• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.441-444
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• 1989

This correspondence presents a recursive estimation algorithm which, unlike conventional ones; updates the estimates only when a sufficient improvement can be obtained with a bounded noise assumption, the resulting sequence of estimates is a sequence of convex sets(ellipsoids) in the parameter space. For the cases studied, the algorithm use less than 20 percent of the. data to update, the estimate and still acquired good accuracy for spectral estimation.

• Publications of The Korean Astronomical Society
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• v.7 no.1
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• pp.1-7
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• 1992

We may consider the following three fundamental epistemological questions concerning cosmology. Can cosmology at last understand the origin of the universe? Can computers at last create? Can life be formed at last synthetically? These questions are in some sense related to the liar paradox containing the self-reference and, therefore. may not be answered by recursive processes in finite time. There are, however. various implications such that the chaos may break the trap of the self-reference paradox. In other words, Goedel's incompleteness theorem would not apply to chaos, even if the chaos can be generated by recursive processes. Internal relations among cosmology, epistemology and chaos must be investigated in greater detail.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2005.11a
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• pp.45-46
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• 2005

In this paper, a passive telemetry sensor system using Unscented Kalman Filter(UKF) is proposed. Specially, to show the effective tracking performance of the UKF, we compared with the tracking performance of Recursive Least Square Estimation (RLSE) using linearization.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.419-423
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• 1996

These days, industrial robots are required to have high speed and high precision in doing various tasks. Recently, the adaptive control algorithms for those nonlinear robots have been developed. With spatial vector space, these adaptive algorithms including recursive implementation are simply described. Without sensing joint acceleration and computing the inversion of inertia matrix, these algorithms which include P.D. terms and feedforward terms have global tracking convergence. In this paper, the feasibility of the proposed control method is illustrated by applying to 2 DOF SCARA robot in DSP(Digital Signal Processing).

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.10a
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• pp.121-122
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• 2006

• Honam Mathematical Journal
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• v.41 no.4
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• pp.823-835
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• 2019

A solution for Nevanlinna-Pick interpolation problem with low complexity is constructed via non-recursive method. More precisely, a stable rational function satifying the given interpolation data in the complex right half plane is found by solving a homogeneous interpolation problem related to a minial interpolation problem for the given data in the right half plane together with its mirror-image data.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10a
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• pp.548-553
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• 1992

In this paper and recursive version of orthogonal ARMA identification algorithm is proposed. The basic algorithm is based on Gram-Schmidt orthogonalization of automatically selected basis functions from specified function space, but does not require explicit creation of orthogonal functions. By using two dimensional autocorrelations and crosscorrelations of input and output with constant data length, identification algorithm is extended to cope slowly time-varying or order-varying delayed system.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.4
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• pp.48-54
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• 1994

A recursive on-line algorithm with orthogonal ARMA identification is proposed for linear systems with unkonwn time delay, order, and parameters. The algorithm is based on the Gram-Schmidt orthogonalization of basis functions, and extendedto recursive form by using two dimensional autocorrelations and crosscorrelations of input and output with constant data length. The proposed algorith can cope with slowly time-varying or order-varying delayed system. Various simulations reveal the performance of the algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.1
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• pp.44-53
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• 2009

In this paper, Recursive Least Squares (RLS) and Fourier Transform Regression (FTR) methods for estimating stability and control derivatives of small unmanned helicopter are evaluated together with MMLE technique. Flight data simulated by using a commercial small-scale helicopter model are exploited to estimate the parameters with accuracies for hover and cruise modes. The performances of the system identification methods are also compared by analyzing the responses of the reconstructed systems using estimated derivatives.