Longitudinal flight control system design via Laguerre based model predictive control

The purpose of this paper is to evaluate the performance and computation time of Laguerre based model predictive control in the longitudinal motion of an aircraft. A Laguerre based model predictive algorithm is developed to control the longitudinal dynamics of an aircraft subject to state and input constraints. Then, the performance and the computation time of the designed controller are compared to the ones of the standard version of model predictive control. The results show that the Laguerre based model predictive control improves the computation time as much as 7.2% with a negligible trade-off in performance degradation. Because performing aircraft maneuvers needs to solve constrained optimization problems in short time samples, this study suggests the application of Laguerre based model predictive control for such purpose. Furthermore, by allowing to use shorter sampling times, the method could be used in real-time implementation of agile aircraft with fast dynamics.