Real-time Fault Estimation for a Class of Discrete-Time Linear Parameter-Varying Systems

Chris van der Ploeg, Emilia Silvas, Nathan van de Wouw, Peyman Mohajerin Esfahani

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Estimating and detecting faults is crucial in ensuring safe and efficient automated systems. In the presence of disturbances, noise, or varying system dynamics, such estimation is even more challenging. To address this challenge, this letter proposes a novel filter to estimate multiple fault signals for a class of discrete-time linear parameter-varying (LPV) systems. The design of such a filter is formulated as an optimization problem and is solved recursively, while the system dynamics may vary over time. Conditions for the existence and detectability of the fault are introduced and the problem is formulated and solved using the quadratic programming framework. We further propose an approximate scheme that can be arbitrarily precise while it enjoys an analytical solution, which supports real-time implementation. The method is illustrated and validated on an automated vehicle's lateral dynamics, which is a practically relevant example for LPV systems. The results show that the estimation filter can decouple unknown disturbances and known or measurable parameter variations in the dynamics while estimating the unknown fault.

Original languageEnglish
Pages (from-to)1988-1993
JournalIEEE Control Systems Letters
Publication statusPublished - 2022

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • Estimation
  • Fault detection
  • Fault diagnosis
  • fault estimation
  • linear parameter-varying systems.
  • Mathematical models
  • Q measurement
  • Real-time systems
  • Time-varying systems
  • Vehicle dynamics


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