• 한국컴퓨터그래픽스학회논문지
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• 제23권4호
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• pp.11-19
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• 2017

우리는 액체와 고체가 혼합된 표면을 세밀하게 복원하기 위해 하이브리드 부호거리장과 적응형 유체표면기술을 통합한 유체표면복원의 새로운 파이프라인을 제안한다. 이전 입자기반 유체 시뮬레이션은 입자가 불규칙하게 분포 될 때 유체표면에 노이즈 문제가 발생한다. 이 문제를 줄이기 위해 스무딩(Smoothing)기법을 적용하면 반복적인 스무딩과정으로 인해 선명하고 디테일한 유체의 표면적 특징을 소실하여 유체의 디테일이 사라지는 문제가 발생한다. 우리의 방법은 유체를 구성하는 입자기반의 부호거리값과 고체를 구성하는 삼각형기반의 부호거리값을 결합하여 하이브리드 부호거리장을 구성한다. 그리고 적응적으로 유체의 표면을 복원하는 방법을 제안하여 전체적인 효율성을 한 층 개선시킨다. 이렇게 하면 고체와 액체 부분의 세밀한 표면적 특징을 표현할 수 있을 뿐만 아니라 두 재질이 혼합되었을 때도 디테일한 표면의 특징과 부드러운 유체표면을 모두 나타낼 수 있다. 또한, 가이딩 형상이란 개념을 소개하여 부호거리값을 빠르게 얻어 올 수 있는 방법을 제안한다. 결과적으로, 하이브리드 부호거리장과 메쉬 재복원 기술을 적응형 프레임워크에서 통합함으로써 유체표면을 복원하는 파이프라인의 전반적인 효율성을 개선시켰다.

• 제어로봇시스템학회논문지
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• 제10권2호
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• pp.112-124
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• 2004

A neural network based adaptive reconfigurable flight controller is presented for a class of discrete-time nonlinear flight systems in the presence of variations of aerodynamic coefficients and control effectiveness decrease caused by control surface damage. The proposed adaptive nonlinear controller is developed making use of the backstepping technique for the angle of attack, sideslip angle, and bank angle command following without two time separation assumption. Feedforward multilayer neural networks are implemented to guarantee reconfigurability for control surface damage as well as robustness to the aerodynamic uncertainties. The main feature of the proposed controller is that the adaptive controller is developed under the assumption that all of the nonlinear functions of the discrete-time flight system are not known accurately, whereas most previous works on flight system applications even in continuous time assume that only the nonlinear functions of fast dynamics are unknown. Neural networks learn through the recursive weight update rules that are derived from the discrete-time version of Lyapunov control theory. The boundness of the error states and neural networks weight estimation errors is also investigated by the discrete-time Lyapunov derivatives analysis. To show the effectiveness of the proposed control law, the approach is i]lustrated by applying to the nonlinear dynamic model of the high performance aircraft.

• 한국지능시스템학회논문지
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• 제26권5호
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• pp.402-408
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• 2016

본 논문에서는 퍼지 슬라이딩 평면의 개념을 터미널 슬라이딩 평면의 기울기를 선정하는데 적용한 일차원 퍼지규칙 슬라이딩 평면을 이용한 터미널 슬라이딩 제어기를 제안하였다. 터미널 슬라이딩 모드 제어기의 개념을 확장하여 연속인 도달법칙을 가지는 터미널 슬라이딩 모드 제어 입력을 제안하였다. 컴퓨터 모의실험에서 제안한 제어기는 터미널 슬라이딩 모드 제어기 보다 빠른 수렴 특성과 채터링이 발생하지 않는 특성을 보여주었으며 일차원 퍼지 규칙을 사용하여 계산량이 작다는 장점을 가지고 있다.

• 제어로봇시스템학회논문지
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• 제9권4호
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• pp.329-339
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• 2003

A neural network based adaptive controller design method is proposed for reconfigurable flight control systems in the presence of variations in aerodynamic coefficients or control effectiveness decrease caused by control surface damage. The neural network based adaptive nonlinear controller is developed by making use of the backstepping technique for command following of the angle of attack, sideslip angle, and bank angle. On-line teaming neural networks are implemented to guarantee reconfigurability and robustness to the uncertainties caused by aerodynamic coefficients variations. The main feature of the proposed controller is that the adaptive controller is designed with assumption that not any of the nonlinear functions of the system is known accurately, whereas most of the previous works assume that only some of the nonlinear functions are unknown. Neural networks loam through the weight update rules that are derived from the Lyapunov control theory. The closed-loop stability of the error states is also investigated according to the Lyapunov theory. A nonlinear dynamic model of an F-16 aircraft is used to demonstrate the effectiveness of the proposed control law.

• Journal of Electrical Engineering and Technology
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• 제12권6호
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• pp.2365-2377
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• 2017

This paper addresses two interrelated problems concerning the tracking control of pod propulsion unmanned surface vessel (USV), namely, the modeling of pod propulsion USV, and tracking controller design. First, based on MMG modeling theory, the model of pod propulsion USV is derived. Furthermore, a practical adaptive neural tracking controller is proposed by backstepping technique, neural network approximation and adaptive method. Meanwhile, unlike some existing tracking methods for surface vessel whose control algorithms suffer from "explosion of complexity", a novel neural shunting model is introduced to solve the problem. Using a Lyapunov functional, it is proven that all error signals in the system are uniformly ultimately bounded. The advantages of the paper are that first, the underactuated characteristic of pod propulsion USV is proved; second, the neural shunting model is used to solve the problem of "explosion of complexity", and this is a combination of knowledge in the field of biology and engineering; third, the developed controller is able to capture the uncertainties without the exact information of hydrodynamic damping structure and the sea disturbances. Numerical examples have been given to illustrate the performance and effectiveness of the proposed scheme.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.689-693
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• 2000

In this paper, we proposed a decoupled adaptive fuzzy sliding-mode control scheme in designing the SMC of a class of fourth-order nonlinear systems. These systems are decoupled the whole system into two second-order systems such that each subsystem has a separate control target expressed in terms of a sliding surface. Then, information from the secondary target conditions the main target, which, in turn, generates a control action to make both subsystem move toward their sliding surface. respectively, and Two sets of fuzzy rule bases are utilized to represent the equivalent control input with unknown system functions of the main target, The membership functions of the THEN-part. which is used to construct a suitable equivalent control of SMC. are changed according to adaptive law, Under this design scheme, we not only maintain the distribution of membership functions over state space but also reduce considerably computing time, we apply the decoupled adaptive sliding-mode control to control a nonlinear inverted pendulum system and confirms the validity of the proposed approach.

• 대한전자공학회논문지SP
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• 제38권1호
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• pp.19-32
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• 2001

본 논문에서는 영상의 밝기 값을 마치 3차원 지형과 같은 개념으로 간주하여 여기에 물이 흐르는 개념을 적용하여 국부 적응 (locally adaptive) thresholding 방법을 제안하였다. 문자를 추출해내기 위해 제안한 방법에서는 지형 표면에 물을 붓는 과정을 수행하였다. 물은 지형의 낮은 곳으로 흐르게 되어 계곡 (valley)에 쌓인다. 이때 문자와 배경으로 구성된 문서영상에서 쌓인 물의 양을 기준으로 두 개의 영역을 구분을 하였다. 제안한 water flow model의 개념을 적용한 threholding 방법은 국부 적응 thresholding의 특성을 나타낸다. 합성 영상과 실제 영상을 이용하여 전산 모의 실험을 수행함으로써 제안한 방법이 문서 영상을 효과적으로 이진화할 수 있음을 보였다.

• International Journal of Control, Automation, and Systems
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• 제5권3호
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• pp.283-294
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• 2007

In this paper, a nonlinear controller based on adaptive sliding-mode method which has a sliding surface vector including new boundizing function is proposed and applied to a two-wheeled welding mobile robot (WMR). This controller makes the welding point of WMR achieve tracking a reference point which is moving on a smooth curved welding path with a desired constant velocity. The mobile robot is considered in view of a kinematic model and a dynamic model in Cartesian coordinates. The proposed controller can overcome uncertainties and external disturbances by adaptive sliding-mode technique. To design the controller, the tracking error vector is defined, and then the sliding surface vector including new boundizing function and the adaptation laws are chosen to guarantee that the error vector converges to zero asymptotically. The stability of the dynamic system is shown through the Lyapunov method. In addition, a simple way of measuring the errors by potentiometers is introduced. The simulations and experimental results are shown to prove the effectiveness of the proposed controller.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.122-122
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• 2020

Urban flood simulation plays a vital role in national flood early warning, prevention and mitigation. In recent studies on 2-dimensional flood modeling, the integrated run-off inundation model is gaining grounds due to its ability to perform in greater computational efficiency. The adaptive quadtree shallow water numerical technique used in this model implements the adaptive mesh refinement (AMR) in this simulation, a procedure in which the grid resolution is refined automatically following the flood flow. The method discounts the necessity to create a whole domain mesh over a complex catchment area, which is one of the most time-consuming steps in flood simulation. This research applies the dynamic grid refinement method in simulating the recent extreme flood events in Metro Manila, Philippines. The rainfall events utilized were during Typhoon Ketsana 2009, and Southwest monsoon surges in 2012 and 2013. In order to much more visualize the urban flooding that incorporates the flow within buildings and high-elevation areas, Digital Surface Model (DSM) resolution of 5m was used in representing the ground elevation. Results were calibrated through the flood point validation data and compared to the present flood hazard maps used for policy making by the national government agency. The accuracy and efficiency of the method provides a strong front in making it commendable to use for early warning and flood inundation analysis for future similar flood events.

• 제어로봇시스템학회논문지
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• 제9권5호
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• pp.347-353
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• 2003

A nonlinear speed controller for a surface mounted permanent magnet synchronous motor (PMSM) based on a newly developed adaptive backstepping approach is presented To compensate parameter uncertainties and load torque disturbance, a nonlinear adaptive backstepping control law and adaptive law are derived systematically through virtual control input and suitable Lyapunov function. Also, speed observer without using costly speed sensor is presented. Simulation results show that the proposed controller can observe the speed and track the reference speed signal generated by a reference model.