U-Model Based Adaptive Control of Gas Process Plant

E. Hasan; Rosdiazli Bin Ibrahim; Syed Saad Azhar Ali; Kishore Bingi; Syed Faizan Gilani

doi:10.1016/j.procs.2017.01.186

U-Model Based Adaptive Control of Gas Process Plant

E. Hasan^*
, Rosdiazli Bin Ibrahim
, Syed Saad Azhar Ali
, Kishore Bingi
, Syed Faizan Gilani

^*Corresponding author for this work

Research output: Contribution to journal › Conference article › peer-review

8 Scopus citations

Abstract

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.

Original language	English
Pages (from-to)	119-124
Number of pages	6
Journal	Procedia Computer Science
Volume	105
DOIs	https://doi.org/10.1016/j.procs.2017.01.186
State	Published - 2016
Externally published	Yes
Event	IEEE International Symposium on Robotics and Intelligent Sensors, IRIS 2016 - Tokyo, Japan Duration: 17 Dec 2016 → 20 Dec 2016

Bibliographical note

Publisher Copyright:
© 2017 The Authors.

Keywords

Adaptive
Gas Process Plant
Industrial Process Control
Newton-Raphson Controller
System Identification
U-Model

ASJC Scopus subject areas

General Computer Science

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.procs.2017.01.186

Cite this

@article{06847a7c7201480390537f22eabaf7cf,

title = "U-Model Based Adaptive Control of Gas Process Plant",

abstract = "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.",

keywords = "Adaptive, Gas Process Plant, Industrial Process Control, Newton-Raphson Controller, System Identification, U-Model",

author = "E. Hasan and Ibrahim, \{Rosdiazli Bin\} and Ali, \{Syed Saad Azhar\} and Kishore Bingi and Gilani, \{Syed Faizan\}",

note = "Publisher Copyright: {\textcopyright} 2017 The Authors.; IEEE International Symposium on Robotics and Intelligent Sensors, IRIS 2016 ; Conference date: 17-12-2016 Through 20-12-2016",

year = "2016",

doi = "10.1016/j.procs.2017.01.186",

language = "English",

volume = "105",

pages = "119--124",

journal = "Procedia Computer Science",

issn = "1877-0509",

publisher = "Elsevier B.V.",

}

TY - JOUR

T1 - U-Model Based Adaptive Control of Gas Process Plant

AU - Hasan, E.

AU - Ibrahim, Rosdiazli Bin

AU - Ali, Syed Saad Azhar

AU - Bingi, Kishore

AU - Gilani, Syed Faizan

PY - 2016

Y1 - 2016

N2 - 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.

AB - 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.

KW - Adaptive

KW - Gas Process Plant

KW - Industrial Process Control

KW - Newton-Raphson Controller

KW - System Identification

KW - U-Model

UR - https://www.scopus.com/pages/publications/85016134376

U2 - 10.1016/j.procs.2017.01.186

DO - 10.1016/j.procs.2017.01.186

M3 - Conference article

AN - SCOPUS:85016134376

SN - 1877-0509

VL - 105

SP - 119

EP - 124

JO - Procedia Computer Science

JF - Procedia Computer Science

T2 - IEEE International Symposium on Robotics and Intelligent Sensors, IRIS 2016

Y2 - 17 December 2016 through 20 December 2016

ER -

U-Model Based Adaptive Control of Gas Process Plant

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

UN SDGs

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Cite this