SYSYMay 16, 2022

On the tightest interval-valued state estimator for linear systems

arXiv:1805.041823 citationsh-index: 29
AI Analysis

Provides a theoretical foundation for optimal interval estimation in linear systems, but is incremental as it formalizes known concepts without new practical algorithms.

The paper derives the tightest possible interval-valued state estimator for linear systems, which is the intersection of all interval-valued estimators, but is infinite-dimensional in general, requiring over-approximations for practical use.

This paper discusses an interval-valued state estimator for linear dynamic systems. In particular, we derive an expression of the tightest possible interval-valued estimator in the sense that it is the intersection of all interval-valued estimators. This estimator appears, in a general setting, to be an infinite dimensional dynamic system. Therefore, practical implementation requires some over-approximations which would yield a good trade-off between computational complexity and tightness.

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