Aerospace Guidance, Control, and Optimization
This research develops and tests advanced guidance, control, and optimization methods for aerospace and autonomous systems, focusing on real-time solutions and flight experiments.
This grant is no longer accepting proposals
NRC Research Associateship Programs has archived this opportunity.
Funder: NRC Research Associateship Programs
Due Dates: May 1, 2025 (Next deadline)
Funding Amounts: Base stipend approximately $67,000/year plus $3,000 travel allowance; supplements based on experience; typical duration 2-3 years.
Summary: Fellowship supporting postdoctoral and senior researchers to conduct advanced research in aerospace guidance, control, and optimization of nonlinear dynamical systems with real-time applications and flight experiments.
Key Information: Open to U.S. citizens and permanent residents; requires PhD; research conducted on-site at Naval Postgraduate School in Monterey, CA; strong mathematical and computational skills needed.
Description
This fellowship opportunity at the Naval Postgraduate School (NPS) supports research in aerospace guidance, control, and optimization, focusing on nonlinear dynamical systems. The research program emphasizes theoretical, numerical, and experimental approaches to modeling, analysis, and solving nonlinear and nonsmooth optimal control problems. A key goal is to develop revolutionary methods that enable faster-than-real-time solutions for optimal vehicle maneuvers, including flight implementation on spacecraft such as those aboard the International Space Station.
The program advances pseudospectral optimal control theory, including mathematical proofs of convergence and consistency, and applies these methods experimentally to unmanned flight and ground vehicles in both laboratory and field environments. Researchers will have access to state-of-the-art laboratories and planned flight experiments to test and demonstrate new concepts. The research aims to produce practical solutions for real-time aerospace and autonomous system applications.
Candidates should possess exceptional mathematical and computational skills and be capable of working independently with minimal supervision.
Key Research Areas
- Nonlinear and nonsmooth dynamic optimization
- Guidance and control of aerospace and autonomous vehicles
- Pseudospectral optimal control theory
- Experimental implementation on unmanned systems
- Robust numerical methods for optimization
- Flight experiments and real-time applications
