• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2007년도 춘계학술대회 학술발표 논문집 제17권 제1호
• /
• pp.390-393
• /
• 2007

In this paper, applications of self recurrent neuro-fuzzy controller to stabilization of nonlinear system are considered. The architecture of self recurrent neuro-fuzzy controller is fix layer, and the hidden layer is comprised of self recurrent architecture. Also, generalized dynamic error-backpropagation algorithm is used for the learning of the self recurrent neuro-fuzzy controller. To demonstrate the efficiency of the self recurrent neuro-fuzzy control algorithm presented in this study, a self recurrent neuro-fuzzy controller was designed and then a comparative analysis was made with LQR controller through an simulation.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제4권2호
• /
• pp.187-192
• /
• 2004

In this paper, we proposed the method to design fuzzy controller using the experience of the operating expert and experimental numeric data for the robust control about the noise and disturbance instead of the traditional PID controller for the main steam temperature control of the thermal power plant. The temperature of main steam temperature process has to be controlled uniformly for the stable electric power output. The process has the problem of the hunting for the cases of various disturbances. In that case, the manual action of the operator happened to be introduced in some cases. We adopted the TSK (Takagi-Sugeno-Kang) model as the fuzzy controller and designed the fuzzy rules using the informations extracted directly from the real plant and various operating condition to solve the above problems and to apply practically. We implemented the real fuzzy controller as the Function Block module in the DCS(Distributed Control System) and evaluated the feasibility through the experimental results of the simulation.

• 한국지능시스템학회논문지
• /
• 제13권5호
• /
• pp.564-570
• /
• 2003

본 논문에서는 동력학이 비선형이고, 상태가 불명확하거나 시간에 따라 변화하는 헬리콥터 시스템의 제어를 위해 TSK 퍼지시스템을 이용한 적응 퍼지제어기 설계 방법을 제안한다. 논문에서 제안한 적응 퍼지제어기는 규범모델의 출력을 시스템의 출력이 추종하도록 퍼지제어기 파라미터를 직접 조정하는 규범모델 적응 퍼지제어기이다 또한 Lyapunov 함수를 이용하여 폐루프 시스템의 안정성을 보장하면서 최적인 적응법칙을 유도하였다. 실험실용 모델 헬리콥터 시스템에 대한 실험에서 시스템에 외란이 가해질 때, 제안되고 설계된 적응 퍼지제어기는 적응이 없는 퍼지제어기에 비해 시스템의 상태변화에 성공적인 제어가 실행됨을 보여주었다.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1998년도 The Third Asian Fuzzy Systems Symposium
• /
• pp.320-325
• /
• 1998

Underwater robotic vehicles (URVs) have been an important tool for various underwater tasks because they have greater speed, endurance, depth capability, and safety than human divers. As the use of such vehicles increases, the vehicle control system becomes one of the most critical subsytems to increase autonomy of the vehicle. The vehicle dynamics are nonlinear and their hydrodynamic coefficients are often difficult to estimate accurately. In this paper a new type of fuzzy model-based controller based on Takagi-Sugeno-Kang fuzzy model is designed and applied to the control of of an underwater robotic vehicle. The proposed fuzzy controller : 1) is a nonlinear controller, but a linear state feedback controller in the consequent of each local fuzzy control rule ; 2) can guarantee the stability of the closed-loop fuzzy system ; 3) is relatively easy to implement. Its good performance as well as its robustness to the change of parameters have been shown and compared with the re ults of conventional linear controller by simulation.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2000년도 하계학술대회 논문집 D
• /
• pp.2290-2292
• /
• 2000

Robustness characteristics to the modelling imprecision and some disturbances could be achieved in sliding mode control. However, there are drawbacks such as discontinuous control and chattering. Recently, many researches have been developing to solve such the problems. In sliding mode control, overall control input could be divided into two parts which are equivalent control input and sliding mode control input. Sliding mode control input is a function of the switching surfaces and can be designed with their linear combinations. In this paper, the sliding mode control input is designed by TSK fuzzy model. The proposed method gives the continuous sliding control input and reject the chattering phenomenon.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2002년도 ICCAS
• /
• pp.109.6-109
• /
• 2002

In this paper, the scheme of fuzzy system construction using GA(genetic algorithm) and FCM(Fuzzy c-means) clustering algorithm is proposed for TSK(Takagi-Sugeno-Kang) type fuzzy system. in the structure identification, input data is trans-formed by PCA(Principal Component Analysis) to reduce the correlation among input data components. And then, the number of fuzzy rule is obtained by a given performance criterion. In the parameter identification, the premise parameters are optimally searched by GA. On the other hand, the consequent parameters are estimated by RLSE(Recursive Least Square Estimate) to reduce the search space. From this, one can systematically obtain optimal parameter and the v..

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2005년도 ICCAS
• /
• pp.1254-1259
• /
• 2005

In this paper, we proposed a learning algorithm for the neuro-fuzzy modeling using a learning rule to adapt clustering. The proposed algorithm includes the data partition, assigning the rule into the process of partition, and optimizing the parameters using predetermined threshold value in self-constructing algorithm. In order to improve the clustering, the learning method of neuro-fuzzy model is extended and the learning scheme has been modified such that the learning of overall model is extended based on the error-derivative learning. The effect of the proposed method is presented using simulation compare with previous ones.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
• /
• pp.126-129
• /
• 2002

An intelligent digital redesign technique (IDR) for the observer-based output feedback Takagi-Sugeno (T-5) fuzzy control system with fuzzy outputs is developed. The considered IDR condition is cubically parameterized as convex minimization problems of the norm distances between linear operators to be matched.'rho stability condition is easily embedded and the separations principle is explicitly shown.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2004년도 ICCAS
• /
• pp.975-980
• /
• 2004

Positioning system is widely used for many practical applications. This system requires a good controller to achieve high accuracy and fast response with simple and self-adjustable design. In order to satisfy the above requirements, a new practical controller for positioning systems, namely nominal characteristic trajectory following (NCTF) controller with PI compensator, has been proposed. However, the effect of actuator saturation can not be completely compensated for integrator windup when the object parameters vary. This paper presents a method to improve the NCTF controller by overcoming the problem of integrator windup by adopting a fuzzy system. The improvement of the NCTF controller is evaluated through simulation using a rotary positioning system. The simulation result has demonstrated the effectiveness of the compensated NCTF in overcoming the problem of integrator windup.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1997년도 하계학술대회 논문집 B
• /
• pp.425-427
• /
• 1997

In this paper, a new approach to modeling and control of nonlinear systems using fuzzy theory is presented. To express the various and complex behavior of nonlinear system, we combine multiple model method with hierachical prioritized structure. The mountain clustering technique is used in partitioning of system, and TSK rule structure is adopted to form the fuzzy rules. Also we soften the paradigm of Mamdani's inference mechanism by using Yager's S-OWA operators.