• Journal of Advanced Marine Engineering and Technology
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• 제38권1호
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• pp.39-47
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• 2014

본 연구에서는, 자동으로 조작되는 밸브의 제어기로 사용되는 유압모션 제어기의 한계점인 설정치 추종성능과 외란 억제성능을 개선하기 위한 방법으로 기존의 PID 제어기에 피드-포워드 제어기를 추가한 2자유도(DOF) PID 제어기를 이용하였다. 이 제어기의 제어인자(Parameter)를 최적화시키는 도구로 실수코딩 유전알고리즘(Real Coded Genetic Algorithm, RCGA)을 이용하고 시뮬레이션을 통해 제어기의 성능을 검증하였다.

• 제어로봇시스템학회논문지
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• 제14권9호
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• pp.948-955
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• 2008

The conventional PID controller has been widely employed in industry. However, the PID controller with one degree of freedom(DOF) can not optimize both set-point tracking response and disturbance rejection response at the same time. In order to solve this problem, a few types of 2DOF PID controllers have been suggested. In this paper, a tuning formula for a 2DOF PID controller is presented. The optimal parameter sets of the 2DOF PID controller are determined based on the first-order plus time delay process and a real-coded genetic algorithm(RCGA) such that the ITAE performance criterion is minimized. The tuning rule is then addressed using calculated parameter sets and another RCGA. A set of simulation works are carried out on three processes with time delay to verify the effectiveness of the proposed rule.

• Journal of Electrical Engineering and Technology
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• 제8권3호
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• pp.490-498
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• 2013

This paper discusses the application of evolutionary multi-objective optimization algorithms namely Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and Modified NSGA-II (MNSGA-II) for solving the Combined Economic Emission Dispatch (CEED) problem with valve-point loading. The valve-point loading introduce ripples in the input-output characteristics of generating units and make the CEED problem as a non-smooth optimization problem. IEEE 57-bus and IEEE 118-bus systems are taken to validate its effectiveness of NSGA-II and MNSGA-II. To compare the Pareto-front obtained using NSGA-II and MNSGA-II, reference Pareto-front is generated using multiple runs of Real Coded Genetic Algorithm (RCGA) with weighted sum of objectives. Furthermore, three different performance metrics such as convergence, diversity and Inverted Generational Distance (IGD) are calculated for evaluating the closeness of obtained Pareto-fronts. Numerical results reveal that MNSGA-II algorithm performs better than NSGA-II algorithm to solve the CEED problem effectively.

• Journal of Advanced Marine Engineering and Technology
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• 제31권5호
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• pp.599-605
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• 2007

This paper presents a method for identifying various systems based on input-output data and a real-coded genetic algorithm(RCGA). The advantages of this technique are, first, it is not dependent on the deterministic or stochastic nature of the systems and, second, the globally optimized models for the original systems can be identified without the need of a differentiable measure function of linearly separable parameters. Under suitable hypotheses, the estimation error is shown to converge in probability to zero. The performance of the proposed algorithm is demonstrated through several simulations.

• Journal of Advanced Marine Engineering and Technology
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• 제30권6호
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• pp.753-759
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• 2006

Integrating processes are frequently encountered in process industries. In this paper, new tuning formulae of the PID controllers for set-point tracking and load disturbance rejection are presented for integrating processes involving time delay. First, the controller parameter sets are tuned using a real-coded genetic algorithm (RCGA) such that performance criterion(IAE, ISE or ITSE) is minimized. Then, tuning rules are addressed using tuned PID parameter sets. tuning model and another RCGA. The performances of the proposed rules are tested on two processes.

• 한국마린엔지니어링학회:학술대회논문집
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• 한국마린엔지니어링학회 2005년도 전기학술대회논문집
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• pp.268-273
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• 2005

The conventional PID controller has been widely used in many industrial control system because engineers can easily understand how to deal with three parameters of PID controller. The conventional tuning methods, however, have a tendency depend on experience and experiment. In this paper a real-coded genetic algorithm is used to search for the optimal parameters of PID controller for marine diesel engine. Simulation results compared with conventional PID controller tuning methods show the effectiveness and good performance of proposed scheme.

• 한국추진공학회:학술대회논문집
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• 한국추진공학회 2008년도 제31회 추계학술대회논문집
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• pp.23-27
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• 2008

본 논문에서는 실수코드 유전 알고리즘(RCGA)과 인공신경망(ANN)을 이용하여 항공기용 터보 축엔진의 결함 진단에 관한 연구를 수행하였다. 인공신경망만을 이용하여 엔진의 결함을 판단 할 경우 많은 학습데이터 때문에 지역 최소점으로 수렴하는 단점이 있다. 이를 개선하기 위해 전역 최소점을 찾는 능력이 뛰어난 실수코드 유전 알고리즘을 사용하였다. 5% 이내의 RMS 결함오차로 높은 결함 예측 신뢰도를 가짐을 확인하였다.

• 한국항해항만학회지
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• 제35권3호
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• pp.227-233
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• 2011

본 연구는 선박용 Night Vision 시스템을 개발하기 위한 선행연구로 2축 지그와 이를 구동할 수 있는 PCU 보드를 제작하고, 추종 및 안정화 제어루틴을 얻는 문제를 다룬다. 개발한 지그와 PCU 보드를 6DOF 모션 시뮬레이터와 결합하여 실험환경을 구축하고 RCGA를 이용하여 지그 모델의 파라미터를 얻고, 추정된 모델과 RCGA를 이용하여 2DOF PID 제어기를 동조한다. 실험과 시뮬레이션을 통해 제안하는 2자유도 PID 제어기의 유효성을 검토한다.

• Structural Engineering and Mechanics
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• 제61권2호
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• pp.283-293
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• 2017

The main contribution of the present paper is to propose an intelligent fuzzy inference system approach for modeling the debonding strength of masonry elements retrofitted with Fiber Reinforced Polymer (FRP). To achieve this, the hybrid of meta-heuristic optimization methods and adaptive-network-based fuzzy inference system (ANFIS) is implemented. In this study, particle swarm optimization with passive congregation (PSOPC) and real coded genetic algorithm (RCGA) are used to determine the best parameters of ANFIS from which better bond strength models in terms of modeling accuracy can be generated. To evaluate the accuracy of the proposed PSOPC-ANFIS and RCGA-ANFIS approaches, the numerical results are compared based on a database from laboratory testing results of 109 sub-assemblages. The statistical evaluation results demonstrate that PSOPC-ANFIS in comparison with ANFIS-RCGA considerably enhances the accuracy of the ANFIS approach. Furthermore, the comparison between the proposed approaches and other soft computing methods indicate that the approaches can effectively predict the debonding strength and that their modeling results outperform those based on the other methods.

• Journal of Advanced Marine Engineering and Technology
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• 제39권10호
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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.