• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.04a
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• pp.217-220
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• 2005

The RPO algorithm is a recently developed tool in the area of reinforcement Loaming, And it has been shown In be very successful in several application problems. In this paper, we consider a robot-control problem utilizing a modified RPO algorithm in which its critic network is adapted via RLS(Recursive Least Square) algorithm. We also developed a MATLAB-based animation program, by which the effectiveness of the training algorithms were observed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.238-242
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• 2002

In this paper. we consider an OFDM system with cochannel interference and the use of adaptive antenna arrays to suppress such interference. Based on the conventional RLS criterion, we derive a new Recursive Least Square (RLS) adaptive beamforming algorithm for antenna arrays applied in an OFDM system. Computer simulation shows that. when applied to the OFDM system. the proposed algorithm is capable of combating cochannel interference in both AWGN channel and multipath Rayleigh fading channel with AWGN.

• Proceedings of the KIEE Conference
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• 2007.10a
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• pp.433-434
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• 2007

In this paper, active control of noise in a HVAC duct is considered. Most adaptive control filters have used FIR structures based on filtered-x LMS algorithms. But, the IIR structures are more desirable for the active control of duct noise in order to remove the poles introduced by the acoustic feedback and presented an algorithm to adjust the coefficients of an IIR filter using the recursive least mean square (RLMS) algorithm. A smoothed LMS algorithm is proposed to improve a convergent speed of filter parameters when the noise is wide band and power of input is time varying. And computer simulations have performed to show the effectiveness of the proposed algorithm.

• Journal of Electrical Engineering and Technology
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• v.7 no.1
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• pp.132-140
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• 2012

A non-conservative robust Kalman filter (NCRKF) is applied to flight data to identify the aerodynamic derivatives of an unmanned autonomous vehicle (UAV). The NCRKF is formulated using UAV lateral motion data and then compared with results from the conventional Kalman filter (KF) and the recursive least square (RLS) method. A superior performance for the NCRKF is demonstrated by simulation and real flight data. The NCRKF is especially effective in large uncertainties in vehicle modeling and in measuring flight data. Thus, it is expected to be useful in missile and aircraft parameter identification.

• Proceedings of the KIEE Conference
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• 1999.07a
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• pp.382-384
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• 1999

We propose a new method for detecting Backemf of a motor and estimating parameters of a motor using Recursive Least Square Estimator. The motor speed is obtained from the estimated parameters. We experiment the PID speed controller with the estimated speed.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.11 no.8
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• pp.1428-1436
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• 2000

An adaptive predistorter linearizer suitable for the DSP implementation is proposed. Predistortion is performed by the DSP instead of the analog predistorter. RLS algorithm is employed for the optimization process to minimize the errors between the predistorter and postdistorter output signals. Computer simulation results for our linearizer show good performance.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.7
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• pp.1360-1365
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• 2011

Electro-hydraulic servo motor is used to a lot of in the field of industrial equipment which requires one of the control functions among pressure, flow, and power output. In this paper, linear discrete reference model of the electro-hydraulic servo motor system are made for 1-step ahead predictive control. The parameters of electro-hydraulic servo motor system are estimated using the recursive least square method. 1-step ahead predictive model output of electro-hydraulic servo motor system corresponded to reference model output in spite of estimated parameters are not meet real parameters. Control performance affections are studied due to the forgetting factors variation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.4
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• pp.961-971
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• 1996

The effect of inband TDMA narrow band jammers to DS-CDMA system performance and the suppression techniques are investigated using Monte Carlo simulations. TIA stantard North American Digital Cellular wea used as jammer. Levinson Dubin and conventional recursive least square algorithm were emphasized since these techniques can be implemented with a few DSPs for CDMA application. Two filter structures, i.e., complex suppression filter and real suppression filter in each inphase and quadrature channels, are investigated and their performances are compared. Complex suppression filter with Levinson Durbin algorithm of 20msec updata rate is the most promising with respect to implementation and performance poit of view. Implementation feasibility is discussed and the channel capacity lost by suppression is computed.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.38 no.3
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• pp.247-255
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• 1989

This paper proposes an error model with integral action and a pole-place-ment self-tuning controller for robot manipulators in task coordinates. The controller can reject the offset due to any load disturbance without a detailed description of the robot dynamics. The error model parameters are estimated by the recursive least square identification algorithms, and controller parameters are determined by the pole-placement method. A computer simulation study has been conducted to demonstrate the performance of the proposed control system in task coordinates for a 3-joint and 2-link spatial robot manipulator with payload.

• Proceedings of the KIPE Conference
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• 2017.07a
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• pp.126-127
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• 2017

An accurate State Of Charge (SOC) estimation of battery is the most important technique for Electric Vehicles (EVs) and Energy Storage Systems (ESSs). In this paper a new integrated Unscented Kalman Filter-Particle Filter (UKF-PF) is employed to estimate the SOC of a $LiFePO_4$ battery cell and a significant improvement is obtained as compared to the other methods. The parameters of the battery is modeled by the second order Auto Regressive eXogenous (ARX) model and estimated by using Recursive Least Square (RLS) method to calculate value of each element in the model. The proposed algorithm is established by combining a parameter identification technique using RLS method with ARX model and an SOC estimation technique using UKF-PF.