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Fault Diagnosis Based on Controller Modification Read chapter Read first chapter

2016 | OriginalPaper | Chapter

MPC Framework for System Reliability Optimization

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

Published in: Advanced and Intelligent Computations in Diagnosis and Control

Publisher: 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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previous chapter Decentralized Scheduling of Sensor Networks for Parameter Estimation of Spatio-Temporal Processes
next chapter Towards Robust Predictive Control for Non-linear Discrete Time System
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Metadata
Title
MPC Framework for System Reliability Optimization
Authors
Jean C. Salazar
Philippe Weber
Fatiha Nejjari
Didier Theilliol
Ramon Sarrate
Copyright Year
2016
Book
Advanced and Intelligent Computations in Diagnosis and Control

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

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

Copyright Year: 2016

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

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