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第三十一届中国控制会议

作者： XIONG Jianbin,WANG Qinruo,LIU Yijun,YE Baoyu,WU Haoyi Guang Dong University of Technology,Guang Zhou,510006,China

The algorithm based on extended kalman filter and in combination with linear smoothing was proposed in this paper,as there are some deviations larger abnormal values in measurement of the ship position *** this method was used to process nonlinear continuous *** was applied to ship dynamic ***,we deep analyze nonlinear model of ship dynamic positioning,then turn it into a linear ***,discrete linear model of ship dynamic positioning, finally,filter using the extended kalman filter algorithm and smooth filtered signal using smoothing linear *** experimental results show that the method was simple,reasonable,effective and easy for real-time applications.

关键词： kalman filtering algorithm linear smoothing algorithm Ship dynamic positioning discretization

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FUZZY PREDICTION OF CHAOTIC TIME SERIES BASED ON FUZZY CLUSTERING

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ASIAN JOURNAL OF CONTROL 2011年第4期13卷 576-581页

作者： Wang, Hongwei Lian, Jie Dalian Univ Technol Sch Control Sci & Engn Dalian Liao Ning Peoples R China

The main purpose of this paper is to study a new method to model and predict a chaotic time series using a fuzzy model. First, the GK fuzzy clustering method is used to confirm the input space of the fuzzy model. The goal is to divide the training patterns into representative groups so that patterns within one cluster are more similar than those belonging to other clusters. Then, the kalman filtering algorithm with singular value decomposition is applied to estimate the consequent parameters of the fuzzy model in order to avoid error delivery and error accumulation. The effectiveness of the proposed method is evaluated through simulated examples, including Mackey-Glass time series and Lorenz chaotic systems. The results show that the proposed method provides effective and accurate prediction.

关键词： Singular value decomposition kalman filtering algorithm GK fuzzy clustering chaotic time series

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Calibration and evaluation of a combined fracture model of microvoid growth that may compete with shear in the polycrystalline microstructure by means of evolutionary algorithms

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COMPUTATIONAL MATERIALS SCIENCE 2009年第1期45卷 133-149页

作者： Jackiewicz, J. Univ Technol & Life Sci Dept Mech Engn PL-85796 Bydgoszcz Poland

Changes of stress or strain ratios during an operation can have an effect on cracking during metalworking processes. Therefore, there is a substantive interest of the aluminum and steel industries of the manufacturing sectors in numerical simulations of the fracture processes of typical structural materials. In this paper, a calibration procedure of material parameters for a combined fracture model of microvoid growth that may compete with shear in the polycrystalline microstructure is described. The paper then proceeds to evaluating the probability of structural failure on the basis of the combined fracture model according to the calibrated material parameters. An assessment of the probability of structural failure is important to improve the quality of manufacturing processes, but also to reduce their costs. (C) 2008 Elsevier B.V. All rights reserved.

关键词： Phenomenological fracture criteria Micromechanical models for the simulation of ductile fracture kalman filtering algorithm Assessment of the joint probability density function Searching the extremum of the objective function with the evolution strategy

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Research on the Effect of Ship's Deck Deflection on Angular Rate Matching Based Transfer Alignment Process

Research on the Effect of Ship's Deck Deflection on Angular ...

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IEEE International Conference on Mechatronics and Automation

作者： Zhou, Weidong Ding, Guoqiang Hao, Yanling Cui, Guangzhao Harbin Engn Univ Coll Automat Harbin 150001 Peoples R China Zhengzhou Univ Light Ind Henan Key Lab Informat Elect Appliances Zhengzhou 450002 Peoples R China

ISBN: (纸本)9781424426928

This paper analyzes reasons of ship-carrier deck deformation and its effect on parameters of SINS Attitude Heading Reference System (SAHRS). With second order Markov stochastic process theory it constructs ship's deck deformation model. According to inertial measurement matching method, it formulates the dynamic system equation and the observation equation based on angular-rate matching algorithm. And then it evaluates the system model with kalman filtering. Furthermore, this paper proposes an iterative filtering system equation according to the property of dynamic system and evaluates the performance with iterative filtering algorithm. From simulation results we can see, the kalman filtering algorithm can effectively eliminate the effect of ship's deck deformation error, decrease the error of transfer alignment system, and significantly improve its precision, similar to that of the iterative filtering method. But in the iterative filtering algorithm, at the initial iteration period, the iterative results can effectively track output value of the system model, and with the iterative number increasing its tracking error increases gradually. So from the perspective of system design requirements the kalman filtering algorithm is superior to the iterative filtering algorithm. Research results in this paper have important theoretical and application value in the study or design of high-precision transfer alignment system based on shipboard.

关键词： Transfer Alignment Inertial Matching algorithm Angular-rate Matching kalman filtering algorithm Iterative filtering algorithm

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Short-term electric load forecasting based on kalman filtering algorithm with moving window weather and load model

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ELECTRIC POWER SYSTEMS RESEARCH 2004年第1期68卷 47-59页

作者： Al-Hamadi, HM Soliman, SA Univ Qatar Coll Engn Power Syst Res Grp Dept Elect Engn Doha Qatar

This paper presents a novel time-varying weather and load model for solving the short-term electric load-forecasting problem. The model utilizes moving window of current values of weather data as well as recent past history of load and weather data. The load forecasting is based on state space and kalman filter approach. Time-varying state space model is used to model the load demand on hourly basis. kalman filter is used recursively to estimate the optimal load forecast parameters for each hour of the day. The results indicate that the new forecasting model produces robust and accurate load forecasts compared to other approaches. Better results are obtained compared to other techniques published earlier in the literature. (C) 2003 Elsevier B.V. All rights reserved.

关键词： short-term electric load kalman filtering algorithm moving window

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Harmonic modeling of linear and nonlinear loads based on kalman filtering algorithm

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ELECTRIC POWER SYSTEMS RESEARCH 2004年第2期72卷 147-155页

作者： Soliman, SA Alammari, RA Univ Qatar Dept Elect Engn Doha Qatar

Most harmonic nonlinear load modeling techniques developed in the last two decades, assume that the load connected to the load bus has a constant admittance, inductive or capacitive, which depends on the mode of operation of the load (constant R, L, and C). This is not true, since the loads in most cases are nonlinear and they inject harmonics into the system. This paper presents a new application of kalman filtering (KF) to nonlinear load modeling in the presence or absence of harmonics. The proposed technique uses directly available samples of the load voltage and current to estimate, and track the variation of load parameters. The proposed algorithm can be used directly on-line for harmonics load modeling, as well as, to track the load power active and reactive. The effects of the critical parameters on the behavior of the proposed algorithm are discussed. Results for different simulated examples and practical examples from field measurements are reported in the paper. The conclusion drawn from these examples is that the algorithm is successful in estimating the load parameters. (C) 2004 Elsevier B.V. All rights reserved.

关键词： harmonics load modeling kalman filtering algorithm power in nonsinusoidal voltage

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A generalized model and solution algorithm for estimation of the dynamic freeway origin-destination matrix

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TRANSPORTATION RESEARCH PART B-METHODOLOGICAL 2007年第5期41卷 554-572页

作者： Lin, Pei-Wei Chang, Gang-Len Univ Missouri Dept Civil & Mech Engn Kansas City MO 64110 USA Univ Maryland Dept Civil & Environm Engn College Pk MD 20742 USA

This study presents a generalized model for estimating the dynamic freeway O-D distribution, based on measurable time series of mainline and ramp flows, and estimated travel time distributions. The proposed model captures the speed discrepancy among drivers, due either to their desired speeds or responses to congestion, with an embedded travel time distribution function and the identified interrelations between time-varying ramp and mainline flows. With the employed mainline information and travel time function, the proposed system equation has increased its observability with less parameters. The proposed model with a specially designed algorithm offers the potential for use in a network of realistic size, such as the 1-95 freeway corridor between the Maryland 1-695 and 1-495 beltways. Extensive numerical analyses with respect to the sensitivity of both input measurement errors and the selection of initial parameters on the estimation results have revealed that the proposed model is sufficiently robust for real-world applications. Published by Elsevier Ltd.

关键词： dynamic origin-destination estimation kalman filtering algorithm

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Comparison between object and pixel level approaches for change detection in multispectral images by using neural networks

Comparison between object and pixel level approaches for cha...

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Conference on Image and Signal Processing for Remote Sensing IX

作者： Nemmour, H Chibani, Y Univ Sci & Technol Houari Boumediene Signal Proc Lab Fac Elect & Comp Sci Algiers 16111 Algeria

ISBN: (纸本)0819451215

We propose in this paper the investigation of the change detection approaches based on the pixel level and the object level. The pixel level approach is based on the simultaneous analysis of multitemporal data, while the object level approach uses a comparative analysis of independently produced classifications of data. Thereby, the comparison is established by using the multilayer neural network classifier. Usually, the backprogation algorithm is used as a training rule. In this paper, we investigate the use of the kalman filtering (KF) as the training algorithm for detecting changes in remotely sensed imagery. By using SPOT images and evaluation criteria, the detailed comparison indicates that the KF algorithm is preferable compared to the BP algorithm in terms of convergence rate, stability and change detection accuracy.

关键词： change detection neural network backpropagation kalman filtering algorithm comparative analysis simultaneous analysis

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Polynomial algorithm of the spatial forecast of atmospheric state parameters based on the kalman filtering and its application

Polynomial algorithm of the spatial forecast of atmospheric ...

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9th Joint International Symposium on Atmospheric and Ocean Optics/Atmospheric Physics

作者： Kurakov, VA Komarov, VS Kreminskii, AV Lomakina, NY Popov, YB Popova, AI Suvorov, SS Tomsk State Univ Control Syst & Radioelect Tomsk 634055 Russia

ISBN: (纸本)0819448281

In the paper, the problem of spatial forecast of mesoscale fields at the point of space uncovered by meteorological information is discussed. The algorithms for estimating and forecasting the atmospheric parameters based on kalman filtering theory. The offered algorithm takes into account horizontal statistical structure of afield at separate atmospheric levels and its time dynamics. The atmospheric parameter in a point is defined on the basis of a second-order polynomial model. The offered algorithm of the spatial forecast is investigated on the data long-term balloon observations for layer-by-layer averaging of temperature, zonal and meridional 1 wind velocity components.

关键词： spatial forecast kalman filtering algorithm mesoscale fields of temperature and zonal and meridional wind velocity components

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The real-time prediction algorithm for ultrasonic P/O transducers' VR interface

The real-time prediction algorithm for ultrasonic P/O transd...

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3rd World Congress on Intelligent Control and Automation

作者： Wu, ZC Ge, Y Yu, CD Fang, TJ Chinese Acad Sci Inst Intelligent Machines Key Labs Transducers Technol Hefei 230031 Peoples R China

ISBN: (纸本)7312012035

The measurement of Position gt Orientation (P/O) is an important study area in VR technology, 3D ultrasonic P/O transducers have been widely used in this aspects for its low cost high precision and simple algorithms. But for environment influence and TOF(time of flight)of ultrasound wave, the results of measurement are non-continuous and time-delayed, which could not be used as feedback signals for control. An improved kalman filtering algorithm has been offered for real-time prediction of the measured object in this paper. As a result, the algorthm also can be used to eliminate measurement errors influenced by environment.

关键词： 3-D ultrasonic P/O Transducers kalman filtering algorithm Real-time Predication

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