Model Predictive Control Architecture for Rotorcraft Inverse Simulation

Abstract

A novel inverse simulation scheme is proposed for applications to rotorcraft dynamic models. The algorithm adopts an architecture that closely resembles that of a model predictive control scheme, where the controlled plant is represented by a high-order helicopter model. A fast solution of the inverse simulation step is obtained on the basis of a lower-order, simplified model. The resulting control action is then propagated forward in time using the more complex one. The algorithm compensates for discrepancies between the models by updating initial conditions for the inverse simulation step and introducing a simple guidance scheme in the definition of the tracked output variables. The proposed approach allows for the assessment of handling quality potential on the basis of the most sophisticated model, while keeping model complexity to a minimum for the computationally more demanding inverse simulation algorithm. The reported results, for an articulated blade, single main rotor helicopter model, demonstrate the validity of the approach.