• Structural Engineering and Mechanics
• /
• 제88권6호
• /
• pp.535-549
• /
• 2023

Deep extreme learning machine (DELM) and multi-verse optimization algorithms (MVO) are hybridized for designing an optimal and adaptive control framework for uncertain buildings. In this approach, first, a robust model predictive control (RMPC) scheme is developed to handle the problem uncertainty. The optimality and adaptivity of the proposed controller are provided by the optimal determination of the tunning weights of the linear programming (LP) cost function for clustered external loads using the MVO. The final control policy is achieved by collecting the clustered data and training them by DELM. The efficiency of the introduced control scheme is demonstrated by the numerical simulation of a ten-story benchmark building subjected to earthquake excitations. The results represent the capability of the proposed framework compared to robust MPC (RMPC), conventional MPC (CMPC), and conventional DELM algorithms in structural motion control.

• Journal of Communications and Networks
• /
• 제16권4호
• /
• pp.430-435
• /
• 2014

The performance of a distributed database system depends particularly on the site-allocation of the fragments. Queries access different fragments among the sites, and an originating site exists for each query. A data allocation algorithm should distribute the fragments to minimize the transfer and settlement costs of executing the query plans. The primary cost for a data allocation algorithm is the cost of the data transmission across the network. The data allocation problem in a distributed database is NP-complete, and scalable evolutionary algorithms were developed to minimize the execution costs of the query plans. In this paper, quadratic assignment problem heuristics were designed and implemented for the data allocation problem. The proposed algorithms find near-optimal solutions for the data allocation problem. In addition to the fast ant colony, robust tabu search, and genetic algorithm solutions to this problem, we propose a fast and scalable hybrid genetic multi-start tabu search algorithm that outperforms the other well-known heuristics in terms of execution time and solution quality.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
• /
• pp.109-112
• /
• 1997

In this note, we investigate a noniterative design method of an observer-based robust H$\_$2/ controller in the presence of structured real parameter uncertainty by applying Riccati approach based on the guaranteed cost function. Motivated by the numerical difficulty of the problem, we try to develop a simple design method named as block-diagonal approach, which can be solved by the LMIs method. By assuming the block-diagonal structure of Riccati solution, the original problem can be derived into two sequentially decoupled optimization problems as LQG control problem. The proposed method seems to be numerically efficient in obtaining a feasible compensator.

• 대한기계학회논문집A
• /
• 제22권4호
• /
• pp.811-825
• /
• 1998

An approximate line search is presented for dynamic response optimization with Augmented Lagrange Multiplier(ALM) method. This study empolys the approximate a augmented Lagrangian, which can improve the efficiency of the ALM method, while maintaining the global convergence of the ALM method. Although the approximate augmented Lagragian is composed of only the linearized cost and constraint functions, the quality of this approximation should be good since an approximate penalty term is found to have almost second-order accuracy near the optimum. Typical unconstrained optimization algorithms such as quasi-Newton and conjugate gradient methods are directly used to find exact search directions and a golden section method followed by a cubic polynomial approximation is empolyed for approximate line search since the approximate augmented Lagrangian is a nonlinear function of design variable vector. The numberical performance of the proposed approach is investigated by solving three typical dynamic response optimization problems and comparing the results with those in the literature. This comparison shows that the suggested approach is robust and efficient.

• 전자공학회논문지SC
• /
• 제40권3호
• /
• pp.99-108
• /
• 2003

본 논문에서는 시변 시간지연을 가지는 특이시스템에 대한 보장비용 상태제환 제어기 설계방법을 제시한다. 보장비용 제어기가 존재할 충분조건과 보장비용 제어기 설계방법 및 보장비용 함수의 상한치를 구하는 최적화 문제를 선형행렬부등식, 특이치 분해(singular value decomposition), 슈어 여수(Schur complements) 정리, 변수 치환 등에 의하여 제시한다. 구한 충분조건은 선형행렬부등식의 형태로 되기 때문에 보장비용 제어기의 이득과 보장비용 함수의 상한치를 포함하는 충분조건의 모든 해를 동시에 구할 수 있다, 또한, 제안한 알고리듬을 이용하면 변수 불확실성과 시변 시간지연을 동시에 가지는 특이시스템에 대한 강인 보장비용 제어기 설계문제에도 쉽게 확장됨을 보인다. 마지막으로, 제안한 알고리듬의 타당성을 수치예제를 통하여 확인한다.

• 화약ㆍ발파
• /
• 제31권2호
• /
• pp.1-5
• /
• 2013

스웨덴 식 벤치발파 설계방식에 대하여 실험계획법을 이용하여 설계인자를 분석하였다. 분석에 사용된 직교배열은 $L_9(3^4)$이었고 변수는 각각 3수준의 값을 갖는 천공직경, 화약의 종류, 공의 경사와 암석의 종류로 하였다. 분석결과 저항선 결정 영향요소는 천공직경, 화약의 종류, 암석의 종류 그리고 공의 경사 순이었으며 비장약량 영향요소는 암석의 종류, 화약의 종류 그리고 비천공장에 영향을 미치는 요소는 천공직경과 화약의 종류순이었다. 또 강건설계를 이용한 경제성 검토에서 최적인자 선택이 가능함을 확인하였다.

• 한국국방경영분석학회지
• /
• 제31권2호
• /
• pp.28-44
• /
• 2005

The previous studies approach the field artillery fire scheduling problem as deterministic and do not explicitly include information on the potential scenario changes. Unfortunately, the effort used to optimize fire sequences and reduce the total time of engagement is often inefficient as the collected military intelligence changes. Instead of modeling the fire sequencing problem as deterministic model, we consider a stochastic artillery fire scheduling model and devise a solution methodology to integrate possible enemy attack scenarios in the evaluation of artillery fire sequences. The goal is to use that information to find robust solutions that withstand disruptions in a better way, Such an approach is important because we can proactively consider the effects of certain unique scheduling decisions. By identifying more robust schedules, cascading delay effects will be minimized. In this paper we describe our stochastic model for the field artillery fire sequencing problem and offer revised robust stochastic model which considers worst scenario first. The robust stochastic model makes the solution more stable than the general two-stage stochastic model and also reduces the computational cost dramatically. We present computational results demonstrating the effectiveness of our proposed method by EVPI, VSS, and Variances.

• 한국항해항만학회지
• /
• 제43권6호
• /
• pp.462-468
• /
• 2019

해양석유 생산은 예기치 못한 유가 하락과 글로벌 석유물류의 변화로 인한 여러 가지 어려움에 직면하고 있다. 이 연구는 불확실성하의 해양석유생산 최적화를 위한 추계적 모형을 제시한다. 제시된 추계적 모형은 강인한 최적화 모형과 리코스 제한 최적화 모형을 사용하고 리코스 이익 변동의 척도로 하위부분평균을 사용한다. 제안된 모형을 바탕으로 불확실성 하의 원유의 가격과 수요에 관한 시나리오 기반의 자료를 사용하여 수행한 계산실험 및 결과를 검토하여 보고하였다. 이 연구는 불학실성 하에서 위험을 고려한 해양석유생산 문제에 대한 의사결정에 유의하게 적용될 수 있을 것이다.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2006년도 추계학술대회 논문집 전력기술부문
• /
• pp.393-395
• /
• 2006

In competitive market, it is important to establish a plan of transmission expansion considering uncertainty of future generation and load behavior. For this reason, revised transmission expansion model is proposed in this paper. In the proposed model, information of predictable future condition are included in a cost function of transmission expansion investment. Also, to reduce risk of the investment, mean-variance Markowitz approach is added to the objective function of cost. By optimization programming, the most robust and the minimum cost plan can be obtained.

• 전기학회논문지
• /
• 제61권3호
• /
• pp.459-465
• /
• 2012

In this paper, we present a non-fragile guaranteed cost control design method for uncertain nonlinear systems with time varying delays in state and control input, even though the controller gain is perturbed. The uncertain nonlinear term in the systems is norm bounded and the linear matrix inequality(LMI) optimization method is employed as a stability analysis of the systems. We design a robust controller and show the asymptotical stability of uncertain time-varying systems based on Lyapunov method. Also, we guarantee a specific level of performance of the systems. The simulations are carried out to demonstrate the effectiveness of the proposed method.