• Title/Summary/Keyword: Recursive least squares method

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Temperature control of a batch PMMA polymerization reactor using adaptive predictive control algorithm

  • Huh, Yun-Jun;Ahn, Sung-Mo;Rhee, Hyun-Ku
    • 제어로봇시스템학회:학술대회논문집
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    • 1995.10a
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    • pp.51-55
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    • 1995
  • An adaptive unified predictive control (UPC) algorithm is applied to a batch polymerization reactor for poly(methyl methancrylate) (PMMA) and the effects of controller parameters are investigated. Computational studies are performed for a batch polymerization system model developed in this study. A transfer function in parametric form is estimated by recursive least squares (RLS) method, and the UPC algorithm is implemented to control the reactor temperature on the basis of this transfer function. The adaptive unified predictive controller shows a better performance than the PID controller for tracking set point changes, especially in the latter part of reaction course when gel effect becomes significant. Various performance can be acquired by selecting adequate values for parameters of the adaptive unified predictive controller; in other words, the optimal set of parameters exists for a given set of reaction conditions and control objective.

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Frequency-Domain RLS Algorithm Based on the Block Processing Technique (블록 프로세싱 기법을 이용한 주파수 영역에서의 회귀 최소 자승 알고리듬)

  • 박부견;김동규;박원석
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.240-240
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    • 2000
  • This paper presents two algorithms based on the concept of the frequency domain adaptive filter(FDAF). First the frequency domain recursive least squares(FRLS) algorithm with the overlap-save filtering technique is introduced. This minimizes the sum of exponentially weighted square errors in the frequency domain. To eliminate discrepancies between the linear convolution and the circular convolution, the overlap-save method is utilized. Second, the sliding method of data blocks is studied Co overcome processing delays and complexity roads of the FRLS algorithm. The size of the extended data block is twice as long as the filter tap length. It is possible to slide the data block variously by the adjustable hopping index. By selecting the hopping index appropriately, we can take a trade-off between the convergence rate and the computational complexity. When the input signal is highly correlated and the length of the target FIR filter is huge, the FRLS algorithm based on the block processing technique has good performances in the convergence rate and the computational complexity.

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Control of DC Servo Motor using PID Controller Self-Tuning (PID제어기의 자기동조를 이용한 직류 서보전동기의 위치제어)

  • Kim, Gwon-Sub;Lee, Oh-Keol;Kim, Sang-Hyo;Ko, Tai-Eun
    • Proceedings of the KIEE Conference
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    • 1996.07b
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    • pp.1113-1115
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    • 1996
  • The servo system requires faster and more accurate dynamic responses. A new technique for the position control of DC servo motors is presented in this paper. The proposed technique employs a Self Tuning Regulator Proportional Integral Derivative(STR PID) position control systems in order to improve the dynamic performance of a DC servo motor. Recursive -least -squares (RLS) method is used in order to estimate the STR PID coefficients, $K_P$, $K_I$, and $K_D$. In order to consider dynamics such as voltage, angular velocity, and rotor angle, the above method was applied position control system.

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Probabilistic damage detection of structures with uncertainties under unknown excitations based on Parametric Kalman filter with unknown Input

  • Liu, Lijun;Su, Han;Lei, Ying
    • Structural Engineering and Mechanics
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    • v.63 no.6
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    • pp.779-788
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    • 2017
  • System identification and damage detection for structural health monitoring have received considerable attention. Various time domain analysis methodologies based on measured vibration data of structures have been proposed. Among them, recursive least-squares estimation of structural parameters which is also known as parametric Kalman filter (PKF) approach has been studied. However, the conventional PKF requires that all the external excitations (inputs) be available. On the other hand, structural uncertainties are inevitable for civil infrastructures, it is necessary to develop approaches for probabilistic damage detection of structures. In this paper, a parametric Kalman filter with unknown inputs (PKF-UI) is proposed for the simultaneous identification of structural parameters and the unmeasured external inputs. Analytical recursive formulations of the proposed PKF-UI are derived based on the conventional PKF. Two scenarios of linear observation equations and nonlinear observation equations are discussed, respectively. Such a straightforward derivation of PKF-UI is not available in the literature. Then, the proposed PKF-UI is utilized for probabilistic damage detection of structures by considering the uncertainties of structural parameters. Structural damage index and the damage probability are derived from the statistical values of the identified structural parameters of intact and damaged structure. Some numerical examples are used to validate the proposed method.

Vibration Characteristics of Cantilever Beam with a Crack (단일 크랙을 갖는 외팔보의 진동특성)

  • Kim, Jong-Do;Jo, Ji-Yun;Yoon, Moon-Chul
    • Journal of the Korean Society of Manufacturing Technology Engineers
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    • v.23 no.3
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    • pp.223-229
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    • 2014
  • In this paper, the natural frequency and damping ratio are analyzed with the acceleration signal of an Euler-Bernoulli beam using the impact hammer test. The results are presented according to crack depth and position using the recursive least squares method. The results are compared and investigated with FEM analysis of CATIA. Both methods agree well with each other regarding the natural mode characteristics. The captured acceleration can be used for the calculation of the natural frequency and damping ratio using time series methods that are based on the measured acceleration. Using these data, a recursive time series model with the acceleration signal was configured and the behaviors of the natural frequency and damping ratio were investigated and analyzed. Finally, the results can be used for the prediction of crack position and depth under different crack conditions for an Euler-Bernoulli beam.

Number Plate Detection System by Using the Night Images

  • Yoshimori, S.;Mitsukura, Y.;Fukumi, M.;Akamatsu, N.
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1249-1253
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    • 2003
  • License plate recognition is very important in an automobile society. This is because, since plate detection accuracy has large influence on subsequent number recognition, it is very important. However, it is very difficult to do it, because a background and a body color of cars are similar to that of the license plate. In this paper, we propose a new thresholds determination method in the various background by using the real-coded genetic algorithm (RGA). By using RGA, the most likely plate colors are decided under various lighting conditions. First, the average brightness Y values of images are calculated. Next, relationship between the Y value and the most likely plate color thresholds (upper and lower bounds)are obtained by RGA. The relationship between thresholds decided from RGA and brightness average is aproximate by using the recursive least squares (RLS) algorithm. In the case of plate detection, thresholds are decided from these functions.

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Self-Tuning Adaptive Control Using State Observer (상태 관측기를 이용한 자기-동조 적응 제어)

  • Kim, Yoon-Ho;Yoon, Byung-Do;Oh, Gi-Hong
    • Proceedings of the KIEE Conference
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    • 1991.11a
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    • pp.223-226
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    • 1991
  • In this paper, the problem of designing on adaptive controller for dc drives using state observers, which is operated under varying load conditions, is addressed. A robust self-tuning controller that can track a constant reference and reject constant load disturbances is also studied. This scheme is very attractive since the estimates of system parameters are available in real time. Parameter estimation is based on the recursive least squares method and the control algorithm of the pole placement technique. Also, state observer systems are applied. State observer systems are required to estimate the states quickly and exactly without being affected by the disturbances.

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A study on the improvement of DGPS positioning accuracy using a kalman filtering method (칼만 필터를 이용한 DGPS의 위치측정 정확도 향상에 관한 연구)

  • 주세철;오정헌;이창복;김영욱;김기두
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.5
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    • pp.109-178
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    • 1996
  • For each reference station and user, the proposed DGPS system is implemented by a GPS module and a modem. The reference station makes plans of the receiving schedule from the satellite sets at each period and then provides the correction data for various satellite sets in a period. Users can utilize the correction data continuously and efficiently through the recursive least squares lattice filters. Furthermore, after taking DGPS techniques, we can improve the positioning accuracy using a kalman filter by decreasing anti-common errors between a reference station and a user. Experimental results show the positioning accuracy of better than 5 meters in almost real time.

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Study of Harmonic Sources Management Method using Control Chart (컨트롤 차트를 이용한 고조파 전압 왜곡 발생원 관리기법 연구)

  • Han, Jong-Hoon;Lee, Key-Byung;Jang, Gil-Soo;Park, Chang-Hyun
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.197-198
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    • 2011
  • A technique to manage harmonic pollution at the point of common coupling (PCC) has been presented using a control chart. The recursive least-squares technique has been used to estimate the parameters of the Thevenin equivalent load model. With the estimated data from the measured voltage and current waveform at the PCC during certain period violating upper control limit, the individual contributions to the distortion of voltage waveform at an interested harmonic frequency have been calculated and shown by simple graph.

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The development of semi-active suspension controller based on error self recurrent neural networks (오차 자기순환 신경회로망 기반 반능동 현가시스템 제어기 개발)

  • Lee, Chang-Goo;Song, Kwang-Hyun
    • Journal of Institute of Control, Robotics and Systems
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    • v.5 no.8
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    • pp.932-940
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    • 1999
  • In this paper, a new neural networks and neural network based sliding mode controller are proposed. The new neural networks are an mor self-recurrent neural networks which use a recursive least squares method for the fast on-line leammg. The error self-recurrent neural networks converge considerably last than the back-prollagation algorithm and have advantage oi bemg less affected by the poor initial weights and learning rate. The controller for suspension system is designed according to sliding mode technique based on new proposed neural networks. In order to adapt shding mode control mnethod, each frame dstance hetween ground and vehcle body is estimated md controller is designed according to estimated neural model. The neural networks based sliding mode controller approves good peiformance throllgh computer sirnulations.

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