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Title: Performance Optimization and Guidance of a Low-Altitude Skid-to-Turn Vehicle. Part II: Optimal Guidance
The problem of guidance and control of an air-to-surface low-altitude skid-to-turn vehicle is considered. The objective is to steer the vehicle to a ground target from an initial state such that the vehicle remains at a constant low altitude for as long as possible and performs a bunt maneuver (negative sensed-acceleration load) rapidly at the end of the trajectory in order to attain terminal target conditions. The vehicle is modeled as a point mass in motion over a flat Earth, and the vehicle is controlled using thrust magnitude, angle of attack, and sideslip angle. The guidance and control problem is posed as a decreasing-horizon optimal control problem and is re-solved numerically at constant guidance cycles. The work described in this paper is the second part of a two-part sequence on trajectory optimization and guidance of a skid-to-turn vehicle. In both cases, the objective is to minimize the time taken by the vehicle to complete a bunt maneuver subject to the following constraints: dynamic, boundary, state, path, and interior-point event constraints. In the second part of this two-part study, a numerical guidance law is employed to re-solve the optimal control problem on a shrinking horizon. An assessment is made as to the time required to re-solve the optimal control problem both in the absence and presence of a time delay, where the time delay is the amount of time required to solve the numerical approximation of the optimal control problem at the start of each guidance cycle. The results of this study identify that in the absence and presence of a time delay, the size of the mesh on subsequent guidance cycles decreases, the time required to solve the reduced-horizon optimal control problem is small compared to the guidance cycle duration time, and the terminal conditions are met with sufficient accuracy. Thus, the results show that the guidance law presented in this paper has the potential to solve optimal control problems in real-time.  more » « less
Award ID(s):
1819002 1522629
NSF-PAR ID:
10094024
Author(s) / Creator(s):
;
Date Published:
Journal Name:
2019 AIAA Guidance, Navigation, and Control Conference, San Diego
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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