Abstract
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 language | English (US) |
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Pages (from-to) | 157-162 |
Number of pages | 6 |
Journal | 6th IFAC Conference on Analysis and Design of Hybrid Systems ADHS 2018: Oxford, United Kingdom, 11—13 July 2018 |
Volume | 51 |
Issue number | 16 |
DOIs | |
State | Published - Jan 1 2018 |
Keywords
- Robust estimators
- bounded-error estimation
- missing data
ASJC Scopus subject areas
- Control and Systems Engineering