The online estimation of a maneuvering steady-state condition of an aircraft, called the dynamic trim, is used to estimate the allowable control travel during flight, a key information in pilot cueing for envelope limit protection. In this paper a new methodology is presented where adaptive models are used to estimate online local dynamic trim conditions, while requiring very limited a priori vehicle information. Adaptive neural networks are employed to enable online learning. The models are used to estimate future aircraft responses and artificial margins on controls that would keep the aircraft response within its flight envelope limits. A linear helicopter model and the XV-15 tiltrotor model are used to demonstrate the method in simulation.