Zonotoptic Fault Estimation for Discrete-Time LPV Systems with Bounded Parametric Uncertainty

Meng Zhou, Zhengcai Cao, Mengchu Zhou, Jing Wang, Zhenhua Wang

Research output: Contribution to journalArticlepeer-review

49 Scopus citations


This paper presents a novel interval fault estimation approach by using zonotope technique for discrete-Time linear parameter-varying systems in the presence of bounded parametric uncertainties, measured perturbation, and system disturbance. First, an augmented descriptor system is generated by using augmentation technique. Thus, the problem of interval fault estimation is transformed into the interval augmented state estimation. Then, an outer approximation of the new augmented state estimation domain is computed by using zonotope method. A zonotope should be consistent with the given outputs, perturbation, disturbance, and parametric uncertainties. Besides, it is minimized at each sampled time via an analytic formulation. Finally, a vehicle lateral dynamic nonlinear model is utilized to show the feasibility and effectiveness of the proposed zonotopic fault estimation technique.

Original languageEnglish (US)
Article number8667901
Pages (from-to)690-700
Number of pages11
JournalIEEE Transactions on Intelligent Transportation Systems
Issue number2
StatePublished - Feb 2020

All Science Journal Classification (ASJC) codes

  • Automotive Engineering
  • Mechanical Engineering
  • Computer Science Applications


  • Interval fault estimation
  • descriptor method
  • discrete-Time LPV systems
  • parametric uncertainty
  • zonotope


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