• Title/Summary/Keyword: modelling errors

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Stabilization Position Control of a Ball-Beam System Using Neural Networks Controller (신경회로망 제어기을 이용한 볼-빔 시스템의 안정화 위치제어)

  • 탁한호;추연규
    • Journal of the Korean Institute of Navigation
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    • v.23 no.3
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    • pp.35-44
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    • 1999
  • This research aims to seek active control of ball-beam position stability by resorting to neural networks whose layers are given bias weights. The controller consists of an LQR (linear quadratic regulator) controller and a neural networks controller in parallel. The latter is used to improve the responses of the established LQR control system, especially when controlling the system with nonlinear factors or modelling errors. For the learning of this control system, the feedback-error learning algorithm is utilized here. While the neural networks controller learns repetitive trajectories on line, feedback errors are back-propagated through neural networks. Convergence is made when the neural networks controller reversely learns and controls the plant. The goals of teaming are to expand the working range of the adaptive control system and to bridge errors owing to nonlinearity by adjusting parameters against the external disturbances and change of the nonlinear plant. The motion equation of the ball-beam system is derived from Newton's law. As the system is strongly nonlinear, lots of researchers have depended on classical systems to control it. Its applications of position control are seen in planes, ships, automobiles and so on. However, the research based on artificial control is quite recent. The current paper compares and analyzes simulation results by way of the LQR controller and the neural network controller in order to prove the efficiency of the neural networks control algorithm against any nonlinear system.

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Improving Covariance Based Adaptive Estimation for GPS/INS Integration

  • Ding, Weidong;Wang, Jinling;Rizos, Chris
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • v.1
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    • pp.259-264
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    • 2006
  • It is well known that the uncertainty of the covariance parameters of the process noise (Q) and the observation errors (R) has a significant impact on Kalman filtering performance. Q and R influence the weight that the filter applies between the existing process information and the latest measurements. Errors in any of them may result in the filter being suboptimal or even cause it to diverge. The conventional way of determining Q and R requires good a priori knowledge of the process noises and measurement errors, which normally comes from intensive empirical analysis. Many adaptive methods have been developed to overcome the conventional Kalman filter's limitations. Starting from covariance matching principles, an innovative adaptive process noise scaling algorithm has been proposed in this paper. Without artificial or empirical parameters to be set, the proposed adaptive mechanism drives the filter autonomously to the optimal mode. The proposed algorithm has been tested using road test data, showing significant improvements to filtering performance.

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Development of the Adaptive Algorithm for Time Delay Systems (시간지연 시스템 제어를 위한 적응제어 알고리즘 개발)

  • Lee, Soon-Young
    • Journal of IKEEE
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    • v.13 no.1
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    • pp.36-40
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    • 2009
  • In control of time delay systems, if the informations about the system model and the disturbance can be estimated exactly, the ideal response can be achieved by using Smith predictor controller. Therefore, in this paper, an adaptive algorithm is proposed to control time delay systems existing modelling errors and disturbance. An adaptive observer to estimate disturbance and system model is designed and adaptive laws adjusting the observer are proposed. The new Smith predictor controller is designed using the proposed adaptive observer. As a result, the proposed controller can eliminate the effects of the disturbance and the modelling error. The effectiveness and the improved performance of the proposed system are verified by computer simulation.

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Neuro-fuzzy based prediction of the durability of self-consolidating concrete to various sodium sulfate exposure regimes

  • Bassuoni, M.T.;Nehdi, M.L.
    • Computers and Concrete
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    • v.5 no.6
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    • pp.573-597
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    • 2008
  • Among artificial intelligence-based computational techniques, adaptive neuro-fuzzy inference systems (ANFIS) are particularly suitable for modelling complex systems with known input-output data sets. Such systems can be efficient in modelling non-linear, complex and ambiguous behaviour of cement-based materials undergoing single, dual or multiple damage factors of different forms (chemical, physical and structural). Due to the well-known complexity of sulfate attack on cement-based materials, the current work investigates the use of ANFIS to model the behaviour of a wide range of self-consolidating concrete (SCC) mixture designs under various high-concentration sodium sulfate exposure regimes including full immersion, wetting-drying, partial immersion, freezing-thawing, and cyclic cold-hot conditions with or without sustained flexural loading. Three ANFIS models have been developed to predict the expansion, reduction in elastic dynamic modulus, and starting time of failure of the tested SCC specimens under the various high-concentration sodium sulfate exposure regimes. A fuzzy inference system was also developed to predict the level of aggression of environmental conditions associated with very severe sodium sulfate attack based on temperature, relative humidity and degree of wetting-drying. The results show that predictions of the ANFIS and fuzzy inference systems were rational and accurate, with errors not exceeding 5%. Sensitivity analyses showed that the trends of results given by the models had good agreement with actual experimental results and with thermal, mineralogical and micro-analytical studies.

A Study on the Color Modelling Method for Color Picture Tube Color Display (CPT 색제시를 위한 색모델링 방법 연구)

  • 이응주
    • Journal of Korea Multimedia Society
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    • v.3 no.6
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    • pp.586-591
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    • 2000
  • Color pictures on CPT are generally affected by the receiver characteristic and the condition of exterior illuminants. Moreover, readjustment of incorrect color in the CPT causes color distortion on a given picture. This paper describes a color adjustment method for modelling of CPT at the view point of observer in the ordinary lighting condition. To develop this method, we proposed ways of luminance recompensation under the gamma transformation for the intensity of illuminant, hue/saturation compensation for the types of illuminant and control of specific color for the reference. Based on these method, a color correlation system is suggested with the goal of reducing the color errors which are represented due to the influence of reflectance component of illuminants, the gamma transformation of CPT and the frequently adjustment of reference scene to set a optimum color.

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Performance analysis on the geometric correction algorithms using GCPs - polynomial warping and full camera modelling algorithm

  • Shin, Dong-Seok;Lee, Young-Ran
    • Proceedings of the KSRS Conference
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    • 1998.09a
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    • pp.252-256
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    • 1998
  • Accurate mapping of satellite images is one of the most important Parts in many remote sensing applications. Since the position and the attitude of a satellite during image acquisition cannot be determined accurately enough, it is normal to have several hundred meters' ground-mapping errors in the systematically corrected images. The users which require a pixel-level or a sub-pixel level mapping accuracy for high-resolution satellite images must use a number of Ground Control Points (GCPs). In this paper, the performance of two geometric correction algorithms is tested and compared. One is the polynomial warping algorithm which is simple and popular enough to be implemented in most of the commercial satellite image processing software. The other is full camera modelling algorithm using Physical orbit-sensor-Earth geometry which is used in satellite image data receiving, pre-processing and distribution stations. Several criteria were considered for the performance analysis : ultimate correction accuracy, GCP representatibility, number of GCPs required, convergence speed, sensitiveness to inaccurate GCPs, usefulness of the correction results. This paper focuses on the usefulness of the precision correction algorithm for regular image pre-processing operations. This means that not only final correction accuracy but also the number of GCPs and their spatial distribution required for an image correction are important factors. Both correction algorithms were implemented and will be used for the precision correction of KITSAT-3 images.

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XCEL: Object-oriented Spreadsheet (XCEL: 객체지향 스프레드시트)

  • 최종명;유재우
    • Journal of KIISE:Software and Applications
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    • v.30 no.11
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    • pp.1102-1111
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    • 2003
  • Spreadsheet is one of the most widely used programming tool because of its ease of use, however there have been few researches on applying object-oriented techniques in developing spreadsheet applications. Generally, spreadsheet applications contain a lot of errors, and spreadsheet has some drawbacks such as low reusability and hard maintenance. In order to solve these problems, we introduce an object-oriented spreadsheet system, named XCEL. It enables users to develop applications using systematic techniques with data modelling method, and allows users to apply object-oriented technologies to spreadsheet programming. The data modelling method allows to define classes using XML and flowchart, and the spreadsheet represents an object with contiguous cells. XCEL has advantage that users can apply object-oriented technology to spreadsheet programming.

Modelling of noise-added saturated steam table using the neural networks (신경회로망을 사용한 노이즈가 첨가된 포화증기표의 모델링)

  • Lee, Tae-Hwan;Park, Jin-Hyun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2008.05a
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    • pp.205-208
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    • 2008
  • In numerical analysis numerical values of thermodynamic properties such as temperature, pressure, specific volume, enthalpy and entropy are required. But most of the thermodynamic properties of the steam table are determined by experiment. Therefore they are supposed to have measurement errors. In order to make noised thermodynamic properties corresponding to errors, random numbers are generated, adjusted to appropriate magnitudes and added to original thermodynamic properties. the neural networks and quadratic spline interpolation method are introduced for function approximation of these modified thermodynamic properties in the saturated water based on pressure. It was proved that the neural networks give smaller percentage error compared with quadratic spline interpolation. From this fact it was confirmed that the neural networks trace the original values of thermodynamic properties better than the quadratic interpolation method.

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Floating-Poing Quantization Error Analysis in Subband Codes System

  • Park, Kyu-Sik
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.1E
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    • pp.41-48
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    • 1997
  • The very purpose of subband codec is the attainment of data rate compression through the use of quantizer and optimum bit allocation for each decimated signal. Yet the question of floating-point quantization effects in subband codec has received scant attention. There has been no direct focus on the analysis of quantization errors, nor on design with quantization errors embedded explicitly in the criterion. This paper provides a rigorous theory for the modelling, analysis and optimum design of the general M-band subband codec in the presence of the floating-point quantization noise. The floating-point quantizers are embedded into the codec structure by its equivalent multiplicative noise model. We then decompose the analysis and synthesis subband filter banks of the codec into the polyphase form and construct an equivalent time-invariant structure to compute exact expression for the mean square quantization error in the reconstructed an equivalent time-invariant structure to compute exact expression for the mean square quantization error in the reconstructed output. The optimum design criteria of the subband codec is given to the design of the analysis/synthesis filter bank and the floating-point quantizer to minimize the output mean square error. Specific optimum design examples are developed with two types of filter of filter banks-orthonormal and biorthogonal filter bank, along with their perpormance analysis.

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Accuracy Simulation of Precision Rotary Motion Systems (회전운동 시스템의 정밀도 시뮬레이션 기술)

  • Hwang, Joo-Ho;Shim, Jong-Youp;Hong, Seong-Wook;Lee, Deug-Woo
    • Journal of the Korean Society for Precision Engineering
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    • v.28 no.3
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    • pp.285-291
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    • 2011
  • The error motion of a machine tool spindle directly affects the surface errors of machined parts. The error motions of the spindle are not desired errors in the three linear direction motions and two rotating motions. Those are usually due to the imperfect of bearings, stiffness of spindle, assembly errors, external force or unbalance of rotors. The error motions of the spindle have been needed to be decreased to desired goal of spindle's performance. The level of error motion is needed to be estimated during the design and assembly process of the spindle. In this paper, the estimation method for the five degree of freedom (5 D.O.F) error motions of the spindle is suggested. To estimate the error motions of the spindle, waviness of shaft and bearings, external force model was used as input data. And, the estimation models are considering geometric relationship and force equilibrium of the five degree of the freedom. To calculate error motions of the spindle, not only imperfection of the shaft, bearings, such as rolling element bearing, hydrostatic bearing, and aerostatic bearing, but also driving elements such as worm, pulley, and direct driving motor systems, were considered.