English   español  
Por favor, use este identificador para citar o enlazar a este item: http://hdl.handle.net/10261/167163
COMPARTIR / IMPACTO:
Estadísticas
logo share SHARE logo core CORE   Add this article to your Mendeley library MendeleyBASE

Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL
Exportar a otros formatos:
Título

Set-membership approach and Kalman observer based on zonotopes for discrete-time descriptor systems

AutorWang, Ye; Puig, Vicenç; Cembrano, Gabriela
Palabras claveDiscrete-time descriptor systems
Set-membership approach
Kalman observer
Zonotopes
Unknown inputs
Fecha de publicación2018
EditorElsevier
CitaciónAutomatica 93: 435-443 (2018)
ResumenThis paper proposes a set-membership state estimator and a zonotopic Kalman observer for discrete-time descriptor systems. Both approaches are developed in a set-based context considering system disturbances, measurement noise, and unknown inputs. This set-membership state estimation approach determines the set of consistent states with the model and measurements by constructing a parameterized intersection zonotope. Two methods to minimize the size of this intersection zonotope are provided: one inspired by Kalman filtering and the other based on solving an optimization problem involving a series of linear matrix inequalities. Additionally, we propose a zonotopic Kalman observer for discrete-time descriptor systems. Moreover, the relationship between both approaches is discussed. In particular, it is proved that the zonotopic Kalman observer in the current estimation type is equivalent to the set-membership approach. Finally, a numerical example is used to illustrate and compare the effectiveness of the proposed approaches.
Versión del editorhttps://doi.org/10.1016/j.automatica.2018.03.082
URIhttp://hdl.handle.net/10261/167163
Identificadoresdoi: 10.1016/j.automatica.2018.03.082
issn: 0005-1098
Aparece en las colecciones: (IRII) Artículos
Ficheros en este ítem:
Fichero Descripción Tamaño Formato  
Set-Kalman.pdf1,31 MBAdobe PDFVista previa
Visualizar/Abrir
Mostrar el registro completo
 


NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.