• 한국정밀공학회지
• /
• 제15권9호
• /
• pp.56-67
• /
• 1998

This paper introduces a friction compensation fuzzy logic controller, which utilizes a rule-based approach. The paper explains the algorithm of the proposed controller and compares it with a conventional PID controller in simulations and experiments. For the experiments, the two control algorithms were implemented on a 3-axis milling machine in contour milling. These simulation and experimental analyses show that the proposed fuzzy logic controller has superior performance over conventional PID controllers In terms of part contour accuracy.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제15권1호
• /
• pp.12-19
• /
• 2015

In order to guide the robots move along a collision-free path efficiently and reach the goal position quickly in the unknown multi-obstacle environment, this paper presented the navigation problem of a wheel mobile robot based on proximity sensors by fuzzy logic controller. Then a genetic algorithm was applied to optimize the membership function of input and output variables and the rule base of the fuzzy controller. Here the environment is unknown for the robot and contains various types of obstacles. The robot should detect the surrounding information by its own sensors only. For the special condition of path deadlock problem, a wall following method named angle compensation method was also developed here. The simulation results showed a good performance for navigation problem of mobile robots.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1999년도 하계학술대회 논문집 B
• /
• pp.897-899
• /
• 1999

This paper presents a scaling factor tuning method to improve the performance of fuzzy logic controller. Tuning rules and reasoning are utilized off-line to determine the scaling factors based on absolute value of the error and its difference. In this paper We proposed a new method to generate fuzzy logic controllers throught genetic algorithm. The developed approach is subsequently applied to the design of proportional plus integral type fuzzy controller for a dc-servo motor control system. The performance of this control system is demonstrated higher than a conventional fuzzy logic controller(FLC).

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1997년도 하계학술대회 논문집 D
• /
• pp.838-840
• /
• 1997

This presents a design method for fuzzy logic controllers of TCSC using genetic algorithm. Fuzzy logic controllers are applied to damp the dynamic disturbances sum as sudden changes of AC system loads. The dynamic performances of fuzzy logic controllers are compared with those of PI controllers. The simulation results show that dynamic performances of fuzzy controllers have better response than those of PI controllers when the AC system load changes.

• 제어로봇시스템학회논문지
• /
• 제6권1호
• /
• pp.104-111
• /
• 2000

A fuzzy logic Run-by-Run(RbR) controller and an in -line wafer characteristics prediction scheme for the rapid thermal processing system have been developed for the study of process repeatability. The fuzzy logic RbR controller provides a framework for controlling a process which is subject to disturbances such as shifts and drifts as a normal part of its operation. The fuzzy logic RbR controller combines the advantages of both fuzzy logic and feedback control. It has two components : fuzzy logic diagnostic system and model modification system. At first, a neural network model is constructed with the I/O data collected during the designed experiments. The wafer state after each run is assessed by the fuzzy logic diagnostic system with featuring step. The model modification system updates the existing neural network process model in case of process shift or drift, and then select a new recipe based on the updated model using genetic algorithm. After this procedure, wafer characteristics are predicted from the in-line wafer characteristics prediction model with principal component analysis. The fuzzy logic RbR controller has been applied to the control of Titanium SALICIDE process. After completing all of the above, it follows that: 1) the fuzzy logic RbR controller can compensate the process draft, and 2) the in-line wafer characteristics prediction scheme can reduce the measurement cost and time.

• Journal of Communications and Networks
• /
• 제7권3호
• /
• pp.337-352
• /
• 2005

In this paper, a fuzzy logic implementation of the random early detection (RED) mechanism [1] is presented. The main objective of the proposed fuzzy controller is to reduce the loss probability of the RED mechanism without any change in channel utilization. Based on previous studies, it is clear that the performance of RED algorithm is extremely related to the traffic load as well as to its parameters setting. Using fuzzy logic capabilities, we try to dynamically tune the loss probability of the RED gateway. To achieve this goal, a two-input-single-output fuzzy controller is used. To achieve a low packet loss probability, the proposed fuzzy controller is responsible to control the $max_{p}$ parameter of the RED gateway. The inputs of the proposed fuzzy controller are 1) the difference between average queue size and a target point, and 2) the difference between the estimated value of incoming data rate and the target link capacity. To evaluate the performance of the proposed fuzzy mechanism, several trials with file transfer protocol (FTP) and burst traffic were performed. In this study, the ns-2 simulator [2] has been used to generate the experimental data. All simulation results indicate that the proposed fuzzy mechanism out performs remarkably both the traditional RED and Adaptive RED (ARED) mechanisms [3]-[5].

• 한국정보통신학회논문지
• /
• 제10권1호
• /
• pp.212-219
• /
• 2006

퍼지 논리 제어기(FLC : Fuzzy Logic Controller)를 사용할 때, 가장 중요한 것은 소속 함수의 범위를 정하는 것과 규칙의 형태를 결정하는 것이다. 소속 함수의 범위나 규칙의 형태는 자금까지 전문가가 임의로 정하는 방법을 사용하였다. 그러나 기존의 방법을 사용하면, 전문가의 주관적인 규칙과 소속 함수가 생성될 수 있고, 소속함수의 경우 최적의 범위를 정확히 예측하기 어려운 단점이 있다. 본 논문에서는 이런 단점을 보완하기 위해, 유전자 알고리즘을 사용함으로써 최적의 소속 함수와 규칙의 형태를 구하려 하였다. 제시하는 방법의 타당성을 검증하기 위해 자동차 주행 제어 문제에 적용시켜 보았다.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2005년도 심포지엄 논문집 정보 및 제어부문
• /
• pp.30-32
• /
• 2005

Mobility of an indoor wheeled robot is affected by adhesion force that is related to various floor conditions. When the adhesion force between driving wheels and floor decreases suddenly, the robot begins slip. In order to overcome this slip problem, optimal slip velocity must be decided for stable movement of wheeled robot. First of all, this paper shows that conventional PI control can not be applied to a wheeled robot of the light weight. Secondly, proposed fuzzy logic is applied to the Takagi-Sugeno model for the configuration of fuzzy sets. For the design of Takagi-Sugeno model and fuzzy rule, proposed algorithm uses FCM(Fuzzy c-mean clustering method) algorithm. The proposed fuzzy logic controller(FLC) is pretty useful with prevention of the slip phenomena for the controller performance in the re-adhesion control strategy.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.56.3-56
• /
• 2001

This study describes the jump error smoothing scheme with fuzzy logic based on the scalar adaptive filter. The scalar adaptive filter is an useful algorithm for smoothing abrupt jump errors. However, the performances of scalar adaptive algorithm depend on the variance of real signal. So to design an effective algorithm, many informations of real and jump signal are required. In this paper, the fuzzy rules are designed by the analysis of scalar adaptive filter, and then the improved and simplified scheme is developed for smoothing the jump error. Simulations to INS/GPS integrated system show that the proposed method is effective.

• 한국지능시스템학회논문지
• /
• 제2권3호
• /
• pp.58-67
• /
• 1992

This paper presents a method on applying Genetric Algorithms(GA), which is a well-know high performance optimizing algorithm, to construct the self-organizing fuzzy logic controller. Fuzzy logic controller considered in this paper utilized Sugeno's hybrid inference method. which has an advantage of simple defuzzification process in the inference engine. Genetic algorithm is used to find the iptimal parameters in the FLC. The proposed approach will be demonstrated using 2 d. o. f robot manipulator to verify its effectiveness.