• Title, Summary, Keyword: fuzzy controller

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Weighted fuzzy controller composed of position type fuzzy controller and velocity type fuzzy controller (위치형퍼지제어기와 속도형퍼지제어기로 구성된 퍼지 가중치 제어기)

  • 김병수;박준열
    • 제어로봇시스템학회:학술대회논문집
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    • pp.181-183
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    • 1996
  • Generally, While position type fuzzy controller has good performance in transient period, it has uniform steady state error of response. While velocity type fuzzy controller is capable of reducing steady state error of response, it is hard to develop the performance in transient period. In order to have both good performance in transient period and ability to reduce the steady state error of response, weighting fuzzy controller, which is composed of these two fuzzy controllers, is proposed. For the decision of weight to each fuzzy controller, Weighting fuzzy set is established according to the system state variables and applied to each fuzzy controller. The proposed weighted fuzzy controller has the merits of both position type fuzzy controller and velocity type fuzzy controller simultaneously.

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Gain Tuning of a Fuzzy Logic Controller Superior to PD Controllers in Motor Position Control

  • Kim, Young-Real
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.14 no.3
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    • pp.188-199
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    • 2014
  • Although the fuzzy logic controller is superior to the proportional integral derivative (PID) controller in motor control, the gain tuning of the fuzzy logic controller is more complicated than that of the PID controller. Using mathematical analysis of the proportional derivative (PD) and fuzzy logic controller, this study proposed a design method of a fuzzy logic controller that has the same characteristics as the PD controller in the beginning. Then a design method of a fuzzy logic controller was proposed that has superior performance to the PD controller. This fuzzy logic controller was designed by changing the envelope of the input of the of the fuzzy logic controller to nonlinear, because the fuzzy logic controller has more degree of freedom to select the control gain than the PD controller. By designing the fuzzy logic controller using the proposed method, it simplified the design of fuzzy logic controller, and it simplified the comparison of these two controllers.

Stability Analysis and Proposal of a Simple Form of a Fuzzy PID Controller

  • Lee, Byung-Kyul;Kim, In-Hwan;Kim, Jong-Hwa
    • Journal of the Korean Society of Marine Engineering
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    • v.28 no.8
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    • pp.1299-1312
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    • 2004
  • This paper suggests the simple form of a fuzzy PID controller and describes the design principle, tracking performance, stability analysis and changes of parameters of a suggested fuzzy PID controller. A fuzzy PID controller is derived from the design procedure of fuzzy control. It is well known that a fuzzy PID controller has a simple structure of the conventional PID controller but posses its self-tuning control capability and the gains of a fuzzy PID controller become nonlinear functions of the inputs. Nonlinear calculation during fuzzification, defuzzification and the fuzzy inference require more time in computation. To increase the applicability of a fuzzy PID controller to digital computer, a simple form of a fuzzy PID controller is introduced by the backward difference mapping and the analysis of the fuzzy input space. To guarantee the BIBO stability of a suggested fuzzy PID controller, ‘small gain theorem’ which proves the BIBO stability of a fuzzy PI and a fuzzy PD controller is used. After a detailed stability analysis using ‘small gain theorem’, from which a simple and practical method to decide the parameters of a fuzzy PID controller is derived. Through the computer simulations for the linear and nonlinear plants, the performance of a suggested fuzzy PID controller will be assured and the variation of the gains of a fuzzy PID controller will be investigated.

A fuzzy dynamic learning controller for chemical process control

  • Song, Jeong-Jun;Park, Sun-Won
    • 제어로봇시스템학회:학술대회논문집
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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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Design of Parallel Type Fuzzy Controller Using Model Reference Plant (플랜트 모델참조를 이용한 병렬형 퍼지제어기 설계)

  • 추연규
    • Journal of Institute of Control, Robotics and Systems
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    • v.9 no.5
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    • pp.379-383
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    • 2003
  • Parallel type fuzzy controller is designed by using a hybrid connected type fuzzy-PID controller and a model reference fuzzy controller. The first controller, consists of a fuzzy-PI and a fuzzy-PD making a hybrid type fuzzy-PID controller, plays a role as firstly reaching stable responses and secondly overcoming disturbance in plants. The second controller, model reference fuzzy controller, plays a role as reaching faster responses than other controllers. We have confirmed that the controller produces rapid and stable responses and overcomes disturbance by using parallel type fuzzy controller in a DC motor application.

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.

ADAPTIVE FUZZY CONTROLLER IMPLEMENTED ON THERMAL PROCESS

  • Abd el-geliel, M.
    • 제어로봇시스템학회:학술대회논문집
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    • pp.84-89
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    • 2003
  • Fuzzy controller is one of the succeed controller used in the process control in case of model uncertainties. But it my be difficult to fuzzy controller to articulate the accumulated knowledge to encompass all circumstance. Hence, it is essential to provide a tuning capability. There are many parameters in fuzzy controller can be adapted, scale factor tuning of normalized fuzzy controller is one of the adaptation parameter. Two adaptation methods are implemented in this work on an experimental thermal process, which simulate heating process in liquefied petroleum gases (LPG) recovery process in one of petrochemical industries: Gradient decent (GD) adaptation method; supervisory fuzzy controller. A comparison between the two methods is discussed.

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Genetically optimized self-tuning Fuzzy-PI controller for HVDC system (HVDC 시스템을 위한 진화론적으로 최적화된 자기 동조 퍼지제어기)

  • Wang, Zhong-Xian;Yang, Jueng-Je;Ahn, Tae-Chon
    • Proceedings of the KIEE Conference
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    • pp.279-281
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    • 2006
  • In this paper, we study an approach to design a self-tuning Fuzzy-PI controller in HVDC(High Voltage Direct Current) system. In the rectifier of conversional HVDC system, turning on, turning off, triggering and protections of thyristors have lots of problems that can make the dynamic instability and cannot damp the dynamic disturbance efficiently. The above problems are solved by adapting Fuzzy-PI controller for the fire angle control of rectifier.[7] The performance of the Fuzzy-PI controller is sensitive to the variety of scaling factors. The design procedure dwells on the use of evolutionary computing(Genetic Algorithms, GAs). Then we can obtain the optimal scaling factors of the Fuzzy-PI controller by Genetic Algorithms. In order to improve Fuzzy-PI controller, we adopt FIS to tune the scaling factors of the Fuzzy-PI controller on line. A comparative study has been performed between Fuzzy-PI and self-tuning Fuzzy-PI controller, to prove the superiority of the proposed scheme.

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A Fuzzy Traffic Controller Considering the spillback on the Multiple Crossroads

  • Kim, Young-Sik
    • Journal of Korean Institute of Intelligent Systems
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    • v.13 no.6
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    • pp.722-728
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    • 2003
  • In this paper, we propose a fuzzy traffic controller of Sugeno`s fuzzy model so as to model the nonlinear characteristics of controlling the traffic light. It use a degree of the traffic congestion of the preceding roads as an input so that it can cope with traffic congestion appropriately, which causes the loss of fuel and our discomfort. First, in order to construct fuzzy traffic controller of Sugeno`s fuzzy model, we model the control process of the traffic light by using Mamdani`s fuzzy model, which has the uniform membership functions of the same size and shape. Second, we make Mamdani`s fuzzy model with the non-uniform membership functions so that it can exactly reflect the knowledge of experts and operators. Last, we construct the fuzzy traffic controller of Sugeno`s fuzzy model by learning from the input/output data, which is retrieved from Mamdani`s fuzzy model with the non-uniform membership functions. We compared and analyzed the fixed traffic light controller, the fuzzy traffic controller of Mamdani`s fuzzy model and the fuzzy traffic controller of Sugeno`s fuzzy model by using the delay time and the proportion of the entered vehicles to the occurred vehicles. As a result of comparison, the fuzzy traffic controller of Sugeno`s fuzzy model showed the best performance.

A Study on the Performance Improvement of a Nonlinear Fuzzy PID Controller (비선형 퍼지 PID 제어기의 성능 개선에 관한 연구)

  • 김인환;이병결;김종화
    • Journal of the Korean Society of Marine Engineering
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    • v.27 no.7
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    • pp.852-861
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    • 2003
  • In this paper, in order to improve the disadvantages of the fixed design-parameter fuzzy PID controller. a new fuzzy PID controller named a variable design-parameter fuzzy PID controller is suggested. The main characteristic of the suggested controller is to adjust design-parameters of the controller by comparing magnitudes between fuzzy controller inputs at each sampling time when controller inputs are measured. As a result. all fuzzy input partitioned spaces converge within a time-varying normalization scale. and the resultant PID control action can always be applied precisely regardless of operating input magnitudes. In order to verify the effectiveness of the suggested controller. several a computer simulations for a nonlinear system are executed and the control parameters of the variable design-parameter fuzzy PID controller are throughly analyzed.