Helicopter Control with Dynamic Inversion and Inflow Rate Estimation

Abstract

The constant growth in the Unmanned Aerial Systems industrial sector, and the perspective of a future smart air mobility, pose a challenge in the development of increasingly reliable, robust, and performing control algorithms. Control systems landscape is extremely wide and offers several solutions for this challenge, nevertheless it is still necessary the exploration of new and more performing solutions. When a physic-based design approach is chosen for the control, paramount importance takes the knowledge of the vehicle state at every time step. Helicopter dynamics presents several inner state variables which are usually not measurable during the flight. Among these, the inflow ratio is one of the most important. Scope of this paper is the preliminary investigation of a velocity controller based on the inverse simulation of a minimum complexity model for a small-scale helicopter. An estimation of the mean induced inflow angle is also considered to improve the controller performance. The estimation is done by an extended Kalman filter. Different maneuvers have been simulated on a 11 d.o.f. helicopter model.