• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.399-401
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• 1989

Utilizing an interconnected set of neuron-like elements, the present study is to provide a method of parameter estimation for a second order linear time invariant system of self-tuning controller. The result from the proposed method is evaluated by comparing with those obtained by the recursive least square (RLS) identification algorithm and extended recursive least square (ERLS) algorithm, and it shows that, although the smoothness of system performance is still to be improved, the effectiveness of shorter computing time is demonstrated which may be of considerable value to real time computing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.3
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• pp.288-295
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• 2013

In this paper, we compare the existing channel estimation technique for 4S (Ship to Ship, Ship to Shore) maritime communications under AWGN channel model, Rician fading channel model, and Rayleigh fading channel model respectively. In general, the received signal is corrupted by multipath and ISI (Inter Symbol Interference). The estimation of a time-varying multipath fading channel is a difficult task for the receiver. Its performance can be improved if an appropriate channel estimation filter is used. The simulation is performed in MATLAB. In this simulation, we use the popular estimation algorithms, LMS (Least Mean Square) and RLS (Recursive Least-Squares) are compared with respect to AWGN, Rician and Rayleigh channels.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.20 no.4
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• pp.1-6
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• 2012

The accurate information of mass properties is required for the precise control of the spacecraft. The mass properties, mass and inertia, are changeable by some reasons such as consumption of propellant, deployment of solar panel, sloshing, environmental effect, etc. The gyro-based attitude data including noise and bias reduces the control accuracy so it needs to be compensated for improvement. This paper introduces a real-time inertia estimation method for the attitude determination of STSAT-3, Korea Science Technology Satellite. In this method we first filter the gyro noise with the Extended Kalman Filter(EKF), and then estimate the moment of inertia by using the filtered data from the EKF based on the Recursive Least Square(RLS).

• Journal of Power Electronics
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• v.18 no.2
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• pp.492-501
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• 2018

In the rotor-flux oriented control used in induction motors, the electrical parameters of the motors should be identified. Among these parameters, the mutual inductance and rotor resistance should be accurately tuned for better operations. However, they are more difficult to identify than the stator resistance and stator transient inductance. The rotor resistance and mutual inductance can change in operations due to flux saturation and heat generation. When detuning of these parameters occurs, the performance of the control is degenerated. In this paper, a novel method for the concurrent identification of the two parameters is proposed based on recursive least square estimation and model reference adaptive control.

• The Transactions of the Korean Institute of Power Electronics
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• v.5 no.6
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• pp.575-583
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• 2000

In this paper, a novel estimation alogrithm of mechanical parameters in two-mass system proposed. The inertia of a load and a motor and the stiffness are estimated by using RLS(Recursive Least Square) algorithm and acceleration information of motor. The effectiveness of the proposed scheme is verified with simulation and experiments results.

• Structural Engineering and Mechanics
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• v.34 no.1
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• pp.1-14
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• 2010

The innovative intelligent fuzzy weighted input estimation method which efficiently and robustly estimates the unknown time-varying input force in on-line is presented in this paper. The algorithm includes the Kalman Filter (KF) and the recursive least square estimator (RLSE), which is weighted by the fuzzy weighting factor proposed based on the fuzzy logic inference system. To directly synthesize the Kalman filter with the estimator, this work presents an efficient robust forgetting zone, which is capable of providing a reasonable compromise between the tracking capability and the flexibility against noises. The capability of this inverse method are demonstrated in the input force estimation cases of the plate structure system. The proposed algorithm is further compared by alternating between the constant and adaptive weighting factors. The results show that this method has the properties of faster convergence in the initial response, better target tracking capability, and more effective noise and measurement bias reduction.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.6
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• pp.1070-1079
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• 2016

In this paper, the design of recursive radial basis function neural networks based on incremental fuzzy c-means is introduced for processing the big data. Radial basis function neural networks consist of condition, conclusion and inference phase. Gaussian function is generally used as the activation function of the condition phase, but in this study, incremental fuzzy clustering is considered for the activation function of radial basis function neural networks, which could effectively do big data processing. In the conclusion phase, the connection weights of networks are given as the linear function. And then the connection weights are calculated by recursive least square estimation. In the inference phase, a final output is obtained by fuzzy inference method. Machine Learning datasets are employed to demonstrate the superiority of the proposed classifier, and their results are described from the viewpoint of the algorithm complexity and performance index.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.517-522
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• 2019

This paper proposes a new motor parameter estimation method. Because the proposed method is based on difference equations, it does not affect the error in the voltage magnitude so called dead-time effect. Information on the motor constant may be needed to improve the motor control performance. For example, a control technique called DTC (Direct Torque Control) requires a motor constant when calculating the torque and flux magnitude. As another example, in the case of predictive control, information on the motor parameters is required to generate voltage references. Because the constant of the motor fluctuates according to the driving environment, it is essential to estimate the correct motor constant because the control performance is degraded when incorrect motor information is used. In the proposed scheme, the motor constant estimated based on the voltage difference equation is obtained using the RLS (Recursive Least Square) technique. The RLS algorithm is applied to obtain the value through an iterative calculation so that the estimation performance is robust to noise. The simulation results carried out with surface mounted permanent magnet motors confirmed the validity of the proposed method.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.1
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• pp.51-57
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• 2011

Information of the lateral velocity and the sideslip angle in a vehicle is very useful in many active vehicle safety applications such as yaw stability control and rollover prevention. Because cost-effective sensors to measure the lateral velocity and the sideslip angle are not available, reliable algorithms to estimation them are necessary. In this paper, a sliding mode observer is designed to estimate the lateral velocity. The side slip angle is estimated using the recursive least square with the disturbance observer and the pseudo integral. The estimated parameters from the combined estimation method are updated recursively to minimize the discrepancy between the model and the physical plant, and any possible effects caused by disturbances. The performance of the proposed monitoring system is evaluated through simulations and experiments.

• Proceedings of the KIEE Conference
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• 2002.07a
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• pp.203-205
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• 2002

This paper presents the fault location estimation algorithm in transmission line using a recursive least square error method (RLSE). To minimize the computational burden of the digital relay a RLSE approach is used. Computer simulation results of the RLSE algorithm seem promising, indicating that it should be considered for further testing and evaluation.