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박영환 忠州大學校 2010 한국교통대학교 논문집 Vol.45 No.-
A ship is a nonlinear system and its dynamics are very complex and uncertain due to the inertia, Coriolis and centripetal forces, hydrodynamic forces and moments. Fuzzy system is basically able to cope with system dynamic uncertainty especially for non-linear systems. So, in this paper an adaptive fuzzy controller is proposed for the ship speed and steering control. The proposed controller can control the ship without the exact ship dynamic model and its effectiveness is proved via a simulation study for a model ship.
태양광 발전의 효율 증대를 위한 새로운 MPPT 알고리즘 개발
박영환 한국교통대학교 2014 한국교통대학교 논문집 Vol.49 No.-
In this paper, a novel MPPT(Maximum Power Point Tracking) algorithm is proposed for the improvement of PV(Photovoltaic) generation efficiency. A MPPT algorithm with an adaptive fuzzy control system is proposed for the duty ratio control of a switching device in a DC-DC converter of PV generation system. The duty ratio of a switching device determines the output voltage of DC-DC converter and affects the maximum power point of the PV generation system. Basically, the DC-DC converter dynamics are nonlinear and uncertain. Because adaptive fuzzy control system is good for the uncertain nonlinear system, the transient performance of PV system with the proposed adaptive fuzzy control system is better than that with the general linear control system in tracking the desired output voltage of the DC-DC converter. The improved tracking performance of DC-DC converter output voltage improves the power efficiency of the whole PV generation system
朴永煥 충주대학교 산업대학원 2002 大學院論文輯 Vol.3 No.-
This papaer describes the design of a robust adaptive fuzzy observer for uncertain nonlinear dynamical system. The Lyapunov synthesis approach is used to guarantee a uniform ultimate boundedness property of the state estimation error, as well as of all other signals in the closed-loop system. Especially, We have focused on the realization of minimal dynamic order of the observer. For the purpose, we propose a new method in which no strictly proper(SPR) condition is needed and combine dynamic rule insertion scheme with on-line estimation of fuzzy parameters. No {\it a priori} knowledge of an upper bounds on the optimal parameters and modeling errors is required. The theoretical results are illustrated through a simulation example.
朴英煥 충주대 산업과학기술연구소 2001 産業科學論文集 Vol.9 No.-
Due to the nonlinearity and resistance uncertainty, induction motors are typical systems to which nonlinear and adaptive control schemes are applied. In general, feedback linearizing control guarantees the linear characteristics of the closed loop system globally and adaptive fuzzy control is robust to the nonlinear function uncertainty of the system dynamics, hence overcomes the restriction of linear parameterization of the uncertainty. Therefore in this paper, an adaptive fuzzy input-output linearizing control, in the form of combining those two schemes, is applied to the speed tracking and flux regulation of induction motors so as to enhance the control performance and to enlarge the class of uncertainty for the induction motor control.