• Title/Summary/Keyword: Tuning parameter

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Speed Control of Induction Motor by Means of Expert PLC in Variable load (가변부하시 전문가 PLC에 의한 유도전동기의 속도제어)

  • Park, Wal-Seo;Oh, Hun
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.16 no.2
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    • pp.54-58
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    • 2002
  • PID Controller is widely used as automatic equipment for industry. However, when a system has various characters, parameter decision and tuning for accurate control is a hard task. In this paper, expert auto-tuning PID controller using PLC is presented as away of solving this problem. Expert auto tuning algorithm is based on Ziegler-Nichols step response and expert knowledge. The test of control performance is carried out in practical speed control of Induction Motor in variable load, the experimental results suggest its superior performance.

Study On PID Gain Tuning Using CRA For DCS System (DCS 시스템에서 CRA를 이용한 PID 이득 Tuning에 관한 연구)

  • Lee, Sang-Hoon;Kang, Yun-Bok;Park, Ok-Deuk;Kim, Hyun-Su;Long, Nguyen Phi;Hieu, Nguyen Hoang;Kim, Han-Sil
    • Proceedings of the KIEE Conference
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    • 2006.10c
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    • pp.306-308
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    • 2006
  • 산업현장에서 가장 많이 활용되고 있는 PID제어기의 이론적인 배경을 토대로 실제 DCS 기반 플랜트에서 PID Tuning Method에 의한 PID제어기를 구현하고 제어성능을 확인한다. 또한 DCS(Distribute Control System)의 PID Controller를 분석하고 전 공정제어 System 중 일부분을 ARMA Modeling하여 만족스런 성능이 구현되도록 최적의 PID gain Parameter를 찾는다.

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Auto-tuning of PID/PIDA Controllers based on Step-response (스텝응답에 기반한 PID/PIDA 제어기의 자동동조)

  • Ahn, Kyung-Pil;Lee, Jun-Sung;Lim, Jae-Sik;Lee, Young-Il
    • Journal of Institute of Control, Robotics and Systems
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    • v.15 no.10
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    • pp.974-981
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    • 2009
  • In this paper, a method of auto-tuning of PID (Proportional-Integral-Derivative) and PIDA (Proportional-Integral-Derivative-Acceleration) controllers is proposed that can be applied to a time-delayed second order model. The proposed identification method is based on step responses, but it can be easily automated rising digital controller unlike the existing graphical identification methods. We provide a ways to yield parameter identifications which is independent to initial values of the plants. The tuning rule is based on the pole-placement strategy and is formulated so that it can be implemented using a digital controller with ease.

A Study on the Implementation of a DC Servo Motor Speed Controller Using Self-tuning PID Algorithm, with Multi-processor (자기동조 PID 알고리즘을 이용한 다중processor 방식의 DC 서보모타 속도제어기의 구현)

  • Chung, Kee-Chull;Yang, Hai-Won
    • Proceedings of the KIEE Conference
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    • 1989.07a
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    • pp.125-128
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    • 1989
  • This paper presents a DC servo motor controller using self-tuning PID algorithm, which can support Multi-processor for the real time processing. Computer simulation as well as experiment using Multi-processor(8088) are implemented with self-tuning PID algorithm. Presented algorithm is used to compare the performance of the controller with that of the classical PID controller through computer simulation and experiment. The result which use the Self-Tuning algorithm show that motor output follows the reference input trajectory fairly well inspite of load disturbances and parameter variations.

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A Model-Based Tuning Rule of the PID Controller (PID 제어기의 모델기반 동조규칙)

  • 김도응;신명호;권봉재;유성호;박승수;진강규
    • Proceedings of the Korean Society of Marine Engineers Conference
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    • 2002.05a
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    • pp.261-266
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    • 2002
  • In this Paper, we Propose model-based tuning rules of the PID controller incorporating with genetic algorithms. Three sets of optimal PID parameters for step set-point tracking are obtained based on the first-order time delay model of plants and a genetic algorithm which minimizes performance indices(IAE, ISE and ITAE). Then tuning rules are obtained using the tuned parameter sets, potential rule models and a genetic algorithm. Simulation is carried out to verify the effectiveness of the proposed rules.

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Self-Tuning Controller design for the motion control of a Single Rod Hydraulic Cylinder (편로드 유압실린더의 운동제어를 위한 자기동조 제어기설계)

  • 김정태;김문생
    • Journal of KSNVE
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    • v.8 no.3
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    • pp.441-449
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    • 1998
  • A self-tuning control scheme, incorporated with the simplified 1st-order ARMAX(Auto-Regressive Moving Average eXogenous) model, for single rod hydraulic cylinder which has varying dynamic characteristics is presented here. An adaptive controller is developed for the system that uses feedforward and optimal feedback control for simultaneous parameter identification and tracking control. Through experimental results, the performance comparison of the self-tuning controller with a fixed gain proportional controller clearly shows its superior ability in handling load changes in quiescent states.

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Load Variation Compensated Neural Network Speed Controller for Induction Motor Drives

  • Oh, Won-Seok;Cho, Kyu-Min;Kim, Young-Tae;Kim, Hee-Jun
    • KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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    • v.3B no.2
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    • pp.97-102
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    • 2003
  • In this paper, a recurrent artificial neural network (RNN) based self-tuning speed controller is proposed for the high-performance drives of induction motors. The RNN provides a nonlinear modeling of a motor drive system and could provide the controller with information regarding the load variation system noise, and parameter variation of the induction motor through the on-line estimated weights of the corresponding RNN. Thus, the proposed self-tuning controller can change the gains of the controller according to system conditions. The gain is composed with the weights of the RNN. For the on-line estimation of the RNN weights, an extended Kalman filter (EKF) algorithm is used. A self-tuning controller is designed that is adequate for the speed control of the induction motor The availability of the proposed controller is verified through MATLAB simulations and is compared with the conventional PI controller.

Tuning the Architecture of Support Vector Machine: The Case of Bankruptcy Prediction

  • Min, Jae-H.;Jeong, Chul-Woo;Kim, Myung-Suk
    • Management Science and Financial Engineering
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    • v.17 no.1
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    • pp.19-43
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    • 2011
  • Tuning the architecture of SVM (support vector machine) is to build an SVM model of better performance. Two different tuning methods of the grid search and the GA (genetic algorithm) have been addressed in the literature, each of which has its own methodological pros and cons. This paper suggests a combined method for tuning the architecture of SVM models, which employs the GAM (generalized additive models), the grid search, and the GA in sequence. The GAM is used for selecting input variables, and the grid search and the GA are employed for finding optimal parameter values of the SVM models. Applying the method to a bankruptcy prediction problem, we show that SVM model tuned by the proposed method outperforms other SVM models.

Rule-based controller by Modified Ziegler-Nichols tuning (개선된 Ziegler-Nichols 동조에 의한 규칙기반 PID제어기 설계)

  • Lee, Won-Hyok;Choi, Jeong-Nae;Kim, Jin-Kwon;Hwang, Hyung-Soo
    • Proceedings of the KIEE Conference
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    • 1998.07b
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    • pp.775-777
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    • 1998
  • The Ziegler-Nichols parameter tuning has been widely known as a fairly heuristic method to good determine setting of PID controllers, for a wide range of common industrial processes. We extract process knowledge required for rule base controller through tuning experiment and simulation study, such as set point weighting and normalised gain and dead time of process. In this paper, we presents a rule base PID controller by extracted process knowledge and the modified Ziegler-Nichols tuning. Computer simulation are provided demonstrate the feasibility of this approach.

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Quick Variance Change Point Detection for Time Series in Progress

  • Park, Yoon-Sung;Park, Kyoung-Hwa;Choi, Sung-Hwan;Kim, Tae-Yoon
    • Journal of the Korean Data and Information Science Society
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    • v.16 no.2
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    • pp.289-300
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    • 2005
  • In this article quick variance change point (VCP) detection problem for time series is considered. For this variance VCP detector equipped with tuning parameters is proposed. A major tool for the detector is moving variance ratio (MVR) which monitors variance change of a given time series. Tuning process of detector is investigated via simulation, which shows that tuning parameters are critical in achieving sensitivity and adaptiveness of detector.

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