Journal article
A linear, robust and convergent interpolatory algorithm for quantifying model uncertainties
Systems & control letters, Vol.18(3), pp.173-177
1992
DOI: 10.1016/0167-6911(92)90002-A
Abstract
This paper presents a linear, interpolatory, convergent uncertainty estimation scheme which is robust in the face of disturbance. The idea is that by simply changing from Lagrange interpolation to Hermite interpolation an effective scheme is derived for estimation of uncertainty. It is shown that the proposed scheme has the advantage that in the face of corrupted data, the error in the derived uncertainty bound is independent of the degree of the approximating polynomial, i.e. if ϵ denotes the maximum magnitude of the disturbance, then the maximum possible error in the uncertainty bound is ϵ.
Details
- Title: Subtitle
- A linear, robust and convergent interpolatory algorithm for quantifying model uncertainties
- Creators
- Sundar RamanEr-Wei Bai
- Resource Type
- Journal article
- Publication Details
- Systems & control letters, Vol.18(3), pp.173-177
- Publisher
- Elsevier B.V
- DOI
- 10.1016/0167-6911(92)90002-A
- ISSN
- 0167-6911
- eISSN
- 1872-7956
- Language
- English
- Date published
- 1992
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984083234402771
Metrics
11 Record Views