Over the last years, two new technologies to solve optimal-control problems were successfully developed: that is, pseudospectral optimal controlandconvex optimization, withthe former for solving the generalnonlinear programming problemand the latter aimed at solving convex problems (for example, second-order conic problems) in real time. In this paper, a framework for combining them, with a motivational example, is described. The benefits of the new proposed method aredemonstrated for thedescentphase of theNASAMars Science Laboratory.Numerical simulations showthat the proposed algorithms lead to more accurate results with respect to standard transcription methods.
Sagliano, M. (2018). Pseudospectral convex optimization for powered descent and landing. JOURNAL OF GUIDANCE CONTROL AND DYNAMICS, 41(2), 320-334 [10.2514/1.G002818].
Pseudospectral convex optimization for powered descent and landing
Sagliano M.
2018
Abstract
Over the last years, two new technologies to solve optimal-control problems were successfully developed: that is, pseudospectral optimal controlandconvex optimization, withthe former for solving the generalnonlinear programming problemand the latter aimed at solving convex problems (for example, second-order conic problems) in real time. In this paper, a framework for combining them, with a motivational example, is described. The benefits of the new proposed method aredemonstrated for thedescentphase of theNASAMars Science Laboratory.Numerical simulations showthat the proposed algorithms lead to more accurate results with respect to standard transcription methods.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
