Distributed state estimation and model predictive control : application to fault tolerant control

Kamel Menighed (1) , Christophe Aubrun (1) , Joseph Julien Yamé (1)

1 CRAN - Centre de Recherche en Automatique de Nancy

In this paper, a distributed and networked control system architecture based on unsupervised and independent Model Predictive Control/Kalman-Filter (MPC/KF) schemes, is proposed. Interconnected subsystems, possibly located at different sites, exchange information via the communication network. For the partial local state measurement, the key component for realistic Distributed Model Control (DMPC) formulation is the state estimations. These state stimations are provided by Kalman filters. In this distributed framework, MPC and KF algorithms may require information from other sub-controllers to achieve their task in a cooperative way. The given distributed and cooperative control system architecture may be suitable for Fault Tolerant Control (FTC) in a network of distributed subsystems. This insight gained the design of such architecture is used to implement FTC under actuator faults.

Mots clés: Sensor Networks and Networked Control; Fault Detection; Complex Systems

Domaines: Automatique

Kamel Menighed, Christophe Aubrun, Joseph Julien Yamé. Distributed state estimation and model predictive control : application to fault tolerant control. 7th IEEE International Conference on Control and Automation, ICCA 2009, Dec 2009, Chrischurch, New Zealand. pp.936-941, ⟨10.1109/ICCA.2009.5410390⟩. ⟨hal-00456251⟩