Open AccessFuzzy Reset-Based H ∞ Unknown Input Observer Design for Uncertain Nonlinear Systems With Unmeasurable Premise Variables
Author(s) -
Zeinab Echreshavi,
Mokhtar Shasadeghi,
Mohammad Hasan Asemani,
Saleh Mobayen,
Afef Fekih
Publication year - 2021
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2021.3125952
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
This paper proposes an $H_{\infty }$ reset unknown input observer (R-UIO) based on the Takagi-Sugeno (T-S) fuzzy model for the state estimation of nonlinear uncertain systems. Firstly, $H_{\infty }$ unknown input observer (UIO) is designed for TSFM-based nonlinear systems with measurable and unmeasurable premise variables. Then, according to the importance of observers based on unmeasurable premise variables, the results on UIO is modified to propose R-UIO. The sufficient conditions for the stabilization of the estimation error are derived in terms of linear matrix inequalities (LMIs). The proposed R-UIO benefits from less computation complexity to find the feasible parameters, improvement of the estimation process in viewpoints of convergence speed and overshoot. To verify the effectiveness of the recommended approaches, the methods are applied to a practical system.