Optimal Trajectory Reconfiguration And Retargeting For A Reusable Launch Vehicle
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Optimal Trajectory Reconfiguration and Retargeting for the X-33 Reusable Launch Vehicle
This thesis considers the problem of generating optimal entry trajectories for a reusable launch vehicle following a control surface failure. The thesis builds upon the work of Dr. David Doman, Dr. Michael Oppenheimer and Dr. Michael Bolender of the Air Vehicles Directorate, Air Force Research Lab Dayton Ohio. The primary focus of this work is to demonstrate the feasibility of inner loop reconfiguration and outer loop trajectory retargeting and replanning for the X-33 reusable launch vehicle (RLV) following the imposition of a control surface failure. The trajectory generation model employs path constraints generated by an AFRL trim deficiency algorithm coupled with an inner loop control allocator and aerodynamic database that captures the full 6-DOF vehicle aerodynamic effects while utilizing an outer loop 3-DOF model. The resulting optimal trajectory does not violate the trim deficiency constraints and provides additional margins for trajectories flown during failure conditions. The footprints generated by the thesis show that contemporary footprint analysis for vehicles experiencing control surface failures are overly optimistic when compared to those footprints that consider vehicle aerodynamic stability and realistic landable attitudes at the threshold of the landing runway. The results of the thesis also show the performance reductions resulting from decoupling the inner and outer loop and that trajectories can be generated to the landing runway without using a region of terminal area energy management.
Optimal Trajectory Reconfiguration and Retargeting for a Reusable Launch Vehicle
Autonomous reusable launch vehicles (RLV) are being pursued as low-cost alternatives to expendable launch vehicles and the Shuttle. The employment of autonomous reusable launch vehicles requires additional guidance and control robustness to fulfill the role of an adaptive human pilot, in the event of failures or unanticipated conditions. The guidance and control of these vehicles mandate new guidance strategies that are able to identify and adapt to vehicle failures during the flight and still return to earth safely. This work utilizes an online trim algorithm that provides the outer loop with the feasible range of Mach number and angle of attack, for which the vehicle can be rotationally trimmed. The algorithm allows one to include 6-degree-of-freedom (DOF) trim effects and constraints in a reduced order dynamical model which is used in the solution of an optimal control problem. A direct pseudospectral method is used to solve a two-point-boundary-value problem which determines the optimal entry trajectory subject to appropriate constraints such as normal load, dynamic pressure limits, heat load limits, and state dependent constraints.
Fault Tolerant Optimal Trajectory Generation for Reusable Launch Vehicles
Reconfigurable inner-loop control laws improve the fault tolerance of a vehicle to control effector failures; however, in order to preserve stability, the unfailed effectors may be deployed to off-nominal positions to compensate for undesirable perturbations caused by the failed effectors. The effectors acting under the influence of a reconfigurable control law can produce significant perturbations to the nominal forces produced by the wing and body and can also affect the range of flight conditions over which the vehicle can be controlled. Three degree-of-freedom (3 DOF) dynamical models used in trajectory optimization for aerospace vehicles typically include wing-body aerodynamic force effects but ignore the aerodynamic forces produced by the control surfaces. In this work, a method for including these trim effects as well as control induced trajectory constraints in a 3 DOF model is presented.