Real-Time Trajectory Optimization for High-Performance Guidance & Control

Autonomous systems of today rely on trajectory planning to achieve complex tasks. With the increasing capabilities of such systems, there is a need for a framework that not only allows for accurate modeling of these tasks, but also enables real-time generation of feasible trajectories to achieve them. This dissertation presents trajectory generation methods, using gradient-based optimization and set-based dynamic programming, for a large class of optimal, robust, and resilient control problems. These methods are intended for adoption onboard agile autonomous systems—such as reusable rockets—that mandate high-performance guidance & control.

Author dc:creator

• Kamath, Abhinav Girish

Advisor dc:contributor.advisor

• Açıkmeşe, Behçet

• Aerospace engineering

Statement dc:rights

• none

Language dc:language.iso

en_US

Handle dc:identifier.uri

https://hdl.handle.net/1773/55127

OAI identifier oai:identifier

oai:digital.lib.washington.edu:1773/55127