Sensor Placement for Flapping Wing Model Using Stochastic Observability Gramians

Autor:	Boyacıoğlu, Burak, Babaei, Mahnoush, Mamo, Amanuel H., Bergbreiter, Sarah, Daniel, Thomas L., Morgansen, Kristi A.
Rok vydání:	2023
Předmět:	Electrical Engineering and Systems Science - Systems and Control 93B07
Druh dokumentu:	Working Paper
Popis:	Systems in nature are stochastic as well as nonlinear. In traditional applications, engineered filters aim to minimize the stochastic effects caused by process and measurement noise. Conversely, a previous study showed that the process noise can reveal the observability of a system that was initially categorized as unobservable when deterministic tools were used. In this paper, we develop a stochastic framework to explore observability analysis and sensor placement. This framework allows for direct studies of the effects of stochasticity on optimal sensor placement and selection to improve filter error covariance. Numerical results are presented for sensor selection that optimizes stochastic empirical observability in a bioinspired setting. Comment: 12 pages, 5 figures, 2 tables, to be published in the proceedings of the 2024 American Control Conference
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2310.00127 Zobrazit plný text záznamu View this record from Arxiv