U-Model Based Adaptive Control of Gas Process Plant

Industrial process control holds great importance while dealing with nonlinear control. System modeling and controller design is considered to be a critical challenge for researchers as well as plant operators. Resultantly, significant amount of research work has been prompted in the area of Adaptiv...

Full description

Main Authors: Hasan, E., Ibrahim, R.B., Ali, S.S.A., Bingi, K., Gilani, S.F.
Format: Article
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-eprints.20276 /
Published: Elsevier B.V. 2017
Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016134376&doi=10.1016%2fj.procs.2017.01.186&partnerID=40&md5=98783976d9f910241a2a769c8a782c81
http://eprints.utp.edu.my/20276/
Tags: Add Tag
No Tags, Be the first to tag this record!
id utp-eprints.20276
recordtype eprints
spelling utp-eprints.202762018-04-23T01:01:43Z U-Model Based Adaptive Control of Gas Process Plant Hasan, E. Ibrahim, R.B. Ali, S.S.A. Bingi, K. Gilani, S.F. Industrial process control holds great importance while dealing with nonlinear control. System modeling and controller design is considered to be a critical challenge for researchers as well as plant operators. Resultantly, significant amount of research work has been prompted in the area of Adaptive Control. Their biggest advantage is that unknown system parameters are tuned online and adjusted adaptively. In this research work, an adaptive controller, based upon a recently developed U-Model is suggested. U-Model is a simplified polynomial structure that adaptively adjusts system parameters online. Being less complex in structure, design and development of U-Model based controller is simple. Previously, it has performed well in different applications regarding system identification and controller design. This motivates us to undertake a Gas Process Plant for our research work using U-Model. The proposed control strategy is verified by a simulation. © 2017 The Authors. Elsevier B.V. 2017 Article PeerReviewed https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016134376&doi=10.1016%2fj.procs.2017.01.186&partnerID=40&md5=98783976d9f910241a2a769c8a782c81 Hasan, E. and Ibrahim, R.B. and Ali, S.S.A. and Bingi, K. and Gilani, S.F. (2017) U-Model Based Adaptive Control of Gas Process Plant. Procedia Computer Science, 105 . pp. 119-124. http://eprints.utp.edu.my/20276/
institution Universiti Teknologi Petronas
collection UTP Institutional Repository
description Industrial process control holds great importance while dealing with nonlinear control. System modeling and controller design is considered to be a critical challenge for researchers as well as plant operators. Resultantly, significant amount of research work has been prompted in the area of Adaptive Control. Their biggest advantage is that unknown system parameters are tuned online and adjusted adaptively. In this research work, an adaptive controller, based upon a recently developed U-Model is suggested. U-Model is a simplified polynomial structure that adaptively adjusts system parameters online. Being less complex in structure, design and development of U-Model based controller is simple. Previously, it has performed well in different applications regarding system identification and controller design. This motivates us to undertake a Gas Process Plant for our research work using U-Model. The proposed control strategy is verified by a simulation. © 2017 The Authors.
format Article
author Hasan, E.
Ibrahim, R.B.
Ali, S.S.A.
Bingi, K.
Gilani, S.F.
spellingShingle Hasan, E.
Ibrahim, R.B.
Ali, S.S.A.
Bingi, K.
Gilani, S.F.
U-Model Based Adaptive Control of Gas Process Plant
author_sort Hasan, E.
title U-Model Based Adaptive Control of Gas Process Plant
title_short U-Model Based Adaptive Control of Gas Process Plant
title_full U-Model Based Adaptive Control of Gas Process Plant
title_fullStr U-Model Based Adaptive Control of Gas Process Plant
title_full_unstemmed U-Model Based Adaptive Control of Gas Process Plant
title_sort u-model based adaptive control of gas process plant
publisher Elsevier B.V.
publishDate 2017
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016134376&doi=10.1016%2fj.procs.2017.01.186&partnerID=40&md5=98783976d9f910241a2a769c8a782c81
http://eprints.utp.edu.my/20276/
_version_ 1741196345824247808
score 11.62408

Similar Items