ABSTRACT
Rotorcraft development presents unique control challenges related to noise, vibration, and flight. Model Predictive Control (MPC) is proposed as a holistic approach to rotorcraft flight control capable of explicitly accounting for operational constraints. The first part of this chapter describes MPC design using linear parameter-varying (LPV) approximation of nonlinear dynamics. This procedure has several advantages including known quality of approximation and polynomial-time computability. Details of MPC problem formulation and its implementation are presented. As a first application, we consider active control of aeromechanical instability, which is a major hurdle in the development of soft-in-plane rotorcraft. A simple nonlinear parameter-varying model that contains a Hopf bifurcation is used to capture the essential features of this instability. The effectiveness of MPC in suppressing nonlinear vibrations subject to control constraints is illustrated. As a second and more involved application, we present the design of an MPC-based flight control system (FCS) for the XV-15 tilt rotor. The FCS was implemented on a 6-DOF high-fidelity XV-15 real-time simulator. Test pilots flew several missions on the simulator with MPC in the loop including a highly nonlinear conversion maneuver. They observed significant reductions in work load, fast response to commands, and rated MPC performance from good to excellent during these simulated maneuvers.
