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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Institute of Electrical and Electronics Engineers Inc.
2020
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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/ |
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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. |
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Devan, P.A.M. Hussin, F.A.B. Ibrahim, R. Bingi, K. Abdulrab, H.Q.A. |
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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 |
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Institute of Electrical and Electronics Engineers Inc. |
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2020 |
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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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13.18916 |