Engine limit detection and avoidance for helicopters with multiple limits

In this paper, adaptive neural network based approximate models with concurrent learn- ing schemes are used to estimate approaching limits of multiple parameters of a helicopter engine, namely the Turbine Gas Temperature and the Gas Generator Speed. The collective control channel is used to estimate the corresponding allowable control travel in order not to exceed an imposed limit. This information can be used to cue pilots or to design control systems that ensure a safe flight. Simulation results are obtained through a high fldelity simulation environment with coupled helicopter and engine dynamics.