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meetings - Space Flight Mechanics Committee

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Feb 14, 2013 Kauai Salon 3<br />

SESSION 27: SPACECRAFT GUIDANCE, NAVIGATION, AND CONTROL -- II<br />

Chair: Dr. Marcus Holzinger, Georgia Institute of Technology<br />

8:00 AAS Precision Landing at Mars Using Discrete-event Drag Modulation<br />

13-438 Zachary Putnam, Georgia Institute of Technology; Robert Braun, Georgia Institute<br />

of Technology<br />

An entry, descent, and landing system concept for achieving Mars Science Laboratory class<br />

accuracy for a Mars Exploration Rover class payload at Mars is presented. The concept uses<br />

a single drag-area jettison event to control its trajectory during entry. A three-degree-offreedom<br />

trajectory simulation is used in conjunction with Monte Carlo techniques to assess<br />

the performance of the entry, descent, and landing system concept. Results indicate a<br />

terminal accuracy competitive with pre-flight Mars Science Laboratory estimates and a<br />

significant reduction in peak heat rate and integrated heat load relative to the Mars<br />

Exploration Rover entry system.<br />

8:20 AAS Decentralized Guidance of Swarms of <strong>Space</strong>craft Using a Model Predictive<br />

13-439 Control Implementation of Sequential Convex Programming<br />

Daniel Morgan, University of Illinois at Urbana-Champaign; Soon-Jo Chung,<br />

University of Illinois at Urbana-Champaign; Fred Y. Hadaegh, NASA / Caltech JPL<br />

This paper presents a decentralized, model predictive control algorithm for the<br />

reconfiguration of swarms of spacecraft composed of hundreds to thousands of agents with<br />

limited capabilities. In our prior work, sequential convex programming has been used to<br />

determine collision-free, fuel-efficient trajectories for the reconfiguration of spacecraft<br />

swarms. This paper uses a model predictive control implementation of the sequential<br />

convex programming algorithm in real-time. By updating the optimal trajectories during the<br />

reconfiguration, the model predictive control algorithm becomes decentralized and more<br />

robust to errors in sensing and actuation.<br />

8:40 AAS <strong>Space</strong>craft Maneuvering via Atmospheric Differential Drag Using an<br />

13-440 Adaptive Lyapunov Controller<br />

David Perez, Rensselaer Polytechnic Institute; Riccardo Bevilacqua, Rensselaer<br />

Polytechnic Institute<br />

An adaptive Lyapunov Controller originally proposed by the authors in previous work for a<br />

rendezvous maneuver using differential drag is here generalized allowing for the tracking of<br />

reference trajectories or dynamics. The control algorithm is tested using Systems Tool Kit<br />

simulations for a Re-phase, a Fly-around, and a rendezvous maneuvers. The interest in<br />

autonomous propellant-less maneuvering comes from the desire of reducing costs for<br />

performing formation maneuvering. Successful autonomous propellant-less maneuvering of<br />

LEO S/C can be achieved using Differential Drag.<br />

9:00 AAS Model Diagnostics and Dynamic Emulation: Enhancing the Understanding<br />

23 rd AAS / AIAA <strong>Space</strong> <strong>Flight</strong> <strong>Mechanics</strong> Meeting Page 97

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