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

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 t...

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Bibliographic Details
Published in2009 IEEE International Conference on Control and Automation pp. 936 - 941
Main Authors Menighed, K., Aubrun, C., Yame, J.-J.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.12.2009
Subjects
Communication networks
Communication system control
Control systems
Distributed control
Fault tolerance
Fault tolerant systems
Networked control systems
Predictive control
Predictive models
State estimation
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Summary: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 estimations 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.
ISBN:1424447062
9781424447060
ISSN:1948-3449
1948-3457
DOI:10.1109/ICCA.2009.5410390