• Title/Summary/Keyword: Fuzzy Logic Systems

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Vehicle traction control using fuzzy logic algorithm (퍼지 로직 알고리듬을 이용한 차량 구동력 제어)

  • 박성훈;권동수
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.680-683
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    • 1996
  • The dynamics of the vehicle system has highly nonlinear components such as an engine, a torque converter and variable road condition. This thesis proposes a Fuzzy Logic Algorithm that shows better control performance than Antiwindup PI in the highly nonlinear vehicle system. Traction Control System(TCS), which adjusts throttle valve opening by Fuzzy Logic Algorithm improves vehicle drivability, steerability and stability when vehicle is starting and cornering. When a throttle valve is opened at large degree, Fuzzy Logic Algorithm shows better performances like a small settling time and a small oscillation than Antiwindup PI in simulation. The decreased desired slip ratio improves steerability in the simulation when a vehicle is cornering. The Fuzzy Logic Algorithm has been tested by a 1/5-scale vehicle for tracking the constant desired velocity.

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Deadzone compensation of a XY table using fuzzy logic (XY 테이블의 퍼지 데드존 보상)

  • 장준오
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.41 no.2
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    • pp.17-28
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    • 2004
  • A deadzone compensator is designed for a XY positioning table using fuzzy logic. The classification property of fuzzy logic systems makes them a natural candidate for the rejection of errors induced by the deadzone, which has regions in which it behaves differently. A tuning algorithm is given for the fuzzy logic parameters, so that the deadzone compensation scheme becomes adaptive, guaranteeing small tracking errors and bounded parameter estimates. Formal nonlinear stability proofs are given to show that the tracking error is small. The fuzzy logic deadzone compensator is implemented on a XY positioning table to show its efficacy.

Fuzzy Precompensated PI Controller for Inverter-type Air-Conditioner (인버터형 에어컨의 온도 제어를 위한 퍼지 전단 보상된 PI 제어기)

  • 장보인;이선우;정문종;유장현;김상권;박윤서
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1997.10a
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    • pp.185-188
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    • 1997
  • In this paper, a fuzzy precompensated PI controller for inverter-type air-conditioner is presented. The presented control scheme is composed of a fuzzy logic precompensator and PI controller, in which two control schemes are serially connected. The rules of the fuzzy precompensator is designed to improve the performance by considering the nonlinear characteristics of a temperature dynamics. The experimental results show the effectiveness of the proposed controller.

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Improved Mold Level Control for Continuous Steel Casting by Fuzzy Logic Control

  • Kueon, Yeongseob;Xiao, Wendong
    • Transactions on Control, Automation and Systems Engineering
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    • v.1 no.1
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    • pp.1-7
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    • 1999
  • This paper gives a simulation study of a new fuzzy logic control(FLC) approach for the mold level control in continuous casting processes. The proposed FLC is PID type hybridizing the conventional fuzzy PI control and Fuzzy PD control with a simplified design scheme. It is shown that, compared with the conventional control, this new control strategy can achieve superior performance for steady-state response and is more robust against process parameter variations and disturbances.

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Fuzzy control for a flexible arm manipulator

  • Fortuna, L.;LoPresti, M.;Vinci, C.
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1037-1040
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    • 1993
  • In this paper a fuzzy controller for a flexible arm with one degree of freedom is presented. Goal of the control is to drive the manipulator to the position $\theta$0 avoiding the oscillations due the elasticity of the arm. The performances of the fuzzy controller are evaluated through a series of simulations that shows appreciable results both for the transient and the steady behaviour.

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Uninorm logic: toward a fuzzy-relevance logic(2)

  • Yang, Eun-Suk
    • Korean Journal of Logic
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    • v.11 no.1
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    • pp.131-156
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    • 2008
  • This paper first investigates several uninorm logics (introduced by Metcalfe and Montagna in [8]) as fuzzy-relevance logics. We first show that the uninorm logic UL and its extensions IUL, UML, and IUML are fuzzy-relevant; fuzzy in Cintula's sense, i.e., the logic L is complete with respect to linearly ordered L-matrices; and relevant in the weak sense that ${\Phi}{\rightarrow}{\Psi}$ is a theorem only if either (i) $\Phi$ and $\Psi$ share a sentential variable or constant, or (ii) both $\sim\Phi$ and $\Psi$ are theorems. We next expand these systems to those with $\triangle$.

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Unsupervised Real-time Obstacle Avoidance Technique based on a Hybrid Fuzzy Method for AUVs

  • Anwary, Arif Reza;Lee, Young-Il;Jung, Hee;Kim, Yong-Gi
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.8 no.1
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    • pp.82-86
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    • 2008
  • The article presents ARTMAP and Fuzzy BK-Product approach underwater obstacle avoidance for the Autonomous underwater Vehicles (AUV). The AUV moves an unstructured area of underwater and could be met with obstacles in its way. The AUVs are equipped with complex sensorial systems like camera, aquatic sonar system, and transducers. A Neural integrated Fuzzy BK-Product controller, which integrates Fuzzy logic representation of the human thinking procedure with the learning capabilities of neural-networks (ARTMAP), is developed for obstacle avoidance in the case of unstructured areas. In this paper, ARTMAP-Fuzzy BK-Product controller architecture comprises of two distinct elements, are 1) Fuzzy Logic Membership Function and 2) Feed-Forward ART component. Feed-Forward ART component is used to understanding the unstructured underwater environment and Fuzzy BK-Product interpolates the Fuzzy rule set and after the defuzzyfication, the output is used to take the decision for safety direction to go for avoiding the obstacle collision with the AUV. An on-line reinforcement learning method is introduced which adapts the performance of the fuzzy units continuously to any changes in the environment and make decision for the optimal path from source to destination.

Design and implementation of a throttle valve controller for engine dynamometer systems using fuzzy logic (퍼지논리를 사용한 엔진 동력계 시스템의 트로틀 밸브 제어기 설계 및 구현)

  • Shin, Wee-Jae;Lee, Sang-Yun
    • Journal of Institute of Control, Robotics and Systems
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    • v.3 no.6
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    • pp.588-593
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    • 1997
  • This paper shows a design and implementation of throttle valve controller for engine dynamometer system using fuzzy logic. Recently, we demanded the excellent measuring equipment so as to improve engine performance. The throttle valve control for engine dynamometer system is a very particular part in the engine control. Since the structure of engine dynamometer system is very complicated and has nonlinear elements which are influenced by disturbance of vibration, heating, cooling, and energy loss so on. In this paper, fuzzy logic control application have been successful in throttle valve control problem for engine dynamometer system in which the conventional control had difficulties dealing with the system. In this study, we propose a method that the control strategy uses Fuzzy Look-up table and normalization and obtained the satisfying result from realized throttle valve controller for engine dynamometer system.

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Design of Multiple Fuzzy Prediction System based on Interval Type-2 TSK Fuzzy Logic System (Interval Type-2 TSK 퍼지논리시스템 기반 다중 퍼지 예측시스템 설계)

  • Bang, Young-Keun;Lee, Chul-Heui
    • Journal of the Korean Institute of Intelligent Systems
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    • v.20 no.3
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    • pp.447-454
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    • 2010
  • This paper presents multiple fuzzy prediction systems based on an Interval type-2 TSK fuzzy Logic System so that the uncertainty and the hidden characteristics of nonlinear data can be reflected more effectively to improve prediction quality. In proposed method, multiple fuzzy systems are adopted to handle the nonlinear characteristics of data, and each of multiple system is constructed by using interval type-2 TSK fuzzy logic because it can deal with the uncertainty and the characteristics of data better than type-1 TSK fuzzy logic and other methods. For input of each system, the first-order difference transformation method are used because the difference data generated from it can provide more stable statistical information to each system than the original data. Finally, computer simulations are performed to show the effectiveness of the proposed method for two typical time series examples.