Continuous-Time Optimization of Time-Varying Cost Functions via Finite-Time Stability with Pre-Defined Convergence Time

In this paper, we propose a new family of continuous-time optimization algorithms for time-varying, locally strongly convex cost functions, based on discontinuous second-order gradient optimization flows with provable finite-time convergence to local optima. To analyze our flows, we first extend a w...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Proceedings of the American Control Conference s. 88 - 93
Hlavní autoři: Romero, Orlando, Benosman, Mouhacine
Médium: Konferenční příspěvek
Jazyk:angličtina
Vydáno: AACC 01.07.2020
Témata:
Acceleration
Convergence
Cost function
Heuristic algorithms
Modeling
Stability analysis
ISSN:2378-5861
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:In this paper, we propose a new family of continuous-time optimization algorithms for time-varying, locally strongly convex cost functions, based on discontinuous second-order gradient optimization flows with provable finite-time convergence to local optima. To analyze our flows, we first extend a well-know Lyapunov inequality condition for finite-time stability, to the case of arbitrary time-varying differential inclusions, particularly of the Filippov type. We then prove the convergence of our proposed flows in finite time. We illustrate the performance of our proposed flows on a quadratic cost function to track a decaying sinusoid.
ISSN:2378-5861
DOI:10.23919/ACC45564.2020.9147809