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62nd IEEE Conference on Decision and Control, CDC 2023 / 13-15 December 2023

Direct Data-Driven State-Feedback Control of General Nonlinear Systems

Through the use of the Fundamental Lemma for linear systems, a direct data-driven state-feedback control synthesis method is presented for a rather general class of nonlinear (NL) systems. The core idea is to develop a data-driven representation of the so-called velocity-form, i.e., the time-difference dynamics, of the NL system, which is shown to admit a direct linear parameter-varying (LPV) representation. By applying the LPV extension of the Fundamental Lemma in this velocity domain, a state-feedback controller is directly synthesized to provide asymptotic stability and dissipativity of the velocity-form. By using realization theory, the synthesized controller is realized as a NL state-feedback law for the original unknown NL system with guarantees of universal shifted stability and dissipativity, i.e., stability and dissipativity w.r.t. any (forced) equilibrium point, of the closed-loop behavior. This is achieved by the use of a single sequence of data from the system and a predefined basis function set to span the scheduling map. The applicability of the results is demonstrated on a simulation example of an unbalanced disc.

Url
https://doi.org/10.1109/CDC49753.2023.10384139
Authors
Verhoek, C.
Koelewijn, P. J. W.
Haesaert, S.
Tóth, R.
Institutes

Kapcsolat

Prof. Dr. Péter Gáspár

H-1111 Budapest, Kende u. 13-17.

+36 1 279 6000

autonom@nemzetilabor.hu

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