Model Predictive Control for Solving the Helicopter Motion Control Problem

Abstract

AbstractIn this chapter, the model predictive control (MPC) approach is proposed to use for solving the helicopter control problem for three models of helicopters: Bo105 S123, Lynx ZD559, and Puma SA330. The Bo105 S123 is a light, twin-engine helicopter for multipurpose use. The Lynx ZD559 is a twin-engine helicopter used for a variety of roles from tactical transport to armed escort. The Puma SA330 is a twin-engine helicopter designed to carry both people and cargo for civil and battlefield operations. Application of the MPC strategy permits obtaining a series of control actions for the considered models of helicopters to reach desired trajectories. The control is calculated by minimizing the cost function reflecting the degree of closeness between wanted trajectories and computed (predictive) trajectories and the effect of an applied control signal. The control is corrected at each sampling instant over the control horizon to achieve wished trajectories over the prediction horizon. Analysis of how the control and prediction horizons and parameters of the cost functions and wished trajectories influence the dynamics of the helicopter’s motion is carried out.KeywordsModel predictive controlReceding horizon controlFlight controlHelicopter motion controlControl systemsOptimal controller