• 조명전기설비학회논문지
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• 제18권6호
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• pp.70-77
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• 2004

산업 응용분야에서 유도전동기 구동시스템의 예상치 않은 고장은 전체 계통의 정지, 막대한 손실 등을 가져올 수 있다. 이러한 문제점을 해결하는 방법 중에 하나로서 본 논문은 유도전동기 구동을 위한3상 전압형 PWM 인버터에 개방-스위치 손상의 고장진단에 대하여 연구한다. 고장진단 방법으로는, 먼저 고장의 특징추출을 위하여 3상 전류를 d-q 전류로 변환한 후 평균 전류벡터를 구한다. 다음으로 여러 종류의 고장 패턴을 진단하기 위하여 한 인공지능 알고리즘을 제안한다. 제안된 기법은 일반적인 뉴로-퍼지 시스템(adaptive neuro-fuzzy algorithm)의 전제 부에 클러스터링을 도입한 기법으로 적은 계산 양과 좋은 성능을 갖는다. 최종적으로, 여러 불확실한 요소를 가진 고장계통에 대하여 제안된 알고리즘의 유용성을 모의실험에 의해 검증하였다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권1호
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• pp.27-32
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• 2006

Verbal communication is the most commonly used mean of communication. A spoken word carries a lot of informations about speakers and their emotional states. In this paper we designed a model to recognize emotional states in a speech, a first phase of two phases in developing a toy machine that recognizes emotional states in a speech. We conducted an experiment to extract and analyse the emotional state of a speaker in relation with speech. To analyse the signal output we referred to three characteristics of sound as vector inputs and they are the followings: frequency, intensity, and period of tones. Also we made use of eight basic emotional parameters: surprise, anger, sadness, expectancy, acceptance, joy, hate, and fear which were portrayed by five selected students. In order to facilitate the differentiation of each spectrum features, we used the wavelet transform analysis. We applied ANFIS (Adaptive Neuro Fuzzy Inference System) in designing an emotion recognition model from a speech. In our findings, inference error was about 10%. The result of our experiment reveals that about 85% of the model applied is effective and reliable.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2000년도 추계학술대회 논문집
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• pp.144-147
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• 2000

In this paper, ANFIS intelligence control of a semi-active suspension system is investigated. The strength of the ER damper is controlled by a high voltage power supply. This paper deals with a two-degree-of-freedom suspension using the damper with ERF for a quarter vehicle system. The control law for semi-active suspensions modeled in this study is developed using passive and ANFlS control method. Computer simulation results show that the semi-active suspension with ERF damper has good performances of ride quality

• Geomechanics and Engineering
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• 제31권4호
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• pp.339-352
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• 2022

Studying slope stability is an important branch of civil engineering. In this way, engineers have employed machine learning models, due to their high efficiency in complex calculations. This paper examines the robustness of various novel optimization schemes, namely equilibrium optimizer (EO), Harris hawks optimization (HHO), water cycle algorithm (WCA), biogeography-based optimization (BBO), dragonfly algorithm (DA), grey wolf optimization (GWO), and teaching learning-based optimization (TLBO) for enhancing the performance of adaptive neuro-fuzzy inference system (ANFIS) in slope stability prediction. The hybrid models estimate the factor of safety (F_S) of a cohesive soil-footing system. The role of these algorithms lies in finding the optimal parameters of the membership function in the fuzzy system. By examining the convergence proceeding of the proposed hybrids, the best population sizes are selected, and the corresponding results are compared to the typical ANFIS. Accuracy assessments via root mean square error, mean absolute error, mean absolute percentage error, and Pearson correlation coefficient showed that all models can reliably understand and reproduce the F_S behavior. Moreover, applying the WCA, EO, GWO, and TLBO resulted in reducing both learning and prediction error of the ANFIS. Also, an efficiency comparison demonstrated the WCA-ANFIS as the most accurate hybrid, while the GWO-ANFIS was the fastest promising model. Overall, the findings of this research professed the suitability of improved intelligent models for practical slope stability evaluations.

• 한국우주과학회:학술대회논문집(한국우주과학회보)
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• 한국우주과학회 2011년도 한국우주과학회보 제20권1호
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• pp.32.2-32.2
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• 2011

State dependent Riccati equation (SDRE) control technique has been widely used in the control society. Although it solves nonlinear optimal control problems, which minimizes state error and control efforts simultaneously, it has drawbacks when it is to be applied to the real time systems in that it requires much computational efforts. So the real time system whose computational ability is limited (for example, satellites) cannot afford to use SDRE controller. To solve this problem, a hybrid controller which is based on MSDRE (Modified SDRE) and ANFIS (Adaptive Neuro-Fuzzy Inference System) has been proposed by Abdelrahman et al. (2010). We propose a hybrid controller based on SDRE and ANFIS, and apply the hybrid controller to the hardware attitude simulator to perform a HIL (Hardware-In-the-Loop) simulation. Through HIL simulation, it is demonstrated that the hybrid controller satisfies the control requirement and the computation load is reduced significantly. In addition, the effects of statistical properties of the ANFIS training data to the performance of the ANFIS controller have been analyzed.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1082-1084
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• 1999

A fault detection of power system must be fast and correctly over input signal without relation to any disturbance. But, it is difficult to detect fault state for digital relay comparison of fault perfectly. In this Paper, we measure each Phase current and infer type of fault using ANFIS(Adaptive Neuro-Fuzzy Inference System).

• Journal of Mechanical Science and Technology
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• 제19권8호
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• pp.1670-1681
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• 2005

In-situ diagnosis of chiller performance is an essential step for energy saving business. The main purpose of the in-situ diagnosis is to predict the performance of a target chiller. Many models based on thermodynamics have been proposed for the purpose. However, they have to be modified from chiller to chiller and require profound knowledge of thermodynamics and heat transfer. This study focuses on developing an easy-to-use diagnostic technique that is based on adaptive neuro-fuzzy inference system (ANFIS). The effect of sample data distribution on training the ANFIS is investigated. It is found that the data sampling over 10 days during summer results in a reliable ANFIS whose performance prediction error is within measurement errors. The reliable ANFIS makes it possible to prepare an energy audit and suggest an energy saving plan based on the diagnosed chilled water supply system.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.2768-2770
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• 2001

본 논문은 지능형 알고리즘과 이미지 프로세싱 방법을 결합한 새로운 방법으로 칼라 매칭 시스템에 구현한다. 칼라 매칭 시스템은 이미지 프로세싱을 이용하여 칼라의 RGB 데이터를 분석한 후 얻어진 색상정보를 가지고 사용자가 원하는 칼라는 구현하는 시스템이다. 칼라 매칭 시스템의 모델링에 이용되는 지능형 모델은 퍼지 추론과 적응 퍼지 추론 시스템(Adaptive Neuro-Fuzzy Inference System: ANFIS)이며, 최소 자승법을 기반으로 한 회귀 다항식과 비교하여 제안된 지능형 모델에 대한 성능과 실용성을 검증한 후 델파이를 이용하여 구현하였다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1999년도 하계학술대회 논문집 C
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• pp.1314-1317
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• 1999

In this paper, we design an Adaptive Neuro-Fuzzy Inference System(ANFIS) Precompensator for the performance improvement of conventional proportional integral derivative (PID) controller that the governor system of power plant constantly maintains the load frequency of two-area power system. The ANFIS Precompensator is expressed as the membership functions of premise parameters and the linear combination of consequent parameters by Sugeno's fuzzy if-then rules using nonlinear input-output relation for the set point automatic modification maintaining conventional PID controller. The proposed compensation design technique is hoped to be satisfactory method overcome difficulty of exact modelling and arising problems by the complex nonlinearities of power system, and our design shows merit that is easily implemented by adding an ANFIS precompenastor to an existing PID controller without replacement.

• International journal of advanced smart convergence
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• 제3권2호
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• pp.18-21
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• 2014

A control application requirements currently used is very low, such as packet loss rate, minimum delay on sensor networks with quality of service (QoS) requirements some packet delivery guarantee. This paper is the sampling period at the end of the actuator and sensor data transfer related to the Miss ratio for each source sensor node, use the controller and the internal ANFIS. The proposed scheme has the advantages of simplicity, scalability, and General. Simulation results of the proposed scheme can provide QoS support in WSANs.