Fractional-order predictive pi controller for dead-time processes with set-point and noise filtering

In most of the industrial process plants, PI/PID controllers have been widely used because of its simple design, easy tuning, and operational advantages. However, the performance of these controllers degrades for the processes with long dead-time and variation in set-point. Up next, a PPI controller...

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Main Authors: Devan, P.A.M., Hussin, F.A.B., Ibrahim, R., Bingi, K., Abdulrab, H.Q.A.
Format: Article
Published: Institute of Electrical and Electronics Engineers Inc. 2020
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102766544&doi=10.1109%2fACCESS.2020.3029068&partnerID=40&md5=8faff9e413529fa9e7f7bcad352fd4bf
http://eprints.utp.edu.my/23217/
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spelling my.utp.eprints.232172021-08-19T05:53:01Z Fractional-order predictive pi controller for dead-time processes with set-point and noise filtering Devan, P.A.M. Hussin, F.A.B. Ibrahim, R. Bingi, K. Abdulrab, H.Q.A. In most of the industrial process plants, PI/PID controllers have been widely used because of its simple design, easy tuning, and operational advantages. However, the performance of these controllers degrades for the processes with long dead-time and variation in set-point. Up next, a PPI controller is designed based on the Smith predictor to handle dead-time processes by compensation technique, but it failed to achieve adequate performance in the presence of external noise, large disturbances, and higher-order systems. Furthermore, the model-based controllers structure is complex in nature and requires the exact model of the process with more tunable parameters. Therefore, in this research, a fractional-order predictive PI controller has been proposed for dead-time processes with added filtering abilities. The controller uses the dead-time compensation characteristics of the Smith predictor and the fractional-order controller's robustness nature. For the high peak overshoot, external noise, and disturbance problems, a new set-point and noise filtering technique is proposed, and later it is compared with different conventional methods. In servo and regulatory operations, the proposed controller and filtering techniques produced optimal performance. Multiple real-time industrial process models are simulated with long dead-time to evaluate the proposed technique's fiexibility, set-point tracking, disturbance rejection, signal smoothing, and dead-time compensation capabilities. © 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved. Institute of Electrical and Electronics Engineers Inc. 2020 Article NonPeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102766544&doi=10.1109%2fACCESS.2020.3029068&partnerID=40&md5=8faff9e413529fa9e7f7bcad352fd4bf Devan, P.A.M. and Hussin, F.A.B. and Ibrahim, R. and Bingi, K. and Abdulrab, H.Q.A. (2020) Fractional-order predictive pi controller for dead-time processes with set-point and noise filtering. IEEE Access, 8 . pp. 183759-183773. http://eprints.utp.edu.my/23217/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
description In most of the industrial process plants, PI/PID controllers have been widely used because of its simple design, easy tuning, and operational advantages. However, the performance of these controllers degrades for the processes with long dead-time and variation in set-point. Up next, a PPI controller is designed based on the Smith predictor to handle dead-time processes by compensation technique, but it failed to achieve adequate performance in the presence of external noise, large disturbances, and higher-order systems. Furthermore, the model-based controllers structure is complex in nature and requires the exact model of the process with more tunable parameters. Therefore, in this research, a fractional-order predictive PI controller has been proposed for dead-time processes with added filtering abilities. The controller uses the dead-time compensation characteristics of the Smith predictor and the fractional-order controller's robustness nature. For the high peak overshoot, external noise, and disturbance problems, a new set-point and noise filtering technique is proposed, and later it is compared with different conventional methods. In servo and regulatory operations, the proposed controller and filtering techniques produced optimal performance. Multiple real-time industrial process models are simulated with long dead-time to evaluate the proposed technique's fiexibility, set-point tracking, disturbance rejection, signal smoothing, and dead-time compensation capabilities. © 2020 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.
format Article
author Devan, P.A.M.
Hussin, F.A.B.
Ibrahim, R.
Bingi, K.
Abdulrab, H.Q.A.
spellingShingle Devan, P.A.M.
Hussin, F.A.B.
Ibrahim, R.
Bingi, K.
Abdulrab, H.Q.A.
Fractional-order predictive pi controller for dead-time processes with set-point and noise filtering
author_facet Devan, P.A.M.
Hussin, F.A.B.
Ibrahim, R.
Bingi, K.
Abdulrab, H.Q.A.
author_sort Devan, P.A.M.
title Fractional-order predictive pi controller for dead-time processes with set-point and noise filtering
title_short Fractional-order predictive pi controller for dead-time processes with set-point and noise filtering
title_full Fractional-order predictive pi controller for dead-time processes with set-point and noise filtering
title_fullStr Fractional-order predictive pi controller for dead-time processes with set-point and noise filtering
title_full_unstemmed Fractional-order predictive pi controller for dead-time processes with set-point and noise filtering
title_sort fractional-order predictive pi controller for dead-time processes with set-point and noise filtering
publisher Institute of Electrical and Electronics Engineers Inc.
publishDate 2020
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102766544&doi=10.1109%2fACCESS.2020.3029068&partnerID=40&md5=8faff9e413529fa9e7f7bcad352fd4bf
http://eprints.utp.edu.my/23217/
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score 13.18916