Optimization-Based Design of Bounded-Error Estimators Robust to Missing Data

Kwesi J. Rutledge, Sze Zheng Yong, Necmiye Ozay

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


Non-asymptotic bounded-error state estimators that provide hard bounds on the estimation error are crucial for safety-critical applications. This paper proposes a class of optimal bounded-error affine estimators to achieve a novel property we are calling Equalized Recovery that can be computed by leveraging ideas from the dual problem of affine finite horizon optimal control design. In particular, by using Q-parametrization, the estimator design problem is reduced to a convex optimization problem. An extension of this estimator to handle missing data (e.g., due to package drops or sensor glitches) is also proposed. These ideas are illustrated with a numerical example motivated by vehicle safety systems.

Original languageEnglish (US)
Pages (from-to)157-162
Number of pages6
Journal6th IFAC Conference on Analysis and Design of Hybrid Systems ADHS 2018: Oxford, United Kingdom, 11—13 July 2018
Issue number16
StatePublished - Jan 1 2018


  • Robust estimators
  • bounded-error estimation
  • missing data

ASJC Scopus subject areas

  • Control and Systems Engineering


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