2026-09-18T20:13:16Zhttps://digital.lib.washington.edu/server/oai/request

oai:digital.lib.washington.edu:1773/551272026-02-06T11:00:44Zcom_1773_4888col_1773_4889

Açıkmeşe, Behçet Kamath, Abhinav Girish 2026-02-05T19:30:24Z 2026-02-05T19:30:24Z 2026-02-05 2025 Kamath_washington_0250E_29127.pdf https://hdl.handle.net/1773/55127 Thesis (Ph.D.)--University of Washington, 2025 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. application/pdf en_US none Aerospace engineering Aeronautics and astronautics Real-Time Trajectory Optimization for High-Performance Guidance & Control Thesis Open Access open.access