A Model-Free Data-Driven Algorithm for Continuous-Time Control
Presented is an algorithm to synthesize an infinite-horizon LQR optimal feedback controller for continuous-time systems. The algorithm does not require knowledge of the system dynamics, but instead uses only a finite-length sampling of (possibly suboptimal) input-output data. The algorithm is based on a constrained optimization problem that enforces a necessary condition on the dynamics of the optimal value function along an arbitrary trajectory. This paper presents the derivation as well as shows examples applied to both linear and nonlinear systems inspired by air vehicles.
Authors
- Katia Estabridis (ORCID: https://orcid.org/0000-0002-5010-4858)
- Alireza Farahmandi
- Matthew R. Kirchner (ORCID: https://orcid.org/0000-0003-3715-636X)
- D. Reed Robinson (ORCID: https://orcid.org/0000-0001-8302-2026)
- Gary A. Hewer (ORCID: https://orcid.org/0000-0002-5447-0708)
- Sean R. Bowerfind (ORCID: https://orcid.org/0009-0009-8010-2405)
- Paula Chen (ORCID: https://orcid.org/0000-0003-0439-9330)
Institutions
- Naval Air Warfare Center Weapons Division (US)
- Auburn University (US)
Publication Details
- Published
- 2025-03-01
- DOI
- https://doi.org/10.1109/aero63441.2025.11068607
- Citations
- 1
- Primary Topic
- Advanced Control Systems Optimization
- Type
- article
- Field-Weighted Citation Impact
- 1.21
Funders
- U.S. Department of Defense
- Office of Naval Research