Parameter Identification for Inflight Detection of Aircraft Icing

Abstract Recently increasing interest in aircraft icing has motivated the proposal of a new ice management system that would coordinate existing ice protection systems while providing inflight monitoring of ice accretion effects. Since these effects are manifested in changes in the flight dynamics, parameter identification is a critical element of ice detection. In this context, the parameter identification must provide timely estimates that are accurate in the presence of disturbances. Both a batch leastsquares algorithm and an H∞ full-state derivative information algorithm are evaluated under the assumption that state derivative information is available. Simulation results show that these algorithms provide a timely, accurate, and unambiguous icing indication