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2012年中国智能电网学术研讨会

作者： GAO Hou-lei 高厚磊 LIU Yi-qing 刘益青 SU Jian-jun 苏建军 CUI De-min 崔得民 LIU Jian 刘建 XIANG Min-jiang 向珉江 Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education(Shandong Un 电网智能化调度与控制教育部重点实验室(山东大学) 山东济南250061 Dezhou Power Supply Company Dezhou 253008China 德州供电公司山东德州 253008

为解决传统变电站后备保护在配置和原理方面存在的问题，提出了适用于智能变电站的基于电流差动原理的站域后备保护新方案。该方案以变电站及所有出线为保护对象，定义了四类不同特性的差动区，根据其处于制动状态或者差动状态来实现故... 详细信息

为解决传统变电站后备保护在配置和原理方面存在的问题，提出了适用于智能变电站的基于电流差动原理的站域后备保护新方案。该方案以变电站及所有出线为保护对象，定义了四类不同特性的差动区，根据其处于制动状态或者差动状态来实现故障定位，并根据主保护和断路器的动作信号确定后备保护的跳闸策略。详细阐述了站域差动后备保护的工作原理、故障元件定位流程以及主、后备保护之间的协调控制方法。采用该方案的智能变电站，保留传统的面向间隔的主保护，集中配置站域后备保护，简化了后备保护的配置和整定。利用PSCAD软件构建了典型变电站仿真模型，对正常运行、保护区内外故障等不同运行状态进行了全面仿真，验证了所提方案的正确性。

关键词：智能变电站站域后备保护电流差动原理仿真模型

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Mobile robot's electronic compass calibration based on modified Fourier Neural Network

Mobile robot's electronic compass calibration based on modif...

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IEEE Conference on Robotics, Automation and Mechatronics

作者： Gong Kun Deng Fang Ma Tao Gong Kun is with School of Automation Beijing Institute of Technology and Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) Beijing China Deng Fang is with School of Automation Beijing Institute of Technology and Key Laboratory of Advanced Control of Iron and Steel Process (Ministry of Education) Beijing China Ma Tao is with School of Automation Beijing Institute of Technology and Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing China

In order to improve the precision of the azimuth measured by mobile robot's electronic compass, this paper proposes a new calibration method based on Fourier Neural Network trained by Modified Particle Swarm Optimization (MPSO-FNN). This method makes use of Fourier Neural Network (FNN) to establish the error compensation model of electronic compass's azimuth, and introduces Modified Particle Swarm Optimization (MPSO) algorithm to optimize the weights of neural network. Thus the comparatively accurate error model of azimuth is obtained to compensate the output of electronic compass. This method not only has strong nonlinear approximation capability, but also overcomes the neural networks' shortcomings which are too slow convergence speed, oscillation, and easy to fall into local optimum and sensitive to the initial values. Experimental results demonstrate that after calibrated by this method, the range of azimuth error reduces to -0.35°~0.70° from -3.4°~25.2°, and the average value of absolute error is only 0.30°.

关键词： Compass Azimuth Biological neural networks Particle swarm optimization Training Accuracy Automation

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Real-Time Wide-Field Monitoring system Based on Image Mosaicing Technique and Its Application

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IFAC Proceedings Volumes 2011年第1期44卷 14928-14933页

作者： Li-hui Zou Jie Chen Juan Zhang Jing-hua Lu School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision (Beijing Institute of Technology) Ministry of Education Beijing 100081 China

Abstract Common surveillance system is usually limited by the scope of observation, which may increase the probability of missing or misjudging suspicious targets. A wide-field monitoring system based on efficient image mosaicing algorithm is proposed in this paper. It can monitor a wide field for both short and long distance in real time and highlight the detected moving objects simultaneously. The image mosaicing is not only aimed at obtaining the wide field of view, but also utilized in motion detection for forming a wide-field motion mask. A simulation platform is developed to verify the performance of the system. The experiment results show that it satisfies the demands of high resolution and real-time implementation. The system is of high practical value to transportation surveillance or other applications.

关键词： safety analysis image processing transportation

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Adaptive sliding mode control of electromechanical actuator with improved parameter estimation

Adaptive sliding mode control of electromechanical actuator ...

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Asian control Conference

作者： Hao Li Yongqiang Bai Zhong Su School of Automation Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing China Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing China

An adaptive sliding mode control scheme for electromechanical actuator has been presented. The adaptive control strategy can estimate the uncertain parameters and adaptively compensate the modeled dynamical uncertainties, while the sliding mode control method overcomes the unmodelled dynamics. In the adaptive law an equivalent output injection of the sliding mode observer which contains the parameter estimation error is used, and estimates of parameters can approximate the true values without prediction-error that is typically used in compositive adaptive law. Due to the improved estimation of uncertain parameters, the sliding mode law can robustifies the design against model uncertainties with a small swithcing gain. Stability of the system with the proposed approach has been proved and it has also been shown that the system states can reach the sliding mode in finite time. Finally, the effectiveness of the proposed control scheme has been exhibited via simulation examples.

关键词： Parameter estimation Sliding mode control Actuators Aerodynamics Robustness Adaptive control Uncertainty

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Medical Image Segmentation Using Mean Shift Algorithm and General Edge Detection

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IFAC Proceedings Volumes 2011年第1期44卷 9656-9661页

作者： Jinghua Lu Jie Chen Juan Zhang Lihui Zou 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 (Tel: 86-010-68913795)

Abstract The segmentation of the medical image faces the challenges of the existence of large number of diverse structures of human anatomy and inevitable artifacts induced from the imaging procedure. In this paper we treat some structures and artifacts as general edge features, and introduce the edge information into the mean shift segmentation algorithm in both clustering and the fusion steps. Considering the medical images as two dimensional signals, the general edge can be detected and described with its local spatial frequency properties. The segmentation results show the improvement in preserving the completeness of details while sketching the overall structures.

关键词： image segmentation signal processing medical application

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3D Multi-Constraint Route Planning for UAV Low-altitude Penetration Based on Multi-Agent Genetic Algorithm

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IFAC Proceedings Volumes 2011年第1期44卷 11821-11826页

作者： Jin-Ping Wu Zhi-Hong Peng Jie Chen School of Automation Beijing Institute of Technology Beijing 100081 Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Ministry of Education P. R. China

Abstract Low-altitude penetration is one of the most important military applications of Unmanned Aerial Vehicles (UAVs). 3D route planning, which is a complex multi-objective optimization problem with multiple constraints, is the key technology of UAV low altitude-penetration. A 3D route planning method based on Multi-Agent Genetic Algorithm (MAGA) is proposed in this paper. Specifically, a dynamic route representation form is proposed to improve the flight route accuracy. An efficient constraint handling method is used to simplify the treatment of multi-constraint and reduce the time-cost of planning computation. More importantly, details are presented to show how to apply MAGA to 3D route planning while some necessary improvements of MAGA are proposed to make it more efficient. Simulation and analysis illustrate the effectiveness of this method.

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Online Path Planning for UAV Using an Improved Differential Evolution Algorithm

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IFAC Proceedings Volumes 2011年第1期44卷 6349-6354页

作者： Xing Zhang Jie Chen Bin Xin Hao Fang 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 Tel: 86-10-68912464-22

Abstract This paper presents a 3D online path planning algorithm for unmanned aerial vehicle (UAV) flying in partially known hostile environment. In order to provide a smooth fight route for UAV, the algorithm adopts B-Spline curve to describe UAV's path whose control points are optimized by an improved differential evolution algorithm. The planner gradually produces a smooth path for UAV from starting location to its target. Regarding path planning performance, the proposed improved diferential evolution based planner is compared with its three competitors which are based on classical differential evolution, genetic algorithm and particle swarm optimization, respectively. Numerical simulation demonstrates that the proposed UAV path planner not only produces high-quality feasible flight routes for UAV, but also obviously outperforms its competitors.

关键词： UAV online path planning differential evolution B-Spline

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Differential evolution with adaptive population size combining lifetime and extinction mechanisms

Differential evolution with adaptive population size combini...

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作者： Zhang, Chunmei Chen, Jie Xin, Bin Cai, Tao Chen, Chen School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing China School of Electronic Information Engineering Taiyuan University of Science and Technology Shanxi China Department of Automation Tsinghua University Beijing China

ISBN: (纸本)9788995605646

Differential Evolution (DE) is a simple and efficient numerical optimization method. Most DE variants in the literature adopt fixed population size. This paper incorporates into DE the mechanisms of lifetime and extinction which regulate DE's population size in an adaptive manner. The population size is adjusted according to the online progress of fitness improvement. Two schemes of inserting new individuals are proposed to match different mechanisms respectively. The performance of these innovations is examined through the optimization of benchmark problems. The results show that the proposed adaptive population sizing strategy is efficient for improving the convergence and efficiency of the DE. © 2011 Asian control Association.

关键词： Optimization

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Multi-group consensus via pinning control with non-linear heterogeneous agents

Multi-group consensus via pinning control with non-linear he...

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Asian control Conference

作者： Wei Sun YongQiang Bai Rui Jia Rui Xiong Jie Chen Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing China Beijing Institute of Technology Beijing Beijing CN

The agents connected by networks are capable to reach a prescribed state if only a small fraction of them are controlled with feedback information. The present work tries to stabilize groups of non-linear agents in a directed network onto a stable state with several equilibriums. The agent dynamics can be identical or heterogeneous. But the agents in the same group share a same non-linear model. The conditions to reach multiple consensus states are provided under both non-switching and switching topologies. The maximum number of heterogeneous equilibriums is discussed. It is proved theoretically and by simulations that under certain conditions, pinning control can lead a multi-group network to reach a multi-valued consensus state.

关键词： Topology Network topology Switches Eigenvalues and eigenfunctions Convergence Laplace equations

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Multi-agent based simulation for underground safety accidents

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Journal of Convergence Information Technology 2011年第11期6卷 309-316页

作者： Cai, Linqin Pan, Yuyou Cen, Ming Yu, Jimin Key Laboratory of Network control and Intelligent Instrument Chongqing University of Posts and Telecommunications Ministry of Education Chongqing 400065 China Research Center on Complex System Analysis and Control Chongqing University of Posts and Telecommunications Chongqing 400065 China

Traditional experiments with human subjects for underground safety accidents are almost impossible because of safety and ethical issues. Based on Multi-agent technology, virtual mine architecture was presented to simulate underground safety accidents. In proposed multi-agent framework, multiple agents cooperate with each other through synchronization and message passing mechanisms to reveal the complex interactive characteristics of human-machine-environment related factors resulting in underground safety accidents. Furthermore, the design and implementation of virtual miner agent model was emphasized. Combined with internal attributes, virtual miner's behavior is constructed by a set of parameterized basic actions and controlled by personalized action selection mechanism. The simulating results on typical accidents of propdrawing operation in stope face show the proposed approaches are effective to reconstruct accident process in virtual mine for assisting underground safety accident analysis and prevention.

关键词： Virtual reality

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