Abstract:
Vertical speed is a critical limit for rotorcraft at low height above terrain and low speed flight conditions. In this paper an adaptive estimation algorithm is proposed to estimate allowable control travel on the collective axis at the onset of pre-defined vertical speed limits. A concurrent learning neural network based framework is used to model vertical speed online and used to predict future values of the vertical speed for given collective inputs. The generated online model is used to estimate the control sensitivity of the collective axis to formulate the allowable control travel. A generic nonlinear utility helicopter model is used to show estimation and avoidance of vertical speed limits.