Abstract
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.
Original language | English |
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Title of host publication | 2023 62nd IEEE Conference on Decision and Control, CDC 2023 |
Publisher | Institute of Electrical and Electronics Engineers |
Pages | 3688-3693 |
Number of pages | 6 |
ISBN (Electronic) | 979-8-3503-0124-3 |
DOIs | |
Publication status | Published - 19 Jan 2024 |
Event | 62nd IEEE Conference on Decision and Control, CDC 2023 - Singapore, Singapore Duration: 13 Dec 2023 → 15 Dec 2023 Conference number: 62 |
Conference
Conference | 62nd IEEE Conference on Decision and Control, CDC 2023 |
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Abbreviated title | CDC 2023 |
Country/Territory | Singapore |
City | Singapore |
Period | 13/12/23 → 15/12/23 |
Keywords
- Data-driven Control
- Linear Parameter-Varying Systems
- Nonlinear Systems