Parameter Identification with Finite-Convergence Time Alertness Preservation

TL;DR

This paper introduces two novel parameter identification methods that guarantee finite-time convergence and maintain this property even when parameters change, applicable in both continuous and discrete time.

Contribution

The main novelty is the development of FCT estimators that preserve finite convergence time despite parameter variations, unlike previous versions.

Findings

Estimators converge in finite time under weak excitation conditions.

The schemes maintain finite convergence time even with parameter changes.

Both continuous and discrete-time implementations are provided.

Abstract

In this brief note we present two new parameter identifiers whose estimates converge in finite time under weak interval excitation assumptions. The main novelty is that, in contrast with other finite-convergence time (FCT) estimators, our schemes preserve the FCT property when the parameters change. The previous versions of our FCT estimators can track the parameter variations only asymptotically. Continuous-time and discrete-time versions of the new estimators are presented