Trajectory optimization using mixed-integer linear programming

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2002.

Bibliographic Details
Main Author: Richards, Arthur George, 1977-
Other Authors: Jonathan P. How.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2005
Subjects:
Online Access:http://hdl.handle.net/1721.1/16873
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author Richards, Arthur George, 1977-
author2 Jonathan P. How.
author_facet Jonathan P. How.
Richards, Arthur George, 1977-
author_sort Richards, Arthur George, 1977-
collection MIT
description Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2002.
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spelling mit-1721.1/168732019-04-09T19:21:31Z Trajectory optimization using mixed-integer linear programming Trajectory optimization using MILP Richards, Arthur George, 1977- Jonathan P. How. Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics. Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics. Aeronautics and Astronautics. Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2002. Includes bibliographical references (p. 121-129). This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections. This thesis presents methods for finding optimal trajectories for vehicles subjected to avoidance and assignment requirements. The former include avoidance of collisions with obstacles or other vehicles and avoidance of thruster plumes from spacecraft. Assignment refers to the inclusion of decisions about terminal constraints in the optimization, such as assignment of waypoints to UAVs and the assignment of spacecraft to positions in a formation. These requirements lead to non-convex constraints and difficult optimizations. However, they can be formulated as mixed-integer linear programs (MILP) that can be solved for global optimality using powerful, commercial software. This thesis provides several extensions to previous work using MILP. The constraints for avoidance are extended to prevent plume impingement, which occurs when one spacecraft fire thrusters towards another. Methods are presented for efficient simplifications to complex problems, allowing solutions to be obtained in practical computation times. An approximation is developed to enable the inclusion of aircraft dynamics in a linear optimization, and also to include a general form of waypoint assignment suitable for UAV problems. Finally, these optimizations are used in model predictive control, running in real-time to incorporate feedback and compensate for uncertainty. Two major application areas are considered: spacecraft and aircraft. Spacecraft problems involve minimum fuel optimizations, and include ISS rendezvous and satellite cluster configuration. Aircraft problems are solved for minimum flight-time, or in the case of UAV problems with assignment, waypoint values and vehicle capabilities are included. Aircraft applications include air traffic management and coordination of autonomous UAVs. The results in this thesis provide a direct route to globally-optimal solutions of these non-convex trajectory optimizations. by Arthur George Richards. S.M. 2005-05-19T15:06:46Z 2005-05-19T15:06:46Z 2002 2002 Thesis http://hdl.handle.net/1721.1/16873 51686447 eng M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 129 p. 1419891 bytes 1419588 bytes application/pdf application/pdf application/pdf Massachusetts Institute of Technology
spellingShingle Aeronautics and Astronautics.
Richards, Arthur George, 1977-
Trajectory optimization using mixed-integer linear programming
title Trajectory optimization using mixed-integer linear programming
title_full Trajectory optimization using mixed-integer linear programming
title_fullStr Trajectory optimization using mixed-integer linear programming
title_full_unstemmed Trajectory optimization using mixed-integer linear programming
title_short Trajectory optimization using mixed-integer linear programming
title_sort trajectory optimization using mixed integer linear programming
topic Aeronautics and Astronautics.
url http://hdl.handle.net/1721.1/16873
work_keys_str_mv AT richardsarthurgeorge1977 trajectoryoptimizationusingmixedintegerlinearprogramming
AT richardsarthurgeorge1977 trajectoryoptimizationusingmilp