Set-valued observer-based active fault-tolerant model predictive control

This paper proposes an integrated actuator and sensor active fault-tolerant model predictive control scheme. In this scheme, fault detection is implemented by using a set-valued observer, fault isolation (FI) is performed by set manipulations, and fault-tolerant control is carried out through the de...

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Detalles Bibliográficos
Autores: Xu, Feng, Puig Cayuela, Vicenç|||0000-0002-6364-6429, Ocampo-Martínez, Carlos|||0000-0001-9251-6044, Wang, Xueqian
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:2117/108308
Acceso en línea:https://hdl.handle.net/2117/108308
https://dx.doi.org/10.1002/oca.2284
Access Level:acceso abierto
Palabra clave:Fault tolerance (Engineering)
actuator and sensor faults
fault detection and isolation
fault-tolerant control
model predictive control
set-valued observer
Anàlisi de fallades (Enginyeria)
Àrees temàtiques de la UPC::Informàtica
Descripción
Sumario:This paper proposes an integrated actuator and sensor active fault-tolerant model predictive control scheme. In this scheme, fault detection is implemented by using a set-valued observer, fault isolation (FI) is performed by set manipulations, and fault-tolerant control is carried out through the design of a robust model predictive control law. In this paper, a set-valued observer is used to passively complete the fault detection task, while FI is actively performed by making use of the constraint-handling capability of robust model predictive control. The set-valued observer is chosen to implement fault detection and isolation (FDI) because of its simple mathematical structure that is not affected by the type of faults such as sensor, actuator, and system-structural faults. This means that only one set-valued observer is needed to monitor all considered actuator and sensor statuses (health and fault) and to carry out the fault detection and isolation task instead of using a bank of observers (each observer matching a health/fault status). Furthermore, in the proposed scheme, the advantage of robust model predictive control is that it can effectively deal with system constraints, disturbances, and noises and allow to implement an active FI strategy, which can improve FI sensitivity when compared with the passive FI methods. Finally, a case study based on the well-known two-tank system is used to illustrate the effectiveness of the proposed fault-tolerant model predictive control scheme.