• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.11
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• pp.93-101
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• 1993

The transfer function of vector-controlled induction motor is represented along with both unstructured and structured uncertainty such as the error of rotor time constant and current ripple. The low-pass-filter behavior of a magnetizing inductance gets rid of unstructured uncertainty in the transfer function. The robust controller to compensate variation of the transfer function is designed using simple P-I linear controllers. The coefficients of speed PI controller are determined from an overshoot and a rising time of system and the coefficients of model-following PI controller are obtained using the solution of Riccati equation of LQR control in the state space equation of the error system. Experimental results with the DSP-based model-following robust controller are shown a good robustness against the structured uncertainty of the motor.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.5 no.2
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• pp.25-37
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• 2001

We consider the finite element method applied to nonlinear Sobolev equation with smooth data and demonstrate for arbitrary order ($k{\geq}2$) finite element spaces the optimal rate of convergence in $L_{\infty}\;W^{1,{\infty}}({\Omega})$ and $L_{\infty}(L_{\infty}({\Omega}))$ (quasi-optimal for k = 1). In other words, the nonlinear Sobolev equation can be approximated equally well as its linear counterpart. Furthermore, we also obtain superconvergence results in $L_{\infty}(W^{1,{\infty}}({\Omega}))$ for the difference between the approximate solution and the generalized elliptic projection of the exact solution.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.2
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• pp.184-191
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• 2003

A parallel manipulator has high stiffness and all the joint errors on the device are not accumulated at the end -effector unlike a serial manipulator. These are the reasons why the parallel manipulator has been widely used in many fields of industry. In the parallel manipulator, it is very important to predict the exact pose of the end-effector when we want to control the end-effector motion. Installation errors have to be determined in order to predict and control the actual position and pose of the end-effector. This paper presents an algorithm to find the whole 36 joint error components with joint clearance errors and measurement errors considered, when a link length measurement sensor is used and data more than 36 times are acquired for 36 different configurations. A simulation test using this algorithm is performed with a Matlab program which uses the Levenberg-Marquardt method that is known to be efficient for non-linear optimization.

• Journal of the Korean Data and Information Science Society
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• v.18 no.1
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• pp.73-80
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• 2007

Cointegration(together with VARMA(vector ARMA)) has been proven to be useful for analyzing multivariate non-stationary data in the field of financial time series. It provides a linear combination (which turns out to be stationary series) of non-stationary component series. This linear combination equation is referred to as long term equilibrium between the component series. We consider two sets of Korean bivariate financial time series and then illustrate cointegration analysis. Specifically estimated VAR(vector AR) and VECM(vector error correction model) are obtained and CV(cointegrating vector) is found for each data sets.

• Proceedings of the IEEK Conference
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• 2002.06c
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• pp.17-20
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• 2002

This paper proposes a new 75 fuzzy model approximation method which reduces error in nonlinear fuzzy model approximation over the V-type decision rules. Employing rational Bezier curves used in computer graphics to represent curves or surfaces, the proposed method approximates the decision rule by constructing a tractable linear equation in the highly non-linear fuzzy rule interval. This algorithm is applied to the self-adjusting air cushion for spinal cord injury patients to automatically distribute the patient's weight evenly and balanced to prevent decubitus. The simulation results indicate that the performance of the proposed method is bettor than that of the conventional TS Fuzzy model in terms of error and stability.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.11a
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• pp.660-664
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• 2003

The optimal thickness distribution of an active damping layer is sought so that it satisfies a certain constraint on the dynamic performance of a system minimizing control efforts. To obtain a topologically optimized configuration, which includes size and shape optimization, thickness of the active damping layer is interpolated using linear functions. With the control energy as the objective function to be minimized, the state error energy is introduced as the dynamic performance criterion for the system and used lot a constraint. The optimal control gains are evaluated from LQR simultaneously as the optimization of the layer position proceeds. From numerical simulation, the topologically optimized distribution of the active damping layer shows the same dynamic performance and cost as the Idly covered counterpart, which is optimized only in terms of control gains, with less amount of the layer.

• Communications of the Korean Mathematical Society
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• v.37 no.3
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• pp.939-955
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• 2022

In this paper, we study a first-order non-linear singularly perturbed Volterra integro-differential equation (SPVIDE). We discretize the problem by a uniform difference scheme on a Bakhvalov-Shishkin mesh. The scheme is constructed by the method of integral identities with exponential basis functions and integral terms are handled with interpolating quadrature rules with remainder terms. An effective quasi-linearization technique is employed for the algorithm. We establish the error estimates and demonstrate that the scheme on Bakhvalov-Shishkin mesh is O(N^-1) uniformly convergent, where N is the mesh parameter. The numerical results on a couple of examples are also provided to confirm the theoretical analysis.

• Animal Bioscience
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• v.37 no.11
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• pp.1962-1969
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• 2024

Objective: The objectives were to validate a previously published equation for estimating basal endogenous losses (BEL) of crude protein (CP) in pigs fed nitrogen-free diets and to develop prediction equations for BEL of CP and amino acids (AA). Methods: A total of 139 observations from 123 experiments in 117 papers that determined the BEL of CP and AA in pigs were collected. For the validation of the previous equation for the BEL of CP, 94 observations that were not used for developing the previous equation were used. All observations were used to develop novel equations for estimating BEL of CP in pigs based on the initial body weight (IBW). Results: The validation study indicated that the slope for BEL of CP, representing a linear bias, was less than zero (-0.56; standard error [SE] = 0.130; p<0.001). The intercept for BEL of CP, representing a mean bias, was less than zero (-3.21; SE = 0.488; p<0.001). The models for estimating BEL of CP (g/kg dry matter intake) in pigs fed a nitrogen-free diet were developed: 20.36-0.077×IBW with R² = 0.11 and p<0.001 and 20.80×e^{(-0.00475×IBW)} with R² = 0.12 and p<0.001. Novel linear models for estimating BEL of AA were developed using BEL of CP as the independent variable. Conclusion: The accuracy of the previous equation for estimating BEL of CP in pigs has been improved by reflecting additional data from recent publications. In the novel linear models for estimating BEL of AA of pigs, BEL of CP was used as an independent variable.

• Journal of applied mathematics & informatics
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• v.31 no.3_4
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• pp.479-490
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• 2013

In this paper, we investigate a priori error estimates and superconvergence of varitional discretization for nonlinear parabolic optimal control problems with control constraints. The time discretization is based on the backward Euler method. The state and the adjoint state are approximated by piecewise linear functions and the control is not directly discretized. We derive a priori error estimates for the control and superconvergence between the numerical solution and elliptic projection for the state and the adjoint state and present a numerical example for illustrating our theoretical results.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.11
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• pp.953-957
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• 2001

This paper is concerned with a transfer alignment method for the SDINS under ship motions. Major error sources of transfer alignment are data transfer time-delay, lever-arm velocity and ship body flexure. Specifically, to reduce alignment errors induced by measurement time-delay effects, the error compensation method through delay state augmentation is suggested. A linearized error model for the velocity and attitude matching transfer alignment system is first derived by linearizing the nonliner measurement equation with respect to its time delay and augmenting the delay state into the conventional linear state equations. And then it is shown via observability analysis and computer simulations that the delay state can be estimated and compensated during ship motions resulting in considerably less alignment errors.