Diagnosis of Poor Control Loop Performance: Development of a Model Based Compensation Algorithm for Control Valve Stiction Nonlinearity

The objective of this paper is to develop a model based compensation algorithm using optimization approach of MIQP based MPC backlash compensator for control valve stiction nonlinearity. Optimization approach stiction compensation is very less focused and studied in the recent literatures. H. Zabiri...

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Main Author: N. Narayanasamy, Anand
Format: Final Year Project
Language: English
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-utpedia.17792 /
Published: IRC 2016
Subjects:
TP Chemical technology
Online Access: http://utpedia.utp.edu.my/17792/1/ANAND%2016213%20Harbound%20Final%20Print.pdf
http://utpedia.utp.edu.my/17792/
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spelling utp-utpedia.177922017-11-23T09:44:35Z http://utpedia.utp.edu.my/17792/ Diagnosis of Poor Control Loop Performance: Development of a Model Based Compensation Algorithm for Control Valve Stiction Nonlinearity N. Narayanasamy, Anand TP Chemical technology The objective of this paper is to develop a model based compensation algorithm using optimization approach of MIQP based MPC backlash compensator for control valve stiction nonlinearity. Optimization approach stiction compensation is very less focused and studied in the recent literatures. H. Zabiri et al proposed Mixed Integer Quadratic Programming (MIQP) based Model Predictive Controller (MPC) that uses optimization approach compensation for backlash nonlinearities in control loop. Stiction compensation is the main scope of study specifically model based compensation using optimization approach. IRC 2016-01 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/17792/1/ANAND%2016213%20Harbound%20Final%20Print.pdf N. Narayanasamy, Anand (2016) Diagnosis of Poor Control Loop Performance: Development of a Model Based Compensation Algorithm for Control Valve Stiction Nonlinearity. IRC, Universiti Teknologi PETRONAS.
institution Universiti Teknologi Petronas
collection UTPedia
language English
topic TP Chemical technology
spellingShingle TP Chemical technology
N. Narayanasamy, Anand
Diagnosis of Poor Control Loop Performance: Development of a Model Based Compensation Algorithm for Control Valve Stiction Nonlinearity
description The objective of this paper is to develop a model based compensation algorithm using optimization approach of MIQP based MPC backlash compensator for control valve stiction nonlinearity. Optimization approach stiction compensation is very less focused and studied in the recent literatures. H. Zabiri et al proposed Mixed Integer Quadratic Programming (MIQP) based Model Predictive Controller (MPC) that uses optimization approach compensation for backlash nonlinearities in control loop. Stiction compensation is the main scope of study specifically model based compensation using optimization approach.
format Final Year Project
author N. Narayanasamy, Anand
author_sort N. Narayanasamy, Anand
title Diagnosis of Poor Control Loop Performance: Development of a Model Based Compensation Algorithm for Control Valve Stiction Nonlinearity
title_short Diagnosis of Poor Control Loop Performance: Development of a Model Based Compensation Algorithm for Control Valve Stiction Nonlinearity
title_full Diagnosis of Poor Control Loop Performance: Development of a Model Based Compensation Algorithm for Control Valve Stiction Nonlinearity
title_fullStr Diagnosis of Poor Control Loop Performance: Development of a Model Based Compensation Algorithm for Control Valve Stiction Nonlinearity
title_full_unstemmed Diagnosis of Poor Control Loop Performance: Development of a Model Based Compensation Algorithm for Control Valve Stiction Nonlinearity
title_sort diagnosis of poor control loop performance: development of a model based compensation algorithm for control valve stiction nonlinearity
publisher IRC
publishDate 2016
url http://utpedia.utp.edu.my/17792/1/ANAND%2016213%20Harbound%20Final%20Print.pdf
http://utpedia.utp.edu.my/17792/
_version_ 1741195248573349888
score 11.62408

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