This paper deals with the problem of adaptive output regulation of single-input single-output nonlinear systems, with respect to uncertainties in the exosystem. We endow a recently developed post-processing internal model design with a hybrid adaptive structure, which allows to use different identification schemes to adaptively tune the internal model at runtime. Practical regulation results are presented, with the regulation error that is proved to be linearly related to the prediction capabilities of the identifier.
Adaptive output regulation via post-processing internal models and hybrid identifiers / Bin, Michelangelo; Marconi, Lorenzo. - ELETTRONICO. - 2018-:(2017), pp. 1478-1483. (Intervento presentato al convegno 56th IEEE Annual Conference on Decision and Control, CDC 2017 tenutosi a Melbourne Convention and Exhibition Centre (MCEC), aus nel 2017) [10.1109/CDC.2017.8263861].
Adaptive output regulation via post-processing internal models and hybrid identifiers
Bin, Michelangelo
Writing – Original Draft Preparation
;Marconi, LorenzoWriting – Review & Editing
2017
Abstract
This paper deals with the problem of adaptive output regulation of single-input single-output nonlinear systems, with respect to uncertainties in the exosystem. We endow a recently developed post-processing internal model design with a hybrid adaptive structure, which allows to use different identification schemes to adaptively tune the internal model at runtime. Practical regulation results are presented, with the regulation error that is proved to be linearly related to the prediction capabilities of the identifier.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
