Premium
Active fault detection based on set‐membership approach for uncertain discrete‐time systems
Author(s) -
Wang Jing,
Shi Yuru,
Zhou Meng,
Wang Ye,
Puig Vicenç
Publication year - 2020
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.5036
Subject(s) - fault detection and isolation , observer (physics) , control theory (sociology) , computer science , quadratic programming , bounded function , fault (geology) , quadratic equation , discrete time and continuous time , process (computing) , set (abstract data type) , interval (graph theory) , algorithm , mathematical optimization , mathematics , artificial intelligence , control (management) , actuator , programming language , mathematical analysis , statistics , physics , geometry , quantum mechanics , combinatorics , seismology , geology , operating system
Summary Active fault detection facilitates determination of the fault characteristics by injecting proper auxiliary input signals into the system. This article proposes an observer‐based on‐line active fault detection method for discrete‐time systems with bounded uncertainties. First, the output including disturbances, measurement noise and interval uncertainties at each sample time is enclosed in a zonotope. In order to reduce the conservativeness in the fault detection process, a zonotopic observer is designed to estimate the system states allowing to generate the output zonotopes. Then, a proper auxiliary input signal is designed to separate the output zonotopes of the faulty model from the healthy model that is injected into the system to facilitate the detection of small fault . Since the auxiliary input signal generation leads to a nonconvex optimization problem, it is transformed into a mixed integer quadratic programming problem. Finally, a case study based on a DC motor is used to show the effectiveness of the proposed method.