Design of Flexible PID-Plus Bang-Bang Controller with Neural Network Predictive Model

Sung Hoon JUNG; Kwang-Hyun CHO; Tag Gon KIM; Kyu Ho PARK; Jong-Tae LIM

Design of Flexible PID-Plus Bang-Bang Controller with Neural Network Predictive Model

Sung Hoon JUNG, Kwang-Hyun CHO, Tag Gon KIM, Kyu Ho PARK, Jong-Tae LIM

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PID-type controllers have been well-known and widely used in many industries. Their regulation property of those was more improved through the addition of Bang-Bang-action. In spite of the potentials of these PID-plus Bang-Bang controllers, their regulation property is still limited by the fixed window limit value that determines the control action, i. e., PID or Bang-Bang. Thus, this paper presents an approach for improving the regulation property by dynamically changing the window limit value according to the plant dynamics with Neural Network predictive model. The improved regulation property is illustrated through simulation studies for position control of DC servo-motor system in the sense of classical figures of merit such as overshoot and rise time.

Publication: IEICE TRANSACTIONS on Information Vol.E79-D No.4 pp.357-362

Publication Date: 1996/04/25

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Type of Manuscript: PAPER

Category: Computer Applications

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Sung Hoon JUNG, Kwang-Hyun CHO, Tag Gon KIM, Kyu Ho PARK, Jong-Tae LIM, "Design of Flexible PID-Plus Bang-Bang Controller with Neural Network Predictive Model" in IEICE TRANSACTIONS on Information, vol. E79-D, no. 4, pp. 357-362, April 1996, doi: .
Abstract: PID-type controllers have been well-known and widely used in many industries. Their regulation property of those was more improved through the addition of Bang-Bang-action. In spite of the potentials of these PID-plus Bang-Bang controllers, their regulation property is still limited by the fixed window limit value that determines the control action, i. e., PID or Bang-Bang. Thus, this paper presents an approach for improving the regulation property by dynamically changing the window limit value according to the plant dynamics with Neural Network predictive model. The improved regulation property is illustrated through simulation studies for position control of DC servo-motor system in the sense of classical figures of merit such as overshoot and rise time.
URL: https://global.ieice.org/en_transactions/information/10.1587/e79-d_4_357/_p

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@ARTICLE{e79-d_4_357,
author={Sung Hoon JUNG, Kwang-Hyun CHO, Tag Gon KIM, Kyu Ho PARK, Jong-Tae LIM, },
journal={IEICE TRANSACTIONS on Information},
title={Design of Flexible PID-Plus Bang-Bang Controller with Neural Network Predictive Model},
year={1996},
volume={E79-D},
number={4},
pages={357-362},
abstract={PID-type controllers have been well-known and widely used in many industries. Their regulation property of those was more improved through the addition of Bang-Bang-action. In spite of the potentials of these PID-plus Bang-Bang controllers, their regulation property is still limited by the fixed window limit value that determines the control action, i. e., PID or Bang-Bang. Thus, this paper presents an approach for improving the regulation property by dynamically changing the window limit value according to the plant dynamics with Neural Network predictive model. The improved regulation property is illustrated through simulation studies for position control of DC servo-motor system in the sense of classical figures of merit such as overshoot and rise time.},
keywords={},
doi={},
ISSN={},
month={April},}

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TY - JOUR
TI - Design of Flexible PID-Plus Bang-Bang Controller with Neural Network Predictive Model
T2 - IEICE TRANSACTIONS on Information
SP - 357
EP - 362
AU - Sung Hoon JUNG
AU - Kwang-Hyun CHO
AU - Tag Gon KIM
AU - Kyu Ho PARK
AU - Jong-Tae LIM
PY - 1996
DO -
JO - IEICE TRANSACTIONS on Information
SN -
VL - E79-D
IS - 4
JA - IEICE TRANSACTIONS on Information
Y1 - April 1996
AB - PID-type controllers have been well-known and widely used in many industries. Their regulation property of those was more improved through the addition of Bang-Bang-action. In spite of the potentials of these PID-plus Bang-Bang controllers, their regulation property is still limited by the fixed window limit value that determines the control action, i. e., PID or Bang-Bang. Thus, this paper presents an approach for improving the regulation property by dynamically changing the window limit value according to the plant dynamics with Neural Network predictive model. The improved regulation property is illustrated through simulation studies for position control of DC servo-motor system in the sense of classical figures of merit such as overshoot and rise time.
ER -