Data-Driven Control of Linear Time-Varying Systems
| Autor: | Benita Nortmann, Thulasi Mylvaganam |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Computer science Linear system 02 engineering and technology Linear-quadratic regulator State (functional analysis) Data modeling Data-driven 020901 industrial engineering & automation 0202 electrical engineering electronic engineering information engineering Trajectory Applied mathematics 020201 artificial intelligence & image processing Representation (mathematics) Time complexity |
| Zdroj: | CDC 59th IEEE Conference on Decision and Control |
| DOI: | 10.1109/cdc42340.2020.9303845 |
| Popis: | An identification-free control design strategy for discrete-time linear time-varying systems with unknown dynamics is introduced. The closed-loop system (under state feedback) is parametrised with data-dependent matrices obtained from an ensemble of input-state trajectories collected offline. This data-driven system representation is used to classify control laws yielding trajectories which satisfy a certain bound and to solve the linear quadratic regulator problem - both using data-dependent linear matrix inequalities only. The results are illustrated by means of a numerical example. |
| Databáze: | OpenAIRE |
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