• The Journal of the Acoustical Society of Korea
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• v.25 no.2E
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• pp.43-48
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• 2006

Abstract-Using the recursive generalized eigendecomposition method, we develop a recursive form solution to the data least squares (DLS) problem, in which the error is assumed to lie in the data matrix only. Simulations demonstrate that DLS outperforms ordinary least square for certain types of deconvolution problems.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.4
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• pp.7-13
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• 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.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.279-281
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• 2006

A Voltage Instability Predictor(VIP) estimates the proximity of a power system to voltage collapse in real time. Voltage Instability Index(Z-index) from VIP algorithm is estimated using LS(Least Square) method. But this method has oscillations and noise of result due to the system's changing conditions. To suppress oscillations, a larger data window needs to be used. In this paper. I propose the new other method which improves that weakness. It uses RLS(Recursive Least Square) to estimate voltage instability index without a large moving data window so this method is suitable for on-line monitor and control in real time. In order to verify effectiveness of the algorithm using RLS method, the method is tested on HydroQuebec system in real time digital simulator(HYPERSIM).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.7
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• pp.3543-3557
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• 2017

Compression is a very important technique for remotely sensed hyperspectral images. The lossless compression based on the recursive least square (RLS), which eliminates hyperspectral images' redundancy using both spatial and spectral correlations, is an extremely powerful tool for this purpose, but the relatively high computational complexity limits its application to time-critical scenarios. In order to improve the computational efficiency of the algorithm, we optimize its serial version and develop a new parallel implementation on graphics processing units (GPUs). Namely, an optimized recursive least square based on optimal number of prediction bands is introduced firstly. Then we use this approach as a case study to illustrate the advantages and potential challenges of applying GPU parallel optimization principles to the considered problem. The proposed parallel method properly exploits the low-level architecture of GPUs and has been carried out using the compute unified device architecture (CUDA). The GPU parallel implementation is compared with the serial implementation on CPU. Experimental results indicate remarkable acceleration factors and real-time performance, while retaining exactly the same bit rate with regard to the serial version of the compressor.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.3
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• pp.224-229
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• 2012

In this paper, we propose a correction method for astronomical telescope using recursive least square method. There are two ways to move a telescope : equatorial operation and altazimuth operation. We must align polar axis of a equatorial telescope with the north celestial pole and adjust the horizontal axis of a altazimuth telescope exactly to match the celestial coordinate system with the telescope coordinate system. This process needs time and expertise. We can skip existing process and correct a tracking error easily by deriving the relationship of the celestial coordinate system and the telescope coordinate system using the proposed correction method. We obtain the coordinate of a celestial body in the celestial coordinate system and the telescope coordinate system and derive a transformation matrix through the obtained coordinate. We use recursive least square method to estimate the unknown parameters of a transformation matrix. Finally, we implement a telescope control system using a microprocessor and verify the performance of the correction method. Through an experiment, we show the validity of the proposed correction method.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.48 no.3
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• pp.139-143
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• 1999

This paper is on realization of the speed-sensorless vector control of an induction motor using the RLS(Recursive Least Square) algorithm. The speed estimator is including the RLS algorithm and a rotor flux observer. The RLS algorithm has speed and rotor time constant as parameter vectors and rotor flux observer is designed to have robustness to stator resistance variation and through the IP(Integral and Proportional) speed controller stable performance is obtained for estimating rotor speed. Finally the total algorithm are realized in induction motor drive system and its effectiveness is verified.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.2
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• pp.248-254
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• 2018

In this paper, a Monte Carlo-based Recursive Least Square(MC-RLS) method is presented to directly identify the inverse model of the dynamical system. Although a RLS method has been used for the identification based on the deterministic data in the closed loop controlled form, it would be better for RLS to identify the model with random data. In addition, the inverse model obtained by inverting the identified forward model may not work properly. Therefore, MC-RLS can be used for the inverse model identification without proceeding a numerical inversion of an identified forward model. The performance of the proposed method is verified through experimental studies on a control moment gyroscope.

• The Transactions of the Korean Institute of Power Electronics
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• v.20 no.6
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• pp.534-539
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• 2015

The DC overhead line voltage of an electric railway substation swings depending on the accelerating and regenerative-braking energy of trains, and it deteriorates the energy quality of the electric facility in the DC railway substation and restricts the powering and braking performance of subway trains. Recently, an energy storage system or a regenerative inverter has been introduced into railway traction substations to diminish both the variance of the overhead line voltage and the peak power consumption. In this study, the variance of the overhead line voltage in a DC railway substation is modelled by RC parallel circuits in each feeder, and the RC parameters are estimated using the recursive least mean square (RLMS) scheme. The forgetting factor values for the RLMS are selected using simulated annealing optimization, and the modelling scheme of the overhead line voltage variation is evaluated through raw data measured in a downtown railway substation.

• Journal of Power System Engineering
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• v.2 no.2
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• pp.73-80
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• 1998

The identification of drilling joint dynamics which consists of drilling and structural dynamics and the on-line time series detection of malfunction process is substantial not only for the investigation of the static and dynamic characteristics but also for the analytic realization of diagnostic and control systems in drilling. Therefore, We have discussed on the comparative assessment of two recursive time series modeling algorithms that can represent the drilling operation and detect the abnormal geometric behaviors in precision roundshape machining such as turning, drilling and boring in precision diemaking. For this purpose, simulation and experimental work were performed to show the malfunctional behaviors for drilling operation. For this purpose, a new two recursive approach (Recursive Extended Instrument Variable Method : REIVM, Recursive Least Square Method : RLSM) may be adopted for the on-line system identification and monitoring of a malfunction behavior of drilling process, such as chipping, wear, chatter and hole lobe waviness.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.9C
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• pp.735-742
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• 2010

In this paper, we propose adaptive algorithms for interference cancellation in RF repeaters with multiple transmit and receive antennas. When multiple antennas are used in a repeater, the imperfect isolation between transmit and receive antennas causes the feedback interference which is modeled as multi-input multi-output (MIMO) channel. To remove the feedback interference, we derive the least mean square (LMS) algorithm and the recursive least squares (RLS) algorithm for interference cancellation based on adaptive signal processing techniques. Through computer simulations for the proposed algorithms, we analyze the convergence characteristics and compare the steady-state performance for interference cancellation.