• Journal of Advanced Marine Engineering and Technology
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• v.39 no.10
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• pp.1031-1036
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• 2015

Proportional-integral-derivative (PID) controllers are widely used in industrial sites. Most tuning methods for PID controllers use an empirical and experimental approach; thus, the experience and intuition of a designer greatly affect the tuning of the controller. The representative methods include the closed-loop tuning method of Ziegler-Nichols (Z-N), the C-C tuning method, and the Internal Model Control tuning method. There has been considerable research on the tuning of PID controllers for single-input single-output systems but very little for multi-input multi-output systems. It is more difficult to design PID controllers for multi-input multi-output systems than for single-input single-output systems because there are interactive control loops that affect each other. This paper presents a tuning method for the PID controller for a two-input two-output system. The proposed method uses a real-coded genetic algorithm (RCGA) as an optimization tool, which optimizes the PID controller parameters for minimizing the given objective function. Three types of objective functions are selected for the RCGA, and each PID controller parameter is determined accordingly. The performance of the proposed method is compared with that of the Z-N method, and the validity of the proposed method is examined.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2006.10a
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• pp.123-128
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• 2006

This paper presents the design of a surveillance night vision system for marine ships. Both a hardware system and software modules for tracking control are developed. In order to control each control axis with compensation for ship motion, the two-degree of freedom(TDF) PID controller is designed and its parameters are tuned using a real-coded genetic algorithm(RCGA). Simulation demonstrates the effectiveness of the proposed system.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.215-219
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• 2003

In this paper, we generate a trajectory minimized the energy gait of a biped robot for walking a staircase using genetic algorithms and apply to the computed torque controller for the stable dynamic biped locomotion. In the saggital plane, a 6 degree of freedom biped robot that model consists of seven links is used. In order to minimize the total energy efficiency, the Real-Coded Genetic Algorithm (RCGA) is used. Operators of genetic algorithms are composed of a reproduction, crossover and mutation. In order to approximate the walking gait, the each joint angle is defined as a 4-th order polynomial of which coefficients are chromosomes. Constraints are divided into equality and inequality. Firstly, equality constraints consist of position conditions at the end of stride period and each joint angle and angular velocity condition for periodic walking. On the other hand, inequality constraints include the knee joint conditions, the zero moment point conditions for the x-direction and the tip conditions of swing leg during the period of a stride for walking a staircase.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1521-1524
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• 2003

In this paper, we propose a "Distance Correlation Selection operator (DCS)" as a new selection operator. For Genetic Algorithm (GA), many improvements have been proposed. The MGG (Minimal Generation Gap) model proposed by Satoh et.al. shows good performance. The MGG model has all advantages of conventional models and the ability of avoiding the premature convergence and suppressing the evolutionary stagnation. The proposed method is an extension of selection operator in the original MGG model. Generally, GA has two types of selection operators, one is "selection for reproduction", and the other is "selection for survival"; the former is for crossover and the latter is the individuals which survive to the next generation. The proposed method is an extension of the former. The proposed method utilizes distance information between individuals. From this extension, the proposed method aims to expand a search area and improve ability to search solution. The performance of the proposed method is examined with several standard test functions. The experimental results show good performance better than the original MGG model.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.396-396
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• 2000

Multiperiod optimization is the key step to tackle the supply chain optimization problems. Taking supply and demand uncertainty or prediction into consideration during the process synthesis phase leads to the maximization of the profit for the long range time horizon. In this study, new algorithm based on the Genetic Algorithms is proposed for multiperiod optimization formulated in MINLP, GDP and hybrid MINLP/GDP. In this study, the focus is given especially on the design of the Genetic Algorithm suitable to handle disjunctive programming with the same level of MINLP handling capability. Hybridization with the Simulated Annealing is tried. and many heuristics are adopted for this purpose.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.329-330
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• 2007

본 논문에서는 particle swarm optimization(PSO)를 통한 비선형시스템의 퍼지집합 퍼지모델의 최적화 방법을 제안한다. 퍼지 모델링에서 전반부 동정, 즉 구조 동정 및 파라미터 동정은 비선형 시스템을 표현하는데 있어서 매우 중요하다. 퍼지모델의 전반부 동정에 있어 최적화 과정이 필요하며 유전자 알고리즘(Genetic Algorithm; GA)을 이용하여 퍼지모델을 최적화한 연구가 많이 있다. 본 연구는 파라미터 동정 시 최근 여러 가지 어려운 최적화 문제를 수행함에 있어서 성능의 우수성이 증명된 PSO를 이용하여 퍼지집합 퍼지모델의 전반부 파라미터를 동정하였다. 구조동정은 단순 유전자 알고리즘(Simple Genetic Algorithm; SGA)을 이용하여 동정하였으며 파라미터 동정시 실수 코딩유전자 알고리즘(Real Coded Genetic Algorithm; RCGA)와 PSO를 각각 파라미터 동정에 이용하여 성능을 비교하였다.

• Journal of Energy Engineering
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• v.6 no.1
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• pp.11-18
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• 1997

This paper describes a daily operation scheduling of cogeneration systems using Genetic Algorithm. The simulation was performed in the case of bottoming cycle. The efficiency of cogeneration system which has nonlinear characteristic is obtained by the least square method based on the real data of industrial cogeneration system. In this paper, Genetic Algorithm is coded as a vector of floating point representation which can reduce computation time and obtain high precision The simulated results show that the genetic algorithm can be efficiently applied to establish the operation scheduling.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.11
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• pp.2702-2719
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• 2013

A new optimal scheme based on curvelet transform is proposed for retinal image enhancement (RIE) using real-coded quantum genetic algorithm. Curvelet transform has better performance in representing edges than classical wavelet transform for its anisotropy and directional decomposition capabilities. For more precise reconstruction and better visualization, curvelet coefficients in corresponding subbands are modified by using a nonlinear enhancement mapping function. An automatic method is presented for selecting optimal parameter settings of the nonlinear mapping function via quantum genetic search strategy. The performance measures used in this paper provide some quantitative comparison among different RIE methods. The proposed method is tested on the DRIVE and STARE retinal databases and compared with some popular image enhancement methods. The experimental results demonstrate that proposed method can provide superior enhanced retinal image in terms of several image quantitative evaluation indexes.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.4 s.181
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• pp.75-82
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• 2006

In this paper, we propose an optimal trajectory for biped robots to move up-and-down stairs using a genetic algorithm and a computed-torque control for biped robots to be dynamically stable. First, a Real-Coded Genetic Algorithm (RCGA) which of operators are composed of reproduction, crossover and mutation is used to minimize the total energy. Constraints are divided into equalities and inequalities: Equality constraints consist of a position condition at the start and end of a step period and repeatability conditions related to each joint angle and angular velocity. Inequality constraints include collision avoidance conditions of a swing leg at the face and edge of a stair, knee joint conditions with respect to the avoidance of the kinematic singularity, and the zero moment point condition with respect to the stability into the going direction. In order to approximate a gait, each joint angle trajectory is defined as a 4-th order polynomial of which coefficients are chromosomes. The effectiveness of the proposed optimal trajectory is shown in computer simulations with a 6-dof biped robot that consists of seven links in the sagittal plane. The trajectory is more efficient than that generated by the modified GCIPM. And various trajectories generated by the proposed GA method are analyzed in a viewpoint of the consumption energy: walking on even ground, ascending stairs, and descending stairs.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.125-129
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• 2010

본 연구에서는 실수 코딩을 사용하는 유전 알고리즘의 문제공간이 n차원 구면으로 제한된 경우에 사용 할 교배 연산자와 변이 연산자를 제안하고, 이를 실제로 사용한 실험 결과를 제시한다. n차원 실수 공간에서 일반적으로 사용되는 연산자를 n차원 구면에 사영하는 방법을 사용하였으며, 해의 범위가 제한된 경우에 사용할 해의 수선 방법도 제안하였다. 제안된 연산자를 사용하며 몇 가지 최적화 문제를 푸는 실험을 한 결과 평균 오차율 2.0%내에서 최적해를 구함을 확인하였다.