Adaptive Output Regulation via Post-Processing Internal Models and Hybrid Identifiers

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.