• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.63-64
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• 2015

제어 대상이 다양해지고, 제어 변수도 다양해짐에 따라 기존의 PID 제어 시스템으로는 설계자가 원하는 응답 특성을 이끌어내기 어려워지고 있다. 제어 대상의 복잡도가 증가함에 따라 제어 대상에 대한 사용자의 숙련도 또한 제어 품질의 중요 변수이다. 사람의 경험을 제어에 체계적으로 반영하려는 시도 중에 하나가 퍼지이론의 제어 적용이며, 본 논문에서는 간단한 퍼지 제어 시스템을 구현하여 모터 제어에 활용가능성을 확인하고자 한다. 매트랩을 이용한 모의 실험을 통해, 쿼드콥터의 모터에 대하여 PID 제어와 Fuzzy 제어를 적용시켜 그 성능을 비교 및 분석하였다.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1950-1951
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• 2011

본 논문에서는 요구되는 성능을 만족시키는 최적 Fuzzy PI 제어의 정압제어로의 효율적인 적용 및 성능 향상을 위하여 유전자 알고리즘(GA: Genetic Algorithm)을 이용한 제어 설계 방법을 제시 한다. PID제어기는 이해가 쉽고 구조가 간단하여, 실제 구현이 용이하여 공정 산업분야에서 가장 널리 사용되고 있는 제어기 이다. 따라서 단일 입 출력 선형 시스템 에서는 우수한 성능을 보이나 동적 시스템, 고차 시스템 및 수학적 모델 선정이 어려운 시스템에서는 비효율 적이다. 반면, Fuzzy 제어기는 인간의 지식과 경험을 이용한 지적 제어방식으로 IF-THEN형식의 규칙으로부터 제어 입력을 결정하는 병렬형 제어기이다. 이는 과도상태에서 큰 오버슈트 없이 설정치에 도달하게 하는 속응성과 강인성이 좋은 제어기법으로 비선형성이 강하고 불확실하며 복잡한 시스템을 쉽게 제어 할 수 있다는 장점을 지닌다.

• Proceedings of the KIPE Conference
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• 2000.07a
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• pp.460-463
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• 2000

Fuzzy logic control(FLC) has been studied extensively and has been applied in various applications. The most popular control strategy takes the Fuzzy Proportional-Integral(FPI) form while systematic methods have been developed to derive the fuzzy rules and membership functions the choice of the scaling factors remains an open problem, In this paper an analytical FPI scaling factor determining method is derived based on the functional equivalence of the PI and FPI controllers. Simulation have been carried out with a brushless DC motor drive system as test-bed the obtained results drive system as test-bed the obtained results have verified that the derived method is applicable to both the initial choice and further tuning of the FPI scaling factors.

• Journal of Power Electronics
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• v.10 no.1
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• pp.65-71
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• 2010

This paper presents the design and implementation of voltage source inverter type SVPWM based speed control of an induction motor using a fuzzy PI controller. This scheme enables us to adjust the speed of the motor by controlling the frequency and amplitude of the stator voltage; the ratio of the stator voltage to the frequency should be kept constant. A model of the fuzzy control system is implemented in real time with a Xilinx FPGA XC3S 400E. It is introduced to maintain a constant speed to when the load varies.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.11a
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• pp.73-78
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• 1996

In this study, we proposed a fuzzy gain scheduler with intelligent learning algorithm for a reactor control. In the proposed algorithm, we used the gradient descent method to learn the rule bases of a fuzzy algorithm. These rule bases are learned toward minimizing an objective function, which is called a performance cost function. The objective of fuzzy gain scheduler with intelligent learning algorithm is the generation of adequate gains, which minimize the error of system. The condition of every plant is generally changed as time gose. That is, the initial gains obtained through the analysis of system are no longer suitable for the changed plant. And we need to set new gains, which minimize the error stemmed from changing the condition of a plant. In this paper, we applied this strategy for reactor control of nuclear power plant (NPP), and the results were compared with those of a simple PI controller, which has fixed gains. As a result, it was shown that the proposed algorithm was superior to the simple PI controller.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.458-460
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• 1998

The drum level control is initiated by 1-element manual control, and then the control mode is changed to 1-element automatic control mode. Finally, the drum level control is changed to 3-element automatic control mode by the logic based on pre-defined threshold of main steam flow. In terms of plant automation, the automatic 1-element control mode is required from the start-up of boiler. In this paper, the fuzzy controller is adopted for automatic 1-element control of drum level from start-up. It is suggested that the fuzzy controller is used in 1-element control, and the fuzzy-PI cascade controller is used in 3-element control. Finally, the validity of suggested control scheme is shown via simulation.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.173-174
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• 2007

In this paper, a new speed sensorless control based on an instantaneous reactive power and a fuzzy PI compensator are proposed for the interior permanent magnet synchronous motor (IPMSM) drives. The conventional fixed gain PI and PID controllers are very sensitive to step change of command speed, parameter variations and load disturbance. Also, to the estimated speeds are compensated by using an instantaneous reactive power in synchronously rotating reference frame. In a fuzzy compensator, the system control parameters are adjusted by a fuzzy rule based system, which is a logical model of the human behavior for process control. The effectiveness of algorithm is confirmed by the experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.67.1-67
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• 2001

This paper presents a neural network based self-tuning fuzzy PI-PD control scheme for robust speed control of induction motor. The PID controller is being widely used in industrial applications. When continuously used long time, the electric and mechanical parameters of induction motor change, degrading the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, and proposes a neural network based self-tuning fuzzy PI-PD controller whose scaling factors are adjusted automatically. Proposed scheme is simple in structure and computational burden is small ...

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.45.1-45
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• 2001

This paper proposes a Mamdani fuzzy PID controller for controlling a process with small dead time. The controller composes of a parallel structure of fuzzy PI controller and fuzzy PD controller. Each controller has two inputs, error and change of error. Hence, the control signal of the proposed controller is the average value of the output of the fuzzy PI and PD controllers. The Mamdani fuzzy PID controller is easily to be adjusted to meet the desired control system performances both in transient state and steady state. The simulation results of the proposed Mamdani fuzzy PID controller by using the same parameters (proportional gain, integral time and derivative time) as the conventional PID controller are shown. The response of the Mamdani fuzzy PID control system is faster than the conventional PID control system. Both system responses have ...

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.64-72
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• 1995

This paper proposes how to tune the gains of PI controllers in case of gain change in a process control system. Controllers of PI type have been used in industry and the gains of the controllers have been tuned by expert engineers. It, therefore, takes much time and efforts to tune the controllers. It is more difficult to find gains of multi-loop processes. The tuning method of a fuzzy tuner in this paper is developed based on the assumptions that the PI controllers are of analog type and are tuned off-line, and that the characteristic values must be supplied for the tuner. A Tuner using Fuzzy Logic(FLT1 is capable of showing presentlpast states of a process control system and finding gains of PI controllers. The verfication of the FLT is shown by various experiments.