• Title, Summary, Keyword: Adaptive PID controller

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Formation Control of Mobile Robots using Adaptive PID Controller (적응 PID 제어기를 이용한 이동로봇의 군집제어)

  • Park, Jin-Hyun;Choi, Young-Kiu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.11
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    • pp.2554-2561
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    • 2015
  • In this paper, we strengthen the advantages of a simple PID controller as a study on the formation control of mobile robots and propose an adaptive PID controller with robust performance at the dynamics characteristics of following robot. Simulation studies show that the adaptive PID controller has better keeping constant distance and angle such as tracking performance of following robot for the formation control than a conventional PID controller. This is the proposed adaptive PID controller to change the gains is found to represent the best performance. This is able to verify that the performance of the proposed adaptive PID controller is excellent.

Implementation of the Mass Flow Controller using Adaptive PID (적응 PID를 이용한 질량 유량 제어기 구현)

  • Baek, Kwang-Ryul;Cho, Bong-Su
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.1
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    • pp.19-25
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    • 2007
  • The MFC(Mass Flow Controller) is an equipment that measures and controls mass flow rates of fluid. Most of the HFC system is still using the PID algorithm. The PID algorithm shows superior performance on the MFC system. But the PID algorithm in the MFC system has a few problems as followed. The characteristic of the MFC system is changed according to the operating environment. And, when the piezo valve that uses the control valve is assembled in the MFC system, a coupling error is generated. Therefore, it is very difficult to find out the exact parameters of MFC system. In this paper, we propose adaptive PID algorithm in order to compensate these problems of a traditional PID algorithm. The adaptive PID algorithm estimates the parameters of MFC system using LMS(Least Mean Square) algorithm and calculates the coefficients of PID controller. Besides, adaptive PID algorithm shows better transient response because adaptive PID algorithm includes a feedforward. And we implement MFC system using proposed adaptive PID algorithm with self-tuning and Ziegler and Nickels's method. Finally, comparative analysis of the proposed adaptive PID and the traditional PID is shown.

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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    • 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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An Adaptive PID Controller Design based on a Gradient Descent Learning (경사 감소 학습에 기초한 적응 PID 제어기 설계)

  • Park Jin-Hyun;Kim Hyun-Duck;Choi Young-Kiu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.2
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    • pp.276-282
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    • 2006
  • PID controller has been widely used in industry. Because it has a simple structure and robustness to modeling error. But it is difficult to have uniformly good control performance in system parameters variation or different velocity command. In this paper, we propose an adaptive PID controller based on a gradient descent learning. This algorithm has a simple structure like conventional PID controller and a robustness to system parameters variation and different velocity command. To verify performances of the proposed adaptive PID controller, the speed control of nonlinear DC motor is performed. The simulation results show that the proposed control systems are effective in tracking a command velocity under system parameters variation.

Design of PID Controller with Adaptive Neural Network Compensator for Formation Control of Mobile Robots (이동 로봇의 군집 제어를 위한 PID 제어기의 적응 신경 회로망 보상기 설계)

  • Kim, Yong-Baek;Park, Jin-Hyun;Choi, Young-Kiu
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.3
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    • pp.503-509
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    • 2014
  • In this paper, a PID controller with adaptive neural network compensator is proposed to control the formations of mobile robot. The control system is composed of a kinematic controller based on the leader-following robot and dynamic controller for considering the dynamics of the mobile robot. The dynamic controller is constituted by a PID controller and the adaptive neural network compensator for improving the performance and compensating the change in dynamic characteristics. Simulation results show the performance of the PID controller and the neural network compensator for the circular trajectory and linear trajectory. And it is verified that by improving the performance of a PID controller via the adaptive neural network compensator, the following robot's tracking performance is improved.

A Model reference adaptive speed control of marine diesel engine by fusion of PID controller and fuzzy controller

  • Yoo, Heui-Han
    • Journal of the Korean Society of Marine Engineering
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    • v.30 no.7
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    • pp.791-799
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    • 2006
  • The aim of this paper is to design an adaptive speed control system of a marine diesel engine by fusion of hard computing based proportional integral derivative (PID) control and soft computing based fuzzy control methods. The model of a marine diesel engine is considered as a typical non oscillatory second order system. When its model and the actual marine diesel engine ate not matched, it is hard to control the speed of the marine diesel engine. Therefore, this paper proposes two methods in order to obtain the speed control characteristics of a marine diesel engine. One is an efficient method to determine the PID control parameters of the nominal model of a marine diesel engine. Second is a reference adaptive speed control method that uses a fuzzy controller and derivative operator for tracking the nominal model of the marine diesel engine. It was found that the proposed PID parameters adjustment method is better than the Ziegler & Nichols' method, and that a model reference adaptive control is superior to using only PID controller. The improved control method proposed here, could be applied to other systems when a model of a system does not match the actual system.

Adaptive-Tuning of PID Controller using Self-Recurrent Neural Network (자기순환 신경망을 이용한 PID 제어기의 적응동조)

  • 박광현;허진영;하홍곤
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • pp.121-124
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    • 2001
  • In industrial actual control system, PID controller has been used with its high delicate control system in position control system. PID controller has simple structure and superior ability in several characteristics. When the response of system is changed by delay time, variable load , disturbances and external environment, control gain of PID controller must be readjusted on the system dynamic characteristics. Therefore, a control ability of PID controller is degraded when th control gain is inappropriately determined. When the response characteristic of system is changed under a condition, control gain of PID controller must be changed adaptively to be a waited response of system. In this paper an adaptive-tuning type PID controller is constructed by self-recurrent Neural Network(SRNN). applying back-propagation(BP) algorithm. Form the result of computer simulation in the proposed controller, its usefulness is verified.

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Adaptive PID Controller for Nonlinear Systems using Fuzzy Model (퍼지 모델을 이용한 비선형 시스템의 적응 PID 제어기)

  • Kim, Jong-Hua;Lee, Won-Chang;Kang, Geun-Taek
    • Journal of Korean Institute of Intelligent Systems
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    • v.13 no.1
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    • pp.85-90
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    • 2003
  • This paper presents an adaptive PID control scheme for nonlinear system. TSK(Takagi-Sugeno-Kang) fuzzy model is used to estimate the error of control input, and the parameters of PID controller are adapted using the error. The parameters of TSK fuzzy model also adapted to plant. The proposed algorithm allows designing adaptive PID controller which Is adapted to the uncertainty of nonlinear plant and the change of parameters. The usefulness of the proposed algorithm is also certificated by the several simulations.

A Position Control of EHA Systems using Adaptive PID Sliding Mode Control Scheme (적응PID 슬라이딩 모드 제어기법을 적용한 EHA 시스템의 위치제어)

  • Lee, Ji-Min;Park, Sung-Hwan;Park, Min-Gyu;Kim, Jong-Shik
    • Journal of the Korea Society For Power System Engineering
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    • v.17 no.4
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    • pp.120-130
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    • 2013
  • An adaptive PID sliding mode controller is proposed for the position control of electro-hydrostatic actuator(EHA) systems with system uncertainties and saturation in the motor. An EHA prototype is developed and system modeling and parameter identification are executed. Then, adaptive PID sliding mode controller and optimal anti-windup PID controller are designed and the performance and robustness of the two control systems are compared by experiment. It was found that the adaptive PID sliding mode control system has better performance and is more robust to system uncertainties than the optimal anti-windup PID control system.

Adaptive PID Controller for Nonlinear Systems using Fuzzy Model

  • Zonghua Jin;Lee, Wonchang;Geuntaek Kang
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • pp.342-345
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    • 2003
  • This paper presents an adaptive PID control scheme for nonlinear system. TSK(Takagi-Sugeno-Kang) fuzzy model is used to estimate the error of control input, and the parameter of PID controller are adapted using the error. The parameters of TSK fuzzy model are also adapted to plant. The proposed algorithm allows designing adaptive PID controller which is adapted to the uncertainty of nonlinear plant and the change of parameters. The usefulness of the proposed algorithm is also certificated by the several simulations.

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