Open AccessRobust model predictive control of uncertain fractional systems: a thermal application
Author(s) -
Rhouma Aymen,
Bouani Faouzi
Publication year - 2014
Publication title -
iet control theory and applications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.059
H-Index - 108
eISSN - 1751-8652
pISSN - 1751-8644
DOI - 10.1049/iet-cta.2014.0703
Subject(s) - control theory (sociology) , model predictive control , representation (politics) , internal model , mathematics , operator (biology) , controller (irrigation) , robust control , fractional calculus , integer (computer science) , computer science , mathematical optimization , control (management) , control system , engineering , artificial intelligence , law , repressor , chemistry , biology , biochemistry , political science , transcription factor , agronomy , politics , electrical engineering , gene , programming language
In this study, a robust model predictive control of fractional‐order systems with real uncertain parameters is presented. The Grünwald–Letnikov's method is used as an internal model to predict the plant future dynamic behaviour. This method consists in replacing the non‐integer derivation operator of the adopted system representation by a discrete approximation. Therefore a robust fractional model predictive control is developed based on an uncertain fractional model. Moreover, the output deviation approach is adopted to design the j ‐step ahead output predictor, and the corresponding control law is obtained by the resolution of a min–max optimisation problem that takes into account the uncertainties of the fractional‐order model parameters and under input constraints. The efficiency and the performances of the proposed predictive controller are illustrated with practical results of a thermal system.