• 대한전기학회논문지:시스템및제어부문D
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• 제53권11호
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• pp.747-752
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• 2004

This paper presents an iterative linear matrix inequality (LMI) approach to the design of a static output feedback (SOF) stabilization controller. A linear penalty function is incorporated into the objective function for the non-convex rank constraint so that minimizing the penalized objective function subject to LMIs amounts to a convex optimization problem. Hence, the overall procedure results in solving a series of semidefinite programs (SDPs). With an increasing sequence of the penalty parameter, the solution of the penalized optimization problem moves towards the feasible region of the original non-convex problem. The proposed algorithm is, therefore, convergent. Extensive numerical experiments are Deformed to illustrate the proposed algorithm.

• 한국전산구조공학회논문집
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• 제20권3호
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• pp.303-309
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• 2007

무한영역에서 진행하는 탄성파를 유한영역에서 수치적으로 해석하기 위해 많은 흡수경계조건들이 제안되어져 왔다. Paraxial 경계조건은 흡수경계조건의 하나로서 스칼라 및 탄성파 방정식의 paraxial 근사화를 통해 얻어지며, 그 성능이 우수하고 수치해석시 계산적 부담을 주지 않는다. 그러나 경계조건이 복잡한 편미분 방정식으로 표현되어 있어 유한요소해석으로의 적용이 어렵다. 본 논문에서는 penalty function method를 이용하여 전체 에너지 범함수와 paraxial 경계조건을 함께 변분정식화 함으로써 유한요소해석을 수행하였다. 유한요소해석에 가장 적용이 용이하며, 많이 사용되어지는 Lysmer-Kuhlemeyer의 흡수경계조건과 성능을 비교함으로써 연구결과의 타당성을 입증하였다.

• 대한수학회지
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• 제36권2호
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• pp.317-332
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• 1999

In this paper we deal with the optimal control problem for the semilinear functional differential equations with unbounded delays. We will also establish the regularity for solutions of the given system. By using the penalty function method we derive the optimal conditions for optimality of an admissible state-control pairs.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 1997년도 추계학술대회논문집
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• pp.40-44
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• 1997

The governing functional in plastic deformation has to satisfy the incompressible condition. This incompressible condition imposed on the velocity fields can be removed by introducing either the Langrange multiplier or the penalty function into the functional. In the study two-dimensional rigid plastic FEM programs using by Lagrange multiplier and penalty function are developed. A compression of cylinder and a spike forging are simulated to compare the data of loads, local mean stresses and reductions of volume.

• 한국소성가공학회:학술대회논문집
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• 한국소성가공학회 1997년도 추계학술대회논문집
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• pp.57-61
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• 1997

The governing functional in plastic deformation has to satisfy the incompressible condition. This incompressible condition imposed on the velocity fields can be removed by introducing either the Langrange multiplier or the penalty function into the functional. In this study two-dimensional rigid plastic FEM programs using by Langrange multiplier and penalty function are developed. A compression of cylinder and a spike forging are simulated to compare the data of loads, local mean stresses and reductions of volume.

• Journal of Information Processing Systems
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• 제17권2호
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• pp.306-317
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• 2021

The unbalance between system ergodic sum rate and high fairness is one of the key issues affecting the performance of non-orthogonal multiple access (NOMA) system. To solve the problem, this paper proposes a power allocation algorithm to realize the ergodic sum rate maximization of NOMA system. The scheme is mainly achieved by the construction algorithm of fair model based on α fair utility function and the optimal solution algorithm based on the interior point method of penalty function. Aiming at the construction of fair model, the fair target is added to the traditional power allocation model to set the reasonable target function. Simultaneously, the problem of ergodic sum rate and fairness in power allocation is weighed by adjusting the value of α. Aiming at the optimal solution algorithm, the interior point method of penalty function is used to transform the fair objective function with unequal constraints into the unconstrained problem in the feasible domain. Then the optimal solution of the original constrained optimization problem is gradually approximated within the feasible domain. The simulation results show that, compared with NOMA and time division multiple address (TDMA) schemes, the proposed method has larger ergodic sum rate and lower Fairness Index (FI) values.

• 대한기계학회논문집A
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• 제25권6호
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• pp.988-995
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• 2001

Functionally graded materials(FGMs) are highlighted to be suitable for high temperature engineering due to their continuous distribution of material properties. In this paper, an optimal design is executed for determining the optimal material volume distribution pattern that minimizes the steady-state thermal stress of FGM heat-resisting composites. The interior penalty function method and the golden section method are employed as optimization techniques while the finite element method is used for thermal stress analysis. Through numerical simulations we suggest the volume fraction distributions that considerably improve initial thermal stress distributions.

• Journal of applied mathematics & informatics
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• 제29권5_6호
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• pp.1395-1407
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• 2011

When a Sequential Quadratic Programming (SQP) method is used to solve the nonlinear programming problems, one of the main difficulties is that the Quadratic Programming (QP) subproblem may be incompatible. In this paper, an SQP algorithm is given by modifying the traditional QP subproblem and applying a class of $l_{\infty}$ penalty function whose penalty parameters can be adjusted automatically. The new QP subproblem is compatible. Under the extended Mangasarian-Fromovitz constraint qualification condition and the boundedness of the iterates, the algorithm is showed to be globally convergent to a KKT point of the non-linear programming problem.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.729-731
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• 2004

This paper deals with the design of a low order $H_{\infty}$ controller by using an iterative linear matrix inequality (LMI) method. The low order $H_{\infty}$ controller is represented in terms of LMIs with a rank condition. To solve the non-convex rank-constrained LMI problem, a linear penalty function is incorporated into the objective function so that minimizing the penalized objective function subject to LMIs amounts to a convex optimization problem. With an increasing sequence of the penalty parameter, the solution of the penalized optimization problem moves towards the feasible region of the original non-convex problem. The proposed algorithm is, therefore, convergent. Numerical experiments show the effectiveness of the proposed algorithm.

• Journal of the Korean Data and Information Science Society
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• 제22권5호
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• pp.951-959
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• 2011

The proposed method is based on a penalized censored regression model with L1-penalty. We use the iteratively reweighted least squares procedure to solve L1 penalized log likelihood function of censored regression model. It provide the efficient computation of regression parameters including variable selection and leads to the generalized cross validation function for the model selection. Numerical results are then presented to indicate the performance of the proposed method.