• Title/Summary/Keyword: Nonlinear optimization

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OPTIMIZATION AND IDENTIFICATION FOR THE NONLINEAR HYPERBOLIC SYSTEMS

  • Kang, Yong-Han
    • East Asian mathematical journal
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    • v.16 no.2
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    • pp.317-330
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    • 2000
  • In this paper we consider the optimal control problem of both operators and parameters for nonlinear hyperbolic systems. For the identification problem, we show that for every value of the parameter and operators, the optimal control problem has a solution. Moreover we obtain the necessary conditions of optimality for the optimal control problem on the system.

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Structural Optimization for Non-Linear Behavior Using Equivalent Static Loads (II) - Structural Examples - (선형 등가정하중을 이용한 비선형 거동 구조물의 최적설계 (II) - 구조예제 -)

  • Park Ki-Jong;Park Gyung-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.8 s.239
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    • pp.1061-1069
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    • 2005
  • In part I of this papter Nonlinear Response Optimization using Equivalent Static Loads (NROESL) method/algorithm is developed to conduct optimization for nonlinear behavior structures. The method/algorithm is also verified to show its convergency and optimality. In this present paper, the NROESL algorithm is applied to several structural problems with geometric and/or material nonlinearity. Conventional optimization with sensitivity analysis using the finite difference method is also applied to the same examples. The results of the optimizations are compared. The proposed method is very efficient and derives good solutions.

Structural Optimization for Non-Linear Behavior Using Equivalent Static Loads (I) (선형 등가정하중을 이용한 비선형 거동 구조물의 최적설계 (I) - 알고리듬 -)

  • Park Ki-Jong;Park Gyung-Jin
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.29 no.8 s.239
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    • pp.1051-1060
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    • 2005
  • Nonlinear Response Optimization using Equivalent Static Loads (NROESL) method/algorithm is proposed to perform optimization of non-linear response structures. The conventional method spends most of the total design time on nonlinear analysis. The NROESL algorithm makes the equivalent static load cases for each response and repeatedly performs linear response optimization and uses them as multiple loading conditions. The equivalent static loads are defined as the loads in the linear analysis, which generates the same response field as those in non-linear analysis. The algorithm is validated for the convergence and the optimality. The proposed algorithm is applied to a simple mathematical problem to verify the convergence and the optimality.

Power System Equilibrium Optimization (EOPT) with a Nonlinear Interior Point Method (비선형 내점법을 이용한 전력계통 평형점 최적화 (EOPT))

  • Song, Hwa-Chang;Dosano, Jose Rodel
    • Proceedings of the KIEE Conference
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    • 2006.07a
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    • pp.8-9
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    • 2006
  • This paper presents a new methodology to calculate an optimal solution of equilibrium to power system differential algebraic equations. It employs a nonlinear interior point method for solving the optimization formulation, which includes dynamic equations representing two-axis synchronous generator models with AVR and speed governing control, algebraic equations, and steady-state nonlinear loads. Equilibrium optimization (EOPT) is useful for diverse purposes in power system analysis and control with consideration of the system frequency constraint.

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A Study on Nonlinear Parameter Optimization Problem using SDS Algorithm (SDS 알고리즘을 이용한 비선형 파라미터 최적화에 관한 연구)

  • Lee, Young-J.;Jang, Young-H.;Lee, Kwon-S.
    • Proceedings of the KIEE Conference
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    • 1998.07b
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    • pp.623-625
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    • 1998
  • This paper focuses on the fast convergence in nonlinear parameter optimization which is necessary for the fitting of nonlinear models to data. The simulated annealing(SA) and genetic algorithm(GA), which are widely used for combinatorial optimization problems, are stochastic strategy for search of the ground state and a powerful tool for optimization. However, their main disadvantage is the long convergence time by unnecessary extra works. It is also recognised that gradient-based nonlinear programing techniques would typically fail to find global minimum. Therefore, this paper develops a modified SA which is the SDS(Stochastic deterministic stochastic) algorithm can minimize cost function of optimal problem.

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Optimization of fuzzy controller for nonlinear buildings with improved charged system search

  • Azizi, Mahdi;Ghasemi, Seyyed Arash Mousavi;Ejlali, Reza Goli;Talatahari, Siamak
    • Structural Engineering and Mechanics
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    • v.76 no.6
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    • pp.781-797
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    • 2020
  • In recent years, there is an increasing interest to optimize the fuzzy logic controller with different methods. This paper focuses on the optimization of a fuzzy logic controller applied to a seismically excited nonlinear building. In most cases, this problem is formulated based on the linear behavior of the structure, however in this paper, four sets of objective functions are considered with respect to the nonlinear responses of the structure as the peak interstory drift ratio, the peak level acceleration, the ductility factor and the maximum control force. The Improved Charged System Search is used to optimize the membership functions and the rule base of the fuzzy controller. The obtained results of the optimized and the non-optimized fuzzy controllers are compared to the uncontrolled responses of the structure. Also, the performance of the utilized method is compared with various classical and advanced optimization algorithms.

Structured Static Output Feedback Stabilization (구조적인 제약을 갖는 정적 출력 되먹임 안정화 제어기)

  • Lee, Joon Hwa
    • Journal of the Institute of Electronics and Information Engineers
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    • v.50 no.3
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    • pp.155-159
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    • 2013
  • In this paper, a nonlinear matrix inequality problem and a nonlinear optimization problem are proposed for obtaining a structured static output feedback controller. The proposed nonlinear optimization problem has LMI (Linear Matrix Inequality) constraints and a nonlinear objective function. Using the conditional gradient method, the nonlinear optimization problem can be solved. A numerical example shows the effectiveness of the proposed approach.

Computational enhancement to the augmented lagrange multiplier method for the constrained nonlinear optimization problems (구속조건식이 있는 비선형 최적화 문제를 위한 ALM방법의 성능향상)

  • 김민수;김한성;최동훈
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.15 no.2
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    • pp.544-556
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    • 1991
  • The optimization of many engineering design problems requires a nonlinear programming algorithm that is robust and efficient. A general-purpose nonlinear optimization program IDOL (Interactive Design Optimization Library) is developed based on the Augmented Lagrange Mulitiplier (ALM) method. The ideas of selecting a good initial design point, using resonable initial values for Lagrange multipliers, constraints scaling, descent vector restarting, and dynamic stopping criterion are employed for computational enhancement to the ALM method. A descent vector is determined by using the Broydon-Fletcher-Goldfarb-Shanno (BFGS) method. For line search, the Incremental-Search method is first used to find bounds on the solution, then the bounds are reduced by the Golden Section method, and finally a cubic polynomial approximation technique is applied to locate the next design point. Seven typical test problems are solved to show IDOL efficient and robust.

Topology optimization of nonlinear single layer domes by a new metaheuristic

  • Gholizadeh, Saeed;Barati, Hamed
    • Steel and Composite Structures
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    • v.16 no.6
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    • pp.681-701
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    • 2014
  • The main aim of this study is to propose an efficient meta-heuristic algorithm for topology optimization of geometrically nonlinear single layer domes by serially integration of computational advantages of firefly algorithm (FA) and particle swarm optimization (PSO). During the optimization process, the optimum number of rings, the optimum height of crown and tubular section of the member groups are determined considering geometric nonlinear behaviour of the domes. In the proposed algorithm, termed as FA-PSO, in the first stage an optimization process is accomplished using FA to explore the design space then, in the second stage, a local search is performed using PSO around the best solution found by FA. The optimum designs obtained by the proposed algorithm are compared with those reported in the literature and it is demonstrated that the FA-PSO converges to better solutions spending less computational cost emphasizing on the efficiency of the proposed algorithm.

Navigation of a Mobile Robot Using Nonlinear Least Squares Optimization (비선형 최적화 방법을 이용한 이동로봇의 주행)

  • Kim, Gon-Woo;Cha, Young-Youp
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.60 no.7
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    • pp.1404-1409
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    • 2011
  • The fundamental research for the mobile robot navigation using the numerical optimization method is presented. We define the mobile robot navigation problem as an unconstrained optimization problem to minimize the cost function with the pose error between the goal position and the position of a mobile robot. Using the nonlinear least squares optimization method, the optimal speeds of the left and right wheels can be found as the solution of the optimization problem. Especially, the rotational speed of wheels of a mobile robot can be directly related to the overall speed of a mobile robot using the Jacobian derived from the kinematic model. It will be very useful for applying to the mobile robot navigation. The performance was evaluated using the simulation.