Offline state estimation for hybrid systems via nonsmooth variable projection

We propose an offline algorithm that simultaneously estimates discrete and continuous components of a hybrid system’s state. We formulate state estimation as a continuous optimization problem by relaxing the discrete component and using a robust loss function to accommodate large changes in the cont...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Automatica (Oxford) Ročník 115; s. 108871
Hlavní autoři:	Zhang, Jize, Pace, Andrew M., Burden, Samuel A., Aravkin, Aleksandr
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.05.2020
Témata:	Hybrid systems Mechanical systems Nonlinear systems Optimization State estimation Hybrid systems Mechanical systems State estimation Nonlinear systems Optimization
ISSN:	0005-1098, 1873-2836
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Popis
Shrnutí:	We propose an offline algorithm that simultaneously estimates discrete and continuous components of a hybrid system’s state. We formulate state estimation as a continuous optimization problem by relaxing the discrete component and using a robust loss function to accommodate large changes in the continuous component during switching events. Subsequently, we develop a novel nonsmooth variable projection algorithm with Gauss–Newton updates to solve the state estimation problem and prove the algorithm’s global convergence to stationary points. We demonstrate the effectiveness of our approach by comparing it to a state-of-the-art filter bank method, and by applying it to simple piecewise-linear and -nonlinear mechanical systems undergoing intermittent impact.
ISSN:	0005-1098 1873-2836
DOI:	10.1016/j.automatica.2020.108871