• Journal of Electrical Engineering and information Science
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• v.1 no.2
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• pp.101-108
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• 1996

A new speed controller based on the fuzzy algorithm with hierarchical structure is presented. The input variables of the controller are speed error and its derivative(change of error), where the output variable is the change of torque current command. Several comparisons were performed with conventional PI (proportional plus integral) controller and proposed controller. These controllers are applied to the laboratory model drive system with 2.2kW induction motor. Some simulation and experimental results show that the speed controller using fuzzy algorithm is more robust than the conventional PI controller.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1097-1098
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• 2011

This paper proposes high performance control of induction motor drive using fuzzy neural network precompensation PI(FNPPI) controller. To apply industrial processes, control methods is requested technique that can be demonstrate high performance and robust about load disturbance, parameter variation and uncertainty of model, etc. The PI controller dose not show satisfactory performance due to fixed gain. Therefore, this paper proposes FNPPI which is adjusted input values of PI controller according to operating conditions of motor by FNN controller mixed neural network and fuzzy. And this paper proves validity of proposed control algorithm through result analysis.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.5
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• pp.173-179
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• 2000

While a cutting tool is machining a workpiece at various cutting depth, the feedrate is usually selected based on the maximum depth of cut. Even if this selection can avoid power saturation or tool breakage, it is very conservative compared to the capacity of the machine tools and can reduce the productivity significantly. Many adaptive control techniques that can adjust the feedrate to maintain the constant cutting force have been reported. However, these controllers are not very widely used in manufacturing industry because of the limitations in measuring the cutting force signals. In this paper, turning force control systems based on the estimated cutting force signals are proposed. A synthesized cutting force monitor is introduced to estimate the cutting force as accurately as a dynamometer does. Three control strategies of PI, adaptive and fuzzy logic controllers are applied to investigate the feasibility of utilizing the estimated cutting force fur turning force control. The experimental results demonstrate that the proposed systems can be easily realized in CNC lathe with requiring little additional hardware.

• The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.9 no.4
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• pp.103-110
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• 1995

Fuzzy theory is recently finding wide popularity in various applications that include management, economics, medicine and process control system. This paper describes application of fuzzy logic in a current control system that use a inverter welding machine. The Fuzzy control is then extended to the current loop control, replacing the conventional proportional-integral(PI) control methods. The fuzzy control algorithms have been developed in detail and verified by experiments of a inverter welding system. The experimentation study indicates the superiority of fuzzy control over the I control methods. Fuzzy control seems to have a lot of promise in the applications of welding process control system.

• 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 KIEE Conference
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• 2003.07d
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• pp.2164-2166
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• 2003

An automatic operation of train is executed by an automatic train operation(ATO) system. The main function of ATO system is to control train speed. So it makes the train stop at the programmed position accurately and improve riding comfort. In this paper, A fuzzy control is designed for speed control. The simulation is executed for verifying the speed control performance of the fuzzy system and comparing with that of the conventional PI.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.2
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• pp.346-349
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• 1994

In this paper, we implemented the variable spped controller of an induction motor using the self-tuning fuzzy control algorithms, which recently is invoking the remarkable interest. Also we preposed a self-tuning technique of scale factors which could easily design the fuzzy speed controller. Comparing with conventional PI speed controller, the performances of proposed fuzzy controller such as dynamic responses and its the robustness against load disturbance were substantially improved.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.418-420
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• 1989

Many complex industrial processes cannot be satisfactorily controlled using the results of modern control theory, mainly because their precise structure is unknown. However this is often balanced by a considerable amount of operator's heuristic knowledges for the process which is difficult to quantify and utilize. Fuzzy set theory is a relatively new concept which allows this qualitativeness to be expressed rigorously and therefore in this paper modified PI type fuzzy logic controller is introduced and its usefulness for control is assessed.

• International Journal of Air-Conditioning and Refrigeration
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• v.15 no.2
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• pp.61-69
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• 2007

This paper deals with fuzzy control with a feedforward compensator to progress both energy saving and coefficient of performance (COP) in a variable speed refrigeration system. Both the capacity and superheat are controlled simultaneously and independently in the system. By adopting the fuzzy theory, the controller design for the capacity and superheat is possible without depending on a dynamic model of the system. Moreover, the feedforward compensator of the superheat can reduce influence of the interfering loop between the capacity and superheat. Some experiments are conducted to design appropriate fuzzy controller by an iteration manner. The results show that the proposed fuzzy controller with the compensator can establish good control performances for the complicated refrigeration system in spite of its inherent strong non-linearity. Also, the fuzzy control performances were investigated by comparing to the model based PI control experimental results to evaluate transient behavior under the control.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1086-1088
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• 1993

A robust fuzzy self-organizing controller(SOC) is proposed for an environmental temperature chamber. Although fuzzy SOC can improve the performance of nonlinear system, the controller is ineffective to solve the performance degradation owing to the time varying factors. In this paper, we construct the fuzzy SOC with a predictive scheme based on the 386PC. The usefulness of the proposed scheme is shown through the comparison of the PI controller and the fuzzy controller.