Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Dory Merhy"'
Autor:
Thomas Chevet, Cristina Stoica Maniu, Israel Hinostroza, Teodoro Alamo, Eduardo F. Camacho, Sofiane Ben Chabane, Dory Merhy, Maria Makarov
Publikováno v:
International Journal of Control
International Journal of Control, Taylor & Francis, 2020, ⟨10.1080/00207179.2020.1825796⟩
International Journal of Control, Taylor & Francis, 2020, ⟨10.1080/00207179.2020.1825796⟩
International audience; In the context of state estimation of dynamical systems subject to bounded perturbations and measurement noises, this paper proposes an application of a guaranteed ellipsoidal-based set-membership state estimation technique to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f7fd77f04421f66261f02169537c4c50
https://hal.archives-ouvertes.fr/hal-02972596/file/Guaranteed_Set_Membership_State_Estimation_of_an_Octorotor_s_Position_for_Radar_Applications__2_.pdf
https://hal.archives-ouvertes.fr/hal-02972596/file/Guaranteed_Set_Membership_State_Estimation_of_an_Octorotor_s_Position_for_Radar_Applications__2_.pdf
Publikováno v:
ICSTCC
23rd International Conference on System Theory, Control and Computing
23rd International Conference on System Theory, Control and Computing, Oct 2019, Sinaia, Romania
23rd International Conference on System Theory, Control and Computing
23rd International Conference on System Theory, Control and Computing, Oct 2019, Sinaia, Romania
International audience; This paper presents an ellipsoidal set-membership state estimation technique for discrete-time linear time-invariant descriptor systems with bounded perturbations and noises. The approach proceeds off-line by minimizing a para
Publikováno v:
57th IEEE Conference on Decision and Control (CDC 2018)
57th IEEE Conference on Decision and Control (CDC 2018), Dec 2018, Miami Beach, United States. ⟨10.1109/cdc.2018.8619177⟩
CDC
57th IEEE Conference on Decision and Control (CDC 2018), Dec 2018, Miami Beach, United States. ⟨10.1109/cdc.2018.8619177⟩
CDC
International audience; This paper presents a new zonotopic constrained approach for the Kalman filter that takes advantage of the particular structure of the original optimization problem. This technique consists in projecting the state estimation b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::70c49a579f9200b9da9169dfaadfad81
https://hal.archives-ouvertes.fr/hal-01907119/file/CDCPaper.pdf
https://hal.archives-ouvertes.fr/hal-01907119/file/CDCPaper.pdf