Convex Relaxations for Computational Guidance

The purpose of this course is to develop theoretical and applied skills in optimization and control for spacecraft guidance.

This video introduces convex relaxation techniques for solving non-convex optimal control problems. With improved computational capabilities (driven as much by improved theory as improved hardware), computational guidance is a reality. However, it is still critical to formulate tractable convex optimization problems for real-time guidance. Two classic examples are shown: the minimum time problem and the minimum fuel problem. Newer results have been achieved by Acikmese, Blackmore, Harris and others.

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