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. Nomenclature q = Spacecraft attitude quaternion with respect to an inertial reference frame (4 elements) Ω = Actual angular velocity vector of spacecraft in a body-fixed frame (3 elements) u = Control force vector in a body fixed frame (3 elements) J = Inertia matrix in a body fixed frame (3×3) C = Control gain matrix (3×3) K = Control gain matrix (3×3) x = State vector of the spacecraft in continuous time (7×1) xn = Pre-computed nominal state vector in continuous time. I = Identity matrix (3×3) Xk = Discrete State Vector at time step k Uk = Internal Command Vector at time step k U_xk = Part of Internal command vector that contain desired position and velocities. U_rk = Part of Internal command vector that contain desired valve/switch modes. (Sup)k = Vector of information from Supervisor to the Executive; (Sup)k = [Fk, Pk, Ok, Qk] (MI)k = Vector of information from Mode ID to the Executive; (MI)k = [F_MIk , P_MIk] Fk = Fault vector from supervisor or fault detection scheme at time step k F_MIk = Fault vector from Mode Identification unit at time step k. Pk = Vector containing probability info for each component in Fk P_MIk = Vector containing probability info for each component in F_MIk Ok = Variable containing observability information Qk = Variable containing controllability information Mk = Variable containing mode information FLAG_Supk = Variable containing information about reconfiguration permition FAIL_flag = Variable indicating failure of recovery search by Mode Reconfiguration Cmd_RECk = Vector containing commands needed for recovery. Cmd_MRk = Contains information for recovery search; Cmd_MRk = [F_MIk , X_desk, Constrk] Constrk = Vector encoding Constraints in the system. NV = Vector of zeros with appropriate size Yk = Sensor data at time k (from all the sensors throughout the system) Note: Subscript k everywhere signifies values of variables and vectors at infinitesimally small time step k. * Graduate Student, Aerospace Engineering, Ann Arbor, MI 48109, email: [email protected] . † Associate Professor, Aerospace Engineering, Ann Arbor, MI 48109, email: [email protected], Associate Fellow. AIAA Guidance, Navigation, and Control Conference 2 5 August 2010, Toronto, Ontario Canada AIAA 2010-8301 Copyright © 2010 by Ali Nasir and Ella Atkins. Published by the American Institute of Aeronautics and Astronautics, Inc., with permission.