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Finite‐gain ℒ 1 event‐triggered interval observers design for continuous‐time linear systems
Author(s) -
Rabehi Djahid,
Meslem Nacim,
Ramdani Nacim
Publication year - 2021
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.5463
Subject(s) - aperiodic graph , control theory (sociology) , bounded function , interval (graph theory) , a priori and a posteriori , computer science , stability (learning theory) , sampling (signal processing) , linear system , state (computer science) , upper and lower bounds , mathematics , algorithm , filter (signal processing) , control (management) , mathematical analysis , philosophy , epistemology , combinatorics , artificial intelligence , machine learning , computer vision
This work introduces a new approach based on an event‐triggered mechanism (ETM) to design finite‐gainℒ 1interval observers for linear continuous‐time systems in the presence of unknown‐but‐bounded uncertainties with a priori known bounds on state disturbances and measurement noises. In this setting, aperiodic measurements sampling is controlled in a way to reduce online communication between the sensors and the estimation algorithm. The proposed ETM relies on a dynamic condition that depends on the width of the feasible domain of the system's uncertainties and the width of the estimated state enclosures. Moreover, the proposed approach guarantees the existence of a positive lower bound on the interevent times, which avoids the Zeno phenomenon. On the other hand, although the sensors data are used in an irregular sampling way, theℒ 1‐stability performance of the estimation error is satisfied. Finally, simulation results are given to illustrate the effectiveness of the proposed method.