• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.173-176
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• 1994

In this paper a closed-form predictive control which takes the intervalwise receding horizon strategy is presented and its stability properties are investigated. A slate-space form output predictor is derived which is composed of the one-step ahead optimal output prediction, input and output data of the system. A set of feedback gains are obtained using the dynamic programming algorithm so that they minimize a multi-stage quadratic cost function and they are used periodically.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.160-163
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• 1996

This paper deals with MCMBPC(Multivariable Constrained Model Based Predictive Controller) for nonlinear boiler system with noise and disturbance. MCMBPC is designed by linear state space model obtained from some operating point of nonlinear boiler system and Kalman filter is used to estimate the state with noise and disturbance. The solution of optimization of the cost function constrained on input and/or output variables is achieved using quadratic programming, viz. singular value decomposition (SVD). The controller designed is shown to have excellent tracking performance via simulation applied to nonlinear dynamic drum boiler turbine model for 16OMW unit.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.169.4-169
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• 2001

Conventional methods to solve the nonlinear programming problem range from augmented Lagrangian methods to sequential quadratic programming (SQP) methods. NPSOL, which is a SQP code, has been widely used to solve various optimization problems but is still subject to many numerical problems such as convergence to local optima, difficulties in initialization and in handling non-smooth cost functions. Recently, many evolutionary methods have been developed for constrained optimization. Among them, CEALM (Co-Evolutionary Augmented Lagrangian Method) shows excellent performance in the following aspects: global optimization capability, low sensitivity to the initial parameter guessing, and excellent constraint handling capability due to the benefit of the augmented Lagrangian function. This algorithm is ...

• 제어로봇시스템학회:학술대회논문집
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• 1987.10b
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• pp.203-208
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• 1987

Design problem of output feedback controllers for discrete large scale systems using simplified model is investigated. It is shown that neglecting fast modes does not generally guarantee the stability of the closed loop system. In this paper, the design procedure is proposed to stabilize the system by minimizing a quadratic cost function for the simplified model and a measure of stability for the neglected fast model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.6
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• pp.1048-1057
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• 2008

This paper represents a design method for PID or low-order controllers cascaded with a linear plant in the unit feedback system where it is required to meet the given time response specifications such as overshoot and settling time. This problem is difficult to solve because the zeros of the controller appear in the numerator of the overall system and thus those zeros may make the time response design difficult. In this paper, we propose a new approach based on the partial model matching and the so called K-polynomial. The partial matching problem is formulated to an optimization problem in which a quadratic function of coefficient errors between a target model and the resulting closed loop system is minimized. For the sake of satisfying the closed loop stability, a set of quadratic constraints associated with the cost function is introduced. As a result, the controller designed meets both time response requirements and the closed loop stability, if any. It is shown through several examples that the present method can be easily applied to these problems.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.479-487
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• 2013

State Highway Agencies (SHAs) have started utilizing cost-plus-time bidding (A+B bidding) since Federal Highway Agency (FHWA) declared it operational on May 4, 1995. Although this technique has successfully accelerated many projects by incorporating construction time in the bidding competition, a framework to illustrate the interactions of incentive/disincentive (I/D) rates on the competitiveness of contractors participating in the bid competition is yet to be developed. In a previous research, authors indicated that for each bid competition there is an efficient cap for I/D rates which are dictated by the capabilities of contractors in project acceleration. However, the results of previous study were based on the assumption that there is a statistically significant relationship between cost and time. In this study, the entire cost-plus-time projects implemented by the Oklahoma Department of Transportation (ODOT) were investigated. Then the significance of relationship between cost and time were analyzed for each contractor utilizing Analysis of Variance (ANOVA) technique, and the price-time function of each contractor was determined by regression analysis. The results of the analysis indicate that there is a significant relationship between cost and time for the majority of contractors. However, a quadratic relationship is not always significant and for some contractors a linear price-time relationship is significant. The results of this project can be used not only by ODOT to optimize the incentive/disincentive rates but also by contractors to determine the most competitive strategies of other bid participants.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.172-181
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• 2019

This paper deals with the problem of generating the energy optimal trajectory which is intended to enhance the target tracking performance of a passive homing missile. Noticing that the essence of passive target tracking is the range estimation problem, the target information gathered by passive measurements can be readily analyzed by introducing the range estimator designed in line-of-sight(LOS) frame. Moreover, for the linear filter structure of the suggested range estimator, the cost function associated with the target information is clearly expressed as a function of the line-of-sight rate. Based on this idea, the optimal missile trajectory maximizing the target information is obtained by solving the saddle point problem for an indefinite quadratic cost which consists of the target information and the energy. It is shown that, different from the previous heuristic approaches, the guidance command producing the optimal passive homing trajectory is produced by the modified proportional navigation guidance law whose navigation constant is determined by the weighting coefficient for target information cost.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.34 no.5
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• pp.173-178
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• 1985

The control of a linear system with random coefficients is discussed here. The cost function is of a quadratic form and the random coefficients are assumed to be completely observable by the controller. Stochastic Process involved in the problem by the controller. Stochastic Process involved in the problem formulation is presented to be the unique strong solution to the corresponding stochastic differential equations. Condition for the optimal control is represented through the existence of solution to a Cauchy problem for the given nonlinear partial differential equation. The optimal control is shown to be a linear function of the states and a nonlinear function of random parameters.

• Communications for Statistical Applications and Methods
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• v.30 no.3
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• pp.245-258
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• 2023

This study proposes a modification to the objective function of the support vector machine for the linearly non-separable case of a binary classifier y_i ∈ {-1, 1}. The modification takes into account the position of each data item x_i from its corresponding class centroid. The resulting optimization function involves the centroid mean vector, and the spread of data besides the support vectors, which should be minimized by the choice of hyper-plane β. Theoretical assumptions have been tested to derive an optimal separable hyperplane that yields the minimal misclassification rate. The proposed method has been evaluated using simulation studies and real-life COVID-19 patient outcome hospitalization data. Results show that the proposed method performs better than the classical linear SVM classifier as the sample size increases and is preferred in the presence of correlations among predictors as well as among extreme values.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.6
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• pp.1046-1052
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• 2010

In residential house, photovoltaic (PV) system among various alternatives in renewable energy system is the most efficient and feasible solution for reducing energy consumption and electricity cost. However, relatively high initial cost make people reluctant to install PV system in their houses. Therefore, in the initial state for PV system installation in the house, it is very important to decide proper capacity of the PV system considering the expected energy usage and solar energy supplying condition with the house. This paper proposes a novel optimization model for deciding appropriate capacity of the PV system for residential house. The objective function of the model is to minimize the annual cost including electricity bill, operation and maintenance cost, and annual fixed cost calculated from the initial installation cost based on capital recovery factor (CRF). The model also shows the optimal inclining angle of PV panels of the system. In this paper, we estimate the PV output using PVWATTS (PV simulator of Office of Energy Efficiency and Renewable Energy) and find optimal solutions by Sequential Quadratic Programming (SQP) method using MATLAB software. The proposed approach is finally applied to a residential model house in Gangneung, Gangwon-Do and verified its feasibility for adopting to PV system design for residential houses.