• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.3
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• pp.311-319
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• 1992

In this paper, a direct adaptive pole placement controller for an unknown linear time-invariant single-input single-output nonminimum phase plant is proposed. To design this direct adaptive pole placement controller, the auxiliary signals are introduced. Consequently, a linear equation error model is formulated for estimating both the controller parameters and the additional auxiliary parameters. To estimate the controller parameters and the additional auxiliary parameters, the exponentially weighted least-squares algorithm is implemented, and a method of selecting the characteristic polynomials of the sensitivity function filters is proposed. In this method, all the past measurement data are weighted exponentially. A series of simulations for a nonminimum phase plant is presented to illustrate some features of both the parameter estimation and the output response of this adaptive pole placement controller.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.04b
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• pp.262-266
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• 1995

This paper presents a new adaptive-neuro control scheme to control the velocity and position of SCARA robot with parameter uncertainties. The adaptive control of linear system found wiedly in many areas of control application. While techniques for the adaptive control of linear systems have been well-established in the literature, there are a few corresponding techniques for nonlinear systems. In this paper an attempt is made to present a newcontrol scheme for theadaptive control of ponlinear robot based on a feedforward neural network. The proposed approach incorporates a neuro controller used within a reinforcement learning framework, which reduces the problem to one of learning a stochastic approximation of an unknown average error surface Emphasis is focused on the fact that the adaptive-neuro controoler dose not need any input/output information about the controlled system. The simulation result illustrates the effectiveness of the proposed adaptive-neuro control scheme.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.12
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• pp.73-79
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• 2003

Recently, the tole-robot operations to an unstructured environment have been widely researched. The human's interaction with the tole-robot system can be used to improve robot operation and performance for an unknown environment. The exact modeling based on real environment is fundamental and important process for this interaction. In this paper, we propose an extrinsic parameter calibration and data augmentation method that only uses a circular jig in the hand-eye laser virtual environment. Compared to other methods, easier estimation and overlay can be done by this algorithm. Experimental results using synthetic graphic demonstrate the usefulness of the proposed algorithm.

• Communications for Statistical Applications and Methods
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• v.25 no.4
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• pp.411-430
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• 2018

The Bayesian approach is a suitable alternative in constructing appropriate models for observed record values because the number of these values is small. This paper provides an objective Bayesian analysis method for upper record values arising from the Rayleigh distribution. For the objective Bayesian analysis, the Fisher information matrix for unknown parameters is derived in terms of the second derivative of the log-likelihood function by using Leibniz's rule; subsequently, objective priors are provided, resulting in proper posterior distributions. We examine if these priors are the PMPs. In a simulation study, inference results under the provided priors are compared through Monte Carlo simulations. Through real data analysis, we reveal a limitation of the appropriate confidence interval based on the maximum likelihood estimator for the scale parameter and evaluate the models under the provided priors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.9-15
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• 2011

This paper suggested the fast and easy method of the dielectric constant measurement for planar dielectrics using a microstrip line. The complex permittivity and permeability were presented by the first reflection and transmission coefficient which were derived from the scattering parameters. This method was verified by the measurement of a known planar dielectric using a microstrip line. This method can be applied to the dielectric constant measurement of unknown planar dielectric.

• International Journal of Aeronautical and Space Sciences
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• v.9 no.1
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• pp.129-136
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• 2008

An roll-pitch-yaw integrated autopilot for missiles is designed for compensation of dynamics coupling. The proposed autopilot is based on the classical control technique. The gains of the proposed autopilot are optimized by using co-evolutionary augmented Lagrangian method(CEALM). Several cost functions are compared in order to find feasible control gains. For a case that a bank angle of missiles is unknown, multiple models are used in the autopilot optimization. In nonlinear simulations as well as linear simulations, the proposed autopilot provided good performances.

• Applied Microscopy
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• v.41 no.1
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• pp.75-79
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• 2011

For quantitative analysis of nano-crystal structure, we reported the accuracy improvement method of lattice parameters measured from electron diffraction. For calculation of Au lattice parameters used as a standard crystal structure, it was considered two different acquisition methods (detector and enegy-filter) and three different calculation methods (conventional, least-square and regression fit). As a result, the measurement reliability could be enhanced by using CCD camera which gives higher performance, while energy-filtering did not affect the improvement the camera constant accuracy. Also, the accuracy of lattice parameters could be improved up to $10^{-4}$ order by regression fitting with correction formula. Finally, it is expected that the combination of regression fitting and intensity extraction from energy-filtered precession electron diffraction gives a solution of quantitative structure analysis for unknown nano-crystals.

• 전기의세계
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• v.18 no.1
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• pp.15-23
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• 1969

A lot of recent researches have shown that a Pseudo Random Binary Signal is a quite effective test signal to measure the impulse response of a plant. Generally speaking, however, such a response itself is not satisfactory to determine the appropriate control parameters or control inputs. Here, the author intends to estimate the unknown parameters of the First Order Plant with Dead Time by means of correlation method using M-sequence signal. The time constant T and the dead time L of the plant are eatimated with one tracking loop by automatically adjusting delay time .tau. of M-sequence signal according to variations of T and L. In this paper, a three level M-sequence signal is used as a test signal in order to avoid troublesome operations to calculate partial derivatives of a given performance index with respect to the parameters which are usually required in the Model Method. Several experiments with analogue computer using low pass filters as averaging circuits showed good results as expected.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.563-565
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• 1998

In this paper, we are proposed optimization method of fuzzy model in order to complex and nonlinear system. In the fuzzy modeling, a premise identification is very important to describe the charateristics of a given unknown system. Then, the proposed fuzzy model implements system structure and parameter identification, using the fuzzy inference method and genetic algorithms. Inference method for fuzzy model presented in our paper include the simplified inference and linear inference. Time series data for gas furance and sewage treatment process are used to evaluate the performance of the proposed model. Also, the performance index with weighted value is proposed to achieve a balance between the results of performance for the training and testing data.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.3
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• pp.11-15
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• 1985

A Novel design of MRAC for achieving independent tracking and regulation objectives by applying Pad e-Type approximation in the controller parameter estimation is presented. The design of the controller is done with the unknown plant parameters from the first. The result of the design is a simple control scheme with the reduction of estimation para-meters. The performance of rho proprosed contiol structure in tracking and regulation is compared with the other method by computer simulation.