• 전기학회논문지
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• 제65권5호
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• pp.769-772
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• 2016

In this paper, the overhang structure was applied to the axial flux permanent magnet (AFPM) motor. This paper describes the overhang effect in the AFPM motor. Moreover, the overhang effect was analyzed according to the different overhang length and an optimal overhang structure was proposed. Finally, the proposed structure was applied to design, analysis and experiment of prototype motors. Through the comparison between 3D finite element analysis results and experimental ones, the validity of proposed structure is clarified.

• Journal of Mechanical Science and Technology
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• 제16권1호
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• pp.75-82
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• 2002

A simultaneous optimal design problem of structural and control systems is discussed by taking a 3-D truss structure as an object. We use descriptor forms for a controlled object and a generalized plant because the structural parameters appear naturally in these forms. We consider a minimum weight design problem for structural system and disturbance suppression problem for the control system. The structural objective function is the structural weight and the control objective function is $H_{\infty}$ norm from the disturbance input to the controlled output in the closed-loop system. The design variables are cross sectional areas of the truss members. The conditions for the existence of controller are expressed in terms of linear matrix inequalities (LMI) By minimizing the linear sum of the normalized structural objective function and control objective function, it is possible to make optimal design by which the balance of the structural weight and the control performance is taken. We showed in this paper the validity of simultaneous optimal design of structural and control systems.

• 한국안전학회지
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• 제27권2호
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• pp.57-64
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• 2012

For the vibration control of earthquake-excited buildings, an optimal design method of integrated control system considering soil-structure interaction is studied in this paper. Interaction between soils and the base of the building is simply modeled as lumped parameters and equations of motion are derived. The equations of motion are transformed into the state space equations and the probabilistic excitations such as Kanai-Tajumi power spectral density function is introduced. Then an optimization problem is formulated as finding hybrid or integrated control systems which minimizes the stochastic responses of the building structure for given constraints. In order to investigate the feasibility of the optimization method, an example design and numerical simulations are performed with tenstory building. Finally, numerical results are compared with a conventional design case that soil-structure interaction is not considered.

• 한국정밀공학회지
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• 제21권2호
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• pp.153-159
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• 2004

A control-structure combined optimal design problem is discussed taking a 3-D truss structure as a design object. We use descriptor forms for a controlled object and a generalized plant because the structural parameters appear naturally in these forms. We consider not only minimum weight design problem for structure system, but also suppression problem of the effect of disturbances for control system as the purpose of the design. By minimizing the linear sum of the normalized structural objective function and control objective function, it is possible to make optimal design by which the balance of the structural weight and the control performance is taken.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.302-305
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• 1996

This paper presents a visual servoing combined by Neural Network with optimal structure and predictive control for robotic manipulators to tracking or grasping of the moving object. Using the four feature image information from CCD camera attached to end-effector of RV-M2 robot manipulator having 5 dof, we want to predict the updated position of the object. The Kalman filter is used to estimate the motion parameters, namely the state vector of the moving object in successive image frames, and using the multi layer feedforward neural network that permits the connection of other layers, evolutionary programming(EP) that search the structure and weight of the neural network, and evolution strategies(ES) which training the weight of neuron, we optimized the net structure of control scheme. The validity and effectiveness of the proposed control scheme and predictive control of moving object will be verified by computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.71.2-71
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• 2001

This paper deals with nonlinear system modelling using neural network and genetic algorithm. Application of neural network to control and identification is actively studied because of their approximating ability of nonlinear function. It is important to design the neural network with optimal structure for minimum error and fast response time. Genetic algorithm is getting more popular nowadays because of their simplicity and robustness. In this paper, We optimize neural network structure using genetic algorithm. The genetic algorithm uses binary coding for neural network structure and search for optimal neural network structure of minimum error and response time. Through extensive simulation, Optimal neural network structure is shown to be effective for ...

• 한국지진공학회논문집
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• 제12권2호
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• pp.9-22
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• 2008

이 논문에서는 구조물의 내진성능 향상을 위한 방법으로서 구조부재 및 수동형 감쇠기의 통합최적설계기법을 제시한다. 이는 구조부재 및 감쇠기의 최적배치를 다루는 최적화기법이다. 통합시스템의 최적설계를 위하여 다목적최적화기법을 도입하고, 이를 보다 효율적으로 다루기 위하여 목표신뢰성 제한조건을 갖는 다목적최적화문제로 재구성하였다. 수치해석 예제를 통하여 다양한Pareto 최적해를 제시하였으며, 이들이 기존 설계방법에 상응하는 순차적 설계방법 및 가중합방법에 따른 단일목적함수 최적화방법을 포괄함을 검증하였다. 여러 Pareto 최적해로부터 강성 및 감쇠장치의 사용량을 달리하는 3가지 대표설계안을 선택하고 이들의 내진성능을 다양한 지진하중에 대하여 비교 분석하였다. 이로부터 제시하는 방법이 구조물의 내진성능 향상을 위한 설계방법으로서 효율적으로 적용될 수 있을 것으로 기대된다.

• 산업경영시스템학회지
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• 제32권2호
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• pp.158-170
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• 2009

This paper considers how the optimal export level is influenced by export risk, the degree of risk-averseness for exporting firms, and those firms' cost structure. In addition, export insurance is incorporated into some simple theoretical model to analyze the optimal export level. This paper applies genetic algorithm simulation to show that the exporting firms'risk-averseness do not affect the optimal export decision while export risk and cost function characteristic have relatively more significant effects on the optimal export level. Finally, our findings suggest that the most influential factor for the optimal export levels seems to be the monopoly power of exporting firms.

• 한국소음진동공학회논문집
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• 제24권5호
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• pp.381-389
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• 2014

This study is concerned with the estimation of vibration-field of a cylindrical structure by modal expansion method(MEM). MEM is a technique that identifies modal participation factors using some of vibration signals and natural modes of the structure: The selection of sensor locations has a big influence on predicted vibration results. Therefore, this paper deals with four optimal sensor placement( OSP) methods, EFI, EFI-DPR, EVP, AutoMAC, for the estimation of vibration field. It also finds optimal sensor locations of the cylindrical structure by each OSP method and then performs MEMs. Predicted vibration results compared with reference ones obtained by forced response analysis. The standard deviations of errors between reference and predicted results were also calculated. It is utilized to select the most suitable OSP method for estimation of vibration field of the cylindrical structure.

• 전자공학회논문지S
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• 제35S권4호
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• pp.67-75
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• 1998

In general, Evoluationary Algorithm(EAs) are refered to as methods of population-based optimization. And EAs are considered as very efficient methods of optimal sytem design because they can provice much opportunity for obtaining the global optimal solution. This paper presents a co-evolution scheme of artifical neural networks, which has two different, still cooperatively working, populations, called as a host popuation and a parasite population, respectively. Using the conventional generatic algorithm the host population is evolved in the given environment, and the parastie population composed of schemata is evolved to find useful schema for the host population. the structure of artificial neural network is a diagonal recurrent neural netork which has self-feedback loops only in its hidden nodes. To find optimal neural networks we should take into account the structure of the neural network as well as the adaptive parameters, weight of neurons. So we use the genetic algorithm that searches the structure of the neural network by the co-evolution mechanism, and for the weights learning we adopted the evolutionary stategies. As a results of co-evolution we will find the optimal structure of the neural network in a short time with a small population. The validity and effectiveness of the proposed method are inspected by applying it to the stabilization and position control of the invered-pendulum system. And we will show that the result of co-evolution is better than that of the conventioal genetic algorithm.