Fuel-optimal G-MPSP Guidance for Powered Descent Phase of Soft Lunar Landing

Sachan, Kapil and Padhi, Radhakant (2015) Fuel-optimal G-MPSP Guidance for Powered Descent Phase of Soft Lunar Landing. In: IEEE Conference on Control and Applications (CCA), SEP 21-23, 2015, Sydney, AUSTRALIA, pp. 924-929.

PDF 2015_IEEE_Con_Con_App_924_2016.pdf - Published Version Restricted to Registered users only Download (707kB) | Request a copy

Abstract

A fuel optimal nonlinear sub-optimal guidance scheme is presented in this paper for soft landing of a lunar craft during the powered descent phase. The recently developed Generalized Model Predictive Static Programming (G-MPSP) is used to compute the required magnitude and angle of the thrust vector. Both terminal position and velocity vector are imposed as hard constraints, which ensures high position accuracy and facilitates initiation of vertical descent at the end of the powered descent phase. A key feature of the G-MPSP algorithm is that it converts the nonlinear dynamic programming problem into a low-dimensional static optimization problem (of the same dimension as the output vector). The control history update is done in closed form after computing a time-varying weighting matrix through a backward integration process. This feature makes the algorithm computationally efficient, which makes it suitable for on-board applications. The effectiveness of the proposed guidance algorithm is demonstrated through promising simulation results.

Item Type:	Conference Proceedings
Series.:	IEEE International Conference on Control Applications
Publisher:	IEEE
Additional Information:	Copy right for this article belongs to the IEEE, 345 E 47TH ST, NEW YORK, NY 10017 USA
Keywords:	Model predictive static programming; MPSP; Generalized MPSP; Soft landing; Lunar landing
Department/Centre:	Division of Mechanical Sciences > Aerospace Engineering(Formerly Aeronautical Engineering)
Date Deposited:	04 Mar 2016 06:03
Last Modified:	04 Mar 2016 06:03
URI:	http://eprints.iisc.ac.in/id/eprint/53381

Actions (login required)

View Item