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2nd International Conference on Image Analysis and Signal Processing, IASP'2010

作者： Bin, Zhou Jun-Zheng, Wang Wei, Shen Key Laboratory of Complex System Intelligent Control and Decision School of Automatic Control Beijing Institute of Technology Beijing China

ISBN: (纸本)9781424455553

A multi-bandwidth based tracking algorithm was proposed to search for the global kernel mode when the probability density has multiple peak modes. Firstly, a monotonically decreasing sequence of bandwidths was fixed according to the target scale. At each bandwidth, using mean shift to And out the maximum probability, and starting the next iteration at the previous convergence location. Finally, the best optimal mode could be obtained at the last bandwidth. To accelerate the convergence, over-relaxed strategy was introduced to enlarge the step size. Under the convergence rule, the learning rate was adaptively adjusted by Bhattacharyya coefficients of consecutive iteration convergence. The experimental results show that the proposed multi-bandwidth mean shift tracker is robust in high-speed object tracking, and perform well in occlusions. The adaptive over-relaxed strategy is effective to lower the convergence iterations by enlarging the step size. © 2010 IEEE.

关键词： Bandwidth

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An adaptive hybrid optimizer based on particle swarm and differential evolution for global optimization

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Science China(Information Sciences) 2010年第5期53卷 980-989页

作者： XIN Bin 1,2 ? , CHEN Jie 1,2* , PENG ZhiHong 1,2 & PAN Feng 1,2 1 School of Automation, Beijing Institute of Technology, Beijing 100081, China 2 key laboratory of complex system intelligent control and decision, Ministry of Education, Beijing 100081, China 1. School of Automation Beijing Institute of Technology Beijing 100081 China2. Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China

This paper presents extensive experiments on a hybrid optimization algorithm (DEPSO) we recently developed by combining the advantages of two powerful population-based metaheuristics—differential evolution (DE) and particle swarm optimization (PSO). The hybrid optimizer achieves on-the-fly adaptation of evolution methods for individuals in a statistical learning way. Two primary parameters for the novel algorithm including its learning period and population size are empirically analyzed. The dynamics of the hybrid optimizer is revealed by tracking and analyzing the relative success ratio of PSO versus DE in the optimization of several typical problems. The comparison between the proposed DEPSO and its competitors involved in our previous research is enriched by using multiple rotated functions. Benchmark tests involving scalability test validate that the DEPSO is competent for the global optimization of numerical functions due to its high optimization quality and wide applicability.

关键词： global optimization statistical learning differential evolution particle swarm optimization hybridization adaptation rotated function

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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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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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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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Decentralized control for Arbitrarily Interconnected systems over Lossy Network

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自动化学报 2010年第9期36卷 1321-1327页

作者： LI Hui School of Automation Beijing Institute of TechnologyBeijing 100081P.R.China Key Laboratory of Complex System Intelligent Control and Decision Ministry of EducationBeijing 100081P.R.China

This paper deals with the control of arbitrarily topological interconnected systems where information communicated between subsystems may be lost due to unreliable links. First, the stochastic variable that is responsible for the communication status of lossy network is regarded as a source of model uncertainty. The system is modeled in the framework of linear fractional transformation with a deterministic nominal system and a stochastic model uncertainty. Then, the robust control theory is employed for system analysis. The largest probability of communication failure, tolerated by the interconnected systems keeping mean square stable, can be obtained by solving a μ synthesis optimization problem. Decentralized state feedback controllers are designed to ensure that the whole system is mean square stable for a given communication failure rate, based on the technique of linear matrix inequalities. An illustrative example is presented finally to verify the effectiveness of the proposed model and method

关键词：拓扑子系统通信故障率随机变量

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Object tracking based on multi-bandwidth mean shift with convergence acceleration

Object tracking based on multi-bandwidth mean shift with con...

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International Conference on Image Analysis and Signal Processing, IASP

作者： Zhou Bin Wang Jun-Zheng Shen Wei Key Laboratory of Complex System Intelligent Control and Decision School of Automatic Control Beijing Institute of Technology Beijing China

A multi-bandwidth based tracking algorithm was proposed to search for the global kernel mode when the probability density has multiple peak modes. Firstly, a monotonically decreasing sequence of bandwidths was fixed according to the target scale. At each bandwidth, using mean shift to find out the maximum probability, and starting the next iteration at the previous convergence location. Finally, the best optimal mode could be obtained at the last bandwidth. To accelerate the convergence, over-relaxed strategy was introduced to enlarge the step size. Under the convergence rule, the learning rate was adaptively adjusted by Bhattacharyya coefficients of consecutive iteration convergence. The experimental results show that the proposed multi-bandwidth mean shift tracker is robust in high-speed object tracking, and perform well in occlusions. The adaptive over-relaxed strategy is effective to lower the convergence iterations by enlarging the step size.

关键词： Convergence Acceleration Resists Wet etching Integrated circuit technology Electron beams Electron optics Semiconductor process modeling Optical beams Optical device fabrication

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Formation control based on Flocking Algorithm in Multi-agent system

Formation Control based on Flocking Algorithm in Multi-agent...

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The 8th World Congress on intelligent control and Automation(第八届智能控制与自动化世界大会 WCICA 2010)

作者： Hu Cao Jie Chen Yutian Mao Hao Fang Huagang Liu Education Ministry Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China

This paper mainly addresses flocking control algorithm to implement the “boids” model of Reynolds among the formation control by nonholonomic multi-robots. Firstly, distributed flocking of multiple autonomous agents with double integrator dynamics is studied. The proposed flocking algorithm is a gradient-based protocol combined with a velocity consensus protocol. For the gradient-based term, smooth artificial potential functions which could cope with the problem of shape generation are devised for all the agents. Moreover, the proposed coordinated protocols are applied to the formation control of a team of nonholonomic mobile robots. Finally, simulations and experiments show that the proposed controllers ensure the group formation is stabilized to a desired shape, while all the robots’ velocities and directions converge to the same.

关键词： Protocols Computational modeling Robot kinematics Vehicle dynamics Mobile robots Stability analysis

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control of Spatially Interconnected systems with Random Communication Losses

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自动化学报 2010年第2期36卷 258-266页

作者： LI Hui WU Qing-He HUANG Huang School of Automation Beijing Institute of Technology Beijing 100081 P.R. China Key Laboratory of Complex System Intelligent Control and Decision (Beijing Institute of Technology) Ministry of Education Beijing 100081 P.R. China

This paper deals with analysis and synthesis problems of spatially interconnected systems where communicated information may get lost between subsystems. Spatial shift operator and temporal forward shift operator are introduced to model the interconnected systems as discrete time-space multidimensional linear systems with Markovian jumping parameters which reflect the state of communication channels. To ensure the whole system＇s well-posedness and mean square stability for a given packet loss rate, a condition is derived through analysis. Then a procedure of designing distributed dynamic output feedback controllers is proposed. The controllers have the same structure as the plants and are solved within the linear matrix inequality （LMI） framework. Finally, we apply these results to study the effect of communication losses on the multiple vehicle platoon control system, which further illustrates the effectiveness of the proposed model and method.

关键词： Spatially interconnected system communication loss Markovian jump linear system linear matrix inequality （LMI）

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