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Generation of new exciting regressors for consistent on-line estimation of unknown constant parameters (2104.02210v3)
Published 6 Apr 2021 in stat.ME, cs.SY, and eess.SY
Abstract: The problem of parameter estimation from a standard vector linear regression equation in the absence of sufficient excitation in the regressor is addressed. The first step to solve the problem consists in transforming this equation into a set of scalar ones using the well-known dynamic regressor extension and mixing technique. Then a novel procedure to generate new scalar exciting regressors is proposed.} The superior performance of a classical gradient estimator using this new regressor, instead of the original one, is illustrated with comprehensive simulations.