• 한국산학기술학회논문지
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• 제15권10호
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• pp.6289-6295
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• 2014

BGA 또는 SMD 형태를 갖는 반도체 칩을 인쇄회로 기판에 장착/제거 등의 수리작업에 사용되는 리워크 시스템은 작업 대상물의 손상을 줄이기 위해 열풍 토출구의 온도를 정밀하게 제어할 필요가 있다. 본 논문에서는 비선형 시스템인 리워크 시스템의 열풍 온도 제어를 위해 TSK 퍼지 규칙으로 구성되는 퍼지 PID 제어기 설계 방법을 제시한다. 먼저 제안하는 제어기의 설계 알고리즘을 제시하고, 리워크 시스템에 적용하여 제어기를 설계하는 과정을 보인다. 제안한 제어기의 성능을 확인하기 위하여 온도 제어를 실험한 결과, 제안 방법의 최소자승오차는 9.44로서 일반적으로 사용하는 PID 제어기를 사용한 경우의 오차인 15.88보다 설정온도에 잘 수렴함을 보였다.

• 전기학회논문지
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• 제62권11호
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• pp.1590-1597
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• 2013

Electric power is an important part in economic development. Moreover, an accurate load forecast can make a financing planning, power supply strategy and market research planned effectively. This paper used the fuzzy logic system to predict the regional electric power load. To design the fuzzy prediction system, the correlation-based clustering algorithm and TSK fuzzy model were used. Also, to improve the prediction system's capability, the moving average technique and relative increasing rate were used in the preprocessing procedure. Finally, using four regional electric power load in Taiwan, this paper verified the performance of the proposed system and demonstrated its effectiveness and usefulness.

• International Journal of Control, Automation, and Systems
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• 제2권3호
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• pp.298-309
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• 2004

In this paper, a new evolutionary scheme to design a TSK fuzzy model from relevant data is proposed. The identification of the antecedent rule parameters is performed via the evolutionary algorithm with the unique fitness function and the various evolutionary operators, while the identification of the consequent parameters is done using the least square method. The occurrence of the multiple overlapping membership functions, which is a typical feature of unconstrained optimization, is resolved with the help of the proposed fitness function. The proposed algorithm can generate a fuzzy model with transparent membership functions. Through simulations on various problems, the proposed algorithm found a TSK fuzzy model with better accuracy than those found in previous works with transparent partition of input space.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2002년도 추계학술대회 및 정기총회
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• pp.84-87
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• 2002

This paper presents an adaptive PID control scheme with fuzzy model for nonlinear system. TSK(Takagi-Sugeno-Kang) fuzzy model was used to estimate the error of control input, and the parameter of PID controller was adapted from the error The parameter of TSK fuzzy model was also adapted to plant by comparing the activity output of plant and model output. PID controller which was adapted the uncertainty of nonlinear plant and the change of parameter can be designed by using the presented method. The usefullness of algorithm which was proposed by the simulation of several nonlinear system was also certificated.

• 전기학회논문지
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• 제66권12호
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• pp.1751-1758
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• 2017

This paper presents a fuzzy logic system with data preprocessing to make the accurate electric power load prediction system. The fuzzy logic system acceptably treats the hidden characteristic of the nonlinear data. The data preprocessing processes the original data to provide more information of its characteristics. Thus the combination of two methods can predict the given data more accurately. The former uses TSK fuzzy logic system to apply the linguistic rule base and the linear regression model while the latter uses the linear interpolation method. Finally, four regional electric power load data in taiwan are used to evaluate the performance of the proposed prediction system.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 춘계학술대회 학술발표 논문집 제14권 제1호
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• pp.381-384
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• 2004

본 논문에서는 변조 함수법을 이용하여 비선형 연속시스템의 퍼지모델 파라미터 인식을 위한 새로운 알고리즘을 제시하였다. 동력학 미분방정식은 미분항을 가지고 있기 때문에 입출력 데이터를 이용하여 퍼지모델 파라미터를 인식하는 경우 외란의 영향을 무시할 수 없으므로 퍼지모델 파라미터 인식이 어렵다. 그러나 변조 함수법을 이용하면 미분항을 소거할 수 있어 미분항이 없는 연립방정식으로부터 쉽게 퍼지모델 파라미터 인식이 가능하다 몇 개의 시뮬레이션을 통해 제안한 변조 함수법을 이용한 퍼지모델 파라미터 인식의 정확성과 유효성을 확인할 수 있었다.

• 센서학회지
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• 제21권5호
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• pp.329-338
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• 2012

This paper presents an effective design method for a gas identification system. The design method adopted the sequential combination between the hybrid genetic algorithms and the TSK fuzzy logic system. First, the sensor grouping method by hybrid genetic algorithms led the effective dimensional reduction as well as effective pattern analysis from a large volume of pattern dimensions. Second, the fuzzy identification sub-models allowed handling the uncertainty of the sensor data extensively. By these advantages, the proposed identification model demonstrated high accuracy rates for identifying the five different types of gases; it was confirmed throughout the experimental trials.

• 산업기술연구
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• 제30권A호
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• pp.111-117
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• 2010

To improve the performance of the prediction system, the system should reflect well the uncertainty of nonlinear data. Thus, this paper presents multiple prediction systems based on Type-2 fuzzy sets. To construct each prediction system, an Interval Type-2 TSK Fuzzy Logic System and difference data were used, because, in general, it has been known that the Type-2 Fuzzy Logic System can deal with the uncertainty of nonlinear data better than the Type-1 Fuzzy Logic System, and the difference data can provide more steady information than that of original data. Also, to improve each rule base of the fuzzy prediction systems, the HCBKA (Hierarchical Correlation Based K-means clustering Algorithm) was applied because it can consider correlationship and statistical characteristics between data at a time. Subsequently, to alleviate complexity of the proposed prediction system, a system selection method was used. Finally, this paper analyzed and compared the performances between the Type-1 prediction system and the Interval Type-2 prediction system using simulations of three typical time series examples.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 추계학술대회 학술발표 논문집
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• pp.372-375
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• 2000

퍼지 시스템은 비선형 시스템을 해석하고 제어기 설계 등에 많이 이용되고 있으나 대부분의 그 구현은 PC나 웍스테이션의 프로그램에 의존하고 있다. 고속의 동작을 요구하는 시스템이나 소형 시스템에는 전용 프로세서의 사용이 필요하다. 본 논문에서는 여러 퍼지 시스템 중에서 적은 규칙수로도 효과적인 성능을 나타내고 결론부가 선형식으로 표현되어 ASIC을 이용한 하드웨어화가 용이한 형태를 가진 TSK퍼지 추론 프로세서를 FPGA로 구현한다. ASIC의 설계는 Top-down 방식을 이용하여 전체구성은 Schematic을 이용하고 기능블록은 VHDL로 기술한다. TSK퍼지 추론의 연산은 전제부와 결론부를 병렬연산함으로써 고속처리를 구현하고 이에 필요한 제어부를 설계하였다. 또한 하드웨어 구현을 위해 실수연산을 이산화된 연산으로 바꾸고 이에 따른 나누기 연산자를 구현하였다.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.342-345
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• 2003

This paper presents an adaptive PID control scheme for nonlinear system. TSK(Takagi-Sugeno-Kang) fuzzy model is used to estimate the error of control input, and the parameter of PID controller are adapted using the error. The parameters of TSK fuzzy model are also adapted to plant. The proposed algorithm allows designing adaptive PID controller which is adapted to the uncertainty of nonlinear plant and the change of parameters. The usefulness of the proposed algorithm is also certificated by the several simulations.