• Aerospace Engineering and Technology
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• v.7 no.1
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• pp.61-67
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• 2008

To design flight control law of an unmanned aerial vehicle, automated control gain determination program was developed. The procedure for determination of control gain was formulated as the control gains were designed from the optimal solutions of the optimization problem. PSO algorithm, which is one of the evolutionary computation method, and SQP algorithm, which is one of the nonlinear programming method, are used as optimization problem solver. Thru this technique, computation time required for finding the optimal solution is decreased to 1/5 of that of PSO algorithm and more accurate optimal solution is obtained.

• Structural Engineering and Mechanics
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• v.51 no.2
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• pp.229-248
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• 2014

In this paper, the development of a new optimization software for finite element model updating of engineering structures titled as FemUP is described. The program is used for computational FEM model updating of structures depending on modal testing results. This paper deals with the FE model updating procedure carried out in FemUP. The theoretical exposition on FE model updating and optimization techniques is presented. The related issues including the objective function, constraint function, different residuals and possible parameters for FE model updating are investigated. The issues of updating process adopted in FemUP are discussed. The ideas of optimization to be used in FE model updating application are explained. The algorithm of Sequential Quadratic Programming (SQP) is explored which will be used to solve the optimization problem. The possibilities of the program are demonstrated with a three dimensional steel frame model. As a result of this study, it can be said that SQP algorithm is very effective in model updating procedure.

• East Asian mathematical journal
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• v.28 no.3
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• pp.293-303
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• 2012

Sequential quadratic programming (SQP) has been one of the most important methods for solving nonlinear constrained optimization problems. Recently, filter method, proposed by Fletcher and Leyffer, has been extensively applied for its promising numerical results. In this paper, we present and study an active set SQP-filter algorithm for inequality constrained optimization. The active set technique reduces the size of quadratic programming (QP) subproblem. While by the filter method, there is no penalty parameter estimate. Moreover, Maratos effect can be overcome by filter technique. Global convergence property of the proposed algorithm are established under suitable conditions. Some numerical results are reported in this paper.

• 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 ...

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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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.

• Journal of Power System Engineering
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• v.21 no.6
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• pp.56-61
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• 2017

The check valves are mechanical valves that permit fluids to flow in only one direction, preventing flow from reversing. It is classified as one way directional valves. There are various types of check valves that used in a marine application. A lift type check valve uses the disc to open and close the passage of fluid. The disc lift up from seat as pressure below the disc increases, while drop in pressure on the inlet side or a build up of pressure on the outlet side causes the valve to close. An important concept in check valves is the cracking pressure which is the minimum upstream pressure at which the valve will operate. On the other hand, optimization is a process of finding the best set of parameters to reach a goal while not violating certain constraints. The AMESim software provides NLPQL(Nonlinear Programming by Quadratic Lagrangian) and genetic algorithm(GA) for optimization. NLPQL is the implementation of a SQP(sequential quadratic programming) algorithm. SQP is a standard method, based on the use of a gradient of objective functions and constraints to solve a non-linear optimization problem. A characteristic of the NLPQL is that it stops as soon as it finds a local minimum. Thus, the simulation results may be highly dependent on the starting point which user give to the algorithm. In this paper, we carried out optimization design of the check valve with NLPQL algorithm.

• Smart Structures and Systems
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• v.21 no.5
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• pp.591-600
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• 2018

The probabilistic characterization of wind field characteristics is a significant task for fatigue reliability assessment of long-span railway bridges in wind-prone regions. In consideration of the effect of wind direction, the stochastic properties of wind field should be represented by a bivariate statistical model of wind speed and direction. This paper presents the construction of the bivariate model of wind speed and direction at the site of a railway arch bridge by use of the long-term structural health monitoring (SHM) data. The wind characteristics are derived by analyzing the real-time wind monitoring data, such as the mean wind speed and direction, turbulence intensity, turbulence integral scale, and power spectral density. A sequential quadratic programming (SQP) algorithm-based finite mixture modeling method is proposed to formulate the joint distribution model of wind speed and direction. For the probability density function (PDF) of wind speed, a double-parameter Weibull distribution function is utilized, and a von Mises distribution function is applied to represent the PDF of wind direction. The SQP algorithm with multi-start points is used to estimate the parameters in the bivariate model, namely Weibull-von Mises mixture model. One-year wind monitoring data are selected to validate the effectiveness of the proposed modeling method. The optimal model is jointly evaluated by the Bayesian information criterion (BIC) and coefficient of determination, $R^2$. The obtained results indicate that the proposed SQP algorithm-based finite mixture modeling method can effectively establish the bivariate model of wind speed and direction. The established bivariate model of wind speed and direction will facilitate the wind-induced fatigue reliability assessment of long-span bridges.

• Journal of applied mathematics & informatics
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• v.28 no.3_4
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• pp.823-835
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• 2010

In this paper, A FSQP algorithm for degenerate inequality constraints optimization problems is proposed. At each iteration of the proposed algorithm, a feasible direction of descent is obtained by solving a quadratic programming subproblem. To overcome the Maratos effect, a higher-order correction direction is obtained by solving another quadratic programming subproblem. The algorithm is proved to be globally convergent and superlinearly convergent under some mild conditions. Finally, some preliminary numerical results are reported.

• Magazine of the Korean Society of Agricultural Engineers
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• v.36 no.2
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• pp.111-122
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• 1994

In this study, an algorithm which can be applied to the optimum design of simple steel plate girders was developed, and efficient optimization strategies for the solution of algorithm were found out. The optimum design algorithm consists of 3-levels of optimization. In the first and second levels of optimization, the absolute maximum bending moment and shearing force are extracted and in the third level of optimization, the optimum cross section of steel plate girder is determined. For the optimum design of cross section, the objective function is formulated as the total area of cross section and constraints are derived in consideration of the various stresses and the minimum dimension of flange and web based on the part of steel bridge in the Korea standard code of road bridge. Sequential unconstrained minimization technique using the exterior penalty function method(SUMT-EP), sequential linear programming(SLP) and sequential quadratic programming (SQP) are proved to be efficient and robust strategies for the optimum design of simple plate girder cross section. From the reliable point of view, SLP is the most efficient and robust strategy and SQP is the most efficient one from the viewpoint of converguency and computing time.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.13 no.3
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• pp.285-294
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• 2000

In this paper, a practical procedure for the design optimization of tubular-steel-pile-type substructure in a mooring dolphin is investigated and numerically evaluated. In the finite-dimensional optimum design formulation, geometry and cross-sectional shapes of classified group of piles are identified as design variables. The design objective is the total weight of piles, and the design constraints on stresses, penetration depth, and size limits are imposed. Several classes of practical design alternatives are sought through the linking and fixing of design variables. Among the available numerical optimization codes, both PLBA program and DNCONF subroutine in IMSL library are used. They are based on SQP algorithm and relatively easy to get. A dolphin of numerical example has 20 tubular steel piles, 4 vertical and 16 inclined. Optimum designs for different cases are successfully obtained for the practical purpose.