• 한국정밀공학회지
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• 제20권11호
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• pp.79-90
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• 2003

In this paper, we propose a multisensor-based navigation algorithm for a mobile robot, which is intelligently searching the goal location in unknown dynamic environments using multi-ultrasonic sensor. Instead of using “sensor fusion” method which generates the trajectory of a robot based upon the environment model and sensory data, “command fusion” method by fuzzy inference is used to govern the robot motions. The major factors for robot navigation are represented as a cost function. Using the data of the robot states and the environment, the weight value of each factor using fuzzy inference is determined for an optimal trajectory in dynamic environments. For the evaluation of the proposed algorithm, we performed simulations in PC as well as experiments with IRL-2002. The results show that the proposed algorithm is apt to identify obstacles in unknown environments to guide the robot to the goal location safely.

• International journal of advanced smart convergence
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• 제2권1호
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• pp.12-17
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• 2013

This paper introduces the fuzzy scatter partition-based fuzzy inference system to construct the model for nonlinear process to analyze nonlinear characteristics. The fuzzy rules of fuzzy inference systems are generated by partitioning the input space in the scatter form using Fuzzy C-Means (FCM) clustering algorithm. The premise parameters of the rules are determined by membership matrix by means of FCM clustering algorithm. The consequence part of the rules is represented in the form of polynomial functions and the parameters of the consequence part are estimated by least square errors. The proposed model is evaluated with the performance using the data widely used in nonlinear process. Finally, this paper shows that the proposed model has the good result for high-dimension nonlinear process.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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• pp.182-182
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• 2000

This paper proposes a self tuning fuzzy inference method by the genetic algorithm in the fuzzy-sliding mode control for a robot. Using this method, the number of inference rules and the shape of membership functions are optimized without an expert in robotics. The fuzzy outputs of the consequent part are updated by the gradient descent method. And, it is guaranteed that the selected solution become the global optimal solution by optimizing the Akaike's information criterion. The trajectory trucking experiment of the polishing robot system shows that the optimal fuzzy inference rules are automatically selected by the genetic algorithm and the proposed fuzzy-sliding model controller provides reliable tracking performance during the polishing process.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.13-16
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• 2000

In fuzzy expert systems or database systems that have huge volumes of fuzzy data or large fuzzy rules, the inference time is much increased. Therefore, a high performance parallel fuzzy computing environment is needed. In this paper, we propose a parallel fuzzy inference mechanism in parallel computing environment. In this, fuzzy rules are distributed and executed simultaneously. The ONE_TO_ALL algorithm is used to broadcast the fuzzy input vector to the all nodes. The results of the MIN/MAX operations are transferred to the output processor by the ALL_TO_ONE algorithm. By parallel processing of fuzzy rules or data, the parallel fuzzy inference algorithm extracts effective parallel ism and achieves a good speed factor.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.2164.1_2165.1
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• 2009

In this study we suggest fire detection algorithm using fuzzy inference with input variables of temperature and smoke density to detect electrical fire of early stage. The algorithm consists of membership function of temperature and smoke density and fire probability. The antecedent part of the algorithm consists of temperature and smoke density, and the consequent part consists of fire possibility. The inference rules of the algorithm is estimated to input temperature and smoke density obtained by real fire. With the help of algorithms using fuzzy inference we may be diagnose electrical fire precisely.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2000년도 춘계학술대회 학술발표 논문집
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• pp.130-133
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• 2000

In this paper, a new design methodology named FNNN(Fuzzy Polynomial Neural Network) algorithm is proposed to identify the structure and parameters of fuzzy model using PNN(Polynomial Neural Network) structure and a fuzzy inference method. The PNN is the extended structure of the GMDH(Group Method of Data Handling), and uses several types of polynomials such as linear, quadratic and modified quadratic besides the biquadratic polynomial used in the GMDH. The premise of fuzzy inference rules defines by triangular and gaussian type membership function. The fuzzy inference method uses simplified and regression polynomial inference method which is based on the consequence of fuzzy rule expressed with a polynomial such as linear, quadratic and modified quadratic equation are used. Each node of the FPNN is defined as fuzzy rules and its structure is a kind of neuro-fuzzy architecture Several numerical example are used to evaluate the performance of out proposed model. Also we used the training data and testing data set to obtain a balance between the approximation and generalization of proposed model.

• 한국정밀공학회지
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• 제12권12호
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• pp.139-148
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• 1995

In this paper an electro-hydraulic servo system is designed by using a fuzzy control algorithm. In order to drive an optimal fuzzy control system, a simulation program for the control system has been developed. By this program the fuzzifier and defuzzifier, a fuzzy inference method, a fuzzy relational matrix, and a fuzzy inference method are investigated. As a result, Larsen inference method, 9*9 fuzzy relational matrix, and center of area defuzzifier are turned out the best as parameters. Finally this method is compared with the conventional PID algotithm, and showed that the fuzzy control performs better than PID algorithm. The fuzzy control performs very well adap- tation against uncertain disturbances.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 1999년도 춘계공동학술대회-지식경영과 지식공학
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• pp.353-359
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• 1999

We present a matrix-based inference alorithm suitable for electronic commerce applications. For this purpose, an Extended AND-OR Graph (EAOG) was developed with the intention that fast inference process is enabled within the electronic commerce situations. The proposed EAOG inference mechanism has the following three characteristics. 1. Real-time inference: The EAOG inference mechanism is suitable for the real-time inference because its computational mechanism is based on matric computation.2. Matrix operation: All the subjective knowledge is delineated in a matrix form, so that inference process can proceed based on the matrix operation which is computationally efficient.3. Bi-directional inference: Traditional inference method of expert systems is based on either forward chaining or backward chaining which is mutually exclusive in terms of logical process and exclusive in terms of logical process and computational efficiency. However, the proposed EAOG inference mechanism is generically bi-directional without loss of both speed and efficiency. We have proved the validity of our approach with several propositions and an illustrative EC example.

• 디지털융복합연구
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• 제14권1호
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• pp.203-209
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• 2016

본 논문에서는 퍼지 클러스터를 이용한 비선형 추론을 위한 퍼지 추론 시스템을 소개한다. 전형적으로, 비선형 추론을 위한 퍼지 규칙의 생성은 일반적으로 입력 벡터 차원이 증가하면 규칙의 수가 지수적으로 증가하게 된다. 이러한 문제점을 해결하기 위해, 퍼지 클러스터를 표현할 수 있는 퍼지 클러스터링 알고리즘을 이용하여 입력 벡터 공간을 분산 형태로 분할하여 퍼지 모델의 규칙을 설계한다. 이러한 방법으로 복잡하고 비선형적인 공정을 퍼지 모델링 할 수 있다. 퍼지 규칙의 전반부는 퍼지 클러스터를 갖는 FCM 클러스터링 알고리즘에 의해 결정된다. 퍼지 규칙의 후반부는 4가지 형태의 다항식 함수의 형태를 가지며, 각 규칙의 후반부 파라미터들은 표준 최소자승법을 이용함으로써 추정된다. 그리고 비선형 공정의 특성 및 성능을 평가하기 위하여 비선형 공정으로 많이 이용되고 있는 데이터를 이용한다. 실험 결과는 비선형 추론이 가능하다는 것을 보여준다.

• 한국지능시스템학회논문지
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• 제12권1호
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• pp.7-13
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• 2002

퍼지이론의 응용은 대부분 퍼지추론을 이용하는 것이다. 그러나 퍼지추론은 입력변수의 수가 많아지거나 각 입력변수에 많은 수의 퍼지라벨을 설정할 경우 그 추론에 필요한 계산시간이 많아지게 되며 이러한 것은 컴퓨터 연산의 대수곱(arithmetic product)의 수에 의해 결정된다. 더구나 퍼지추론의 응용이 가장 활발한 퍼지제어분야에서는 이러한 추론시간은 실제 시스템에 적용 시 가장 큰 제약조건이 된다. 특히, 마이크로프로세서를 이용하거나 PC-based 제어기를 설계할 때 이러한 추론시간은 매우 중요한 문제가 된다. 본 논문에서는 이러한 추론시간을 효율적으로 줄이기 위해, 즉 추론 시 필요로 하는 곱 연산의 수를 줄이기 위하여 삼각형 소속함수를 이용하는 퍼지시스템에 적용 가능하며 정보의 손실이 발생되지 않는 간단한 고속 퍼지추론 알고리즘을 제안한다. 이것은 퍼지추론 시 입력상태공간의 분할과 간단한 기하학적 해석을 통해 얻어지는 것이며 결과적으로 퍼지규칙의 수를 줄이는 것과 같다.