Fault tolerance for spacecraft attitude management

We present an autonomy architecture called Fault Tolerant Remote Agent that integrates symbolic reasoning from AI planning/scheduling with physics-based fault-tolerant control. Application to spacecraft attitude management in the presence of diverse failure classes is studied. We first review fault tolerance in AI and control-theoretic contexts and introduce an architecture in which the capabilities of each can be integrated into a more comprehensive fault management framework. We then present fault identification and reconfiguration algorithms for a spacecraft attitude control case study. Simulation results demonstrate good recovery by the spacecraft for situations in which controllability is not lost. These simulations also illustrate how logic-based and physics-based algorithms cooperatively achieve a more comprehensive fault management capability than would be possible with either algorithm class alone.