Model Predictive Control for Helicopter Shipboard Operations in the Ship Airwakes

Abstract

This study investigates the model predictive control design for helicopter shipboard operations in the presence of ship airwakes and rough seas. A control oriented helicopter model that captures the essential dynamics of a generic helicopter, including fuselage dynamics, blade flapping and lead-lagging, and main rotor inflow in the implicit nonlinear ordinary differential equations form, is used for model predictive control design and evaluation. The control equivalent turbulence inputs model and the computational fluid dynamics data of the airwake are incorporated into the nonlinear helicopter model to simulate the airwake’s effects on the helicopter. The feasibility of the model predictive control design is investigated using two case studies: automatic deck landing on a moving ship in sea state 5 with the control equivalent turbulence inputs airwake model, and lateral reposition toward the ship in different wind-over-deck conditions extracted from the computational fluid dynamics airwake data. To improve the overall model predictive control performance, an updating scheme for the internal model of the model predictive control is proposed for helicopter shipboard operations using linearization around operating points. Nonlinear simulations are also performed to explore the capabilities of the model predictive control in handling system constraints, flight deck tracking, and disturbance rejection.