• Journal of Advanced Marine Engineering and Technology
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• v.32 no.8
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• pp.1215-1220
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• 2008

To obtain the shape of the free surface more accurately, computations are carried out by a finite volume method using unstructured meshes and an interface capturing method. Free-surface flow, which is very important in the fields of ship and marine engineering, is numerically simulated for flows of both water and air. Control volumes are used with an arbitrary number of faces and allows a local mesh refinement. The integration is of second order, with a midpoint rule integration and linear interpolation. The method is fully implicit and uses quadratic interpolation. The solution method of pressure-correction type solves sequentially equations of momentum, continuity, conservation, and two-equations turbulence model. Comparison are quantitatively made between the computation and experiment in order to confirm the solution method.

• 전기의세계
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• v.25 no.5
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• pp.70-74
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• 1976

In this paper, the problem of controlling deterministic contimuous linear system with a slightly modified quadratic performance criteria is studied. When the number of out put variables is much lesser then that of state variables, either the controller becomes complex or the performance measure becomes much higher with only output feedback. So the design philosphy treated in this paper lies in finding a compromising point between the controller complexity and the performance measure. thd controller is composed of stasic plus dynamic compensator with order equal to the mtmber of output variables. Several unknowns are unknown parameters are bundled into one, and using Pontryagin's minimum principle, conditions and formula for optimum control are induced which are different from that of Kalman optimal regulator.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1766-1767
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• 2011

본 논문에서는 기존의 proportional-integral-derivative (PID) 제어기의 이득조정과정에서 linear quadratic regulator(LQR)을 이용하여 이득조정을 하는 방법을 제안한다. 제안된 제어기의 이득은 LQR의 수식으로 표현되어지며 Matlab/simulink을 이용한 모의실험을 통해 위치프로파일에 대한 위치추종오차의 성능이 평가되어진다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.3
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• pp.600-603
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• 2007

We propose a method to estimate the asymptotic stability region(ASR) of a mismatched uncertain variable structure system with a bounded controller. The uncertain system under consideration may have mismatched parameter uncertainties in the state matrix. Using linear matrix inequalities(LMIs) we estimate the ASR and we show the quadratic stability of the closed-loop control system in the estimated ASR. We also give a simple LMI-based algorithm for estimating the ASR. Finally, we give a numerical example in order to show the effectiveness of our method.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1794_1795
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• 2009

본 논문에서는 안정도 단계(degree of stability)가 고려된 LQ 최적 제어에 대한 근사 다이나믹 프로그래밍 기법을 제안한다. 제안된 근사 다이나믹 프로그래밍 기법은 시스템 행렬(system matrix)를 모르는 경우에도 구현할 수 있으며, 특정 조건하에서 수렴성을 가짐을 수학적으로 증명하였다. 또한 제안된 알고리즘을 토대로 하는 최소 자승법 기반 실시간 구현 방법에 대해 소개하였으며, 컴퓨터 모의 실험을 통해 제안된 근사 다이나믹 프로그래밍의 성능을 입증하였다.

• Structural Engineering and Mechanics
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• v.49 no.3
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• pp.329-353
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• 2014

Increasing usage of tank cars and their intrinsic instability due to sloshing of contents have caused growing maintenance costs as well as more frequent hazards and defects like derailment and fatigue of bogies and axels. Therefore, varieties of passive solutions have been represented to improve dynamical parameters. In this task, assuming 22 degrees of freedom, dynamic analysis of partially filled tank car traveling on a curved track is investigated. In order to consider stochastic geometry of track; irregularities have been derived randomly by Mont Carlo method. More over the fluid tank model with 1 degree of freedom is also presented by equivalent mechanical approach in terms of pendulum. An active suspension system for described car is designed by using linear quadratic optimal control theory to decrease destructive effects of fluid sloshing. Eventually, the performance of the active suspension system has been compared with that of the passive one and a study is carried out on how active suspension may affect the dynamical parameters such as displacements and Nadal's derailment index.

• 제어로봇시스템학회:학술대회논문집
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• 1995.10a
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• pp.10-13
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• 1995

This paper considers the linear-quadratic optimal regulator problem for nonstandard singularly perturbed systems making use of the recursive technique. We first derive a generalized Riccati differential equation by the Hamilton-Jacobi equation. In order to obtain the feedback gain, we must solve the generalized algebraic Riccati equation. Using the recursive technique, we show that the solution of the generalized algebraic Riccati equation converges with the rate of convergence of O(.epsilon.). The existence of a bounded solution of error term can be proved by the implicit function theorem. It is enough to show that the corresponding Jacobian matrix is nonsingular at .epsilon. = 0. As a result, the solution of optimal regulator problem for nonstandard singularly perturbed systems can be obtained with an accuracy of O(.epsilon.$^{k}$ ). The proposed technique represents a significant improvement since the existing method for the standard singularly perturbed systems can not be applied to the nonstandard singularly perturbed systems.

• Proceedings of the KSR Conference
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• 2006.11a
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• pp.145-159
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• 2006

This paper describes the development of a clustering based fuzzy controller of an electromagnetic suspension vehicle using gain scheduling method and Kalman filter for a simplified single magnet system. Electromagnetic suspension vehicle systems are highly nonlinear and essentially unstable systems For achieving the levitation control of the DC electromagnetic suspension system, we considered a fuzzy system modeling method based on clustering algorithm which a set of input/output data is collected from the well defined Linear Quadratic Gaussian(LQG) controller. Simulation results show that the proposed clustering based fuzzy controller methodology robustly yields uniform performance with adequate gap response over the mass variation range.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.5
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• pp.111-117
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• 2003

The Taylor model concept is introduced to design a controller with input and output data only. The parameters in Taylor model can be estimated using the input and output data and a controller can be designed based on Taylor model. The accuracy of Taylor model approximation can be improved by increasing the observation window and the order of Taylor model. The LQR method is applied to Taylor model to design power system stabilizers (PSS), and compared with the conventional PSS.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.15-15
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• 2000

In the past couple of years, there has been increasing interest in the fusion of neural networks and fuzzy logic. Most of the existing fused models have been proposed to implement different types of fuzzy reasoning mechanisms and inevitably they suffer from the dimensionality problem when dealing with complex real-world problem. To overcome the problem, we propose the self-organizing networks with activation nodes based on fuzzy inference and polynomial function. The proposed model consists of two parts, one is fuzzy nodes which each node is operated as a small fuzzy system with fuzzy implication rules, and its fuzzy system operates with Gaussian or triangular MF in Premise part and constant or regression polynomials in consequence part. the other is polynomial nodes which several types of high-order polynomials such as linear, quadratic, and cubic form are used and are connected as various kinds of multi-variable inputs. To demonstrate the effectiveness of the proposed method, time series data for gas furnace process has been applied.