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Rules-based autonomous obstacle avoidance for mobile robots

Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (science and technology) 2011年第SUPPL. 1期42卷 493-497页

作者： Wang, Qi-Zhi Xu, De School of Computer Science and Information Technology Beijing Jiaotong University Beijing 100044 China Key Laboratory of Intelligent Control of Complex Systems Institute of Automation Chinese Acad. of Sci. Beijing 100080 China

A real time and autonomous obstacle avoidance method based on rules for mobile robots was presented. Wall- along algorithm was dynamically implemented in unknown environment without collision. The results show that th... 详细信息

关键词： Mobile robots

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Unsupervised Learning of Gaussian Mixture Model with Application to Image Segmentation

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电子学报(英文版) 2010年第3期19卷 451-456页

作者： LI Bo LIU Wenju DOU Lihua School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision (Beijing Institute of Technology) Ministry of Education Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

Density estimation via Gaussian mixture modeling has been successfully applied to image segmentation, speech processing and other fields relevant to clustering analysis and Probability density function (PDF) modeling. Finite Gaussian mixture model is usually used in practice and the selection of number of mixture components is a significant problem in its application. For example, in image segmentation, it is the donation of the number of segmentation regions. The determination of the optimal model order therefore is a problem that achieves widely attention. This paper proposes a degenerating model algorithm that could simultaneously select the optimal number of mixture components and estimate the parameters for Gaussian mixture model. Unlike traditional model order selection method, it does not need to select the optimal number of components from a set of candidate models. Based on the investigation on the property of the elliptically contoured distributions of generalized multivariate analysis, it select the correct model order in a different way that needs less operation times and less sensitive to the initial value of EM. The experimental results show the effectiveness of the algorithm.

关键词：高斯混合模型图像分割无监督学习应用概率密度函数椭球等高分布模型估计高斯密度

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Identification of interval models for a class of uncertain systems via linear programming

Identification of interval models for a class of uncertain s...

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作者： Zhang, Guozhu Chen, Jie Li, Zhiping Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology School of Automation Beijing 100081 China

ISBN: (纸本)9781424474264

The interval models of uncertain plants are frequently used in the field of robust control. In this paper, a novel interval model identification method based on linear programming is proposed. By certain prepossessing on the measured data of the plant, the interval model identification problem is transformed into several linear programming problems, which can be easily solved through various algorithms. We have proved that the resultant interval model has a known error bound, provided that certain conditions on the measured data are satisfied. To demonstrate its effectiveness, the proposed method is applied to identify the interval model of a servo system with variant load and inertia. © 2010 AACC.

关键词： Linear programming

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Robust Filtering for Networked systems with Random Transmission Delays and Packet Dropouts

Robust Filtering for Networked Systems with Random Transmiss...

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2011 American control Conference (ACC)

作者： Yunze Cai Hua O. Wang Kazuo Tanaka Xiaoming Xu Department of Mechanical Engineering Boston University Boston MA USA Department of Automation and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiaotong University Shanghai China Department of Mechanical Systems and Intelligent Systems University of Electro-Communications Tokyo Japan Department of Automation Shanghai Jiaotong University Shanghai China University of Shanghai for Science and Technology Shanghai China

This paper addresses a robust H_(infinity) filtering problem for networked systems that are subject to both random transmission delays and packet dropouts. To start with, a data transmission model is established by employing random series with Bernoulli distributions. A sufficient condition for robust stability with H_(infinity) constraints is derived for the filtering error system. The robust filter is designed in terms of the feasibility of a linear matrix inequality (LMI). The numerical examples are provided to show the effectiveness of the data transmission model and the proposed filtering method.

关键词： Delay Filtering Robustness Data models Symmetric matrices Hidden Markov models Markov processes

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A bi-swarm particle swarm optimization with cooperative co-evolution

A bi-swarm particle swarm optimization with cooperative co-e...

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International Conference on Computational Aspects of Social Networks

作者： Ji, Huanhuan Jie, Jing Li, Junji Tan, Ying Division of Complex System and Intelligent Computation Taiyuan University of Science and Technology Taiyuan City 030024 China College of Computer Science and Technology Zhejiang University of Technology ZJUT Hangzhou 310014 China

ISBN: (纸本)9780769542027

In order to develop the global performance of particle swarm optimization(PSO), the paper proposes a biswarm particle swarm optimization with cooperative coevolution (BPSO-CC). BPSO-CC adopts two swarms to go on the search, the first swarm is designated to conduct the coarse search in the whole space, while the second swarm is generated periodically surround the first swarm and designated to make the fine search in the local search area around the first swarm. With the same aim to find out the global optimum, the two swarms go on their search in parallel. at the same time, they keep the cooperative co-evolution through sharing and exchanging the valid information, which can make them search in correct direct and improve the convergent efficiency of PSO validly. The proposed BPSO-CC has been applied to solve some benchmark functions with large scales, the simulation results demonstrate that BPSO-CC is a robust technique for complex optimizations and performs better than SPSO, not only in the convergence precision but also in the efficiency. 2010 IEEE.

关键词： Efficiency

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A Bi-swarm Particle Swarm Optimization with Cooperative Co-evolution

A Bi-swarm Particle Swarm Optimization with Cooperative Co-e...

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International Conference on Computational Aspects of Social Networks(国际社会网络计算会议 CASoN 2010)

作者： Ying Tan Junji Li Huanhuan Ji Jing Jie Division of Complex System and Intelligent Computation Taiyuan University of Science and Technology Division of Complex System and Intelligent Computation Taiyuan University of Science and Technology

In order to develop the global performance of particle swarm optimization(PSO), the paper proposes a bi-swarm particle swarm optimization with cooperative co-evolution (BPSO-CQ. BPSO-CC adopts two swarms to go on the search, the first swarm is designated to conduct the coarse search in the whole space, while the second swarm is generated periodically surround the first swarm and designated to make the Gne search in the local search area around the first swarm. With the same aim to find out the global optimum, the two swarms go on their search in parallel, at the same time, they keep the cooperative co-evolution through sharing and exchanging the valid information, which can make them search in correct direct and improve the convergent efficiency of PSO validly. The proposed BPSO-CC has been applied to solve some benchmark functions with large scales, the simulation results demonstrate that BPSO-CC is a robust technique for complex optimizations and performs better than SPSO, not only in the convergence precision but also in the efficiency.

关键词： Particle Swarm Optimization Bi-swarm Cooperative Co-evolution the Best and the Worst particles

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A method for data stream processing based on curve fitting

A method for data stream processing based on curve fitting

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2010 2nd International Conference on Signal Processing systems, ICSPS 2010

作者： Song, Yixu Hu, Jing Yang, Xiaokui Fu, Jie Xie, Xiufen State Key Laboratory of Intelligent Technology and System Department of Computer Science and Technology Tsinghua University Beijing China Department of Computer Science and Technology University of Science and Technology Beijing Beijing China Sany Intelligent Control Equipment Co. Ltd. Changsha Hunan China

ISBN: (纸本)9781424468911

The sampling storage method which used in the current data stream could not respond data tendency effectively. For the problem, this paper presents a new processing method based on curve fitting. A weighted least-square principle is used to fit the cached stream data and better model description is obtained. Then the fitting results are analyzed by clustering algorithm, which serves as a classifier for polynomial fitting parameters. According to the clustering result, the appropriate window size will be given to fit the periodic stream data. Comparing the function solutions with the actual data, the different methods are adopted to store data according to the comparison result. The experimental results indicate that the proposed method has better fitting accuracy and compression ratio, could meet the requirement of data stream processing. And the data tendency could be responded effectively by the fitting results. © 2010 IEEE.

关键词： Curve fitting

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A theorem for relationship between the MA process and its inversion for ARMAX identification

A theorem for relationship between the MA process and its in...

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作者： Xin, Bin Chen, Jie School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China

ISBN: (纸本)9787894631046

The paper presents a theorem to show the relationship between the parameters of the Moving Average (MA) process and those of its inversed process. The theorem can be used for the parameter identification of the MA process. It is further shown in this paper that the parameter identification of autoregressive moving average with exogenous variable model (ARMAX), based on the identification of its MA part, can be easily achieved. The approach, at first, achieves the identification of the ARX part by directly using least-square estimations to find out a straightforward relationship between estimated parameters and observed data. Then, the inversed model of the MA part is identified in a similar way. Finally, the noise variance can be computed by using identified MA parameters. Numerical simulations validate the effectiveness and efficiency of the proposed approach.

关键词： Least squares approximations

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A multi-robot target tracking algorithm with centroidal Voronoi tessellation and consensus strategy

A multi-robot target tracking algorithm with centroidal Voro...

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作者： Sun, Wei Dou, Lihua Chen, Jie Fang, Hao School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9787894631046

A novel algorithm to solve the target tracking and formation control problem in multi-agent systems is proposed in the present work, which combines centroidal Voronoi tessellations (CVT) with consensus strategy. The algorithm utilizes the connection information among robots to further reduce the system cost function on the basis of CVT configuration. The work load among robots can be averaged by the consensus strategy thus the tracking and formation task can be achieved. The method configures the robots on to local optimal solution which minimize the sensing error. Simulations validated the proposed approach. Comparison is drawn between the pure CVT algorithm and the method with consensus strategy.

关键词： Target tracking

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Chaotic synchronization in RCL-shunted Josephson junctions

Chaotic synchronization in RCL-shunted Josephson junctions

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作者： Lu, Pingli Yang, Ying School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing 100081 China Department of Mechanics and Engineering Science Peking University Beijing 100871 China

ISBN: (纸本)9787894631046

Chaotic synchronization criteria for a class of dynamical networks with each node being RCL-shunted Josephson junction is proposed in this paper. The proposed algorithms, which are established in terms of linear matrix inequalities (LMIs), guarantee the synchronized states to be global asymptotically stable. In addition, an interesting conclusion is reached that the chaotic synchronization in the coupled whole 3N-dimensional networks can be converted into that of 3-dimensional space.

关键词： Linear matrix inequalities

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