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Adaptive Observer with Enhanced Gain to Address Deficient Excitation

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Fouad Giri
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  • PersonId : 941428

Abstract

For joint estimation of state variables and unknown parameters, adaptive observers usually assume some persistent excitation (PE) condition. In practice, the PE condition may not be satis ed, because the underlying recursive estimation problem is ill-posed. To remedy the lack of PE condition, inspired by the ridge regression, this paper proposes a regularized adaptive observer with enhanced parameter adaptation gain. Like in typical ill-posed inverse problems, regularization implies an estimation bias, which can be reduced by using prior knowledge about the unknown parameters.
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Dates and versions

hal-03875702 , version 1 (28-11-2022)

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Qinghua Zhang, Fouad Giri. Adaptive Observer with Enhanced Gain to Address Deficient Excitation. ALCOS 2022 -14th IFAC Workshop on Adaptive and Learning Control Systems, Jun 2022, Casablanca, Morocco. pp.1-5, ⟨10.1016/j.ifacol.2022.07.334⟩. ⟨hal-03875702⟩
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