• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.326-328
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• 2000

인공신경회로망 기술은 선형 또는 비선형성 계산 문제를 복잡도에 무관하게 학습에 의해 자동으로 근사한다. 또한 알고리즘이 단순하며 잡음에 강하여 다양한 분야에 적용되고 있다. 반면 대상시스템의 특성이나 조건이 변경되면 계산성능을 보장할 수 없고, 계산의 신뢰성 보장 한계가 모호하기 때문에 제어문제에는 실용화가 어려운 것으로 알려져 있다. 제안 모델은 인공신경회로망의 장점을 유지하면서, 위와 같은 문제점을 해결한다. 시뮬레이션을 통하여 제안 모델은 기존 제어기에 비해 우수한 추종제어성능을 보이는 것으로 밝혀졌다.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.1
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• pp.118-126
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• 2024

In this paper, the research contents and results related to the automation of the hull-form optimal design of container ships are summarized. A container ship is a ship that generally operates near Froude number of 0.26. To implement hull-form optimal design automation for ships operating at this speed, an optimization algorithm, a hull-form change algorithm, a ship performance prediction algorithm, an automation algorithm, and an iterative calculation technique were applied to develop a numerical analysis computer program that enables hull-form optimal design automation of the container ship, and it was named HOTCONTAINER. In this study, a sensitivity analysis algorithm was developed and applied to appropriately set design variables for hull-form optimal design. To understand the reliability and real ship applicability of the developed algorithm, a numerical analysis was performed on KCS(KRISO Container Ship), a container ship that has been studied in various ways worldwide. Consequently, the optimal ship was derived, and the wave resistance, wave pattern, and wave height of the target and optimal ship were compared. In conclusion, compared the target ship, the optimal ship a 47.63% decrease in wave resistance, and the displacement and wet surface area decreased by 0.50% and 0.39%, respectively.

• Proceedings of the KIPE Conference
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• 2016.07a
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• pp.109-110
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• 2016

본 논문에서는 현재 운행되고 있는 선형 유도전동기의 슬립주파수 고정 방식이 아닌 선형 유도전동기를 이용한 자기부상열차의 슬립주파수와 수직력 및 추진력과의 관계를 이용, 열차의 가감속시 운행패턴에 따라 운행 중 슬립주파수가 가변할 수 있는 슬립주파수 가변패턴을 형성, 선형유도전동기 자기부상시스템에서의 에너지 효율향상 가능성을 검증하였다. 슬립주파수와 수직력, 추진력과의 관계를 이용 슬립주파수 일정 실효치전류제어 알고리즘과 슬립주파수 일정 벡터제어 알고리즘을 사용하여 운전조건과 슬립주파수를 변경하며 운전조건에 따른 가장 효율적인 슬립주파수의 패턴을 형성하였다. 이 후 모의시험과 실차를 이용한 실험을 통해 알고리즘에 대한 정당성과 실제 효율의 증가를 통해 타당성을 검증하였다. 앞선 두 가지 알고리즘을 통해 열차부상에 영향을 미치지 않는 범위의 수직력을 가지는 범위내에서 슬립주파수를 가변 운전 조건에 따른 최적의 슬립주파수에 대한 정보를 기반으로 운행 중 가변하는 슬립주파수를 자동열차운전(ATO)시스템에 적용 모의실험을 통해 그 적용가능성과 효율을 검증하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.7 no.5
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• pp.830-836
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• 2006

In this paper described an auto tuning neuro-fuzzy PID controller based neural network. The PID type controller has been widely used in industrial application due to its simply control structure, easy of design, and inexpensive cost. However, control performance of the PID type controller suffers greatly from high uncertainty and nonlinearity of the system, large disturbances and so on. In this paper will design to take advantage of neural network fuzzy theory and pid controller auto toning technique. The value of initial scaling factors of the proposed controller were determined on the basis of the conventional PID controller parameters tuning methods and then they were adjusted by using neural network control techniques. This controller simple structure and computational complexity are less, and also application is easy and performance is excellent in system that is strong and has nonlinearity to system dynamic behaviour change or disturbance. Finally, the proposed auto tuning neuro-fuzzy controller is applied to magnetic levitation. Simulation results demonstrated that the control performance of the proposed controller is better than that of the conventional controller.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.7
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• pp.1231-1237
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• 2022

In the present study, the optimization of the main particulars of a ship using AI-based design search techniques was investigated. For the design search techniques, the SHERPA algorithm by HEEDS was applied, and CFD analysis using STAR-CCM+ was applied for the calculation of resistance performance. Main particulars were automatically transformed by modifying the main particulars of the ship at the stage of preprocessing using JAVA script and Python. Small catamaran was chosen for the present study, and the main dimensions of the length, breadth, draft of demi-hull, and distance between demi-hulls were considered as design variables. Total resistance was considered as an objective function, and the range of displaced volume considering the arrangement of the outfitting system was chosen as the constraint. As a result, the changes in the individual design variables were within ±5%, and the total resistance of the optimized hull form was decreased by 11% compared with that of the existing hull form. Throughout the present study, the resistance performance of small catamaran could be improved by the optimization of the main dimensions without direct modification of the hull shape. In addition, the application of optimization using design search techniques is expected for the improvement in the resistance performance of a ship.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.18 no.10
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• pp.15-23
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• 2017

This paper reports a SOC(State-of-Charge) estimation method using the extended Kalman filter(EKF) algorithm, which can allow real-time implementation and reduce the error of the model and be robust against noise, to accurately estimate and evaluate the charging/discharging state of the EV(Electric Vehicle) battery. The battery was modeled as the first order Thevenin model for the EKF algorithm and the parameters were derived through experiments. This paper proposes the changed method, which can have the SOC to 0% ~ 100% regardless of the aging of the battery by replacing the rated capacity specified in the battery with the maximum chargeable capacity. In addition, This paper proposes the EKF algorithm to estimate the non-linearity interval of the battery and simulation result based on Ah-counting shows that the proposed algorithm reduces the estimation error to less than 5% in all intervals of the SOC.