A New Recursive Least-Squares Method with Multiple Forgetting Schemes

TL;DR

This paper introduces a novel recursive least-squares method that employs multiple forgetting schemes to effectively track parameters changing at different rates, reformulating the problem as a regularized least squares task.

Contribution

It presents a new recursive least-squares approach with multiple forgetting schemes, offering improved tracking of time-varying parameters compared to existing methods.

Findings

Effective in tracking parameters with different change rates

Reformulation as a regularized least squares problem

Simulation confirms improved performance

Abstract

We propose a recursive least-squares method with multiple forgetting schemes to track time-varying model parameters which change with different rates. Our approach hinges on the reformulation of the classic recursive least-squares with forgetting scheme as a regularized least squares problem. A simulation study shows the effectiveness of the proposed method.