Design and implementation of MPC for turbofan engine control system

Abstract

The objective of an aircraft engine control system is to provide required thrust as well as protection against the physical and operational limits. Model predictive control (MPC) technique is an attractive approach that incorporates input/output constraints in its optimization process to fulfill the control requirements of an aircraft engine. However, due to heavy computational burden of MPC, the real-time implementation of this algorithm is challenging and selection of MPC design parameters is crucial. This paper presents the design and hardware implementation of MPC algorithm as well as its HIL testing for turbofan engine control. In addition, a feedback correction technique is employed to compensate the effect of plant-model mismatch. For this purpose, a thermodynamic nonlinear engine model is firstly developed. A multivariable model predictive controller is then designed based on a discrete-time linearized state-space model where the horizons are obtained through a genetic algorithm optimization procedure. Moreover, this controller is implemented on an appropriate hardware taking the real-time aspects into account. Finally, an HIL platform is developed for testing the turbofan engine electronic control unit (ECU). For this purpose, a multi-level throttle command is applied to the ECU and the performance of the engine is evaluated. The results indicate that the controller satisfies all the engine constraints, and confirm the successful software and hardware implementation of the control algorithm in real-time.