• Science of Emotion and Sensibility
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• v.1 no.2
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• pp.93-103
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• 1998

효율적이고 체계적인 퍼지제어를 위해 조작자의 제어동작을 모델링하거나 공정을 모델링하는 기법이 필요하고, 또한 퍼지 추론시에 조건부의 기여도(contribution factor)의 결정과 동작부의 제어량의 결정이 추론의 결과에 중요하다. 본 논문에서는 추론시 조건부의 기여도와 동작부의 세어량이 퍼지 엔트로피의 개념하에서 수행되는 적응 퍼지 추론시스템을 제시한다. 제시된 시스템은 전방향 신경회로망의 토대위에서 구현되며 주건부의 기여도가 퍼지 엔트로피에 의하여 구해지고, 동작부의 제어량은 확장된 퍼지 엔트로피에 의하여 구해진다. 이를 위한 학습 알고리즘으로는 역전파 알고리즘을 이용하여 조건부의 파라미터의 동정을 하고 동작부 파라미터의 동정에는 국부해에 보다 강인한 유전자 알고리즘을 이용하다. 이러한 모델링 기법을 임펄스 잡음과 가우시안 잡음이 첨가된 영상에 적용하여 본 결과, 영상복원시에 발생되는 여러 가지의 경우에 대한 적응성이 보다 양호하게 유지되었고, 전체영상의 20%의 데이터만으로도 객관적 화질에 있어서 기존의 추론 방법에 비해 향상을 보였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.1-6
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• 2008

In this paper, we present the robust fuzzy algorithm for variable speed control of wind turbines. Generally, the plants of wind turbines are consisted of complex nonlinearities, and the parameters of variable speed of wind turbines are represented as uncertain terms. For solving these complexity, we propose the robust fuzzy algorithm. At first, the exact fuzzy modeling are performed for variable speed of wind turbines. Next, we design the fuzzy controller for reanalyzed T-S fuzzy model of the wind turbines, then, we prove the stability of the plant through the Lyapunov stability theorem. At last, an example is included for visualizing the efficiency of the proposed technique.

• Proceedings of the KIPE Conference
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• 2008.10a
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• pp.224-226
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• 2008

본 논문에서는 매트릭스 컨버터로 구동되는 유도전동기의 속도제어 성능을 향상시키기 위한 적응제어 기법을 제안한다. 유도 전동기는 비선형적 마찰력 등으로 인한 비선형적 특성을 가진다. 이러한 비선형적 특성으로 인해 야기되는 왜곡을 보상하고 속도제어 성능을 개선하기 위해 슬라이딩 모드 제어 기법을 적용한다. 슬라이딩 모드에서 발생하는 채터링 현상과 모델링되지 않은 유도 전동기의 불확실성에 의한 제어 성능 저하를 개선하기 위해, 불확실성 추정을 위한 퍼지 기반 불확실성 추정기를 적용한다. 시뮬레이션을 통해 제안한 제어기법의 타당성을 검증한다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.265-276
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• 2017

In this paper, a robust and more accurate trajectory tracking control method for a mobile robot is proposed using WIPDC(Weighted Integral Parallel Distributed Compensation) and T-S Fuzzy disturbance observer. WIPDC reduces the steady state error by adding weighted integral term to PDC. And, T-S Fuzzy disturbance observer makes it possible to estimate and cancel disturbances for a T-S fuzzy model system. As a result, the trajectory tracking controller based on T-S Fuzzy disturbance observer shows robust tracking performance. When the initial postures of a mobile robot and the reference trajectory are different, the initial control inputs to the mobile robot become too large to apply them practically. In this study, also, the problem is solved by designing an initial approach path using a path planning method which employs $B\acute{e}zier$ curve with acceleration limits. Performances of the proposed method are proved from the simulation results.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.17 no.1
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• pp.25-30
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• 2003

In this paper, we propose a fuzzy controller design method for the water level control of the power plant drum in the form of nominimum phase system The proposed method is based on T. Takagi and H. Sugeno's fuzzy model. And we illustrate the improved characteristics as the simulation results, comparing with the conventional the PID and LQ controller design methods.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.298-303
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• 2004

This paper deals with a stochastic stabilization of observer-based output-feedback control Takagi-Sugeno (T-S) fuzzy system with Markovian input delay. The finite Markovian process is adopted to model the input delay of the overall control system. It is assumed that the zero and hold devices are used for control input. The continuous-time T-S fuzzy system with the Markovian input delay is discretized for easy handling delay, accordingly, the discretized T-S fuzzy system is represented by a discrete-time T-S fuzzy system with jumping parameters. The stochastic stabilizability of the jump T-S fuzzy system is derived and formulated in terms of linear matrix inequalities (LMIs). The usefulness of the proposed algorithm is also certificated by simulation of 2 degree of freedom helicopter model.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.4
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• pp.33-42
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• 2010

The induction motor drive applied to field oriented control is widely used in industry applications. However, it is deceased performance and authenticity by saturation, temperature changing, disturbance and parameters changing because modeling of induction motor is nonlinear and complex. In order to control variable speed operation, conventional PI-like controllers are commonly used. These controllers provide limited good performance over a wide range of operation, even under ideal field oriented conditions. This paper proposes self tuning PI controller based on fuzzy-neural network(FNN)-PI controller that is implemented using fuzzy control, neural network, and adaptive fuzzy controller(AFC). Also, this paper proposes estimation of speed using ANN. The proposed control algorithm is applied to induction motor drive system using FNN-PI, AFC and ANN controller. Also, this paper proposes the anlysis results to verify the effectiveness of controller.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.8
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• pp.33-40
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• 2009

This paper presents the high performance control of interior permanent magnet synchronous motor(IPMSM) using space vector(SV) PWM method based on hybrid artificial intelligent(HAI) controller. The HAI controller combines the advantages between adaptive fuzzy control and neural network The SV PWM method is applied to a speed control system of motor in the industry field until now and is feasible to improve harmonic rate of output current, switching frequency and response characteristics. This HAI controller is used instead of conventional PI controller in order to solve problems happening when calculating a reference voltage. The HAI controller improves speed performance by hybrid combination of reference model-based adaptive mechanism method, fuzzy control and neural network. This paper analyzes response characteristics of parameter variation, steady-state and transient-state using proposed HAI controller and this controller compares with conventional fuzzy neural network(FNN) and PI controller. Also, this paper proves validity of HAI controller.

• Journal of the Korean Society of Propulsion Engineers
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• v.20 no.2
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• pp.56-66
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• 2016

Robustness is essential for model based FDI (Fault Detection and Isolation) and it is inevitable to have modeling errors and sensor signal noises during the process of FDI. This study suggests an improved method by applying NARX (Nonlinear Auto Regressive eXogenous) model and Kalman estimator in order to cope with problems caused by linear model errors and sensor signal noises in the process of fault diagnoses. Fault decision is made by the probability of the trend of gradually accumulated errors applying Fuzzy logic, which are robust to instantaneous sensor signal noises. Reliability of fault diagnosis is verified under various fault simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.4
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• pp.506-511
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• 2006

This paper considers a method to design sliding mode observers for a class of uncertain systems using Linear Matrix Inequalities(LMI). In an LMI-based sliding mode observer design method for a class of uncertain systems the switching surface is set to be the difference between the observer and system output. In terms of LMIs, a necessary and sufficient condition is derived for the existence of a sliding-mode observer guaranteeing a stable sliding motion on the switching surface. The gain matrices of the sliding-mode observer are characterized using the solution of the LMI existence condition. The results are illustrated by an example.