This paper deals with subspace method aided data-driven design of robust fault detection and isolation systems. The basic idea is to identify a primary form of residual generators directly from test data and then make use of performance indices to make uniform the design of different type robust residuals. Four algorithms are proposed to design fault detection, isolation and identification resi...

In this study the Fuzzy Robust Principal Component Analysis (FRPCA) method is used to monitor a biological nitrogen removal process, performances of this method are then compared with classical principal component analysis. The obtained results demonstrate the performances superiority of this robust extension compared with the conventional one. In this method fuzzy variant of PCA uses fuzzy mem...

The main goal when synthesizing robust residual generators, for diagnosis and supervision, is to attenuate influence from model uncertainty on the residual while keeping fault detection performance. In this paper, a design algorithm for robust residual generators is developed with two key elements. One is the use of a reference model that represents desired performance, i.e. time or frequency-d...

This paper proposes a robust fault detection observer based on zonotopes for discrete-time uncertain systems with sensor faults and unknown but bounded uncertainties. The main advantage of this method is that the observer gain of the robust zonotopic observer is designed to be robust against bounded uncertainties while being sensitive to faults. In order to detect sensor faults with low magnitu...

Abstract: This paper presents a novel technique for robust fault detection, based on a modified H2/H∞ performance condition, which is described as LMI. Some theoretical results are shown in order to synthesize the residual generation scheme, for systems subjected to parametric uncertainty. The uncertainty parameters are supposed to belong to a polytope. The extended H2/H∞ conditions are obtaine...

Geometric fault detection and isolation filters are known for having excellent fault isolation, fault reconstruction and sensitivity properties under small modeling uncertainty and noise. However they are assumed to be sensitive to model uncertainty and noise. This paper proposes a method to incorporate model uncertainty into the design. First, a geometric filter is designed on the nominal plan...

This paper addresses the optimum design of fault detection systems based on sensor location. A multi-objective optimization problem based on optimal sensor location for fault detection is formulated for linear time invariant system. Measurement outputs are formed by selecting m variables of N available process measurements that ensures a high fault detetion performance. A minimum total measurem...

This paper considers the problem of attitude sensor fault diagnosis in a quadrotor helicopter. The proposed approach is composed of two stages. The first one is the modelling of the system attitude dynamics taking into account the induced communication constraints. Then a robust fault detection and evaluation scheme is proposed using a post-filter designed under a particular design objective. T...

An integrated fault diagnosis based fault tolerant longitudinal control system architecture is proposed for civil aircraft which can accommodate partial or total losses of angle of attack and/or calibrated airspeed sensors. A triplex sensor redundancy is assumed for the normal operation of the aircraft using a gain scheduled longitudinal normal control law. The fault isolation functionality is ...

Fault detection and diagnosis techniques that are essential for defect tolerance, fault tolerance and self-repair of molecular computing systems are discussed. These techniques enable robust molecular computing system design protected from manufacturing defects and run-time errors in the underlying hardware.