• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권1호
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• pp.52-57
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• 2006

In this paper, we have proposed a new adaptive fuzzy control algorithm based on Takagi-Sugeno fuzzy model. The regulation problem for the uncertain SISO nonlinear system is solved by the proposed algorithm. Using the advanced stability theory, the stability of the state, the control gain and the parameter approximation error is proved. Unlike the existing feedback linearization based methods, the proposed algorithm can guarantee the global stability in the presence of the singularity in the inverse dynamics of the plant. The performance of the proposed algorithm is demonstrated through the problem of balancing and swing-up of an inverted pendulum on a cart.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 D
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• pp.2819-2821
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• 2000

We introduce Adaptive Fuzzy Impedance Controller for force control when robot contact with environment. Because robot and environment was always effected by nonlinear conditions. it needs to deal with parameter's uncertainty. As. it induced Fuzzy system in impedance controller. it used fuzzy inference logic that has robustness about uncertainty to tune impedance controller stiffness gain. We applied adaptive fuzzy impedance controller in One-Link Robot system and the method shows a good performance on desired position and force control with intensional contacting environment.

• Journal of Advanced Marine Engineering and Technology
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• 제24권4호
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• pp.435-440
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• 2000

The speed control system of diesel engine is considerably nonlinear. Therefore, a countermeasure such as gain scheduling used to be incorporated to compensate this nonlinearity. On the other hand, it is said that fuzzy control is very robust against nonlinearity. But it is difficult to get a satisfactory response with only fuzzy control in real system. In this paper authors design a fuzzy-PI controller for the speed control of Medium diesel engine and carry out experiments with dedicate system implemented by Intel 80916KC to real diesel engine, Deawoo MAN 6Cyl., 1800rpm driving 3$\psi$220V, 150KW generator. We confirm the effectiveness of proposed control system.

• International Journal of Control, Automation, and Systems
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• 제5권3호
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• pp.324-328
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• 2007

An analytical framework for fuzzy modeling and control of nonlinear systems using a set of linear models is presented. Fuzzy clustering is applied on the aerodynamic coefficients of a missile to obtain an optimal number of rules in a Tagaki-Sugeno fuzzy rule-set. Next, the obtained membership functions and rule-sets are applied to a set of linear optimal controllers towards extraction of a global controller. Reported simulations demonstrate the performance, stability, and robustness of the controller.

• 한국지능시스템학회논문지
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• 제12권3호
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• pp.261-268
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• 2002

This paper represents that auto tunings of membership functions and weights in the fuzzy neural networks are effectively performed by immune algorithm. A number of hybrid methods in fuzzy-neural networks are considered in the context of tuning of learning method, a general view is provided that they are the special cases of either the membership functions or the gain modification in the neural networks by genetic algorithms. On the other hand, since the immune network system possesses a self organizing and distributed memory, it is thus adaptive to its external environment and allows a PDP (parallel distributed processing) network to complete patterns against the environmental situation. Also, it can provide optimal solution. Simulation results reveal that immune algorithms are effective approaches to search for optimal or near optimal fuzzy rules and weights.

• 전력전자학회:학술대회논문집
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• 전력전자학회 2002년도 추계학술대회 논문집
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• pp.40-44
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• 2002

In this paper, robust control method using fuzzy PI parameter tuning is proposed to control constant thrust force on load variation. First, a structure and thrust force equations of the LPM are described. Second, an controller with PI parameter-tuning using a fuzzy theory is proposed to achieve high-precision position with constant thrust force of the LPM. Finally, the effectiveness of an fuzzy PI controller is demonstrated by some simulated and experimental results. Accurate tracking response and superior dynamic performance can be obtained due to the powerful on-line Fuzzy PI gain tuning method with regard parametric variations and load thrust force variations.

• 한국지능시스템학회논문지
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• 제21권4호
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• pp.423-429
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• 2011

본 논문은 고분자 전해질 연료전지 시스템(PEMFC)을 위한 비선형 상호결합 시스템의 분산 퍼지 제어기 설계 기법을 제안한다. 이를 위해 연료전지 시스템의 비선형성을 확인하고, Takagi-Sugeno (T-S) 퍼지 모델링을 통하여 비선형 시스템을 퍼지 모델로 변환한다. 변환된 퍼지 모델을 기반으로 퍼지 관측기를 설계하고 퍼지 시스템을 안정화 시킬 수 있는 분산 퍼지 제어기를 설계한다. 폐루프 시스템의 안정도 조건을 선형 행렬 부등식으로 나타내고, 부등식을 이용하여 제어기의 이득값을 구한다. 마지막으로, 모의실험을 통하여 제어기의 효용성을 평가한다.

• 산업기술연구
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• 제20권B호
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• pp.155-162
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• 2000

Although Fuzzy Logic Controller(FLC) adopted three terms as input gives better performance, FLC is in general composed of two-term control because of the difficulty in the construction of fuzzy rule base. In this paper, a three-term FLC which is similar to PID control but acts as a nonlinear controller is proposed. To reduce the complexity of the rule base design and to increase efficiency. a simplified fuzzy PID control is induced from a hybrid velocity/position type PID algorithm by sharing a common rule base for both fuzzy PI and fuzzy PD parts. It is simple in structure, easy in implementation, and fast in calculation. The phase plane technique is applied to obtain the rule base for fuzzy two-term control and the resultant rule base is Macvicar-Whelan type. And the membership function is a Gaussian function. The frequency response information is used in tuning of the membership functions. Also a tuning strategy for the scaling factors is proposed based on the relationship between PID gain and the scaling factors. Simulation results show better performance and the effectiveness of the proposed method.

• 한국기계가공학회지
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• 제15권2호
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• pp.131-138
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• 2016

In order to improve the performance of an extended Kalman filter, a simplified indirect inference method (SIIM) fuzzy logic system (FLS) is proposed. The proposed FLS is composed of two fuzzy input variables, four fuzzy rules and one fuzzy output. Two normalized fuzzy input variables are the variance between the trace of a prior and a posterior covariance matrix, and the residual error of a Kalman algorithm. One fuzzy output variable is the weighting factor to adjust for the Kalman gain. There is no need to decide the number and the membership function of input variables, because we employ the normalized monotone increasing/decreasing function. The single parameter to be determined is the magnitude of a universe of discourse in the output variable. The structure of the proposed FLS is simple and easy to apply to various nonlinear state estimation problems. The simulation results show that the proposed FLS has strong adaptability to estimate the states of the incoming/outgoing moving objects, and outperforms the conventional extended Kalman filter algorithm by providing solutions that are more accurate.

• 한국지능시스템학회논문지
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• 제14권1호
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• pp.112-117
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• 2004

본 논문에서는 Takagi-Sugeno(T-S) 퍼지 시스템 모델을 이용한 비선형 시스템의 퍼지 슬라이딩 모드제어방식을 제안한다. 이 방식에서는 하나의 T-S 퍼지 모델을 구성하는 각 선형 동력학의 입력 이득행렬을 단일화 하는 과정을 필요로 한다. 이 과정에서 생성되는 입력 불확실성은 슬라이딩 모드 제어의 외란에 대한 처리 방법으로 해결될 수 있다. 또한 기존의 T-S 퍼지 모델에 대한 제어방식에서 처리하지 못했던, 상태변수에 독립적이기 때문에 선형화되지 않는 비선형 항에 대한 문제를 해결할 수 있다. 제안된 제어시스템의 안정도를 보이며 제어 입력이 슬라이딩 평면에 대한 도달조건을 만족함을 보인다. 제안된 제어방식의 타당성과 제어기 설계과정을 보이기 위하여 역진자 시스템에 적용한 시뮬레이션 결과를 보인다.