Thruster Fault Detection for the X38
The Smart Systems Research Lab at NASA Ames Research Center is developing advanced fault detection technologies for the X38/CRV, in collaboration with NASA Johnson Space Center (Code EG - Aeroscience and Flight Mechanics Division). This effort focuses on identifying in near real-time single/multiple hard thruster failure, thruster leaks, and vehicle mass property. This work also includes adaptive reconfiguration control based on the identified thrusters and mass property for a class of future spacecrafts.
For the X38 vehicle, thruster failures are difficult to detect because of the limited sensor capabilities. For the CRV, mass property is difficult to determine accurately as the number of crew members can vary, and the payload brought onboard varies as well. The approach being applied is to use advanced identification technologies and adaptive neural control to provide optimal control of the spacecraft. This approach does not require a mathematical model of the spacecraft a priori but instead it effectively learns an accurate model of the spacecraft from its behavior. The controller uses gathered data from a set of navigational sensors to quasi-statically learn an accurate model of the spacecraft performance. In this manner, the controller can control the spacecraft under a variety of changing conditions such as varying mass, changing center-of-mass location, thruster degradations, failures, and leaks. Optimization methodologies are then used to achieve optimal performance.