Open AccessIntelligent digital redesign for non‐linear systems: observer‐based sampled‐data fuzzy control approach
Author(s) -
Bum Koo Geun,
Bae Park Jin,
Hoon Joo Young
Publication year - 2016
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.2015.0244
Subject(s) - control theory (sociology) , fuzzy control system , fuzzy logic , observer (physics) , linear matrix inequality , computer science , controller (irrigation) , matching (statistics) , stability (learning theory) , state (computer science) , mathematics , control engineering , mathematical optimization , control (management) , artificial intelligence , algorithm , engineering , machine learning , statistics , physics , quantum mechanics , agronomy , biology
In this study, an intelligent digital redesign (IDR) technique is proposed for an observer‐based sampled‐data fuzzy controller of non‐linear systems. By using a Takagi–Sugeno fuzzy model, the pre‐designed analog and sampled‐data fuzzy controllers are supposed, and these discretised closed‐loop systems are obtained, respectively. Based on the IDR problem, the authors guarantee both stability and state‐matching conditions. Unlike the previous techniques, the proposed IDR not only improves the state‐matching performance using the state‐matching error cost function, but is also derived in the strict linear matrix inequality format. In a numerical example, the effectiveness of the proposed technique and the results of the improved performance are shown.