Nonlinear Hierarchical MPC With Application to Aircraft Fuel Thermal Management Systems

Abstract

A nonlinear hierarchical model predictive control (MPC) framework is proposed and applied to maximize the thermal endurance of aircraft. Effectively controlling the fuel temperatures in a nonlinear multitimescale aircraft fuel thermal management system (FTMS) requires controllers capable of long-term planning and fast update rates. In this article, a twolevel hierarchical MPC controller is formulated using successive linearization (SL) that directly accounts for the multitimescale and nonlinear system dynamics to achieve accurate predictive capabilities and computational efficiency. Detailed simulation results show that the proposed hierarchical structure can increase aircraft thermal endurance by at least 21% compared to a centralized approach while significantly reducing the computational cost. The results also show that SL provides a valuable framework for efficiently accounting for nonlinear system dynamics within both levels of the hierarchical MPC formulation.

Model and algorithm analysis of MPC control in aerospace engineering

“…Nowadays, MPC appears in many fields of aerospace. In the last five years, MPC has served to maximize the thermal durability of aircraft, by incorporating the guardian maps (GM) theory to establish a transient trajectory design methodology, reconstructing the trajectory on-line and correcting the tracking commands [2,3]. Furthermore, one paper examines the problem of coupled orbit-attitude control for the flight of solar sail formation.…”