• 대한산업공학회지
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• 제25권3호
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• pp.336-341
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• 1999

The problem of jointly determining the optimum process mean and screening limits for each market is considered in situations where there are several markets with different price/cost structures. The quality characteristic is assumed to be a normal distribution with unknown mean and known variance. A quadratic loss function is utilized for developing the economic model. Methods of finding the optimum process mean and screening limits are presented and a numerical example is given.

• Structural Engineering and Mechanics
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• 제26권4호
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• pp.377-392
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• 2007

A discrete sliding mode control (SMC) method based on hybrid model of neural network and nominal model is proposed to reduce the vibration of flexible structures, which is a robust active controller developed by using a sliding manifold approach. Since the thick boundary layer will reduce the virtue of SMC, the multilayer feed-forward neural network is adopted to model the uncertainty part. The neural network is trained by Levenberg-Marquardt backpropagation. The design objective of the sliding mode surface is based on the quadratic optimal cost function. In course of running, the input signal of SMC come from the hybrid model of the nominal model and the neural network. The simulation shows that the proposed control scheme is very effective for large uncertainty systems.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 추계학술대회 논문집 학회본부
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• pp.107-110
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• 1988

The quadratic cost function J(x) and the normalized residuals $r_N$ are conventionally used for identifying the presence and location of bed measurements in power system state estimation. These are "post estimation" tests and therefore require the complete re-estimation of system states whenever bed data is identified. This paper presents a pre-filter for reducing errors of the raw measurements using an adaptive filter. Each measurement is processed by the adaptive filter before being used in the state estimation. The performance of the adaptive filter is tested and the results are shown in this paper.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.341-343
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• 2000

Traditionally electric power system are operated in such a way that the total fuel cost is minimized regardless of accounting for tie-lines transmission constraint and emissions produced. But tie-lines transmission and emissions constraint are very important issues in the operation and planning of electric power system. This paper presents the Two-Phase Neural Network(TPNN) to solve the Economic Load Dispatch (ELD) problem with tie-lines transmission and emissions constraint considering transmission losses. The transmission losses are obtained from the B-coefficient which approximate the system losses as s quadratic function of the real power generation. By applying the proposed algorithm to the test system, the usefulness of this algorithm is verified.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1994년도 Proceedings of the Korea Automatic Control Conference, 9th (KACC) ; Taejeon, Korea; 17-20 Oct. 1994
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• pp.28-33
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• 1994

An optimal controller, e.g. LQG controller, may not be realistic in the sense that the required control power may not be achieved by existing actuators, and the measured output is not satisfactory. To be realistic, the controller should meet such constraints as sensor or actuator limitation, performance limit, etc. In this paper, the lnput/Output Variance Constrained (IOVC) control problem will be considered from the viewpoint of mathematical programming. A dual version shall be developed to solve the IOVC control problem, whose objective is to find a stabilizing control law attaining a minimum value of a quadratic cost function subject to the inequality constraint on each input and output variance for a stabilizable and detectable plant. One approach to the constrained optimization problem is to use the Kuhn-Tucker necessary conditions for the optimality and to seek an optimal point by an iterative algorithm. However, since the algorithm uses only the necessary conditions, the convergent point may not be optimal solution. Our algorithm will guarantee a sufficiency.

• Journal of the Korean Data and Information Science Society
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• 제18권1호
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• pp.31-40
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• 2007

Many previous researchers tried to analysis relationship between financial index of hospitals such as revenue, expenses, and profit and hospital outcome such as number of inpatient and outpatient or, between that financial index and hospital size including number of hospital beds. However, these studies did not find exact relationship between financial index and hospital efficiency and productivity. Therefore, purpose of the study explores exact relationship between hospital financial outcome and hospital efficiency and productivity using adjusted inpatient days concept from American Hospital Association. Through the empirical analysis, the researchers find that hospital profit has the U-shape quadratic function to operation ratio. 66.9% of operation ratio is changing point and hospitals with 55.8% through 75.0% of operation ration have experience deficit situation. Considering the hospital circumstance, Korean hospitals would be to maintain general hospital type with various specialty departments.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1183-1185
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• 1999

The basic purpose of economic dispatch problem is that minimize fuel cost with inequality constraint of generator output. To solve this problem it is very important to express power loss equation that have quadratic function of generator output power included B-coefficient. This Paper presents a method in determining B-coefficient by use A-matrix that is calculated by loss re-distribution algorithm (LRDA) considering voltage dependent load model (VDLM)s. The Proposed algorithm is tested with IEEE 6 bus sample system, which shows the result in each cases by the change of load component factor.

• 제어로봇시스템학회논문지
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• 제5권2호
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• pp.123-130
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• 1999

In discrete-time controlled system, sampling time is one of the critical parameters for control performance. It is useful to employ different sampling rates into the system considering the feasibility of measuring system or actuating system. The systems with the different sampling rates in their input and output channels are named multirate system. Even though the original continuous-time system is time-invariant, it is realized as time-varying state equation depending on multirate sampling mechanism. By means of the augmentation of the inputs and the outputs over one period, the time-varying system equation can be constructed into the time-invariant equation. The two multirate formulations have some trade-offs in the simplicity to construct the controller, the control performance. It is good issue to determine the suitable formulation in consideration of performance of them. In this paper, the two categories of multirate formulations will be compared in terms of the linear quadratic (LQ) cost function. The results are used to select the multirate formulation and the sampling rates suitable to the desired control performance.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 추계학술대회논문집A
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• pp.646-653
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• 2001

LQG/LTR Control Methology is recently used for the analysis of multi-variable control in frequency domain. Target filter loop is designed by the demanding requirements such as cross-over frequency, disturbance rejection in low frequency domain, zero steady-state error, identification of maximum and minimum singular values and sensor noise rejection in high frequency domain. Loop transfer recovery is accomplished by solving the cheap control and then simulation close to the target filter loop. In this study, LQG/LTR Control Methodology is applied to the seat suspension system. It is found that this technique is very effective to control the system and improve the ride quality of human body.

• International Journal of CAD/CAM
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• 제6권1호
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• pp.89-97
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• 2006

This paper presents a novel approach for non-iterative surface smoothing with feature preservation on arbitrary meshes. Laplacian operator is performed in a global way over the mesh. The surface smoothing is formulated as a quadratic optimization problem, which is easily solved by a sparse linear system. The cost function to be optimized penalizes deviations from the global Laplacian operator while maintaining the overall shape of the original mesh. The features of the original mesh can be preserved by adding feature constraints and barycenter constraints in the system. Our approach is simple and fast, and does not cause surface shrinkage and distortion. Many experimental results are presented to show the applicability and flexibility of the approach.