DOI: https://doi.org/10.15368/theses.2011.26
Available at: https://digitalcommons.calpoly.edu/theses/471
Date of Award
3-2011
Degree Name
MS in Aerospace Engineering
Department/Program
Aerospace Engineering
Advisor
Eric Mehiel
Abstract
The Air Force has been working towards developing technology for operationally responsive space (ORS), which is the ability to launch military assets into space without the long set up time currently required. Part of the solution to ORS is to develop a reusable booster vehicle capable of sending any vehicle into orbit, then descending back to the atmosphere and landing unpowered so that it may take another vehicle into orbit with a 48 hour turnaround time. Currently classical gain tuning techniques are used to design a controller for a specific mission, which may hinder the vehicle’s ability to perform multiple missions if gains have to be re-tuned. Advanced nonlinear control methods like dynamic inversion and backstepping may eliminate the need to use classical gain tuning techniques that may increase quick turnaround time, reliability, and performance. Both methods consider the dynamics of the vehicle allowing the controller to be applied to the whole flight envelope. However, they are model-based methods that require knowledge of plant aerodynamics. The objective was to develop a backstepping outer loop and dynamic inversion inner loop controller for a reusable launch vehicle configuration and evaluate its robustness characteristics by inserting aerodynamic uncertainties into the static and control surface aerodynamic data separately and together. Both dynamic inversion and backstepping were susceptible to control surface aerodynamic uncertainties more than static aerodynamics. The benefit of using dynamic inversion and backstepping was that it was formulated so that it decouples the system of equations as long as the dynamics were modeled accurately. The control variable became a bank of decoupled integrators. However, when uncertainties were introduced into the plant model, the controller was unable to accurately model the dynamics, which re-introduced axes coupling inherent in the plant. The coupling caused performance in one axis to degrade if another axis degraded.