• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.160-170
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• 2008

Temperature control of an enclosed thermal system which has many applications including Rapid Thermal Processing (RTP) of semiconductor wafers showed an input-constraint violation for nonlinear controllers due to inherent strong coupling between the elements [1]. In this paper, a constrained nonlinear optimal control design is developed, which accommodates input constraints using the linear algebraic equivalence of the nonlinear controllers, for the temperature control of an enclosed thermal process. First, it will be shown that design of nonlinear controllers is equivalent to solving a set of linear algebraic equations-the linear algebraic equivalence of nonlinear controllers (LAENC). Then an input-constrained nonlinear optimal controller is designed based on that LAENC using the constrained linear least squares method. Through numerical simulations, it is demonstrated that the proposed controller achieves the equivalent performances to the classical nonlinear controllers with less total energy consumption. Moreover, it generates the practical control solution, in other words, control solutions do not violate the input-constraints.

• Journal of applied mathematics & informatics
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• v.27 no.1_2
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• pp.1-12
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• 2009

Iterative algorithms are proposed for the least-squares symmetric solution of AXB = E with a submatrix constraint. We characterize the linear mappings from their independent element space to the constrained solution sets, study their properties and use these properties to propose two matrix iterative algorithms that can find the minimum and quasi-minimum norm solution based on the classical LSQR algorithm for solving the unconstrained LS problem. Numerical results are provided that show the efficiency of the proposed methods.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.2 no.2
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• pp.41-47
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• 1998

We consider some numerical solution methods for equality-constrained quadratic problems in the context of structural analysis. Sparse orthogonal schemes for linear least squares problem are adapted to handle the solution step of the force method. We also examine these schemes with substructuring concepts.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.10
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• pp.1874-1881
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• 2010

A recursive linear stochastic error compensation algorithm is newly proposed for target localization in sensor network which provides range difference of arrival(RDOA) measurements. Target localization with RDOA is a well-known nonlinear estimation problem. Since it can not solve with a closed-form solution, the numerical methods sensitive to initial guess are often used before. As an alternative solution, a pseudo-linear estimation scheme has been used but the auto-correlation of measurement noise still causes unacceptable estimation errors under low SNR conditions. To overcome these problems, a stochastic error compensation method is applied for the target localization problem under the assumption that a priori stochastic information of RDOA measurement noise is available. Apart from the existing methods, the proposed linear target localization scheme can recursively compute the target position estimate which converges to true position in probability. In addition, it is remarked that the suggested algorithm has a structural reconciliation with the existing one such as linear correction least squares(LCLS) estimator. Through the computer simulations, it is demonstrated that the proposed method shows better performance than the LCLS method and guarantees fast and reliable convergence characteristic compared to the nonlinear method.

• Journal of Information Processing Systems
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• v.1 no.1 s.1
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• pp.32-35
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• 2005

Image denoising is basic work for image processing, analysis and computer vision. This paper proposes a novel algorithm based on wavelet threshold for image denoising, which is combined with the linear CLS (Constrained Least Squares) filtering and thresholding methods in the transform domain. We demonstrated through simulations with images contaminated by white Gaussian noise that our scheme exhibits better performance in both PSNR (Peak Signal-to-Noise Ratio) and visual effect.

• Journal of Broadcast Engineering
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• v.8 no.2
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• pp.204-208
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• 2003

In this paper, a new matrix vector formulation for a wavelet-based subband decomposition is introduced. This formulation provides a means to compute a regular multi-resolution analysis over many levels of decomposition. With this approach. any single channel linear space-invariant filtering problem can be cast into a multi-channel framework. This decomposition Is applied to the linear space-invariant image restoration problem and propose a frequency-adaptive constrained least squares(CLS) filter. In the proposed filter, we use different parameters adaptively according to subband characteristics. Experimental results are presented for the proposed frequency-adaptive CLS filter These experiments show that if accurate estimates of the subband characteristics are available, the proposed frequency adaptive CLS filter provides significant improvements over the traditional single channel filter.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.90-95
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• 2003

In this paper, an Adaptive Nonlinear Constrained Model Predictive Control (ANCMPC) is presented for a pH control in a fed-batch bio-reactor. The pH model is represented with Hammerstein Model. The static nonlinear part of Hammerstein model is described with the static pH model, and the dynamic linear part of the Hammerstein model is described with the CARIMA model. The parameters of the CARIMA model is estimated on-line with the input and output measurements of the system using a recursive least squares type of identi�cation algorithm. The e�ectiveness of the proposed controller is shown through simulations.

• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.1
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• pp.45-52
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• 2016

This paper suggests a new method of finding regularization parameter for image restoration problems. Wiener filter requires priori information such that power spectrums of original image and noise. Constrained least squares restoration also requires knowledge of the noise level. If the prior information is not available, separate optimization functions for Tikhonov regularization parameter are suggested in the literature such as generalized cross validation and L-curve criterion. In this paper, self-regularization method that connects bias term of augmented linear system and smoothing term of Tikhonov regularization is introduced in the frequency domain and applied to the image restoration problems. Experimental results show the effectiveness of the proposed method.

• Journal of Ocean Engineering and Technology
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• v.36 no.3
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• pp.143-152
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• 2022

To reach a port, a ship must pass through a shallow water zone where seabed effects alter the hydrodynamics acting on the ship. This study examined the maneuvering characteristics of an autonomous surface ship at 3-DOF (Degree of freedom) motion in deep water and shallow water based on the in-port speed of 1.54 m/s. The CFD (Computational fluid dynamics) method was used as a specialized tool in naval hydrodynamics based on the RANS (Reynolds-averaged Navier-Stoke) solver for maneuvering prediction. A virtual captive model test in CFD with various constrained motions, such as static drift, circular motion, and combined circular motion with drift, was performed to determine the hydrodynamic forces and moments of the ship. In addition, a model test was performed in a square tank for a static drift test in deep water to verify the accuracy of the CFD method by comparing the hydrodynamic forces and moments. The results showed changes in hydrodynamic forces and moments in deep and shallow water, with the latter increasing dramatically in very shallow water. The velocity fields demonstrated an increasing change in velocity as water became shallower. The least-squares method was applied to obtain the hydrodynamic coefficients by distinguishing a linear and non-linear model of the hydrodynamic force models. The course stability, maneuverability, and collision avoidance ability were evaluated from the estimated hydrodynamic coefficients. The hydrodynamic characteristics showed that the course stability improved in extremely shallow water. The maneuverability was satisfied with IMO (2002) except for extremely shallow water, and collision avoidance ability was a good performance in deep and shallow water.