Multiple model adaptive estimation applied to the VISTA F-16 flight control system with actuator and sensor failures

Multiple model adaptive estimation is applied to the Variable In-flight Stability Test Aircraft (VISTA) F-16 flight control system. Single actuator and hard sensor failures are introduced and system performance is evaluated. A modified Bayesian approach allows for a blending of state estimates and provides lower bounds to enhance algorithm convergence properties. Scalar residual monitoring aids in resolving ambiguities by demonstrating residual characteristics consistent with a true failure. The algorithm demonstrates good convergence characteristics during purposeful commands and dither signals. Optimizing the dither to improve algorithm performance is effective.<>