.

关键词： Face recognition Databases Face Training Approximation methods Image reconstruction Image recognition

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Global decentralized stabilization for a class of large-scale feedforward nonlinear systems

Global decentralized stabilization for a class of large-scal...

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American control Conference

作者： Qixun Lan Chuanlin Zhang Shihua Li Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing 210096 P. R. China College of Automation Engineering Shanghai University of Electric Power Shanghai 200090 P.R. China School of Automation Southeast University Nanjing 210096 P. R. China

ISBN: (纸本)9781479917730

This paper considers the problem of global decentralized stabilization for a class of large-scale feedforward nonlinear systems. First, by using generalized homogeneous systems theory, a local linear decentralized control law is recursively constructed. Second, a series of nested saturation functions are integrated with the proposed local linear control law to render the whole closed-loop large-scale system global asymptotical stability. Due to the flexibility of the generalized homogeneous systems theory, the proposed approach not only weakens the existing restrictions imposed on the interconnected nonlinearities, but also can be applied to more general classes of large-scale feedforward nonlinear systems. Numerical example shows that the effectiveness of the proposed control scheme.

关键词： Decentralized control Feedforward neural networks Nonlinear systems Closed loop systems Lyapunov methods Asymptotic stability Feedforward systems

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In vitro corrosion of Mg–1.21Li–1.12Ca–1Y alloy

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Progress in Natural Science:Materials International 2014年第5期24卷 492-499页

作者： Rongchang Zeng Weichen Qi Fen Zhang Hongzhi Cui Yufeng Zheng College of Materials Science and Engineering Shandong University of Science and Technology State Key Laboratory of Mining Disaster Prevention and Control Co-founded by Shandong Province and the Ministry of Science and Technology Shandong University of Science and Technology State Key Laboratory for Turbulence and Complex System Department of Materials Science and Engineering College of EngineeringPeking University

The influence of the microstructure on mechanical properties and corrosion behavior of the Mg–1.21Li–1.12Ca–1Y alloy was investigated using OM, SEM, XRD, EPMA, EDS, tensile tests and corrosion measurements. The results demonstrated that the microstructure of the Mg–1.21Li–1.12Ca–1Y alloy was characterized by α-Mg substrate and intermetallic compounds Mg2 Ca and Mg24Y5. Most of the fine Mg2 Ca particles for the as-cast alloy were distributed along the grain boundaries, while for the as-extruded along the extrusion direction. The Mg24Y5 particles with a larger size than the Mg2 Ca particles were positioned inside the grains. The mechanical properties of Mg–1.21Li–1.12Ca–1Y alloy were improved by the grain refinement and dispersion strengthening. Corrosion pits initiated at the α-Mg matrix neighboring the Mg2 Ca particles and subsequently the alloy exhibited general corrosion and filiform corrosion as the corrosion product layer of Mg(OH)2and Mg CO3 became compact and thick.

关键词： Magnesium–lithium alloys Microstructure Mechanical property Corrosion Biomaterial

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Mars Entry Trajectory Tracking Via Constrained Multi-Model Predictive control 33

Mars Entry Trajectory Tracking Via Constrained Multi-Model P...

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第三十三届中国控制会议

作者： WU Chao LI Shihua YANG Jun GUO Lei School of Automation Southeast University & Key Laboratory of Measurement and Control of Complex Systems of EngineeringMinistry of Education School of Automation Science and Electrical Engineering Beihang University & Institute of Instrument Science and Opto-Electronics Engineering

ISBN: (纸本)9781479947249

Tracking law designed for future Mars entry missions is investigated in this article. For precision landing, the nonlinear entry dynamics, complex uncertainties and input saturation constraints are unavoidable problems. Facing these challenges, the Mars entry trajectory tracking scheme via constrained multi-model predictive control(CMPC) is employed. The CMPC is made up of some constrained predictive control(CPC) in different time domain during the Mars entry mission. Each constrained predictive controller consists of a linearized prediction model(obtained by linearizing at different operating point), feedback correction for active model mismatch rejection caused by the complex uncertainties, and constrained rolling optimization for a smooth control input under a saturation constraint. Monte Carlo simulations demonstrate the effectiveness and excellence of the proposed method under the saturation constraint of input and uncertainties of initial state and aerodynamic parameters such as atmospheric density, ballistic coefficient and lift-to-drag ratio.

关键词： Mars Entry,Trajectory Tracking,Constrained Multi-Model Predictive control,Monte Carlo Simulation

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Adaptive fuzzy control of output-constrained switched nonlinear systems

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ICIC Express Letters 2015年第12期9卷 3355-3362页

作者： Niu, Ben Liu, Yanli Shen, Mouquan School of Control Science and Engineering Dalian University of Technology No. 2 Linggong Road Ganjingzi District Dalian China College of Mathematics and Physics Bohai University No. 19 Keji Road New Songshan District Jinzhou China Automation Research Institute Bohai University No. 19 Keji Road New Songshan District Jinzhou China College of Electrical Engineering and Control Science Nanjing Technology University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

In this paper, the problem of adaptive fuzzy tracking control is considered of uncertain switched nonlinear systems with an output constraint. First, a barrier Lyapunov function (BLF) is employed to deal with the output constraint. Then fuzzy logic systems are used to approximate the unknown nonlinearities and backstepping technique is employed to construct an adaptive fuzzy controller. The designed controller guarantees all the closed-loop signals remain bounded while the system output converges to a small neighborhood of the desired reference signal without violating the constraint. An example is given to demonstrate the validity of the developed result. © 2015 ICIC International.

关键词： Lyapunov functions

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Linguistic dynamic analysis for single lane's traffic status based on FCM

Linguistic dynamic analysis for single lane's traffic status...

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2014 International Conference on Informative and Cybernetics for Computational Social systems, ICCSS 2014

作者： Jie, Wang Hong, Mo Fenghua, Zhu College of Electrical AndInformation Engineering Changsha University of Science and Technology Changsha China State Key Laboratory of Management and Control for Complex System Beijing China

ISBN: (纸本)9781479947522

The results of traditional traffic status analysis are mostly single values, whose accuracy can't be determined;fuzzy c-means clustering (FCM) algorithm based on fuzzy theory can calculate the clustering center of plenty data quickly and easily;linguistic dynamic systems could describe the dynamic rules of complex systems in the language level. In this paper, membership functions are decided by FCM;result of a specific time period taken as one example is obtained;it's discussed that linguistic dynamic analysis of traffic status in different period within a day by the same method. © 2014 IEEE.

关键词： Linguistics

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High-level spatial modeling in convolutional neural network with application to pedestrian detection

High-level spatial modeling in convolutional neural network ...

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Canadian Conference on Electrical and Computer engineering (CCECE)

作者： Feng Liu Yongzhen Huang Wankou Yang Changyin Sun School of Automation. Southeast University Nanjing China Key Lab of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China Key Lab of Child Development and Learning Science of Ministry of Education. Southeast University Nanjing China

ISBN: (纸本)9781479958306

Convolutional neural network (CNN) has achieved great success in many vision tasks. A key to this success is its ability to powerful automatically learns both high-level and low-level features. In general, low-level features have a small size of receptive fields and appear multiple times in different locations of objects, while high-level semantic features have a relatively large size of receptive fields and only appear once in a specific location of objects. However, traditional CNN treats these two kinds of features in the same manner, i.e., learning them by the convolution operation, which can be approximately considered as cumulating the probabilities that a feature appears in different locations. This strategy is reasonable for low-level features but not for high-level semantic ones, especially in the case of pedestrian detection, where a local feature can be shared by different locations but a semantic part, e.g., a head, only appears once for a human. To jointly model the spatial structure and appearance of high-level semantic features, we propose a new module to learn spatially weighted max pooling in CNN. The proposed method is evaluated on several pedestrian detection databases and the experimental results show that it achieves much better performance than traditional CNN.

关键词： Convolution Semantics Kernel Deformable models Computational modeling Feature extraction Training

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