Active fault isolation of nonlinear process systems

Design of a Robust Observer with Super-Twisting Algorithm for Simultaneous Concentration Estimation and Faults Reconstruction in a CSTR

This paper deals with the problem of simultaneous concentration and faults estimations of a continuous stirred tank reactor (CSTR) subject to unknown inputs. We propose a combination of two robust nonlinear observers for state estimation and fault reconstruction without any use of a linear approximation of the CSTR dynamic model. Based on the high-gain observer, the proposed scheme can guarantee the asymptotic estimation of the concentration inside the reactor, while, a robust term is added to the nominal plant on the basis of the super-twisting algorithm for fault reconstruction. The stability analysis is proved mathematically using the Lyapunov theory. The effectiveness and robustness of the proposed scheme are illustrated via simulations.

Fuzzy model-based observers for fault detection in CSTR

Under the vast variety of fuzzy model-based observers reported in the literature, what would be the properone to be used for fault detection in a class of chemical reactor? In this study four fuzzy model-based observers for sensor fault detection of a Continuous Stirred Tank Reactor were designed and compared. The designs include (i) a Luenberger fuzzy observer, (ii) a Luenberger fuzzy observer with sliding modes, (iii) a Walcott-Zak fuzzy observer, and (iv) an Utkin fuzzy observer. A negative, an oscillating fault signal, and a bounded random noise signal with a maximum value of ±0.4 were used to evaluate and compare the performance of the fuzzy observers. The Utkin fuzzy observer showed the best performance under the tested conditions.