The paper deals with the problem of adaptive output regulation of nonlinear systems. Building on the design technique recently proposed in [1], we present a new approach where the regulator's internal model is adapted online via Gaussian Processes. Adaptation is performed by following an "event-triggered"logic and hybrid tools are used to analyse the resulting closed-loop system. Unlike the approach of [1], where the steady-state control policy is supposed to belong to a specific finite-dimensional model set, here we only require smoothness. The paper also presents numerical simulations showing how the proposed method outperforms previous approaches.
Gentilini L., Bin M., Marconi L. (2022). Adaptive Nonlinear Regulation via Gaussian Processes. Institute of Electrical and Electronics Engineers Inc. [10.1109/CDC51059.2022.9993066].
Adaptive Nonlinear Regulation via Gaussian Processes
Gentilini L.
Primo
;Bin M.;Marconi L.
2022
Abstract
The paper deals with the problem of adaptive output regulation of nonlinear systems. Building on the design technique recently proposed in [1], we present a new approach where the regulator's internal model is adapted online via Gaussian Processes. Adaptation is performed by following an "event-triggered"logic and hybrid tools are used to analyse the resulting closed-loop system. Unlike the approach of [1], where the steady-state control policy is supposed to belong to a specific finite-dimensional model set, here we only require smoothness. The paper also presents numerical simulations showing how the proposed method outperforms previous approaches.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
