Performance Enhancement of Parameter Estimators via Dynamic Regressor Extension and Mixing

Abstract : A new procedure to design parameter estimators with enhanced performance is proposed in the technical note. For classical linear regression forms, it yields a new parameter estimator whose convergence is established without the usual requirement of regressor persistency of excitation. The technique is also applied to nonlinear regressions with “partially” monotonic parameter dependence-giving rise again to estimators with enhanced performance. Simulation results illustrate the advantages of the proposed procedure in both scenarios.