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Erschienen in:
Fault Diagnosis Based on Controller Modification Kapitel lesen Erstes Kapitel lesen

2016 | OriginalPaper | Buchkapitel

MPC Framework for System Reliability Optimization

verfasst von : Jean C. Salazar, Philippe Weber, Fatiha Nejjari, Didier Theilliol, Ramon Sarrate

Erschienen in: Advanced and Intelligent Computations in Diagnosis and Control

Verlag: Springer International Publishing

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Abstract

This work presents a general framework taking into account system and components reliability in a Model Predictive Control (MPC) algorithm. The objective is to deal with a closed-loop system combining a deterministic part related to the system dynamics and a stochastic part related to the system reliability from an availability point of view. The main contribution of this work consists in integrating the reliability assessment computed on-line using a Dynamic Bayesian Network (DBN) through the weights of the multiobjective cost function of the MPC algorithm. A comparison between a method based on the components reliability (local approach) and a method focused on the system reliability sensitivity analysis (global approach) is considered. The effectiveness and benefits of the proposed control framework are presented through a Drinking Water Network (DWN) simulation.

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Vorheriges Kapitel Decentralized Scheduling of Sensor Networks for Parameter Estimation of Spatio-Temporal Processes
Nächstes Kapitel Towards Robust Predictive Control for Non-linear Discrete Time System
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Metadaten
Titel
MPC Framework for System Reliability Optimization
verfasst von
Jean C. Salazar
Philippe Weber
Fatiha Nejjari
Didier Theilliol
Ramon Sarrate
Copyright-Jahr
2016
Buch
Advanced and Intelligent Computations in Diagnosis and Control

Print ISBN: 978-3-319-23179-2

Electronic ISBN: 978-3-319-23180-8

Copyright-Jahr: 2016

DOI
https://doi.org/10.1007/978-3-319-23180-8_12