• Title/Summary/Keyword: Fuzzy Logic Control

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Design of Fuzzy Logic Controller for Robot Manipulators in the VSS Control Scheme

  • Yi, Soo-Yeong;Chung, Myung-Jin
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1993.06a
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    • pp.1207-1210
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    • 1993
  • There is an opinion of regarding a simple fuzzy logic controller as a kind of Variable Structure Controller in recent years. The opinion may provide an analytical basis which describes the robustness to uncertainty and the stability of a fuzzy logic controller. So in this paper, a fuzzy logic controller based on the Variable Structure System with is designed for a robot manipulator which is a class of complex, nonlinear system with uncertainty. Fuzzy control rules, membership shape of the I/O variables of the fuzzy logic controller are designed for guaranteeing the stability of an overall control system. From a computer simulation of dynamic control of a two link robot manipulator, the design procedure of the fuzzy logic controller is validated.

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Temeperature control method of refrigerator using fuzzy logic controller (퍼지 로직 제어기를 이용한 냉장고 온도 제어 방법)

  • 최병준;한상완;홍석교
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.28-31
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    • 1997
  • This paper describes the quick and precise controlling method for home-applied refrigerator. The proposed controller is based on the fuzzy logic control method and is designed for better performance in maintaining the constant temperature of the refrigerator. The temperature of the refrigerator is controlled by the cooling air blowing fan motor which is put on, off according to fuzzy logic controller. Finally, I study the performance of the proposed controller through the computer simulation about the approximated model of the refrigerator.

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Modeling and Control of Intersection Network using Real-Time Fuzzy Temporal Logic Framework (실시간 퍼지 시간논리구조를 이용한 교차로 네트워크의 모델링과 제어)

  • Kim, Jung-Chul;Lee, Won-Hyok;Kim, Jin-Kwon
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.4
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    • pp.352-357
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    • 2007
  • This paper deals with modeling method and application of Fuzzy Discrete Event System(FDES). FDES have characteristics which Crisp Discrete Event System(CDES) can't deals with and is constituted with the events that is determined by vague and uncertain judgement like biomedical or traffic control. We proposed Real-time Fuzzy Temporal Logic Framework(RFTLF) to model Fuzzy Discrete Event System. It combines Temporal Logic Framework with Fuzzy Theory. We represented the model of traffic signal systems for intersection to have the property of Fuzzy Discrete Event System with Real-time Fuzzy Temporal Logic Framework and designed a traffic signal controller for smooth traffic flow. Moreover, we proposed the method to find the minimum-time route to reach the desired destination with information obtained in each intersection. In order to evaluate the performance of Real-time Fuzzy Temporal Logic Framework model proposed in this paper, we simulated unit-time extension traffic signal controller model of the latest signal control method on the same condition.

A Study on the Gain Tuning of Fuzzy Logic Controller Superior to PI Controller in DC Motor Speed Control (직류 전동기 속도 제어에서 PI 제어기보다 우수한 퍼지 논리 제어기의 이득 선정을 위한 연구)

  • Kim, Young-Real
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.28 no.6
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    • pp.30-39
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    • 2014
  • Through a lot of papers, it has been concluded that fuzzy logic controller is superior to PI controller in motor speed control. Although fuzzy logic controller is superior to PI controller in motor speed control, the gain tuning of fuzzy logic controller is more complicated than that of PI controller. In this paper, using mathematical analysis of the PI and fuzzy controller, the design method of the fuzzy controller that has the same characteristics with the PI controller is proposed. After that, we can design the fuzzy controller that has superior performance than PI controller by changing the envelope of input of fuzzy controller to nonlinear, because the fuzzy controller has more degree of freedom to select the control gain than PI controller. The advantage of fuzzy logic controller is shown through mathematical analysis, and the simulation result using Matlab simulink has been proposed to show the effectiveness of these analysis.

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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Fault Diagnosis in Gas Turbine Engine Using Fuzzy Inference Logic (퍼지 로직 시스템을 이용한 항공기 가스터빈 엔진 오류 검출에 대한 연구)

  • Mo, Eun-Jong;Jie, Min-Seok;Kim, Chin-Su;Lee, Kang-Woong
    • Journal of Institute of Control, Robotics and Systems
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    • v.14 no.1
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    • pp.49-53
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    • 2008
  • A fuzzy inference logic system is proposed for gas turbine engine fault isolation. The gas path measurements used for fault isolation are exhaust gas temperature, low and high rotor speed, and fuel flow. The fuzzy inference logic uses rules developed from a model of performance influence coefficients to isolate engine faults while accounting for uncertainty in gas path measurements. Inputs to the fuzzy inference logic system are measurement deviations of gas path parameters which are transferred directly from the ECM(Engine Control Monitoring) program and outputs are engine module faults. The proposed fuzzy inference logic system is tested using simulated data developed from the ECM trend plot reports and the results show that the proposed fuzzy inference logic system isolates module faults with high accuracy rate in the environment of high level of uncertainty.

Simultaneous precision positioning and vibration suppression of reciprocating flexible manipulators

  • Ma, Kougen;Ghasemi-Nejhad, Mehrdad N.
    • Smart Structures and Systems
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    • v.1 no.1
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    • pp.13-27
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    • 2005
  • Simultaneous precision positioning and vibration suppression of a reciprocating flexible manipulator is investigated in this paper. The flexible manipulator is driven by a multifunctional active strut with fuzzy logic controllers. The multifunctional active strut is a combination of a motor assembly and a piezoelectric stack actuator to simultaneously provide precision positioning and wide frequency bandwidth vibration suppression capabilities. First, the multifunctional active strut and the flexible manipulator are introduced, and their dynamic models are derived. A control strategy is then proposed, which includes a position controller and a vibration controller to achieve simultaneous precision positioning and vibration suppression of the flexible manipulator. Next, fuzzy logic control approach is presented to design a fuzzy logic position controller and a fuzzy logic vibration controller. Finally, experiments are conducted for the fuzzy logic controllers and the experimental results are compared with those from a PID control scheme consisting of a PID position controller and a PID vibration control. The comparison indicates that the fuzzy logic controller can easily handle the non-linearity in the strut and provide higher position accuracy and better vibration reduction with less control power consumption.

Capacity Modulation of a Multi-Type Heat Pump System using PID Control with Fuzzy Logic (퍼지 로직 적용 PID 제어를 이용한 멀티형 열펌프의 용량조절)

  • 김세영;김민수
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.13 no.9
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    • pp.810-817
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    • 2001
  • Performance of a water-to-water multi-type heat pump system using R22 which has tow indoor units has been investigated experimentally. The refrigerant flow rate of each indoor unit was regulated by an electronic expansion valve and the total refrigerant flow rate of the system was controlled by a variable speed compressor. In the system, evaporator outlet pressure of refrigerant and outlet temperatures of secondary fluid from indoor units were selected as control variables. Experiments were executed for both cooling and heating modes using PID control method with fuzzy logic, and results of the test are compared with a classical PID method. In the case of PID control with fuzzy logic, the fuzzy control rules corrects PID parameters each time. Results show that PID control with fuzzy logic has the merits of quick response and reduced overshoot.

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A fuzzy dynamic learning controller for chemical process control

  • Song, Jeong-Jun;Park, Sun-Won
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10b
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    • pp.1950-1955
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    • 1991
  • A fuzzy dynamic learning controller is proposed and applied to control of time delayed, non-linear and unstable chemical processes. The proposed fuzzy dynamic learning controller can self-adjust its fuzzy control rules using the external dynamic information from the process during on-line control and it can create th,, new fuzzy control rules autonomously using its learning capability from past control trends. The proposed controller shows better performance than the conventional fuzzy logic controller and the fuzzy self organizing controller.

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Development of Intelligently Unmanned Combine Using Fuzzy Logic Control -(Graphic Simulation)-

  • N.H.Ki;Cho, S.I.
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 1993.10a
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    • pp.1264-1272
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    • 1993
  • The software for unmanned control of three row typed rice combine has been developed using fuzzy logic. Three fuzzy variables were used : operating status of combine, steering, and speed. Eleven fuzzy rules were constructed and the eleven linguistic variables were used for the fuzzy rules. Six sensors were use of to get input values and sensor input values were quantified into 11 levels. The fuzzy output was infered with fuzzy inferrence which uses the correlation product encoding , and it must have been defuzzified by the method of center of gravity to use it for the control. The result of performance test using graphic simulation showed that the intelligently unmanned control of a rice combine was possible using fuzzy logic control.

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