• Title/Summary/Keyword: Recursive least squares method

Search Result 97, Processing Time 0.024 seconds

An Experimental Study on Realtime Estimation of a Nominal Model for a Disturbance Observer: Recursive Least Squares Approach (실시간 공칭 모델 추정 외란관측기에 관한 실험 연구: 재귀최소자승법)

  • Lee, Sang-Deok;Jung, Seul
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.22 no.8
    • /
    • pp.650-655
    • /
    • 2016
  • In this paper, a novel RLS-based DOB (Recursive Least Squares Disturbance Observer) scheme is proposed to improve the performance of DOB for nominal model identification. A nominal model can be generally assumed to be a second order system in the form of a proper transfer function of an ARMA (Autoregressive Moving Average) model. The RLS algorithm for the model identification is proposed in association with DOB. Experimental studies of the balancing control of a one-wheel robot are conducted to demonstrate the feasibility of the proposed method. The performances between the conventional DOB scheme and the proposed scheme are compared.

Estimation of Aerodynamic Coefficients for a Skid-to-Turn Missile using Neural Network and Recursive Least Square (신경회로망과 순환최소자승법을 이용한 Skid-to-Turn 미사일의 공력 파라미터 추정)

  • Kim, Yun-Hwan;Park, Kyun-Bub;Song, Yong-Kyu;Hwang, Ick-Ho;Choi, Dong-Kyun
    • Journal of the Korean Society for Aviation and Aeronautics
    • /
    • v.20 no.4
    • /
    • pp.7-13
    • /
    • 2012
  • This paper is to estimate aerodynamic coefficients needed to determine the missiles' controller design and stability from simulation data of Skid-to-Turn missile. Method of determining aerodynamic coefficients is to apply Neural Network and Recursive Least Square and results were compared and researched. Also analysing actual flight test data was considered and sensor noise was added. Estimate parameter of data with sensor noise added and estimated performance and reliability for both methods that did not need initial values. Both Neural Network and Recursive Least Square methods showed excellent estimate results without adding the noise and with noise added Neural Network method showed better estimate results.

L1 norm-recursive least squares algorithm for the robust sparse acoustic communication channel estimation (희소성 음향 통신 채널 추정 견실화를 위한 백색화를 적용한 l1놈-RLS 알고리즘)

  • Lim, Jun-Seok;Pyeon, Yong-Gook;Kim, Sungil
    • The Journal of the Acoustical Society of Korea
    • /
    • v.39 no.1
    • /
    • pp.32-37
    • /
    • 2020
  • This paper proposes a new l1-norm-Recursive Least Squares (RLS) algorithm which is numerically more robust than the conventional l1-norm-RLS. The l1-norm-RLS was proposed by Eksioglu and Tanc in order to estimate the sparse acoustic channel. However the algorithm has numerical instability in the inverse matrix calculation. In this paper, we propose a new algorithm which is robust against the numerical instability. We show that the proposed method improves stability under several numerically erroneous situations.

Compensatory cylindricity control of the C.N.C. turing process (컴퓨터 수치제어 선반에서의 진원통도 보상제어)

  • 강민식;이종원
    • Transactions of the Korean Society of Mechanical Engineers
    • /
    • v.12 no.4
    • /
    • pp.694-704
    • /
    • 1988
  • A recursive parameter estimation scheme utilizing the variance perturbation method is applied to the workpiece deflection model during CNC turning process, in order to improve the cylindricity of slender workpiece. It features that it is based on exponentially weighted recursive least squares method with post-process measurement of finish surfaces at two locations and it does not require a priori knowledge on the time varying deflection model parameter. The measurements of finish surfaces by using two proximity sensors mounted face to face enable one to identify the straightness, guide-way, run-out eccentricity errors. Preliminary cutting tests show that the straightness error of the finish surface due to workpiece deflection during cutting is most dominant. Identifying the errors and recursive updating the parameter, the off-line control is carried out to compensate the workpiece deflection error, through single pass cutting. Experimental results show that the proposed method is superior to the conventional multi-pass cutting and the direct compensation control in cutting accuracy and efficiency.

Real- Time Estimation of the Ventricular Relaxation Time Constant

  • Chun Honggu;Kim Hee Chan;Sohn Daewon
    • Journal of Biomedical Engineering Research
    • /
    • v.26 no.2
    • /
    • pp.87-93
    • /
    • 2005
  • A new method for real-time estimating left ventricular relaxation time constant (T) from the left ventricular (LV) pressure waveform, based on the isovolumic relaxation model, is proposed. The presented method uses a recursive least squares (RLS) algorithm to accomplish real-time estimation. A new criterion to detect the end-point of the isovolumic relaxation period (IRP) for the estimation of T is also introduced, which is based on the pattern analysis of mean square errors between the original and reconstructed pressure waveforms. We have verified the performance of the new method in over 4,600 beats obtained from 70 patients. The results demonstrate that the proposed method provides more stable and reliable estimation of τ than the conventional 'off-line' methods.

Performance Analysis of the Robust Least Squares Target Localization Scheme using RDOA Measurements

  • Choi, Ka-Hyung;Ra, Won-Sang;Park, Jin-Bae;Yoon, Tae-Sung
    • Journal of Electrical Engineering and Technology
    • /
    • v.7 no.4
    • /
    • pp.606-614
    • /
    • 2012
  • A practical recursive linear robust estimation scheme is proposed for target localization in the sensor network which provides range difference of arrival (RDOA) measurements. In order to radically solve the known practical difficulties such as sensitivity for initial guess and heavy computational burden caused by intrinsic nonlinearity of the RDOA based target localization problem, an uncertain linear measurement model is newly derived. In the suggested problem setting, the target localization performance of the conventional linear estimation schemes might be severely degraded under the low SNR condition and be affected by the target position in the sensor network. This motivates us to devise a new sensor network localization algorithm within the framework of the recently developed robust least squares estimation theory. Provided that the statistical information regarding RDOA measurements are available, the estimate of the proposition method shows the convergence in probability to the true target position. Through the computer simulations, the omnidirectional target localization performance and consistency of the proposed algorithm are compared to those of the existing ones. It is shown that the proposed method is more reliable than the total least squares method and the linear correction least squares method.

New approach method of finite difference formulas for control algorithm (제어 알고리즘 구현을 위한 새로운 미분값 유도 방법)

  • Kim, Tae-Yeop
    • Journal of IKEEE
    • /
    • v.23 no.3
    • /
    • pp.817-825
    • /
    • 2019
  • Difference equation is useful for control algorithm in the microprocessor. To approximate a derivative values from sampled data, it is used the methods of forward, backward and central differences. The key of computing discrete derivative values is the finite difference coefficient. The focus of this paper is a new approach method of finite difference formula. And we apply the proposed method to the recursive least squares(RLS) algorithm.

An Accurate Estimation of a Modal System with Initial Conditions (ICCAS 2004)

  • Seo, In-Yong;Pearson, Allan E.
    • 제어로봇시스템학회:학술대회논문집
    • /
    • 2004.08a
    • /
    • pp.1694-1700
    • /
    • 2004
  • In this paper, we propose the AWLS/MFT (Adaptive Weighed Least Squares/ Modulation Function Technique) devised by A. E. Pearson et al. for the transfer function estimation of a modal system and investigate the performance of several algorithms, the Gram matrix method, a Luenberger Observer (LO), Least Squares (LS), and Recursive Least Squares (RLS), for the estimation of initial conditions. With the benefit of the Modulation Function Technique (MFT), we can separate the estimation problem into two phases: the transfer function parameters are estimated in the first phase, and the initial conditions are estimated in the second phase. The LO method produces excellent IC estimates in the noise free case, but the other three methods show better performance in the noisy case. Finally, we compared our result with the Prony based method. In the noisy case, the AWLS and one of the three methods - Gram matrix, LS, and RLS- show better performance in the output Signal to Error Ratio (SER) aspect than the Prony based method under the same simulation conditions.

  • PDF

On the Complex-Valued Recursive Least Squares Escalator Algorithm with Reduced Computational Complexity

  • Kim, Nam-Yong
    • The Journal of Korean Institute of Communications and Information Sciences
    • /
    • v.34 no.5C
    • /
    • pp.521-526
    • /
    • 2009
  • In this paper, a complex-valued recursive least squares escalator filter algorithm with reduced computational complexity for complex-valued signal processing applications is presented. The local tap weight of RLS-ESC algorithm is updated by incrementing its old value by an amount equal to the local estimation error times the local gain scalar, and for the gain scalar, the local input autocorrelation is calculated at the previous time. By deriving a new gain scalar that can be calculated by using the current local input autocorrelation, reduced computational complexity is accomplished. Compared with the computational complexity of the complex-valued version of RLS-ESC algorithm, the computational complexity of the proposed method can be reduced by 50% without performance degradation. The reduced computational complexity of the proposed algorithm is even less than that of the LMS-ESC. Simulation results for complex channel equalization in 64QAM modulation schemes demonstrate that the proposed algorithm has superior convergence and constellation performance.

The Efficient Implementation of DGPS System with Low Cost GPS modules Using a Recursive Least Squares Lattice Filtering Method (RLSLF 방식을 적용하여 저가의 GPS 모듈로 구성된 DGPS 시스템의 효율적인 구현)

  • 이창복;주세철;김기두;김영범
    • Journal of the Korean Institute of Telematics and Electronics B
    • /
    • v.32B no.10
    • /
    • pp.1338-1346
    • /
    • 1995
  • In this paper, we suggest the implementation of a DGPS system using two low cost commercial C/A code GPS modules and modems and its efficient operational techniques to provide DGPS service which guarantees the position accuracy of better than 10 meters for more users. The proposed DGPS system can be implemented easil at low cost because it needs a GPS module and a modem for each reference station and user. The reference station makes plans of the receiving schedule from the satellite set at each period and then provides the correction data for various satellite sets in a period. The main contribution of this paper is that users can utilize the correction data continuously and efficiently through the recursive least squares lattice filtering method. Experimental results show the position accuracy of better than 10 meters using the suggested DGPS system in almost real time.

  • PDF