• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.169.4-169
• /
• 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 ...

• 한국항해항만학회지
• /
• 제36권10호
• /
• pp.787-793
• /
• 2012

최적화기법과 선형변환 자동화기법을 도입하여 고속 중형 Ro-Pax선박의 조파저항성능을 향상시킬 수 있는 선형설계방법에 대하여 연구하였다. 최적화기법으로는 SQP(sequential quadratic programming)을 적용하였으며, 선형변환 자동화기법으로는 NURBS(Non-Uniform Rational B-Spline)기법을 적용하였다. 목적함수인 선박의 조파저항성능을 예측하기 위하여 비선형 자유수면 경계조건과 선체의 침하량을 고려한 비점성 유동 해석 기법인 패널법을 적용하였다. 기준선형에 대하여 선형최적화를 수행하였으며 그 결과로 도출된 최적선형에 대하여 모형선을 제작하여 모형시험을 수행하였다. 기준선형과 최적선형에 대한 수치해석을 수행하여 얻은 결과와 최적선형에 대한 모형시험을 수행하여 얻은 결과를 서로 비교하였다.

• 한국항공우주학회지
• /
• 제43권6호
• /
• pp.568-583
• /
• 2015

본 논문에서는 다분야 통합 설계최적화(MDO : Multidisciplinary Design Optimization)를 적용한 지구관측위성의 개념설계 과정 및 결과를 기술하였다. 현재까지 구축된 지구관측 위성의 데이터베이스를 기반으로 주요 파라미터에 대한 개념설계식을 정립하였으며, 다분야 통합 최적설계 아키텍처 중 CO(Collaborative Optimization) 기반을 이용하여 지구관측 위성 시스템의 최적 개념설계를 수행할 수 있는 설계 도구를 개발하였다. 주어진 제약조건을 만족시키면서 위성의 총 질량을 최소화하는 것을 설계 목표로 설정하였으며, 최적화 알고리즘으로는 SQP(Sequential Quadratic Programming)를 이용하였다. 다분야 통합 최적설계를 적용한 개념설계 결과와 ASNARO-1 및 IKONOS-2 위성 규격의 비교를 통해 해당설계도구의 유용성을 검증하였다.

• 한국농공학회지
• /
• 제36권2호
• /
• pp.111-122
• /
• 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.

• 한국공간구조학회:학술대회논문집
• /
• 한국공간구조학회 2008년도 춘계 학술발표회 논문집
• /
• pp.101-106
• /
• 2008

본 연구에서는 서로 상이한 최적화기법인 유전알고리듬과 수학적 프로그래밍기법을 이용하여 지오데식 돔 구조물을 최적화하고 그 결과를 분석하였다. 본 연구에서 도입한 유전알고리즘은 유전연산자인 선택, 교배, 돌연변이 이외에도 재생기법을 도입하여 최적해의 검색성능을 높였다. 그리고 수학적인 프로그래밍기법은 유한차분법을 이용하여 목적함수의 설계민감도를 계산하였으며 세 가지의 다른 검색기법을 이용하여 돔의 크기최적화를 수행하였다. 지오데식 돔의 중앙에 작용하는 집중하중에 저항하는 돔의 각 부재의 크기패턴을 자체 개발된 $ISADO-GA{\alpha}$와 ISADO-OPT를 이용하여 최적 설계하였다. 본 연구를 통하여 제시된 최적결과는 정해가 존재하지 않는 실제 구조물의 최적 값에 대한 유용한 정보를 제공할 뿐만이 아니라 향후 대공간구조의 새로운 구조시스템 개발의 밑거름이 될 것으로 판단된다.

• Journal of Electrical Engineering and Technology
• /
• 제7권4호
• /
• pp.501-512
• /
• 2012

Social welfare maximization in a double-sided auction market is performed by implementing an aggregation-based particle swarm optimization (CAPSO) algorithm for optimal placement and sizing of one Static Synchronous Series Compensator (SSSC) device. Dallied simulation results (without/with line flow constraints and without/with SSSC) are generated to demonstrate the impact of SSSC on the congestion levels of the modified IEEE 14-bus test system. The proposed CAPSO algorithm employs conventional quadratic smooth and augmented quadratic nonsmooth generator cost curves with sine components to improve the accurate of the model by incorporating the valve loading effects. CAPSO also employs quadratic smooth consumer benefit functions. The proposed approach relies on particle swarm optimization to capture the near-optimal GenCos and DisCos, as well as the location and rating of SSSC while the Newton based load flow solution minimizes the mismatch equations. Simulation results of the proposed CAPSO algorithm are compared to solutions obtained by sequential quadratic programming (SQP) and a recently implemented Fuzzy based genetic algorithm (Fuzzy-GA). The main contributions are inclusion of customer benefit in the congestion management objective function, consideration of nonsmooth generator characteristics and the utilization of a coordinated aggregation-based PSO for locating/sizing of SSSC.

• 동력기계공학회지
• /
• 제21권6호
• /
• pp.56-61
• /
• 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.

• 대한조선학회논문집
• /
• 제43권5호
• /
• pp.550-559
• /
• 2006

A design procedure for a ship with minimum total resistance was developed using a numerical optimization method called SQP(Sequential Quadratic Programming) and a CFD technique based on the Rankine source panel method with the nonlinear free surface boundary conditions. During the whole optimization process the geometry of the hull shape was represented based on the NURBS(Non-uniform rational B-spline) technique and the modification of the hull shape was controlled using the Bell-shaped distribution function to keep the fairness of the hull shape before and after the hull modification. The numerical analysis was carried out using 4000TEU container ship in the towing tank facility installed in the Pusan national university to know the validity of the developed algorithm for this study. As the results of the numerical analysis it proved that the resistance of the optimized hull is conspicuously reduced in comparison with the original hull in a wave-making resistance point of view.

• Smart Structures and Systems
• /
• 제6권7호
• /
• pp.767-792
• /
• 2010

In this paper, the optimal design of vibration control system for smart structures has been investigated semi-analytically via the optimization of geometric parameters like the placements and sizes of piezoelectric sensors and actuators (S/As) bonded on the structures. The criterion based on the maximization of energy dissipation was adopted for the optimization of the control system. Based on the sensing and actuating equations, the total energy stored in the system which is used as the objective function was analytically derived with design variables explicitly presented. Two cases of single and combined vibration modes were addressed for a simply supported beam and a simply supported cylindrical shell. For single vibration mode, the optimal distributions of the piezoelectric S/As could be obtained analytically. However, the Sequential Quadratic Programming (SQP) method has to be employed to solve those which violated the prescribed constraints and to solve the case of combined vibration modes. The results of three examples, which include a simply supported beam, a simply supported cylindrical shell and a simply supported plate, showed good agreement with those obtained by the Genetic Algorithm (GA) method. Moreover, in comparison with the GA method, the proposed method is more effective in obtaining better optimization results and is much more efficient in terms of computation time.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.1901-1904
• /
• 2003

MPC or model predictive control is representative of control methods which are able to handle physical constraints. Closed-loop stability can therefore be ensured only locally in the presence of constraints of this type. However, if the system is neutrally stable, and if the constraints are imposed only on the input, global aymptotic stability can be obtained; until recently, use of infinite horizons was thought to be inevitable in this case. A globally stabilizing finite-horizon MPC has lately been suggested for neutrally stable continuous-time systems using a non-quadratic terminal cost which consists of cubic as well as quadratic functions of the state. The idea originates from the so-called small gain control, where the global stability is proven using a non-quadratic Lyapunov function. The newly developed finite-horizon MPC employs the same form of Lyapunov function as the terminal cost, thereby leading to global asymptotic stability. A discrete-time version of this finite-horizon MPC is presented here. The proposed MPC algorithm is also coded using an SQP (Sequential Quadratic Programming) algorithm, and simulation results are given to show the effectiveness of the method.