Open AccessIdentification and Control of Non-Linear System Using Model Predictive controller
Author(s) -
S Suriyakala,
T Hariharasudhan,
D Prince Winston
Publication year - 2022
Publication title -
ymer
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.103
H-Index - 5
ISSN - 0044-0477
DOI - 10.37896/ymer21.03/19
Subject(s) - control theory (sociology) , model predictive control , controller (irrigation) , matlab , system identification , process (computing) , temperature control , identification (biology) , flow (mathematics) , control engineering , computer science , linear model , engineering , control (management) , mathematics , data modeling , botany , geometry , database , artificial intelligence , agronomy , biology , operating system , machine learning
The modeling of level and temperature process is the most common problems in the process industry. In this paper system identification is performed for a hybrid tank system. Hybrid tank is an example for highly non-linear system. This system has two inputs heater current and flow and the outputs are level and temperature. The Main aim of this paper is to maintain level and temperature at a desired value. Input flow is measured using turbine flow meter. The output temperature is measured using RTD. The level is measured using differential pressure transmitter (DPT). The simulation is performed in MATLAB environment using system identification algorithm. Model Predictive controller is implemented for this identified model.