1 research outputs found
On the almost sure central limit theorem for ARX processes in adaptive tracking
The goal of this paper is to highlight the almost sure central limit theorem
for martingales to the control community and to show the usefulness of this
result for the system identification of controllable ARX(p,q) process in
adaptive tracking. We also provide strongly consistent estimators of the even
moments of the driven noise of a controllable ARX(p,q) process as well as
quadratic strong laws for the average costs and estimation errors sequences.
Our theoretical results are illustrated by numerical experiments