تقرير
Generalized Forgetting Recursive Least Squares: Stability and Robustness Guarantees
| العنوان: | Generalized Forgetting Recursive Least Squares: Stability and Robustness Guarantees |
|---|---|
| المؤلفون: | Lai, Brian, Bernstein, Dennis S. |
| سنة النشر: | 2023 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Electrical Engineering and Systems Science - Systems and Control, Electrical Engineering and Systems Science - Signal Processing |
| الوصف: | This work presents generalized forgetting recursive least squares (GF-RLS), a generalization of recursive least squares (RLS) that encompasses many extensions of RLS as special cases. First, sufficient conditions are presented for the 1) Lyapunov stability, 2) uniform Lyapunov stability, 3) global asymptotic stability, and 4) global uniform exponential stability of parameter estimation error in GF-RLS when estimating fixed parameters without noise. Second, robustness guarantees are derived for the estimation of time-varying parameters in the presence of measurement noise and regressor noise. These robustness guarantees are presented in terms of global uniform ultimate boundedness of the parameter estimation error. A specialization of this result gives a bound to the asymptotic bias of least squares estimators in the errors-in-variables problem. Lastly, a survey is presented to show how GF-RLS can be used to analyze various extensions of RLS from the literature. Comment: Accepted to the IEEE Transactions on Automatic Control. Scheduled to appear in the 2024 November issue |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2308.04259 |
| رقم الأكسشن: | edsarx.2308.04259 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |