• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.3
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• pp.335-340
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• 2008

In this paper, a decentralized fuzzy output feedback controller for nonlinear interconnected systems with time delay is proposed. The nonlinear interconnected system is represented to fuzzy system using Takagi-Sugeno (T-S) fuzzy model. The decentralized output feedback controller is designed(or stability of subsystems of the fuzzy interconnected system. The stable condition of the closed-loop subsystem is represented to the linear matrix inequality (LMI) form and control gain is obtained by LMI. An example is given to show the verification discussed throughout the paper.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.8
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• pp.715-719
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• 2001

In this paper, we study the existence and uniqueness of fuzzy solution for the nonlinear fuzzy differential equations with nonlocal initial condition in E$^{2}$$_{N}$

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.05a
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• pp.406-409
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• 2000

We propose the modified neural network which are paralleled to control nonlinear systems. The proposed method is a direct control method to use inverse model of the plant. Nonlinear systems are divided into two parts; linear part and nonlinear part, and it is controlled by RLS method and recursive multi-layer neural network with each other. We simulate to verify the performance of the proposed method and are compared with conventional direct neural network control method. The proposed control method is improved the control performance than the conventional method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.1
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• pp.59-65
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• 2011

The aerodynamic power and torque of wind turbines are extremely nonlinear. Therefore, the overall dynamic behavior of a wind turbine exhibits nonlinear characteristics that are dependent on the magnitude of the wind speed. The nonlinear aerodynamic characteristics of the wind turbine also affect the characteristics of the control system of the wind turbine. Therefore, the analysis of the nonlinear aerodynamic characteristics of wind turbine is essential in designing the wind-turbine controller. In this study, the nonlinear aerodynamic characteristics and the effects of these characteristics on the closed-loop pitch system with PI controller for an 1-mass model of the wind turbine are investigated above rated power.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.269-272
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• 2004

본 논문은 비선형 시스템의 퍼지모델을 위해 정보 granules 기반 퍼지 추론 시스템의 새로운 설계 및 이의 최적화를 제시한다. 퍼지모델은 주로 경험적 방법에 의해 추출되기 때문에 보다 구체적이고 체계적인 방법에 의한 동정 및 최적화 될 필요성이 요구된다. 일반적으로, 정보 granules는 근접성, 유사성 또는 기능성 둥에 인하여 서로 결합되는 요소(특히, 수치 데이터)의 실체이다. 제안된 퍼지 모델은 정보 데이터의 특성을 살리기 위해 HCM 클러스터링 방법에 의해 전반부/후반부 구조 및 파라미터 동정을 시행한다. 두 가지 형태의 퍼지 추론 방법은 간략 추론과 선형추론에 의해 수행되며 삼각형 멤버쉽 함수를 사용한다. 구축된 정보 granule 기반 퍼지 모델은 유전자 알고리즘을 이용하여 전반부 파라미터를 최적으로 동정한다. 제안된 비선형 모델의 성능평가는 수치적인 예를 통해 비교 평가한다.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.4
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• pp.369-376
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• 2016

In this paper, we propose and design a SSD(Simultaneous Single band Duplex) system using 5G(Generation) candidate modulations. Especially, we consider HPA(High Power Amplifier) nonlinearity in the proposed system. And then, we evaluate and analyze performance of the proposed system. As simulation results, performance of SSD-OFDM(Orthogonal Frequency Division Multiplexing), SSD-FMC (Universal Filtered Multi-Carrier), and SSD-FBMC(Filter Bank Multi-Carrier) is severely degraded by HPA nonlinearity. However, performance of SSD-OFDM, SSD-UFMC, and SSD-FBMC is similar in the same condition. That is, OFDM, UFMC, and FBMC have a similar PAPR(Peak to Average Power Ratio) characteristic. Finally, we can confirm that the proposed SSD system can not cancel(SI) self-interference effectively by strong HPA nonlinearity. That is, Reducing PAPR is important in order to avoid effect of HPA nonlinearity in the proposed SSD system.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.779-786
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• 2009

This paper deals with $H_{\infty}$ fuzzy control problem of discrete-time nonlinear Markovian jump systems with time delay. The Takgi and Sugeno fuzzy model is employed to represent a delayed nonlinear system that possesses Markovian jump parameters. A stochastic mode dependent Lyapunov function is employed to analyze the stability and $H_{\infty}$ disturbance attenuation performance of the Markovian jump fuzzy system with time delay. Stochastic Lyapunov function is dependent on the operation modes of the system. A sufficient condition for the existence of fuzzy $H_{\infty}$ controller are given in terms of matrix inequalities. Also numerical example is presented to illustrate the efficient of the proposed design methods.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2658-2661
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• 2004

압전 구동기는 전기적 에너지를 직접 동역학적 에너지로 변환하는 세라믹 구동기이다. 특히 압전 구동기의 개방 회로 시스템은 분자 구조 특성에 의해 비선형적인 히스테리시스 특성과 크리프 특성을 가진다. 이러한 비선형적 시스템을 작은 분해능으로 제어하는 경우 이에 따른 외란, 모델링의 불확실성 둥의 오차가 발생하게 된다. 따라서, 현재 이러한 비선형적 오차를 기존의 PID 및 최적제어를 사용하여 보상하는 방법에 대해서 많은 연구가 진행되고 있다. 본 논문에서는 압전 구동기 위치 결정 시스템 전체에 대해 LQG 제어 및 $H_{\infty}$ 제어를 적용하여 시뮬레이션을 실시하였다. 또한 본 논문은 시뮬레이션 결과를 바탕으로 실제 압전 구동기 위치 결정 시스템에 $H_{\infty}$ 제어를 적용하여 제안된 $H_{\infty}$ 제어기가 시스템 성능에 영향을 주는 외란, 모델링의 불확실성 등을 효과적으로 제거함을 보여준다.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.1
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• pp.9-14
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• 2008

This paper presents an observer design methodology for a special class of multi input multi output(MIMO) nonlinear systems. First, we characterize the class of MIMO nonlinear systems with a triangular structure. Also, the observability matrices that plays an important role in proving the convergence of the proposed observer are generalized to MIMO systems. By using the generalized observability matrices, it is shown that under the boundedness conditions of system state and input, the proposed observer guarantees the local exponential convergence to zero of the estimation error.

• Journal of the Korean Institute of Intelligent Systems
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• v.6 no.2
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• pp.97-105
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• 1996

In this paper, an adaptive model predictive controller for nodinear processes using fuzzy model is proposed. Adaptive structure is implemented by recursive fuzzy modeling. The model and control law can be obtained the same as GPC, because the consequent parts of the fuzzy model comprise linear equations of input and output variables. The proposed Adaptive fuzzy model predictive controller (AFMPC) controls nonlinear process well due to the intrinsic nonlinearity of the fuzzy model. When AFMPC's output is variation in the process control input, it maintains zero steady-state offset for a constant reference input and has superior performance. The properties and performance of the proposed control scheme were examined with nonlinear plant by simulation.