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作者： Zhao, Juan Cai, Tao Deng, Fang Yang, Hongwei School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex Systems Intelligent Control and Decision Ministry of Education BIT Beijing 100081 China

ISBN: (纸本)9789881725592

In this paper, a new strategy based on impulsive control model of high speed roller is proposed. To make the roller hit the specified target, the strategy is summarized as an optimal control model calculating required number of impulses, the igniting time and phase of each impulse, and also an improved Differential Evolution (DE) Algorithm is adopted to resolve. It is too difficult to solve the orderliness of igniting time by Basic DE, so a Mapping Differential Evolution Algorithm (MDE) is proposed, which maps the sorting time variables to random coefficient range [0,1]. In addition, a DE with self-adapting parameter is used to accelerate the convergence rate. Simulation results show the high accuracy of high speed roller with the method. © 2011 Chinese Assoc of Automati.

关键词： Mapping

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Decentralized Loading Coordinations for Large-population Plug-in Electric Vehicles and a few controllable Bulk Loads

Decentralized Loading Coordinations for Large-population Plu...

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IEEE Conference on decision and control

作者： Xiaokun Yin Zhongjing Ma Lei Dong School of Automation Beijing Institute of Technology (BIT) Beijing China School of Automation BIT and the Key Laboratory of Complex System Intelligent Control and Decision (BIT) Ministry of Education Beijing China School of Automation BIT

ISBN: (纸本)9781612848006

This paper studies the loading coordinations for large-population autonomous individual (plug-in) electric vehicles (EVs) and a few controllable bulk loads, e.g. EV fleets, pumped storage hydro units, and so on. Due to the computational infeasibility of the centralized coordination methods to the underlying large-population systems, in this paper we develop a novel game-based decentralized coordination strategy. Following the proposed decentralized strategy update mechanism and under some mild conditions, the system may quickly converge to a nearly valley-fill Nash equilibrium. The results are illustrated with numerical examples.

关键词： (Plug-in) electric vehicles Loading coordination Nash equilibrium (NE) Valley-fill

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Path planning of multiple UAVs low-altitude penetration based on improved Multi-agent Coevolutionary Algorithm

Path planning of multiple UAVs low-altitude penetration base...

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作者： Peng, Zhi-Hong Sun, Lin Chen, Jie Wu, Jin-Ping 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)9789881725592

In order to solve the multi-UAV cooperative path planning problem of low-altitude penetration, the paper proposes an improved Multi-agent Coevolutionary Algorithm (IMACEA), which introduces co-evolution mechanism based on Multi-agent Genetic Algorithm(MAGA) to find the optimal solution of multi-objective optimization problem by combing the agents' perception and response capabilities of environment, information sharing capacity among multi-agent systems and heuristic search ability of heuristic search. At the same time, we use absolute Cartesian coordinates and relative polar coordinates coding method to reduce the search space and speed up the convergence rate. To adapt to multi-path planning problems of UAVs, new multi-agent co-evolution operators are designed. Finally, the proposed algorithm is used for multiple UAVs offline and online route planning, simulation results show the effectiveness of the algorithm. © 2011 Chinese Assoc of Automati.

关键词： Motion planning

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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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Asian control Conference

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

ISBN: (纸本)9781612844879

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.

关键词： Convergence Optimization Benchmark testing Cloning Automation Evolutionary computation Algorithm design and analysis

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Optimal Tuning of Plant-Friendly PID controllers

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Journal of Beijing Institute of Technology 2010年第3期19卷 331-336页

作者：史大威王军政马立玲 Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology

A plant-friendly proportional-integral-derivative （PID） controller optimization framework is proposed to make tradeoffs among set-point response,controller output variations and *** objective function is chosen as the weighted sum of the integral of squared time-weighted error and the integral of squared timeweighted derivative of the control variable with respect to set-point response,while the robustness of the system is guaranteed by constraints on gain and phase *** to the complex structure of the constraints,the problem is solved by genetic *** analysis show the proposed method could efficiently reduce the controller output variations while maintaining a short settling *** on the simulation results,iterative tuning rules for the weighting factor in the objective function are obtained,which allows efficient simple proportional-integral（PI） tuning formulae to be derived.

关键词： PID control plant-friendliness genetic algorithm constrained optimization

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Real-time moving object detection and tracking based on improved mean shift

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Zhongnan Daxue Xuebao (Ziran Kexue Ban)/Journal of Central South University (Science and Technology) 2011年第SUPPL. 1期42卷 823-828页

作者： Lei, Ying-Hui Zhang, Juan Yang, Wen-Jia Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education School of Automation Beijing Institute of Technology Beijing 100081 China

An improved real-time target detection and tracking method was proposed based on moving foreground object in the servo monitoring system. This method extracts moving object based on adaptive mixture of Gaussian when the object comes into the video scene, then tracks the moving object using improved MeanShift algorithm, and makes it in the center of the scene. The algorithm not only ensures the real-timing of the detection and tracking, but also enlarges the sight of the camera when the object is tracked. The experiment results show that this method can automatically detect moving object and do servo tracking.

关键词： Bandpass filters

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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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Moving object detection in framework of compressive sampling

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Journal of Systems Engineering and Electronics 2010年第5期21卷 740-745页

作者： Jing Li JunzhengWang Wei Shen Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing 100081 P. R. China

Compressive sensing is a revolutionary idea proposed recently to achieve much lower sampling rate for *** the image application with limited resources the camera data can be stored and processed in compressed *** algorithm for moving object and region detection in video using a compressive sampling is *** algorithm estimates motion information of the moving object and regions in the video from the compressive measurements of the current image and background *** algorithm does not perform inverse compressive operation to obtain the actual pixels of the current image nor the estimated *** leads to a computationally efficient method and a system compared with the existing motion estimation *** experimental results show that the sampling rate can reduce to 25% without sacrificing performance.

关键词： compressive sampling compressive measurements moving object detection.

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Positioning accuracy of IGPS

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Journal of Harbin Institute of Technology(New Series) 2010年第2期17卷 219-224页

作者：于淼陈杰窦丽华甘明刚 School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education

The positioning accuracy of a short-haul target-locating system,the inverse-GPS(IGPS) ,was analyzed in detail. The relationship between IGPS and the positioning error was discussed. The multiplicative error minimal bound of the geometric dilution of precision (GDOP) about the four-base-station IGPS was also investigated. In order to clarify the practical implementation of IGPS,the multiplicative and additive error factors which affect the positioning accuracy and theoretical estimation of positioning accuracy were presented. By analyzing the experiments of locating a target's position in virtual three-dimensional areas,the positioning performance of IGPS was illustrated. The results show that the multiplicative and additive error factors should be eliminated in IGPS to improve the positioning accuracy.

关键词： inverse-GPS(IGPS) GDOP positioning accuracy

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New Synchronization Algorithm and Analysis of Its Convergence Rate for Clock Oscillators in Dynamical Network with Time-Delays

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Journal of Beijing Institute of Technology 2010年第1期19卷 58-65页

作者：甘明刚于淼陈杰窦丽华 School of Automation Beijing Institute of Technology Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology

New synchronization algorithm and analysis of its convergence rate for clock oscillators in dynamical network with time-delays are presented.A network of nodes equipped with hardware clock oscillators with bounded drift is ***,a dynamic synchronization algorithm based on consensus control strategy,namely fast averaging synchronization algorithm （FASA）,is presented to find the solutions to the synchronization *** FASA,each node computes the logical clock value based on its value of hardware clock and message *** goal is to synchronize all the nodes＇ logical clocks as closely as ***,the convergence rate of FASA is analyzed that proves it is related to the bound by a nondecreasing function of the uncertainty in message delay and network ***,FASA＇s convergence rate is proven by means of the robust optimal ***,several practical applications for FASA,especially the application to inverse global positioning system （IGPS） base station network are ***,numerical simulation results demonstrate the correctness and efficiency of the proposed *** FASA with traditional clock synchronization algorithms （CSAs）,the convergence rate of the proposed algorithm converges faster than that of the CSAs evidently.

关键词： clock synchronization convergence rate dynamical network robust optimal design

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