• Title, Summary, Keyword: PID controller

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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.

Fuzzy PID Controller Design for Tracking Control (퍼지PID제어를 이용한 추종 제어기 설계)

  • 김봉주;정정주
    • 제어로봇시스템학회:학술대회논문집
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    • pp.68-68
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    • 2000
  • This paper presents a fuzzy modified PID controller that uses linear fuzzy inference method. In this structure, the proportional and derivative gains vary with the output of the system under control. 2-input PD type fuzzy controller is designed to obtain the varying gains. The proposed fuzzy PID structure maintains the same performance as the general-purpose linear PID controller, and enhances the tracking performance over a wide range of input. Numerical simulations and experimental results show the effectiveness of the fuzzy PID controller in comparison with the conventional 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.

Application of Neural Network Precompensated PID Controller for Load Frequency Control of Power Systems (전력계통의 부하주파수 제어를 위한 신경회로망 전 보상 PID 제어기 적용)

  • 김상효
    • Journal of the Korean Society of Marine Engineering
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    • v.23 no.4
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    • pp.480-487
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    • 1999
  • In this paper we propose a neural network precompensated PID(NNP PID) controller for load frequency control of 2-area power system. While proportional integral derivative(PID) controllers are used in power system they have many problems because of high nonlinearities of the power system So a neural network-based precompensation scheme is adopted into a conventional PID controller to obtain a robust control to the nonlinearities. The applied neural network precompen-sator uses an error back-propagation learning algorithm having error and change of error as inputand considers the changing component of forward term of weighting factor for reducing of learning time. Simulation results show that the proposed control technique is superior to a conventional PID controller and an optimal controller in dynamic responses about load disturbances. The pro-posed technique can be easily implemented by adding a neural network precompensator to an existing PID controller.

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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.

DC MOTOR SPEED CONTROL USING PID CONTROLLER

  • Loucif, Fatiha
    • 제어로봇시스템학회:학술대회논문집
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    • pp.2557-2561
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    • 2005
  • The PID controller design and choosing PID parameters according to system response are proposed in this paper. Here PID controller is employed to control DC motor speed and Matlab program is used for calculation and simulation. Choosing PID parameters are demonstrated by several contrast experiments and a way for setting PID parameters values is discussed.

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A Study of Position Control Performance Enhancement in a Real-Time OS Based Laparoscopic Surgery Robot Using Intelligent Fuzzy PID Control Algorithm (Intelligent Fuzzy PID 제어 알고리즘을 이용한 실시간 OS 기반 복강경 수술 로봇의 위치 제어 성능 강화에 관한 연구)

  • Song, Seung-Joon;Park, Jun-Woo;Shin, Jung-Wook;Lee, Duck-Hee;Kim, Yun-Ho;Choi, Jae-Soon
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.57 no.3
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    • pp.518-526
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    • 2008
  • The fuzzy self-tuning PID controller is a PID controller with a fuzzy logic mechanism for tuning its gains on-line. In this structure, the proportional, integral and derivative gains are tuned on-line with respect to the change of the output of system under control. This paper deals with two types of fuzzy self-tuning PID controllers, rule-based fuzzy PID controller and learning fuzzy PID controller. As a medical application of fuzzy PID controller, the proposed controllers were implemented and evaluated in a laparoscopic surgery robot system. The proposed fuzzy PID structures maintain similar performance as conventional PID controller, and enhance the position tracking performance over wide range of varying input. For precise approximation, the fuzzy PID controller was realized using the linear reasoning method, a type of product-sum-gravity method. The proposed controllers were compared with conventional PID controller without fuzzy gain tuning and was proved to have better performance in the experiment.

Nonlinear PID Controller with Neural Network based Compensator (신경회로망 보상기를 갖는 비선형 PID 제어기)

  • Lee, Chang-Gu
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.5
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    • pp.225-234
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    • 2000
  • In this paper, we present an nonlinear PID controller with network based compensator which consists of a conventional PID controller that controls the linear components and neuro-compensator that controls the output errors and nonlinear components. This controller is based on the Harris's concept where he explained that the adaptive controller consists of the PID control term and the disturbance compensating term. The resulting controller's architecture is also found to be very similar to that of Wang's controller. This controller adds a self-tuning ability to the existing PID controller without replacing it by compensating the output errors through the neuro-compensator. Various simulations and comparative studies have proven that the proposed nonlinear PID controller produces superior results to other existing PID controllers. When applied to an actual magnetic levitation system which is known to be very nonlinear, it has also produced an excellent results.

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A PID learning controller for DC motors (DC 전동기를 위한 PID 학습제어기)

  • 백승민;이동훈;국태용
    • 제어로봇시스템학회:학술대회논문집
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    • pp.347-350
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    • 1996
  • With only the classical PID controller applied to control of a DC motor, a good (target) performance characteristic of the controller can be obtained, if all the model parameters of DC motor and operating conditions such as external load torque, disturbance, etc. are exactly known. However, in case when some of system parameters or operating conditions are uncertain or unknown, the fixed PID controller does not guarantee the good performance which is assumed with precisely known system parameters and operating conditions. In view of this and robustness enhancement of DC motor control system, we propose a PID learning controller which consists of a set of learning rules for PID gain tuning and learning of an auxiliary input. The proposed PID learning controller is shown to drive the state of uncertain DC motor system with unknown system parameters and external load torque to the desired one globally asymptotically. Computer simulation results are given to demonstrate the effectiveness of the proposed PID learning controller, thereby showing whose superiority to the conventional fixed PID controller.

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Design of a Neural Network Based Self-Tuning Fuzzy PID Controller (신경회로망 기반 자기동조 퍼지 PID 제어기 설계)

  • Im, Jeong-Heum;Lee, Chang-Goo
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.50 no.1
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    • pp.22-30
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    • 2001
  • This paper describes a neural network based fuzzy PID control scheme. The PID controller is being widely used in industrial applications. However, it is difficult to determine the appropriated PID gains in nonlinear systems and systems with long time delay and so on. In this paper, we re-analyzed the fuzzy controller as conventional PID controller structure, and proposed a neural network based self tuning fuzzy PID controller of which output gains were adjusted automatically. The tuning parameters of the proposed controller were determined on the basis of the conventional PID controller parameters tuning methods. Then they were adjusted by using proposed neural network learning algorithm. Proposed controller was simple in structure and computational burden was small so that on-line adaptation was easy to apply to. The experiment on the magnetic levitation system, which is known to be heavily nonlinear, showed the proposed controller's excellent performance.

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