• Structural Engineering and Mechanics
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• 제72권2호
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• pp.181-190
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• 2019

Topology optimization of structures seeking the best distribution of mass in a design space to improve the structural performance and reduce the weight of a structure is one of the most comprehensive issues in the field of structural optimization. In addition to structures stiffness as the most common objective function, frequency optimization is of great importance in variety of applications too. In this paper, an efficient multi-objective Bi-directional Evolutionary Structural Optimization (BESO) method is developed for topology optimization of frequency and stiffness in continuum structures simultaneously. A software package including a Matlab code and Abaqus FE solver has been created for the numerical implementation of multi-objective BESO utilizing the weighted function method. At the same time, by considering the weaknesses of the optimized structure in single-objective optimizations for stiffness or frequency problems, slight modifications have been done on the numerical algorithm of developed multi-objective BESO in order to overcome challenges due to artificial localized modes, checker boarding and geometrical symmetry constraint during the progressive iterations of optimization. Numerical results show that the proposed Multiobjective BESO method is efficient and optimal solutions can be obtained for continuum structures based on an existent finite element model of the structures.

• 전기학회논문지
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• 제62권11호
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• pp.1578-1583
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• 2013

In this paper, stochastic optimization algorithms of PSO (Particle Swarm Optimization) and APSO (Adaptive Particle Swam Optimization) are studied and compared. It is revealed that the APSO provides faster convergence and better search efficiency than the conventional PSO when they are adopted to find the global minimum of a two-dimensional function. The advantages of the APSO comes from the ability to control the inertia weight, and acceleration coefficients. To verify that the APSO is working better than the standard PSO, the design of a 10GHz microstrip patch as one of the elements of a high frequency array antenna is taken as a test-case and shows the optimized result with 5 iterations in the APSO and 28 iterations in th PSO.

• 전자공학회논문지B
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• 제30B권9호
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• pp.36-44
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• 1993

In the development of a high speed and light weight manipulator, it is necessary to consider the flexibility of a robotic arm. The infinite dynamics must be analyzed to obtain the finite mode modeling to achieve the feasible controller design of the robotic arm. The modeling procedures of the flexible robot arm, and natural frequencies and mode shapes by the constrained and unconstrained mode method are illustrated. The transfer function of the robot arm with a payload is also shown. The controller is designed by the pole assignment and optimal control theory to compensate for the unmodelled dynamic effects to the low order system. Also, the pole assignment method involving the harmonic vibration mode is presented through computer simulation.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2000년도 춘계학술발표대회 논문집
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• pp.143-148
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• 2000

In this article, we presents multi-objective design optimization of laminated composite beam using Fuzzy programming method. At first, the two design objectives are minimizing the structural weight and maximizing the buckling load respectively. Fuzzy multi-optimization problem can be formulated based on results of single optimizations. Due to different relative importance of design objectives, membership functions are constructed by adding exponential parameters for different objective's weights. Finite element analysis of composite beam for buckling behavior are carried by Natural mode method proposed by J.Argyris and computational time of analysis can be reduced. With this scheme, a designer can conveniently obtain a compromise optimal solution of a multi-objective optimization problem only by providing some exponential parameters corresponding to the importance of the objective functions.

• 한국해양공학회지
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• 제23권3호
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• pp.1-5
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• 2009

It is necessary to develop an efficient optimization technique to optimize engineering structures that have given design spaces, discrete design values, and several design goals. In this study, an optimum algorithm based on the genetic algorithm was applied to the multi-object problem to obtain an optimum solution that simultaneously minimizes the structural weight and construction cost of panel blocks in ship structures. The cost model was used in this study, which includes the cost of adjusting the weld-induced deformation and applying the deformation control methods, in addition to the cost of the material and the welding cost usually included in the normal cost model. By using the proposed cost model, more realistic optimum design results can be expected.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 1999년도 가을 학술발표회 논문집
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• pp.415-422
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• 1999

This paper describes a new optimum design approach for piled raft foundations using the genetic algorithm. The objective function considered is the cost-based total weight of raft and piles. The genetic algorithm is a search or optimization technique based on nature selection. Successive generation evolves more fit individuals on the basis of the Darwinism survival of the fittest. In formulating the genetic algorithm-based optimum design procedure, the analysis of piled raft foundations is peformed based on the 'hybrid'approach developed by Clancy(1993), and also the simple genetic algorithm proposed by the Goldberg(1989) is used. To evaluate a validity of the optimum design procedure proposed based on the genetic algorithm, comparisons regarding optimal pile placement for minimizing differential settlements by Kim et at.(1999) are made. In addition using proposed design procedure, design examples are presented.

• 한국생산제조학회지
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• 제23권3호
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• pp.266-272
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• 2014

This study proposes a closed-loop shaping control method with $H_{\infty}$ optimization for optical image stabilization (OIS) in mobile phone cameras. The image stabilizer is composed of a horizontal stage constrained by ball bearings and actuated by the magnetic force from voice coil motors. The displacement of the stage is measured by Hall effect sensors. From the OIS frequency response experiment, the transfer function models of the stage and Hall effect sensor were identified. The weight functions were determined considering the tracking performance, noise attenuation, and stability with considerable margins. The $H_{\infty}$ optimal controller was executed using closed-loop shaping and limiting the controller order, which should be less than 6 for real-time implementation. The control algorithm was verified experimentally and proved to operate as designed.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제14권1호
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• pp.35-42
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• 2010

A goal of Magnetic Resonance Imaging is reproducing a spatial map of the effective spin density from the measured Fourier coefficients of a specimen. The imaging procedure can be done by inverse Fourier transformation or backward fast Fourier transformation if the data are sampled on a regular grid in frequency space; however, it is still a challenging question how to reconstruct an image from a finite set of Fourier data on irregular points in k-space. In this paper, we describe some mathematical and numerical properties of imaging techniques from non-uniform MR data using the pseudo-inverse or the diagonal-inverse weight matrix. This note is written as an easy guide to readers interested in the non-uniform MRI techniques and it basically follows the ideas given in the paper by Greengard-Lee-Inati [10, 11].

• 한국정밀공학회지
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• 제20권11호
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• pp.79-90
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• 2003

In this paper, we propose a multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using multi-ultrasonic sensor. Instead of using “sensor fusion” method which generates the trajectory of a robot based upon the environment model and sensory data, “command fusion” method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as experiments with IRL-2002. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• 한국산업융합학회 논문집
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• 제21권3호
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• pp.125-131
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• 2018

In this paper, we propose a homogeneous multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments with moving obstacles using multi-ultrasonic sensor. Instead of using "sensor fusion" method which generates the trajectory of a robot based upon the environment model and sensory data, "command fusion" method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as real experiments with mobile robot, AmigoBot. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.