• 소음진동
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• 제11권1호
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• pp.147-155
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• 2001

This paper is concerned with the real-time automatic tuning of the multi-input multi-output positive position feedback controllers for smart structures by the genetic algorithms. The genetic algorithms have proven its effectiveness in searching optimal design parameters without falling into local minimums thus rendering globally optimal solutions. The previous real-time algorithm that tunes a single control parameter is extended to tune more parameters of the MIMO PPF controller. We employ the MIMO PPF controller since it can enhance the damping value of a target mode without affecting other modes if tuned properly. Hence, the traditional positive position feedback controller can be used in adaptive fashion in real time. The final form of the MIMO PPF controller results in the centralized control, thus it involves many parameters. The bounds of the control Parameters are estimated from the theoretical model to guarantee the stability. As in the previous research, the digital MIMO PPF control law is downloaded to the DSP chip and a main program, which runs genetic algorithms in real time, updates the parameters of the controller in real time. The experimental frequency response results show that the MIMO PPF controller tuned by GA gives better performance than the theoretically designed PPF. The time response also shows that the GA tuned MIMO PPF controller can suppress vibrations very well.

• 한국산학기술학회논문지
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• 제12권3호
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• pp.1063-1069
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• 2011

오늘날, 차량의 성능 향상에 따라 타이어에 대한 요구가 다양화 되고 요구성능이 고도화됨에 따라 타이어의 설계기술에 보다 다양한 기반기술들이 적극적으로 사용되기 시작하였으며, 이에 대한 많은 연구 중 타이어 형상의 최적화를 통한 타이어 성능 향상을 위한 연구들이 활발히 진행되고 있다. 타이어 형상은 운전성능, 회전저항성, 내구성, 승차감, 소음, 내마모성 등과 같은 차량의 주요성능에 직접적인 영향을 미치는 대단히 중요한 설계인자이다. 따라서 본 연구에서는 실험계획법의 하나인 직교배열표와 회귀식을 이용하여 타이어 형상설계 시에 필요한 유한요소 해석시간을 단축시키고 유전자 알고리듬을 이용하여 타이어의 주요 성능을 만족하는 다목적 형상최적설계를 수행하였다.

• 한국정밀공학회지
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• 제14권3호
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• pp.89-97
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• 1997

A genetic algorithm (GA) is a stochastic direct search strategy that mimics the process of genetic evolution. The GA applied herein works on a population of structural designs at any one time, and uses a structured information exchange based on the principles of natural selection and wurvival of the fittest to recombine the most desirable features of the designs over a sequence of generations until the process converges to a "maximum fitness" design. Principles of genetics are adapted into a search procedure for structural optimization. The methods consist of three genetics operations mainly named selection, cross- over and mutation. In this study, a method of finding the optimum topology of truss/beam structure is pro- posed by using the GA. In order to use GA in the optimum topology problem, chromosomes to FEM elements are assigned, and a penalty function is used to include constraints into fitness function. The results show that the GA has the potential to be an effective tool for the optimal design of structures accounting for sizing, geometrical and topological variables.variables.

• 한국소음진동공학회논문집
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• 제25권5호
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• pp.361-368
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• 2015

This paper deals with a robust fine seek controller design problem with multiple constraints using a genetic algorithm. A robust $H\infty$ constraint is introduced to attenuate effectively velocity disturbance caused by the eccentric rotation of the disk. A weighting function is optimally selected based on the estimation of velocity disturbance and the estimated minimum velocity loop gain. A robust velocity loop constraint is considered to minimize the variances of the velocity loop gain and bandwidth against the uncertainties of fine actuator. Finally, a robust fine seek controller is obtained by solving a genetic algorithm with an LMI condition and an appropriate objective function. The proposed controller design method is applied to the fine seek control system of a DVD recording device and is evaluated through the experimental results.

• 한국소음진동공학회논문집
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• 제26권4호
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• pp.398-405
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• 2016

A shape of loop-pipe in a compressor affects the vibration of compressor. In this paper, optimal design of shape of loop-pipe to decrease the stress was carried out. Body and shell were assumed to be rigid, while loop-pipe is considered to be flexible. The finite element model was derived and programmed. Genetic algorithm was used for optimization. Locations of 18 point in loop-pipe were considered as shape variables, while the shapes of loop-pipe were interpolated as polynomials or ellipses. Maximum stress of loop-pipe was used as a fitness function for optimization. The spatial constraints and acceleration response of shell were also considered in optimization. The maximum stress and acceleration could be reduced by 79 % and 49 % respectively.

• 한국지능시스템학회논문지
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• 제11권3호
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• pp.191-199
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• 2001

유전자알고리듬(Genetic Algorithm)은 확률적인 집단 탐색법이고 적응도함수의 형태에 관계없는 직접 탐색법이기 때문에 최근 최적화 방법으로 주목을 받고 있다. 본 논문에서는 Job-shop Schedule Problem에 대하여 교배방법으로 JOX를 사용하며, 효율적인 탐색을 위하여 탐색범위를 축소시키는 강제조작을 형질유전을 고려한 형질유전GT법을 제안하고, 세대교체에 있어 모집단의 다양성을 유지하기 위하여 집단 내에 동일한 개체를 배제하는 방법을 제안한다. 제안 알고리듬을 Fisher & Thompson의 FT10$\times$10 및 FT20$\times$5 문제에 적용하여 유효성을 실험적으로 검증한다.

• 한국소음진동공학회논문집
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• 제25권10호
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• pp.677-684
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• 2015

It is often necessary to predict the vibration patterns of the structures from the signals of finite number of vibration sensors. This study presents the optimal placement of vibration sensors by applying the genetic algorithm and the modal expansion method. The modal expansion method is used to estimate the vibration response of the whole structure. The genetic algorithm is used to estimate the optimal placement of vibration sensors. Optimal sensor placement can be obtained so that the fitness function is minimized in the genetic algorithm. This paper discusses the comparison of the performances of two types of fitness functions, modal assurance criteria(MAC) and condition number( CN). As a result, the estimation using MAC shows better performance than using CN.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1998년도 학술발표대회 논문집 제17권 1호
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• pp.197-200
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• 1998

본 논문에서는 유전자 알고리즘(genetic Algorithm)을 사용하여 벡터 양자화(vector quantization : VQ)를 수행하는 방법을 제안하고자 한다. 벡터 양자화를 수행하여 코드북(codebook)을 생성할 때 생성된 코드북과 학습벡터(training vector)사이에는 반드시 양자화 오차(quantization error)가 발생하는데 기존의 K-means 알고리듬을 사용하여 코드북을 생성했을 경우 양자화 오차를 줄이는데 한계가 있었다. 본 논문에서 제안하는 유전자 알고리즘을 이용한 벡터 양자화는 이 양자화 오차를 감소시키기 위해서 연구되었다. 제안한 방법의 성능을 평가하기 위해 음성데이터를 기존의 K-means 알고리즘에서 클러스터의 중심을 선택하는 방법중의 하나인 Minimax방법으로 코드북을 생성하여 제안한 방법과 양자화 오차를 비교한 결과 양자화 오차가 감소됨을 알 수 있었다.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2007년도 추계학술대회 및 정기총회
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• pp.330-340
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• 2007

IEEE 802.11 wireless LANs employ the backoff algorithm to avoid contentions among STAs when two or more STAs attempt to transmit their data frames simultaneously. The MAC efficiency can be improved if the CW values are adaptively changed according to the channel state of IEEE 802.11 wireless LANs. In this paper, we propose a dynamic contention window control algorithm using the genetic algorithm to improve the MAC throughput of IEEE 802.11 wireless LANs.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 춘계학술대회논문집A
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• pp.797-802
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• 2000

Flow shop scheduling problem involves processing several jobs on common facilities where a setup time Is incurred whenever there is a switch of jobs. Practical aspect of scheduling focuses on finding a near-optimum solution within a feasible time rather than striving for a global optimum. In this paper, a hybrid meta-heuristic method called tabu-genetic algorithm(TGA) is suggested, which combines the genetic algorithm(GA) with tabu list. The experiment shows that the proposed TGA can reach the optimum solution with higher probability than GA or SA(Simulated Annealing) in less time than TS(Tabu Search). It also shows that consideration of setup time becomes more important as the ratio of setup time to processing time increases.