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Sensor Fault Diagnosis Based on a H ∞ Sliding Mode and Unknown Input Observer for Takagi‐Sugeno Systems with Uncertain Premise Variables
Author(s) -
GómezPeñate Samuel,
ValenciaPalomo Guillermo,
LópezEstrada FranciscoRonay,
AstorgaZaragoza CarlosManuel,
OsornioRios Roque A.,
SantosRuiz Ildeberto
Publication year - 2019
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.1913
Subject(s) - control theory (sociology) , observer (physics) , premise , lyapunov function , nonlinear system , fault detection and isolation , mathematics , quadratic equation , convergence (economics) , robustness (evolution) , computer science , artificial intelligence , control (management) , linguistics , philosophy , physics , geometry , biochemistry , chemistry , quantum mechanics , economics , gene , economic growth
This paper presents the design of a H ∞ sliding mode and an unknown input observer for Takagi‐Sugeno (TS) systems. Contrary to the common approaches reported in the literature, which considers exact premise variables, this work deals with the problem of inexact measurements of the premise variables. The proposed method is based on a H ∞ criteria to be robust to disturbances, sensor noise and uncertainty on the premise variables. The observer convergence and stability are established by considering a quadratic Lyapunov function, which relies on a set of Linear Matrix Inequalities. Then, a dedicated observer scheme is considered to detect and isolate sensor faults. Finally, the performance and applicability of the proposed approach are illustrated through numerical experiments on a nonlinear model that represents the lateral dynamics of an electric vehicle.