Robust sensor fault detection and isolation of an anerarobic bioreactor modeled as a descriptor-LPV system

Abstract

This work is dedicated to the design of a robust fault detection system for an anaerobic bioreactor modeled as a Descriptor Linear Parameter Varying system (D-LPV) system with unmeasurable gain scheduling functionss. The main goals are: first, an accurate D-LPV representation of the nonlinear model is obtained by considering the sector nonlinearity modeling approach. Second, a LPV observer is designed to estimate the bioprocess states variables. The observer considers the gains scheduling functions depending on estimated states due to the lack of a biomass mass sensor. Third, in oder to perform fault detection and isolation, by mean of residual generation, a bank of observers is designed. For each observer, sufficient conditions to guarantee asymptotic stability and robustness against disturbance are given by a set of feasible Linear Matrix Inequalities (LMIs). Finally, some simulations in fault-free and faulty operations are considered on the bioreactor system.