Development of a recursive algorithm for parameter uncertainty interval estimation

Anthony Tzes, Qingyang Hu, Ke Le

Research output: Contribution to journalConference articlepeer-review


This article addresses the problem of recursively estimating the parameter uncertainty intervals for a linear discrete system, whose output measurements are contaminated with noise. The estimator provides the maximally tight bounding rectangular hyperparallepiped, whose vertices are computed in an optimal manner so as to contain all parameter values consistent with the system structure and the l1 norm of the error bounds. The proposed method relies on a recursive formulation of the underlying posed linear programming problem in [1], by exploring its distinct structure. The computational effort associated with the finding of this optimal outer box is minimal. A recursive algorithm is presented for the cases of an increasing, and a fixed size sample time-sliding window. Simulation studies are included to highlight the algorithm's performance.

Original languageEnglish (US)
Pages (from-to)3010-3015
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
StatePublished - 1995
EventProceedings of the 1995 34th IEEE Conference on Decision and Control. Part 1 (of 4) - New Orleans, LA, USA
Duration: Dec 13 1995Dec 15 1995

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Modeling and Simulation
  • Control and Optimization


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