Robust fault detection for Uncertain Unknown Inputs LPV system

Sébastien Varrier (1) , Damien Koenig (1) , John Jairo Martinez Molina (1)

1 GIPSA-SLR - GIPSA - Systèmes linéaires et robustesse

This paper focuses on robust fault residual generation for Uncertain Unknown Inputs Linear Parameter Varying (U-LPV) systems. Firstly, the problem is addressed in standard LPV systems based on the adaptation of the parity-space approach. The main objective of this approach is to design a scheduled parity matrix according to the scheduling parameters. It results a perfectly decoupled parity matrix face to the system states. Then, the major contribution of this paper relies on the extension to U-LPV systems. Since most of models which represent practical/real systems are subject to parameters variation, unmodeled dynamics and unknown inputs, the approach is clearly justified. The residual synthesis is rewritten in terms of a new optimization problem and solved using Linear Matrix Inequalities (LMIs) techniques. An applicative illustration is proposed and rests on a vehicle lateral dynamic system.

Mots clés: Robust fault detection (FD); Linear parameter varying (LPV); Uncertain unknown inputs system

Domaines: Automatique / Robotique

Sébastien Varrier, Damien Koenig, John Jairo Martinez Molina. Robust fault detection for Uncertain Unknown Inputs LPV system. Control Engineering Practice, 2014, 22, pp.125-134. ⟨10.1016/j.conengprac.2013.10.002⟩. ⟨hal-00994239⟩