• 제목/요약/키워드: Fuzzy adaptive PID control

검색결과 50건 처리시간 0.039초

Design of Model Following PID Controller Using Fuzzy Tuner (퍼지 동조기법을 이용한 기준모델 추종 PID제어기의 설계)

  • Hong, Hyug-Gi;Moon, Dong-Wook;Kim, Lark-Kyo;Nam, Moon-Hyun
    • Proceedings of the KIEE Conference
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    • 대한전기학회 1999년도 하계학술대회 논문집 B
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    • pp.621-623
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    • 1999
  • In this paper, Model following PID control system, which is combined PID controller with Model Reference Adaptive Controller, is proposed. To decrease complex and much calculation which is produced in tuning process, the tuning method of parameter with fuzzy algorithm is introduced. Fuzzy algorithm isn't used in the form of controller generally much used, but tuner. Experimental results show that proposed controller has the PID parameter be tuned by fuzzy algorithm. Therefore, We expect model following PID to be operated in the real-time control.

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Adaptive Intelligent Control of Nonlinear dynamic system Using Immune Fuzzy Fusion

  • Kim, Dong-Hwa;Park, Jin-Ill
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제3권2호
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    • pp.146-156
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    • 2003
  • Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the PID controller has to be manually tuned by trial and error. This paper suggests control approaches by immune fuzzy for the nonlinear control system inverted pendulum, through computer simulation. This paper defines relationship state variables $x,\dot{x},{\theta},\dot{\theta}$ using immune fuzzy and applied its results to stability.

Improved Neural Network-based Self-Tuning Fuzzy PID Controller for Sensorless Vector Controlled Induction Motor Drives (센서리스 유도전동기의 속도제어를 위한 개선된 신경회로망 기반 자기동조 퍼지 PID 제어기 설계)

  • Kim, Sang-Min;Han, Woo-Yong;Lee, Chang-Goo;Han, Hoo-Suk
    • Proceedings of the KIEE Conference
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    • 대한전기학회 2002년도 하계학술대회 논문집 B
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    • pp.1165-1168
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    • 2002
  • This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for sensorless vector controlled induction motor drives. MRAS(Model Reference Adaptive System) is used for rotor speed estimation. When induction motor is continuously used long time. its electrical and mechanical parameters will change, which degrade the performance of PID controller considerably. This paper re-analyzes the fuzzy controller as conventional PID controller structure, introduces a single neuron with a back-propagation learning algorithm to tune the control parameters, and proposes a variable learning rate to improve the control performance. The proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using DS1102 board show the robustness of the proposed controller to parameter variations.

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The development of an on-line self-tuning fuzzy PID controller (온라인 자기동조 퍼지 PID 제어기 개발)

  • 임형순;한진욱;김성중
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.704-707
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    • 1997
  • In this paper, we present a fuzzy logic based tuner for continuous on-line tuning of PID controllers. The essential idea of the scheme is to parameterize a Ziegler-Nichols-like tuning formula by a singler parameter .alpha., then to use an on line fuzzy logic to self-tune the parameter. The adaptive scaling makes the controller robust against large variations in parametric and dynamics uncertainties in the plant model. New self-tuning controller has the ability to decide when to use PI or PID control by extracting process dynamics from relay experiments. These scheme lead to improved performance of the transient and steady state behavior of the closed loop system, including processes with nonminimum phase processes.

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Adaptive Intelligent Control of Inverted Pendulum Using Immune Fuzzy Fusion

  • Kim, Dong-Hwa
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.2372-2377
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    • 2003
  • Nonlinear dynamic system exist widely in many types of systems such as chemical processes, biomedical processes, and the main steam temperature control system of the thermal power plant. Up to the present time, PID Controllers have been used to operate these systems. However, it is very difficult to achieve an optimal PID gain with no experience, because of the interaction between loops and gain of the PID controller has to be manually tuned by trial and error. This paper suggests control approaches by immune fuzzy for the nonlinear control system inverted pendulum, through computer simulation. This paper defines relationship state variables $x,{\dot{x}},{\theta},\dot{\theta}$ using immune fuzzy and applied its results to stability.

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Adaptive Fuzzy Control of Yo-yo System Using Neural Network

  • Lee, Seung-ha;Lee, Yun-Jung;Shin, Kwang-Hyun;Bien, Zeungnam
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제4권2호
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    • pp.161-164
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    • 2004
  • The yo-yo system has been introduced as an interesting plant to demonstrate the effectiveness of intelligent controllers. Having nonlinear and asymmetric characteristics, the yo-yo plant requires a controller quite different from conventional controllers such as PID. In this paper is presented an adaptive method of controlling the yo-yo system. Fuzzy logic controller based on human expertise is referred at first. Then, an adaptive fuzzy controller which has adaptation features against the variation of plant parameters is proposed. Finally, experimental results are presented.

PID and Adaptive Controllers for a Transportation Mobile Robot with Fork-Type Lifter

  • Nguyen, Van Vui;Tran, Huu Luat;Kim, Yong-Tae
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • 제16권3호
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    • pp.216-223
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    • 2016
  • This paper proposes a new controller design method for a fork-type lifter (FTL) of a transportation mobile robot. The transportation robot needs to pick up a package from a stack on a storage shelf and move on by a planned path in a logistics center environment. The position of the storage shelf is recognized by reading a QR code on the floor, and using this position, the robot can move to reach the storage shelf and pick up the package. PID controllers and an adaptive controller are designed to control the velocity of two wheels and the position of the FTL. An adaptive controller for the lifter is designed to elevate up and down on a slideway to the correct height position of the package on the stack of the storage shelf. The simulation results show that the PID controllers can respond smoothly to the desired angular velocity and the adaptive controller can adapt quickly and correctly to the desired height.

Study on a New and Effective Fuzzy PID Ship Autopilot

  • Le, Minh-Duc;Nguyen, Lan-Anh
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2005년도 ICCAS
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    • pp.1628-1631
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    • 2005
  • Ship Autopilots are usually designed based on the PD and Pill controllers because of simplicity, reliability and easy to construct. However their performance in various environmental conditions is not as good as desired. This disadvantage can be overcome by adjusting works or constructing adaptive controllers. But those methods are complex and not easy to do. This paper presents a new method for constructing a Ship Autopilot based on the combination of Fuzzy Logic Control (FLC) and Linear Control Theory (Pill control). The new Ship Autopilot has the advantages of both the Pill and FLC control methodologies: easy to construct, and optimal control laws can be established based on ship masters' knowledge. Therefore, the new ship autopilot can be well adapted with parameter variations and strong environment effects. Simulation using MATLAB software for a ship with real parameters shows high effectiveness of the Fuzzy Pill autopilot in course keeping and course changing manoeuvres in comparison with the ordinary Pill ship autopilots.

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Design of an Automatic constructed Fuzzy Adaptive Controller(ACFAC) for the Flexible Manipulator (유연 로봇 매니퓰레이터의 자동 구축 퍼지 적응 제어기 설계)

  • 이기성;조현철
    • Journal of the Korean Institute of Intelligent Systems
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    • 제8권2호
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    • pp.106-116
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    • 1998
  • A position control algorithm of a flexible manipulator is studied. The proposed algorithm is based on an ACFAC(Automatic Constructed Fuzzy Adaptive Controller) system based on the neural network learning algorithms. The proposed system learns membership functions for input variables using unsupervised competitive learning algorithm and output information using supervised outstar learning algorithm. ACFAC does not need a dynamic modeling of the flexible manipulator. An ACFAC is designed that the end point of the flexible manipulator tracks the desired trajectory. The control input to the process is determined by error, velocity and variation of error. Simulation and experiment results show a robustness of ACFAC compared with the PID control and neural network algorithms.

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Design of IMC Controller for Nonlinear Systems by Using Adaptive Neuro-Fuzzy Inference System (뉴로 퍼지 시스템을 이용한 비선형 시스템의 IMC 제어기 설계)

  • 강정규;김정수;김성호
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.236-236
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    • 2000
  • Control of Industrial processes is very difficult due to nonlinear dynamics, effect of disturbances and modeling errors. M.Morari proposed Internal Model Control(IMC) system that can be effectively applied to the systems with model uncertainties and time delays. The advantage of IMC systems is their robustness with respect to a model mismatch and disturbances. But it was difficult to apply for nonlinear systems. Adaptive Neuro-Fuzzy Inference System which contains multiple linear models as consequent part is used to model nonlinear systems. Generally, the linear parameters in neuro-fuzzy inference system can be effectively utilized to identify a nonlinear dynamical systems. In this paper, we propose new IMC design method using adaptive neuro-fuzzy inference system for nonlinear plant. Numerical simulation results show that proposed IMC design method has good performance than classical PID controller.

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