• The Transactions of the Korean Institute of Power Electronics
• /
• 제7권3호
• /
• pp.215-223
• /
• 2002

This paper investigates the adaptive control of a fuzzy logic based speed and flux controller fur a vector controlled induction motor drive. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the model reference adaptive control(MRAC) fuzzy controller is evaluated by simulation for various operating conditions. The validity of the Proposed MRAC fuzzy controller is confirmed by performance results for induction motor drive system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 한국해양정보통신학회 1999년도 춘계종합학술대회
• /
• pp.355-360
• /
• 1999

In this paper, we propose a method that optimizes the parameters of fuzzy logic controller : centers and widths of membership functions and scaling factors using genetic algorithm. Before fuzzy logic controller controls a plant in real time, first off it is optimized by genetic algorithm. We select error and error variation between reference trajectory and real output for the input signals of fuzzy controller. We compared and investigated conventional fuzzy control method and proposed method through simulation and experiment using one link manipulator with nonlinear characteristic.

• Journal of the Korean Society for Precision Engineering
• /
• 제15권9호
• /
• pp.56-67
• /
• 1998

This paper introduces a friction compensation fuzzy logic controller, which utilizes a rule-based approach. The paper explains the algorithm of the proposed controller and compares it with a conventional PID controller in simulations and experiments. For the experiments, the two control algorithms were implemented on a 3-axis milling machine in contour milling. These simulation and experimental analyses show that the proposed fuzzy logic controller has superior performance over conventional PID controllers In terms of part contour accuracy.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• 제16권11호
• /
• pp.2474-2479
• /
• 2012

A sensorless vector control of an induction motor provides a good performance in the middle and high speed region. However, in the low speed region, it is very difficult to implement the sensorless vector controller because the feeding voltage measured by the motor is very low. In this paper, to improve the performance of a sensorless vector control of an induction motor in the low speed region under 3Hz, we proposed the fuzzy logic controller using the zooming algorithm. To verify the performance of the proposed controller, an experiment has been performed.

• Journal of the Korean Institute of Intelligent Systems
• /
• 제7권5호
• /
• pp.46-50
• /
• 1997

In fuzzy logic control, static fuzzy rules cannot cope with significant changes of parameters of plants or environment. To solve this prohlem, self-organizing fuzzy control. neural-network-hased fuzzy logic control and so on have heen introduced so far. However, dynamically changed fuzzy rules of these schemes may make a fuzzy logic controller Fall into dangerous situations because the changed fuzzy rules may he incomplete or inconsistent. This paper proposes a new adaptive filzzy logic control scheme using a predictivc neural network. Although some parameters of a controlled plant or environment are changed, proposed fuzzy logic controller changes its decision outputs adaptively and robustly using unchanged initial fuzzy rules and the predictive errors generated hy the predictive neural network by on-line learning. Experimental results with a D<' servo-motor position control problem show that propnsed cnntrol scheme is very useful in the viewpoint of adaptability.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• 제11권3호
• /
• pp.295-300
• /
• 2018

Conventionally, a PI control algorithm has been widely used as a speed control algorithm for BLDC motor. The PI control algorithm has a disadvantage in that is slow to reach the steady state due to the slow speed and torque response with various speed changes. Therefore, in this paper, PWM fuzzy logic control algorithm which can reach the steady state quickly by improving the response speed although there is a little overshoot is proposed. PWM reduces response speed and fuzzy logic control algorithm minimizes overshoot. The proposed PWM fuzzy logic control algorithm consists of DC chopper, PWM duty cycle regulator, and fuzzy logic controller. The performance and validity of the proposed algorithm is verified by simulation with Simulink of Matlab 2018a.

• The KIPS Transactions:PartB
• /
• 제8B권2호
• /
• pp.123-129
• /
• 2001

본 연구에서는 전문가와 운전자의 제어 지식을 더 정확하게 표현하여 퍼지 논리 제어기의 성능을 향상시킬 수 있는 소속함수 수정 알고리즘을 제안한다. 제안된 알고리즘은 제어지식을 더 정확히 표현할 수 있도록 직관적인 지식과 경험으로부터 유추된 대략적인 제어지식을 평가기준으로 하고 입출력 데이터 클러스터링에 의해 소속함수의 형태와 위치를 수정한다. 제안된 방법을 수위 조절 모델과 교통신호 제어 모델에 적용한 실험을 통해서, 제안된 알고리즘이 기존 제어기의 성능을 향상시킬 수 있고, 퍼지 제어기에서 언어적 변수에 대한 구간 설정의 어려움을 해결할 수 있음을 알 수 있었다.

• Journal of Korean Society of Transportation
• /
• 제14권1호
• /
• pp.117-133
• /
• 1996

In the paper a superior performance algorithm compared to the existing vehicle actuated controller and time fixed controller and the additional controller is described through realization of fuzzy traffic phase controller. Fuzzy theory is encouraging since the application is similar to human's decision ability that is approately coped with uncertain conditions. The paper presents that selection of the phase adequated the variable traffic conditions through the fuzzy theory algorithm and decision of optimal cycle time approated the uncertain traffic volume are predominant in traffic jam solution compared to the existing Webster's cycle time decision method and the sequential traffic phase design method and dual-ring phase operation system.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• 제9권3호
• /
• pp.676-683
• /
• 2005

In this paper, we proposed a method that optimal values of fuzzy control rule base and quantization of membership function are searched by genetic algorithm. Proposed method searched the optimal values of membership function and control rules using genetic algorithm by off-line. Then fuzzy controller operates using these values by on-line. Proposed fuzzy control system is optimized the control rule base and membership function by genetic algorithm without expert's knowledge. We investigated proposed method through simulation and experiment using DC motor and one link manipulator, and confirmed the following usefulness.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
• /
• pp.440-443
• /
• 2000

오늘날 도시교통은 계속적으로 증가하는 자동차에 의해 극심한 정체를 겪고 있다. 복잡한 교통상황에서 도시의 한정된 도로를 최적으로 이용함으로써 교통의 흐름을 효율적으로 통제할 수 있는 시스템의 필요성이 높아지고 있다. 멀티 에이전트 시스템은 이러한 복잡한 교통 상황을 해소하는 새로운 방법으로 인식되고 있다. 본 논문에서는 Visual C++ 언어를 이용하여 개발하고 교차로망 시뮬레이션을 위한 에이전트 기반의 퍼지 논리 제어기를 제안하였다. 제안된 퍼지 논리 제어기는 교통량이 많더라도 교통신호 주기를 통제하기에 적합한 방법이며, 이 방법의 효과를 교차로망 시뮬레이션을 이용하여 입증하였다.