Accelerated convergence with improved robustness for discrete-time parameter estimation
Résumé
The dynamic regressor extension and mixing (DREM) method provides a fixedtime converging parameter estimator for persistently excited regressor under bounded measurement noises. This note aims to develop this approach for cases with weaker excitation and regressor constraints. Several nonlinear estimation schemes with fixed-time convergence rates and improved measurement noise robustness properties are proposed here.
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