SUMMARY The main contribution of this paper is the design of a polytopic Unknown Input Proportional Integral Observer (UIPIO) for Linear Varying Parameter (LPV) descriptor systems. This observer is used for actuator Fault Detection and Isolation (FDI). The proposed method is based on the representation of LPV descriptor systems in polytopic form where its parameters evolve in a hypercube domain. The designed polytopic UIPIO is also able to estimate the states and the unknown inputs of the LPV descriptor system. Stability conditions of such observer are expressed in terms of Linear Matrix Inequalities (LMI). An example illustrates the performances of such polytopic UIPIO for multiple actuator faults estimation in spite of disturbances. Copyright c 2011 John Wiley & Sons, Ltd.

https://hal.archives-ouvertes.fr/hal-00605382/document

Fault detection and isolation in linear parameter-varying descriptor systems via proportional integral observer

Advanced model-based FDIR techniques for aerospace systems: Today challenges and opportunities

This paper presents an Adaptive Polytopic Observer (APO) design in order to develop an actuator fault estimation method dedicated to polytopic Linear Parameter Varying (LPV) descriptor systems. This paper extends a fault diagnosis method developed for regular LTI systems to polytopic LPV descriptor systems. Here, time-varying actuator faults are also considered, whereas in many papers, actuator faults are generally assumed to be constant. The design and convergence conditions of this APO are provided. The design is formulated through LMI techniques under equality constraints. The performances of the proposed actuator fault estimation scheme are illustrated using an electrical circuit.

/pdf/actuator-fault-estimation-based-adaptive-polytopic-observer-1bz4sestxs.pdf

Actuator fault estimation based adaptive polytopic observer for a class of LPV descriptor systems

Fault Detection and Isolation in Nonlinear Systems

SUMMARY

This paper presents a robust fault detection and isolation scheme using a sliding mode observer based on a linear parameter varying system, with fault reconstruction capability Both actuator and sensor fault reconstruction schemes are considered that possess robustness against a certain class of uncertainty and corrupted measurements For actuator fault reconstruction, the input distribution matrix (associated with the actuators being monitored) is factorized into fixed and varying components LMIs are used to design the key observer parameters in order to minimize the effect of uncertainty and measurement corruption on the fault reconstruction signal The faults are reconstructed using the output error injection signal associated with the nonlinear term of the sliding mode observer For sensor fault reconstruction, the idea is to reformulate the problem into an actuator fault reconstruction scenario so that the same design procedure can be applied This is achieved by augmenting the original system with the filtered sensors being monitored Simulations using a full nonlinear model of a large transport aircraft are presented and show good fault reconstruction performance Copyright © 2013 John Wiley & Sons, Ltd

/pdf/robust-fault-reconstruction-for-linear-parameter-varying-2v5bmobfy2.pdf

Robust fault reconstruction for linear parameter varying systems using sliding mode observers

The work presented in this paper focuses on the design of robust Fault Detection and Isolation (FDI) filters for dynamic systems characterized by LPV (Linear Parameter Varying) polytopic models. A sufficient condition is established to guarantee sensitivity performance of the residual signal vector to faults. Robustness constraints against model perturbations and disturbances are also taken into account in the design method. A key feature of the proposed method is that the residual structuring matrices are optimized as an integral part of the design, together with the dynamic part (i.e. the filter). The design problem is formulated as a convex optimization problem and solved using LMI (Linear Matrix Inequalities) techniques. The proposed method is illustrated on the secondary circuit of a Nuclear Power Plant.

/pdf/a-method-for-designing-fault-diagnosis-filters-for-lpv-3zwqg3y4a9.pdf

A method for designing fault diagnosis filters for LPV polytopic systems

Fault diagnosis in linear parameter varying systems

A method for designing FDI filters for polytopic LPV models

:
The aim of this communication is to introduce a methodology to solve the FDI (Fault Detection and Isolation) problem in Linear Parameter Varying (LPV) systems. The design problem is formulated within the LPV polytopic modelling framework. A sufficient condition is established for guaranteeing robust fault sensitivity performance level. It is then shown that the problem can be formulated and solved using a reasonable number of LMIs. The overall method is applied to an experimental data set, measured from the secondary circuit of a French nuclear power plant.

Sylvain Grenaille

Papers

A method for designing fault diagnosis filters for LPV polytopic systems

Fault diagnosis in linear parameter varying systems

A method for designing FDI filters for polytopic LPV models

A Method for Designing FDI Filters for Polytopic LPV Models