Sensor fault diagnosis of singular delayed LPV systems with inexact parameters: an uncertain system approach

In this paper, sensor fault diagnosis of a singular delayed linear parameter varying (LPV) system is considered. In the considered system, the model matrices are dependent on some parameters which are real-time measurable. The case of inexact parameter measurements is considered which is close to re...

Descripción completa

Detalles Bibliográficos
Autores: Hassanabadi, Amir Hossein, Shafiee, Masoud, Puig Cayuela, Vicenç|||0000-0002-6364-6429
Tipo de recurso: artículo
Fecha de publicación:2017
País:España
Institución:Universitat Politècnica de Catalunya (UPC)
Repositorio:UPCommons. Portal del coneixement obert de la UPC
Idioma:inglés
OAI Identifier:oai:upcommons.upc.edu:2117/130897
Acceso en línea:https://hdl.handle.net/2117/130897
https://dx.doi.org/10.1080/00207721.2017.1390700
Access Level:acceso abierto
Palabra clave:Detectors
System failures (Engineering)
fault diagnosis
inexact parameters
Singular delayed LPV system
uncertain system approach
unknown input observer (UIO)
Errors de sistemes (Enginyeria)
Àrees temàtiques de la UPC::Informàtica::Automàtica i control
Descripción
Sumario:In this paper, sensor fault diagnosis of a singular delayed linear parameter varying (LPV) system is considered. In the considered system, the model matrices are dependent on some parameters which are real-time measurable. The case of inexact parameter measurements is considered which is close to real situations. Fault diagnosis in this system is achieved via fault estimation. For this purpose, an augmented system is created by including sensor faults as additional system states. Then, an unknown input observer (UIO) is designed which estimates both the system states and the faults in the presence of measurement noise, disturbances and uncertainty induced by inexact measured parameters. Error dynamics and the original system constitute an uncertain system due to inconsistencies between real and measured values of the parameters. Then, the robust estimation of the system states and the faults are achieved with H8 performance and formulated with a set of linear matrix inequalities (LMIs). The designed UIO is also applicable for fault diagnosis of singular delayed LPV systems with unmeasurable scheduling variables. The efficiency of the proposed approach is illustrated with an example.