Data-driven input-to-state stabilization

Fuente: arXiv
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Auteurs principaux: Chen, Hailong, Bisoffi, Andrea, De Persis, Claudio
Format: Preprint
Publié: 2024
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author Chen, Hailong
Bisoffi, Andrea
De Persis, Claudio
author_facet Chen, Hailong
Bisoffi, Andrea
De Persis, Claudio
contents For the class of nonlinear input-affine systems with polynomial dynamics, we consider the problem of designing an input-to-state stabilizing controller with respect to typical exogenous signals in a feedback control system, such as actuator and process disturbances. We address this problem in a data-based setting when we cannot avail ourselves of the dynamics of the actual system, but only of data generated by it under unknown bounded noise. For all dynamics consistent with data, we derive sum-of-squares programs to design an input-to-state stabilizing controller, an input-to-state Lyapunov function and the corresponding comparison functions. This numerical design for input-to-state stabilization seems to be relevant not only in the considered data-based setting, but also in a model-based setting. Illustration of feasibility of the provided sum-of-squares programs is provided on a numerical example.
format Preprint
id arxiv_https___arxiv_org_abs_2407_06044
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Data-driven input-to-state stabilization
Chen, Hailong
Bisoffi, Andrea
De Persis, Claudio
Optimization and Control
Systems and Control
Dynamical Systems
For the class of nonlinear input-affine systems with polynomial dynamics, we consider the problem of designing an input-to-state stabilizing controller with respect to typical exogenous signals in a feedback control system, such as actuator and process disturbances. We address this problem in a data-based setting when we cannot avail ourselves of the dynamics of the actual system, but only of data generated by it under unknown bounded noise. For all dynamics consistent with data, we derive sum-of-squares programs to design an input-to-state stabilizing controller, an input-to-state Lyapunov function and the corresponding comparison functions. This numerical design for input-to-state stabilization seems to be relevant not only in the considered data-based setting, but also in a model-based setting. Illustration of feasibility of the provided sum-of-squares programs is provided on a numerical example.
title Data-driven input-to-state stabilization
topic Optimization and Control
Systems and Control
Dynamical Systems
url https://arxiv.org/abs/2407.06044