In this paper, a simplified aircraft system model is developed correctly emulating the nonlinear dynamics of complex aircraft models under closed-loop control. The simplified model is based on Dubins models used in optimization algorithms for trajectory control of multiple Unmanned Aeriel Vehicles (UAVs). Algorithms optimizing area coverage for reconnaissance based on UAV capabilities, fuel remaining, and time constraints require simple aircraft models providing ecient solutions in near real-time. However, the simplified models should accurately predict UAV dynamics for proper prediction. For this study, a realistic UAV simulation is developed including nonlinear aerodynamics and kinematics. A UAV autonomous navigation algorithm for waypoint-to-waypoint navigation is derived and integrated in the complex UAV simulation. A simplified system model based Dubins model is developed closely matching the full nonlinear UAV simulation. A Rhumb-line navigation algorithm including a velocity-hold and altitude-hold control system is used for closed-loop control. A navigation system utilizing trajectory planning with Dubins curves is also developed. Both control laws are implemented in a simplified Dubins model and tuned to match the full nonlinear simulation under autonomous control including provisions for head and tail wind conditions. Computer simulations are performed demonstrating waypointto-waypoint navigation with desired final heading trajectories for both the full nonlinear UAV model and the simplified Dubins simulation. Simulation time history analysis is used to verify the accuracy of the simplified model compared to the full nonlinear simulation model.
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