• 대한전기학회논문지:전력기술부문A
• /
• 제52권1호
• /
• pp.36-43
• /
• 2003

This paper presents an optimal tuning method for Fuzzy Logic Controller (FLC) of current controller for HVDC using Genetic Algorithm(GA). GA is probabilistic search method based on genetics and evolution theory. The scaling factors of FLC are tuned by using real-time GA. The proposed tuning method is applied to the scaled-down HVDC simulator at Korea Electrotechnology Research Institute(KERI). Experimental result shows that disturbances are well-damped and the dynamic performances of FLC have the better responses than those of PI controller for small and large disturbances such as ULTC tap change, reference DC current change and DC ground fault.

• 한국정보통신학회논문지
• /
• 제10권1호
• /
• pp.212-219
• /
• 2006

퍼지 논리 제어기(FLC : Fuzzy Logic Controller)를 사용할 때, 가장 중요한 것은 소속 함수의 범위를 정하는 것과 규칙의 형태를 결정하는 것이다. 소속 함수의 범위나 규칙의 형태는 자금까지 전문가가 임의로 정하는 방법을 사용하였다. 그러나 기존의 방법을 사용하면, 전문가의 주관적인 규칙과 소속 함수가 생성될 수 있고, 소속함수의 경우 최적의 범위를 정확히 예측하기 어려운 단점이 있다. 본 논문에서는 이런 단점을 보완하기 위해, 유전자 알고리즘을 사용함으로써 최적의 소속 함수와 규칙의 형태를 구하려 하였다. 제시하는 방법의 타당성을 검증하기 위해 자동차 주행 제어 문제에 적용시켜 보았다.

• Structural Engineering and Mechanics
• /
• 제51권4호
• /
• pp.547-564
• /
• 2014

This study focuses on the application of an active tuned mass damper (ATMD) for controlling the seismic response of an 11-story building. The control action is achieved by combination of a fuzzy logic controller (FLC) and Particle Swarm Optimization (PSO) method. FLC is used to handle the uncertain and nonlinear phenomena while PSO is used for optimization of FLC parameters. The FLC system optimized by PSO is called PSFLC. The optimization process of the FLC system has been performed for an 11-story building under the earthquake excitations recommended by International Association of Structural Control (IASC) committee. Minimization of the top floor displacement has been used as the optimization criteria. The results obtained by the PSFLC method are compared with those obtained from ATMD with GFLC system which is proposed by Pourzeynali et al. and non-optimum FLC system. Based on the parameters obtained from PSFLC system, a global controller as PSFLCG is introduced. Performance of the designed PSFLCG has been checked for different disturbances of far-field and near-field ground motions. It is found that the ATMD system, driven by FLC with the help of PSO significantly reduces the peak displacement of the example building. The results show that the PSFLCG decreases the peak displacement of the top floor by about 10%-30% more than that of the FLC system. To show the efficiency and superiority of the adopted optimization method (PSO), a comparison is also made between PSO and GA algorithms in terms of success rate and computational processing time. GA is used by Pourzeynali et al for optimization of the similar system.

• 한국지능시스템학회논문지
• /
• 제9권5호
• /
• pp.496-508
• /
• 1999

Fuzzy System which are based on membership functions and rules can control nonlinear uncertain complex systems well. However Fuzzy logic controller(FLC) has problems; It is difficult to design the stable FLC and FLC depends mainly on individual experience. Although FLC can be designed using the error back-propagation algorithm it takes long time to converge into global optimal parameters. Well-developed linear system theory should not be replaced by FLC but instead it should be suitably used with FLC. A new methodology is introduced for designing THEN-PART membership functions of FLC based on its well-tuned state feedback controller. A example of inverted pendulum is given for demonstration of the robustness of proposed methodology.

• 한국지능시스템학회:학술대회논문집
• /
• 한국퍼지및지능시스템학회 1996년도 추계학술대회 학술발표 논문집
• /
• pp.141-144
• /
• 1996

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
• /
• pp.1080-1085
• /
• 1993

A nonlinear control algorithm for the depth control of underwater vehicles is presented. In order to consider the deadzone effect of the flow control valve, a nonlinear fuzzy logic controller (FLC) is synthesized and combined with a linear proportional-derivative-acceleration (PDA) controller, which is called, the PDA/FLC controller. And, to show the effectiveness of the PDA/FLC control system, it is compared with the linear PDA control system through computer simulation. It is found that the PDA/FLC control scheme is a suitable one to maintain the desirable depth of underwater vehicles with deadzone.

• 제어로봇시스템학회논문지
• /
• 제6권11호
• /
• pp.995-1002
• /
• 2000

In this paper, fuzzy logic controllers(FLC) are designed for control of flight. For tuning FLC, we used adaptive evolutionary algorithms(AEA) which uses a genetic algorithm(GA) and an evolution strategy (ES) in an adaptive manner in order to take merits of two different evolutionary computations. We used AEA to search for optimal settings of the membership functions shape and gains of the inputs and outputs of FLC. Finally, the proposed controller is applied to the high-angle-of-attack flight system for a supermaneuverable version of the f-18 aircraft and compares with other methods.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
• /
• pp.441-446
• /
• 1992

We propose a control architecture for the fuzzy logic control of robot manipulators and a rule base derivation method for a fuzzy logic controller(FLC) using a neural network. The control architecture is composed of FLC and PD(positional Derivative) controller. And a neural network is designed in consideration of the FLC's structure. After the training is finished by BP(Back Propagation) and FEL(Feedback Error Learning) method, the rule base is derived from the neural network and is reduced through two stages - smoothing, logical reduction. Also, we show the performance of the control architecture through the simulation to verify the effectiveness of our proposed method.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1995년도 하계학술대회 논문집 B
• /
• pp.830-832
• /
• 1995

A position Control algorithm of the flexible manipulator is studied. The proposed algorithm is based on a Fuzzy Logic Control(FLC) method using the human's experiences. FLC does not need a dynamic modeling of a flexible manipulator. A Fuzzy logic controller is designed that the end-point of the flexible manipulator tracks the desired trajectory. The control input to the process is determined by the error and variation of error. Simulation result shows a robustness of FLC compared with the PID control algorithm.

• 디지털콘텐츠학회 논문지
• /
• 제2권1호
• /
• pp.51-61
• /
• 2001

퍼지 제어기(FLC)는 고전적인 제어기 보다 외란에 강하고 초기치에 대한 과도응답도 우수할 뿐만 아니라 시스템의 수학적 모델과 파라메터 값을 알지 못하더라도 적절한 제어가 가능하다. 그러나 퍼지 제어기의 제어 규칙 생성은 전문가의 경험과 일단 결정된 제어 규칙은 고정됨으로 인해 제어 시스템의 환경변화에 적응할 수 없는 한계성이 있다. 또한 제어기의 출력값은 미세한 오차를 가지곤 있어 정확한 목표 값에 수렴할 수 없다. 이러한 미세한 오차를 없애기 위하여 여러 가지 방법이 연구되고 있는데, 본 논문에서는 FLC에 NN(Neural Network)과 GA(Genetic Algorithm)를 결합한 GA-FNNIC(유전알고리즘-퍼지 신경망 지능 제어기 : Genetic Algorithm - Fuzzy Neural network Intelligence Controller)를 제안한다. 제안된 GA-FNNIC와 FLC 제어기 간의 출력 특성, 수렴속도, 과도특성과 상승시간에 대해 비교 분석하고, 최종적으로 본 GA-FNNIC가 오차없이 목표치에 정확하게 수렴하는 것을 보인다.