Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Gonenc Gursoy"'
Publikováno v:
ACC
This paper presents a control algorithm for the autonomous landing of a fixed-wing aircraft. In the proposed approach, the classical PID control technique is augmented with a state-dependent coefficient (SDC) nonlinear model inversion. The SDC-based
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::22f3da5d3990d683613cae7ae4e94c8d
https://doi.org/10.23919/acc.2019.8814970
https://doi.org/10.23919/acc.2019.8814970
Autor:
Ilkay Yavrucuk, Gonenc Gursoy
Publikováno v:
Journal of Guidance, Control, and Dynamics. 39:1356-1373
In this paper, two vital signals to enable flight envelope protection, namely the onset to the flight envelope (limit margin) and the available control travel to reach the limit boundary (control margin), are estimated using improved noniterative ada
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a264b803cc2aa1b022952aa81d0eae70
https://doi.org/10.2514/1.g001515
https://doi.org/10.2514/1.g001515
Autor:
Ilkay Yavrucuk, Gonenc Gursoy
Publikováno v:
ALCOSP
Dynamic adaptive models are commonly used to estimate allowable control travel and the proximity to a limiting flight condition in the design of advanced envelope protection algorithms for fly by wire aircraft. In this paper linear models are compens
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::864fcaa0c8417b8a692cd9ccab8e68a7
https://doi.org/10.3182/20100826-3-tr-4015.00052
https://doi.org/10.3182/20100826-3-tr-4015.00052
Publikováno v:
AIAA Guidance, Navigation, and Control Conference.
In this paper, a Kalman Filter based e-modification term is used in the update law of an online learning adaptive neural network controller for a helicopter application. The controller is applied to a high fidelity helicopter simulation model. The ap
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c7fd947776a535856ceaf79dc673ba5f
https://doi.org/10.2514/6.2015-1996
https://doi.org/10.2514/6.2015-1996
Autor:
Gonenc Gursoy, Ilkay Yavrucuk
Publikováno v:
AIAA Atmospheric Flight Mechanics Conference.
In this paper, the adaptive neural network based online limit and control margin estimation algorithms for envelope protection are improved using a non-iterative limit margin estimation methodology. The fixed point solution assumption is removed. Fun
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::601f5c2f7e3856828f88039dc183fabd
https://doi.org/10.2514/6.2015-0748
https://doi.org/10.2514/6.2015-0748
Publikováno v:
AIAA Atmospheric Flight Mechanics (AFM) Conference.
In this paper, adaptive neural network based approximate models with concurrent learning schemes are used to estimate approaching limits of multiple parameters of a helicopter engine, namely the Turbine Gas Temperature and the Gas Generator Speed. Th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b93cc60c888643e9a4cb7ec48f5778bb
https://doi.org/10.2514/6.2013-4689
https://doi.org/10.2514/6.2013-4689
Publikováno v:
AIAA Modeling and Simulation Technologies Conference.
This paper demonstrates a fast and convinent way to model the dynamics of a helicopter with a slung load. A new software tool called Heli-Dyn+ is used to generate high fidelity helicopter math models. One of the benefits of Heli-Dyn+ is that helicopt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::45ea129dd0e47aff17b836d77cc0f4e9
https://doi.org/10.2514/6.2012-4851
https://doi.org/10.2514/6.2012-4851
Autor:
Gonenc Gursoy, Ilkay Yavrucuk
Publikováno v:
AIAA Atmospheric Flight Mechanics Conference.
Neural-network-based adaptive dynamic models are commonly used to estimate allowable control travel and the proximity to a limiting flight condition in the design of advanced envelope protection algorithms for fly-by-wire aircraft. In this paper, lin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99497fcd65781a5b25a24fce81c97134
https://doi.org/10.2514/6.2010-7945
https://doi.org/10.2514/6.2010-7945