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Trajectory Optimization using Mixed-Integer Linear Programming (2002)
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BibTeX
@MISC{Richards02trajectoryoptimization,
author = {Arthur George Richards},
title = {Trajectory Optimization using Mixed-Integer Linear Programming},
year = {2002}
}
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Abstract
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
Keyphrases
mixed-integer linear programming trajectory optimization assignment refers optimal trajectory efficient simplification previous work terminal constraint difficult optimization non-convex constraint global optimality practical computation time plume impingement spacecraft fire thruster thruster plume assignment requirement several extension mixed-integer linear program commercial software
