Open AccessLMI‐based reset unknown input observer for state estimation of linear uncertain systems
Author(s) -
Hosseini Iman,
Khayatian Alireza,
Karimaghaee Paknoush,
Fiacchini Mirko,
Davo Navarro Miguel Angel
Publication year - 2019
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.2018.5777
Subject(s) - control theory (sociology) , reset (finance) , observer (physics) , linear matrix inequality , mathematics , settling time , linear system , lti system theory , convergence (economics) , computer science , stability (learning theory) , norm (philosophy) , mathematical optimization , control (management) , control engineering , engineering , step response , mathematical analysis , physics , quantum mechanics , artificial intelligence , machine learning , law , financial economics , political science , economics , economic growth
This study proposes a novel kind of unknown input observer (UIO) called reset unknown input observer (R‐UIO) for state estimation of linear time invariant (LTI) systems in the presence of disturbance using linear matrix inequality techniques. In R‐UIO, the states of the observer are reset to the after‐reset value based on an appropriate reset law in order to decrease the L 2 norm and settling time of estimation error. It is shown that the application of reset theory to the UIOs in the LTI systems can significantly improve the transient response of the observer. Moreover, the devised approach can be applied to both SISO and MIMO systems. Furthermore, the stability and convergence analysis of the devised R‐UIO is addressed. Finally, the efficiency of the proposed method is demonstrated by simulation results.