On-Line Trajectory Optimization for Autonomous Air Vehicles
Abstract
Successful operation of next-generation unmanned air vehicles will demand a high level of autonomy. Autonomous low-level operation in a high-threat environment dictates a need for on-hoard, robust, reliable and efficient trajectory optimization. in this report, we develop and demonstrate an innovative combination of traditional analytical and numerical solution procedures to produce efficient, robust and reliable means for nonlinear Light path optimization in the presence of time-varying obstacles and threats. The solution procedure exploits the natural time-scale separation that exists in the aircraft dynamics using singular perturbation theory. A reduced order problem involving only the kinematics of the position subspace is treated numerically. The nonlinear aircraft dynamics are to be treated analytically in phase II using a boundary layer analysis that results in an optimal feedback guidance solution. The developed algorithms were coupled with a neural network adaptive autopilot and integrated in an existing unmanned test-bed. This report documents the phase I effort, which produced a demonstration of the developed algorithm in near-real-time flight simulation, and included a simple evaluation of tracking computed trajectories on a rotary wing UAV.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 31, 2003
- Accession Number
- ADA421395
Entities
People
- Anthony J. Calise
- Eric N. Johnson
- J. Eric Corban
- Shannon Twigg