• Title/Summary/Keyword: PID control : Fuzzy controller

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Fuzzy Auto-tuning PID Controller for Servo System (서보 시스템을 위한 퍼지 자동 동조 PID 제어기)

  • Oh, Hun;Yoon, Yang-Woong
    • The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.9 no.1
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    • pp.63-66
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    • 1995
  • PID controller is being used in many servo control system. However, when a control system has variable load, it is difficult to guarantee the accurate control of the system. In the way of solving this problem, in this paper, a auto-tuning method of PID controller parameter using fuzzy rule in variable load is presented. The parameter of PID controller are decided by fuzzy rule according to load variation. The accurate control function of fuzzy auto-tuning is demonstrated by simulation.

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Simulation for Intelligent Cruise Control of vehicle using Fuzzy-PID Controller (Fuzzy-PID 제어기를 이용한 차량의 정속주행 시뮬레이션)

  • 임영도;김승철;박재형
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.2 no.4
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    • pp.603-610
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    • 1998
  • The purpose of this paper is to describe how the characteristics of the movement of cars can be modeled with computers. For this, we use Matlab and simulate the characteristics of the cruise-speed at which the car is driven using the Fuzzy PID controller. The model of the car is designed by M-S(Matlab-Simulink) and each parameter of PID is estimated automatically by the Fuzzy controller. The simulation of the car is carried out on straight base tracks, and then this is compared and analyzed with the simple Fuzzy controller and the simple PID controller.

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Improved Neural Network-Based Self-Tuning fuzzy PID Controller for Induction Motor Speed Control (유도전동기 속도제어를 위한 개선된 신경회로망 기반 자기동조 퍼지 PID 제어기 설계)

  • 김상민;한우용;이창구
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.51 no.12
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    • pp.691-696
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    • 2002
  • This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for induction motor speed control. 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. Proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using dSPACE(DS1102) board are performed to verify the effectiveness of the proposed scheme.

Fuzzy Logic PID controller based on FPGA

  • Tipsuwanporn, V.;Runghimmawan, T.;Krongratana, V.;Suesut, T.;Jitnaknan, P.
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.1066-1070
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    • 2003
  • Recently technologies have created new principle and theory but the PID control system remains its popularity as the PID controller contains simple structure, including maintenance and parameter adjustment being so simple. Thus, this paper proposes auto tune PID by fuzzy logic controller based on FPGA which to achieve real time and small size circuit board. The digital PID controller design to consist of analog to digital converter which use chip TDA8763AM/3 (10 bit high-speed low power ADC), digital to analog converter which use two chip DAC08 (8 bit digital to analog converters) and fuzzy logic tune digital PID processor embedded on chip FPGA XC2S50-5tq-144. The digital PID processor was designed by fundamental PID equation which architectures including multiplier, adder, subtracter and some other logic gate. The fuzzy logic tune digital PID was designed by look up table (LUT) method which data storage into ROM refer from trial and error process. The digital PID processor verified behavior by the application program ModelSimXE. The result of simulation when input is units step and vary controller gain ($K_p$, $K_i$ and $K_d$) are similarity with theory of PID and maximum execution time is 150 ns/action at frequency are 30 MHz. The fuzzy logic tune digital PID controller based on FPGA was verified by control model of level control system which can control level into model are correctly and rapidly. Finally, this design use small size circuit board and very faster than computer and microcontroller.

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Speed Control of BLDC Motor Drive Using an Adaptive Fuzzy P+ID Controller (적응 퍼지 P+ID 제어기를 이용한 BLDC 전동기의 속도제어)

  • Kwon, Chung-Jin;Han, Woo-Yang;Sin, Dong-Yang;Kim, Sung-Joong
    • Proceedings of the KIEE Conference
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    • 2002.07b
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    • pp.1172-1174
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    • 2002
  • An adaptive fuzzy P + ID controller for variable speed operation of BLDC motor drives is presented in this paper. Generally, a conventional PID controller is most widely used in industry due to its simple control structure and ease of design. However, the PID controller suffers from the electrical machine parameter variations and disturbances. To improve the tracking performance for parameter and load variations, the controller proposed in this paper is constructed by using an adaptive fuzzy logic controller in place of the proportional term in a conventional PID controller. For implementing this controller, only one additional parameter has to be adjusted in comparison with the PID controller. An adaptive fuzzy controller applied to proportional term to achieve robustness against parameter variations has simple structure and computational simplicity. The controller based on optimal fuzzy logic controller has an self-tuning characteristics with clustering. Computer simulation results show the usefulness of the proposed controller.

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A Study on the Nonlinear Fuzzy PID Controller with Variable Parameters (가변 파라미터를 갖는 비선형 퍼지 PID 제어기에 관한 연구)

  • Lee, Byung-Kyul;Kim, In-Hwan;Kim, Jong-Hwa
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.2
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    • pp.127-134
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    • 2005
  • This paper proposes a nonlinear fuzzy PID controller with variable parameters to improve slow rising time and divergence occurred by limited input spaces and a resultant limited control input during fuzzification in a fuzzy PID controller with fixed parameters, and describes the design principle and tracking performance of a proposed fuzzy PID controller. The parameters of a proposed controller are adjusted by the stability conditions derived from 'small gain theorem' and satisfy the BIBO stability of overall control system.

Tuning gains of a PID controller using fuzzy logic-based tuners (퍼지 로직 동조기를 이용한 PID 제어기의 이득 조정)

  • 이명원;권순학;이달해
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.184-187
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    • 1996
  • In this paper, an algorithm for tuning gains of a PID controller is proposed. The proposed algorithm is composed of two stages. The first is a stage for Lyapunov function-based initial stabilization of an overall system and rough tuning gains of the PID controller. The other is that for fine tuning gains of the PID controller. All tunings are performed by using the well-known fuzzy logic-based tuner. The computer simulations are performed to show the validity of the proposed algorithm and results are presented.

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A novel self-organizing fuzzy plus PID type controller with application to inverted pendulum control (PID와 자동 학습 퍼지 제어기를 이용한 도립 전자의 제어)

  • 이용노;김태원;서일홍;김기엽
    • 제어로봇시스템학회:학술대회논문집
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    • 1991.10a
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    • pp.681-686
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    • 1991
  • In this paper, a novel self-organizing fuzzy plus PID control algorithm is proposed and analyzed by extensive computer simulations and experiments with an inverted pendulum. Specifically, the proposed self-organizing fuzzy controller consists of a typical fuzzy reasoning part and self organizing part in which both on-line and off-line algorithms are employed to modify the 'then' part of the fuzzy rules and to decide how much fuzzy rules are to be modified after evaluating the control performance, respecfively. And the fuzzy controller is replaced by a PID controller in a prespecified region near by the set point for good settling actions.

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CFWC Scheme for Width Control using CCD Measurement System and Fuzzy PID Controller in Hot Strip Mills (CCD 폭 측정 시스템 및 퍼지 PID를 이용한 CFWC 제어기 설계)

  • Park, Cheol Jae
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.11
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    • pp.991-997
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    • 2013
  • In this paper, we propose a CFWC (CCD and fuzzy PID based width control) scheme to obtain the desired delivery width margin of a vertical rolling mill in hot strip process. A WMS(width measurement system) is composed of two line scan cameras, an edge detection algorithm, a glitch filter, and so on. A dynamic model of the mill is derived from a gauge meter equation in order to design the fuzzy PID controller. The controller is a self-learning structure to select the PID gains from the error and error rate of the width margin. The effectiveness of the proposed CFWC is verified from simulation results under a width disturbance of the entry in the mill. Using a field test, we show that the performance of the width control is improved by the proposed control scheme.

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.