Fault tolerant fuzzy-based model predictive controllers for automotive application

In this paper, a Fuzzy-based Model Predictive Control (FMPC) for a class of nonlinear systems subject to faults and uncertainties is proposed. Our contribution comes from the combination of Parallel Distributed Compensation (PDC) and Model Predictive Control (MPC) for nonlinear systems described by...

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Bibliographic Details
Published in2016 International Conference on Control, Decision and Information Technologies (CoDIT) pp. 117 - 122
Main Authors Ben Hamouda, Lamia, Ayadi, Mounir, Langlois, Nicolas
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2016
Subjects
Actuators
CPS
Fault tolerance
Fault tolerant systems
FTC
LMI
MPC
Observers
Predictive models
Stability criteria
Takagi-Sugeno models
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Summary:In this paper, a Fuzzy-based Model Predictive Control (FMPC) for a class of nonlinear systems subject to faults and uncertainties is proposed. Our contribution comes from the combination of Parallel Distributed Compensation (PDC) and Model Predictive Control (MPC) for nonlinear systems described by Takagi-Sugeno (T-S) fuzzy model. The objective is to design a stable, robust and efficient Fault Tolerant Controller (FTC). The validity of the proposed FTC strategy and its application to faults tolerance is illustrated through an application to a given automotive Cyber-Physical System (CPS).
DOI:10.1109/CoDIT.2016.7593546