Open AccessSampled‐data control of fuzzy systems based on the intelligent digital redesign method via an improved fuzzy Lyapunov functional approach
Author(s) -
Kim Han Sol,
Park Jin Bae,
Joo Young Hoon
Publication year - 2018
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.2017.0341
Subject(s) - control theory (sociology) , fuzzy control system , fuzzy logic , linear matrix inequality , trajectory , matching (statistics) , lyapunov function , state (computer science) , mathematics , computer science , control system , control (management) , artificial intelligence , mathematical optimization , algorithm , nonlinear system , engineering , statistics , astronomy , physics , quantum mechanics , electrical engineering
This study presents a linear matrix inequality (LMI) approach to the sampled‐data control of Takagi–Sugeno fuzzy systems, based on the intelligent digital redesign (IDR) technique. The objective of the IDR is to design a digital control system whose trajectory closely matches that of a given well‐constructed analogue control system by minimising the state‐matching error. In this study, state‐matching performance is enhanced by using a continuous‐time state‐matching criterion, which guarantees that the state‐matching error is minimised through the entire time interval. Unlike previous studies, mismatched information of membership functions for both analogue and digital control systems is directly manipulated. Moreover, the authors introduce an improved fuzzy Lyapunov functional that consists of both membership functions for analogue and digital control systems, which relaxes the conservativeness of LMI conditions. Finally, two examples demonstrating the effectiveness of the authors' method are provided.