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Robust stability clearance of flight control law based on global sensitivity analysis

Journal of Applied Mathematics 2014年第1期2014卷

作者： Ou, Liuli Liu, Lei Dong, Shuai Wang, Yongji Key Lab of Ministry of Education for Image Processing and Intelligent Control School of Automation Huazhong University of Science and Technology 1037 Luoyu Road Wuhan 430074 China

To validate the robust stability of the flight control system of hypersonic flight vehicle, which suffers from a large number of parametrical uncertainties, a new clearance framework based on structural singular value () theory and global uncertainty sensitivity analysis (SA) is proposed. In this framework, SA serves as the preprocess of uncertain model to be analysed to help engineers to determine which uncertainties affect the stability of the closed loop system more slightly. By ignoring these unimportant uncertainties, the calculation of can be simplified. Instead of analysing the effect of uncertainties on which involves solving optimal problems repeatedly, a simpler stability analysis function which represents the effect of uncertainties on closed loop poles is proposed. Based on this stability analysis function, Sobol's method, the most widely used global SA method, is extended and applied to the new clearance framework due to its suitability for system with strong nonlinearity and input factors varying in large interval, as well as input factors supjecting to random distributions. In this method, the sensitive indices can be estimated via Monte Carlo simulation conveniently. An example is given to illustrate the efficiency of the proposed method. © 2014 Liuli Ou et al.

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Genetic Algorithm based Neural Network for the Displacement of Landslide Forecasting

Genetic Algorithm based Neural Network for the Displacement ...

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第三十三届中国控制会议

作者： Jiejie Chen Zhigang Zeng Ping Jiang Huiming Tang The School of Automation Huazhong University of Science and Technology Key Laboratory of Image Information Processing and Intelligent Control Ministry Education Faculty of Engineering China University of Geosciences

This paper proposes two hybrid prediction models using for predicting the displacement of landslide, Genetic Algorithm-Radial Basis Function Neural Network (GA-RBFN) and Genetic Algorithm- Back Propagation Neural Network (GA-BPNN). A case study of Yuhuangge landslide in the Three Gorges reservoir in China is used to illustrate the capability and merit of our schemes. In addition, the result shows that GP-BPNN get better accuracy than GA-RBFN in the same measurements.

关键词： Terrain factors Genetic algorithms Neural networks Forecasting Training Transfer functions Educational institutions

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A real-time EMG pattern recognition method for virtual myoelectric hand control

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NEUROCOMPUTING 2014年 136卷 345-355页

作者： Xing, Kexin Yang, Peipei Huang, Jian Wang, Yongji Zhu, Quanmin Zhejiang Univ Technol Coll Informat Engn Hangzhou 310023 Zhejiang Peoples R China Chinese Acad Sci Inst Automat Natl Lab Pattern Recognit Ctr Res Intelligent Percept & Comp Beijing 100190 Peoples R China Huazhong Univ Sci & Technol Sch Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China China Univ Petr Coll Chem Engn Dept Chem Ind Equipment & Control Engn Qingdao 266580 Peoples R China Univ W England Dept Engn Design & Math Bristol BS16 1QY Avon England

This study proposes a real-time electro-myogram (EMG) pattern recognition approach for the control of multifunction myoelectric hands. In techniques, time and frequency information is extracted by wavelet packet transform (WPT) and the node energy of the WPT coefficients is selected as the feature of the EMG signals. Then a novel feature selection method based on a depth recursive search algorithm is developed so that the high-dimensional features can be reduced by a supervised feature reduction algorithm. Consequently, the support vector machine (SVM) is adopted to give the recognition result. In the experiment, a real-time EMG pattern recognition system is developed to control a virtual hand with EMG signals from antebrachium. The experimental results show both the high accuracy and better real-time performance of the proposed method. (C) 2014 Elsevier B.V. All rights reserved.

关键词： EMG Real-time pattern recognition Wavelet packet Non-parametric weighted feature extraction SVM

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Formation tracking of the second-order multi-agent systems using position-only information via impulsive control with input delays

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Applied Mathematics and Computation 2014年 246卷 572-585页

作者： Yan-Wu Wang Meng Liu Zhi-Wei Liu Jing-Wen Yi School of Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 PR China Department of Automation Wuhan University Wuhan 430072 PR China

In this paper, the formation tracking problem for the second-order multi-agent system with and without input delay are investigated, respectively. The objective is to design the formation tracking algorithm such that a certain follower follows the trajectory of the leader while also maintains a certain desired geometric formation with other agents simultaneously. The impulsive algorithms are designed by using only the relative position information of the neighbors for both the cases with and without the input delay. By using properties of the Laplacian matrix and combining the stability theory of impulsive systems, necessary and sufficient conditions are derived to achieve the formation tracking of the second-order multi-agent system with and without the input delay, respectively. The numerical examples are given to illustrate the effectiveness of our theoretical results.

关键词： Formation tracking Multi-agent system Impulsive control Input delay

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Flocking of partially-informed multi-agent systems avoiding obstacles with arbitrary shape

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Autonomous Agents and Multi-Agent Systems 2014年第5期29卷 943-972页

作者： Li, Jiaojie Zhang, Wei Su, Housheng Yang, Yupu Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Department of Measurement and Control Technology Shanghai Dian Ji University Shanghai China School of Automation Key Laboratory of Image Information Processing and Intelligent Control (Huazhong University of Science and Technology) Ministry of Education National Key Laboratory of Science and Technology on Multispectral Information Processing Huazhong University of Science and Technology Wuhan China

In this paper, we study the flocking problem of multi-agent systems with obstacle avoidance, in the situation when only a fraction of the agents have information on the obstacles. Obstacles of arbitrary shape are allowed, no matter if their boundary is smooth or non-smooth, and no matter it they are convex or non-convex. A novel geometry representation rule is proposed to transfer obstacles to a dense obstacle-agents lattice structure. Non-convex regions of the obstacles are detected and supplemented using a geometric rule. The uninformed agents can detect a section of the obstacles boundary using only a range position sensor. We prove that with the proposed protocol, uninformed agents which maintain a joint path with any informed agent can avoid obstacles that move uniformly and assemble around a point along with the informed agents. Eventually all the assembled agents reach consensus on their velocity. In the entire flocking process, no distinct pair of agents collide with each other, nor collide with obstacles. The assembled agents are guaranteed not to be lost in any non-convex region of the obstacles within a distance constraint. Numerical simulations demonstrate the flocking algorithm with obstacle avoidance both in 2D and 3D space. The situation when every agent is informed is considered as a special case.

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Vessel segmentation in retinal images with a multiple kernel learning based method

Vessel segmentation in retinal images with a multiple kernel...

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International Joint Conference on Neural Networks (IJCNN)

作者： Xiaoming Liu Zhigang Zeng Xiaoping Wang College of Computer Science and Technology Wuhan University of Science and Technology Wuhan China Key Laboratory of Image Information Processing and Intelligent Control Ministry of Education Wuhan China

Blood vessel segmentation is an important problem for quantitative structure analysis of retinal images, and many diseases are related to the structure changes. Manual segmentation is time consuming and computer aided segmentation is required to deal with large amount images. This paper presents a new supervised method for segmentation of blood vessels in retinal photographs. Multiple kernel learning (MKL) is introduced to deal with the problem, utilizing features from Hessian matrix based vesselness measure, response of multiscale Gabor filter, and multiple scale line strength features. The method is evaluated on the publicly available DRIVE and STARE databases. The performance of the MKL method is evaluated and experimental results show the high accuracy of the proposed method.

关键词： image segmentation Retina Biomedical imaging Kernel Blood vessels Accuracy Support vector machines

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Nonlinear H ∞ observer design for one-sided Lipschitz systems

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Neurocomputing 2014年 145卷 505-511页

作者： Wei Zhang Housheng Su Shengchao Su Dazhong Wang Laboratory of Intelligent Control and Robotics Shanghai University of Engineering Science Shanghai 201620 China School of Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China College of Information Science and Technology Donghua University Shanghai 201620 China

This paper is considered with the H ∞ observer design problem for a class of nonlinear systems with the one-sided Lipschitz condition. The systems under consideration include the well-studied Lipschitz system as a special case and possess inherent advantages with respect to conservativeness. For such systems in the presence of noises, we develop a Linear Matrix Inequality (LMI) based approach to design a nonlinear H ∞ observer by carefully dealing with the one-sided Lipschitz condition together with the quadratic inner-bounded condition. The resulting nonlinear H ∞ observer guarantees asymptotic stability of the estimation error dynamics with a prescribed H ∞ performance. Moreover, for the design purpose, the existence condition of the proposed nonlinear H ∞ observer is formulated in terms of LMIs by using a matrix generalized inverse technique. Finally, a simulation example is given to illustrate the effectiveness of the proposed design.

关键词： One-sided Lipschitz nonlinear systems Nonlinear H ∞ observers Observer design State estimation

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Coordinated obstacle avoidance with reduced interaction

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Neurocomputing 2014年 139卷 233-245页

作者： Jiaojie Li Wei Zhang Housheng Su Yupu Yang Hongtao Zhou Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Department of Measurement and Control Technology Shanghai Dian Ji University Shanghai 200240 China School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science and Technology Luoyu Road 1037 Wuhan 430074 China

In this paper, we study the coordinated obstacle avoidance algorithm of multi-agent systems when only a subset of agents has obstacle dynamic information, or every agent has local interaction. Each agent can get partial measuring states information from its neighboring agent and obstacle. Coordinated obstacle avoidance here represents not only the agents moving without collision with an obstacle, but also the agents bypassing and assembling at the opposite side of the obstacle collectively, where the opposite side is defined according to the initial relative position of the agents to the obstacle. We focus on the collective obstacle avoidance algorithms for both agents with first-order kinematics and agents with second-order dynamics. In the situation where only a fixed fraction of agents can sense obstacle information for agents with first-order kinematics, we propose a collective obstacle avoidance algorithm without velocity measurements. And then we extend the algorithm to the case in switched topology. We show that all agents can bypass an obstacle and converge together, and then assemble at the opposite side of the obstacle in finite time, if the agents׳ topology graph is connected and at least one agent can sense the obstacle. In the case where obstacle information is available to only a fixed fraction of agents with second-order kinematics, we propose two collective obstacle avoidance algorithms without measuring acceleration when the obstacle has varying velocity and constant velocity. The switched topology is considered and extended next. We show that agents can bypass the obstacle with their positions and velocities approaching consensus in finite time if the connectivity of switched topology is continuously maintained. Several simulation examples demonstrate the proposed algorithms.

关键词： Obstacle avoidance Consensus Reduced interaction Circular motion Multi-agents

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Algorithms and Experiments on Flocking of Multiagents in a Bounded Space

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IEEE TRANSACTIONS ON control SYSTEMS TECHNOLOGY 2014年第4期22卷 1544-1549页

作者： Chen, Zhiyong Zhang, Hai-Tao Fan, Ming-Can Wang, Dan Li, Dinggen Univ Newcastle Sch Elect Engn & Comp Sci Callaghan NSW 2308 Australia Huazhong Univ Sci & Technol Sch Automat Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan 430074 Peoples R China Dalian Maritime Univ Sch Marine Engn Dalian 116026 Peoples R China Huazhong Univ Sci & Technol Sch Energy & Power Engn Wuhan 430074 Peoples R China

In most scenarios encountered in both natural systems and engineering applications, collective motions are always confined in a bounded space. The conventional flocking formulation with velocity consensus does not apply in these scenarios as agents with a constant velocity that unavoidably move out of any bounded space. In this brief, the conventional flocking formulation and algorithms are generalized to address the issues caused by bouncing boundaries of a bounded space. In addition, the theoretical design was successfully implemented in a group of real robots such that it experimentally achieved a desired flock in a bounded space.

关键词： Collective motion consensus cooperative control multiagent systems nonholonomic vehicles

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Attractor Flow Analysis for Recurrent Neural Network with Back-to-Back Memristors

Attractor Flow Analysis for Recurrent Neural Network with Ba...

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2014 IEEE Symposium on Foundations of Computational Intelligence (FOCI)

作者： Bao, Gang Zeng, Zhigang Huazhong Univ Sci & Technol Sch Automat Wuhan 430074 Hubei Peoples R China Minist Educ Key Lab Image Informat Proc & Intelligent Control Wuhan 430074 Peoples R China China Three Gorges Univ Coll Elect Engn & New Energy Yichang 443002 Peoples R China

ISBN: (纸本)9781479944910

Memristor is a nonlinear resistor with the character of memory and is proved to be suitable for simulating synapse of neuron. This paper introduces two memristors in series with the same polarity (back-to-back) as simulator for neuron's synapse and presents the model of recurrent neural networks with such back-to-back memristors. By analysis techniques and fixed point theory, some sufficient conditions are obtained for recurrent neural network having single attractor flow and multiple attractors flow. At last, simulation with numeric examples is presented to illustrate our results.

关键词： Memristor Neural networks Single attractor flow Multiple attractors flow

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