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Two methods for control system reconfiguration have been investigated. The first method is a robust servomechanism control approach (optimal tracking problem) that is a generalization of the classical proportional-plus-integral control to multiple input-multiple output systems. The second method is a control-allocation approach based on a quadratic programming formulation. A globally convergent fixed-point iteration algorithm has been developed to make onboard implementation of this method feasible. These methods have been applied to reconfigurable entry flight control design for the X-33 vehicle. Examples presented demonstrate simultaneous tracking of angle-of-attack and roll angle commands during failures of the right body flap actuator. Although simulations demonstrate success of the first method in most cases, the control-allocation method appears to provide uniformly better performance in all cases.
This thesis deals with the reconfigurable flight control of the X-33 vehicle. Reconfiguration means to change the control laws to accommodate such situations when some parts of the original system fail or malfunction, so as to maintain the system stability and achieve fair performance. The X-33 vehicle has eight aero surfaces, which provides enough redundancy for reconfiguration design. There are many kinds of potential failures, but here we will focus on the reconfiguration of single aero surface jam scenarios. The X-33 control system is a MIMO (Multi-Input Multi-Output) system, so we will handle it in the state space.
Two methods for control system reconfiguration have been investigated. The first method is a robust servomechanism control approach (optimal tracking problem) that is a generalization of the classical proportional-plus-integral control to multiple input-multiple output systems. The second method is a control-allocation approach based on a quadratic programming formulation. A globally convergent fixed-point iteration algorithm has been developed to make onboard implementation of this method feasible. These methods have been applied to reconfigurable entry flight control design for the X-33 vehicle. Examples presented demonstrate simultaneous tracking of angle-of-attack and roll angle commands during failures of the right body flap actuator. Although simulations demonstrate success of the first method in most cases, the control-allocation method appears to provide uniformly better performance in all cases.
A quaternion-based attitude control system is developed for the X-33 in the ascent flight phase. A nonlinear control law commands body-axis rotation rates that align the angular velocity vector with an Euler axis defining the axis of rotation that will rotate the body-axis system into a desired-axis system. The magnitudes of the commanded body rates are determined by the magnitude of the rotation error. The commanded body rates form the input to a dynamic inversion-based adaptive/reconfigurable control law. The indirect adaptive control portion of the control law uses online system identification to estimate the current control effectiveness matrix to update a control allocation module. The control allocation nominally operates in a minimum deflection mode; however, if a fault is detected, it can operate in a null-space injection mode that excites and decorrelates the effectors without degrading the vehicle response to enable online system identification. The overall 5 stem is designed to provide fault and damage tolerance for the X-33 on ascent.
In order to increase survivability and maximize performance, autonomous vehicles require the development of algorithms that fulfill the role of an adaptive human pilot in response to failures, damage, or uncertain vehicle dynamics. Hence, the guidance and control algorithms implemented on autonomous vehicles must be able to react and compensate, whenever possible, for failures so that their impact can be minimized. In this work, an adaptive reconfigurable inner-loop controller is developed for a modified version of the X-40A Space Maneuvering Vehicle. The purpose of this inner loop control system is to accurately track body-frame angular velocity vector commands, while automatically reacting to and compensating for failures, damage, or uncertain vehicle dynamics.