Direct thrust control for multivariable turbofan engine based on affine linear parameter-varying approach

A novel turbofan Direct Thrust Control (DTC) architecture based on Linear Parameter-Varying (LPV) approach for a two-spool turbofan engine thrust control is proposed in this paper. Instead of transforming thrust command to shaft speed command and pressure ratio command, the thrust will be directly controlled by an optimal controller with two control variables. LPV model of the engine is established for the designing of thrust estimator and controller. A robust LPV H_∞ filter is introduced to estimate the unmeasurable thrust according to measurable engine states. The thrust estimation error system is proved to be Affinely Quadratically Stable (AQS) in the whole parameter box with a prescribed H_∞ performance index γ. Due to the existence of overdetermined equations, the solving of controller parameters is a multi-solution problem. Therefore, Particle Swarm Optimization (PSO) algorithm is used to optimize the controller parameters to obtain satisfactory control performance based on the engine s LPV model. Numerical simulations show that the thrust estimator can acquire smooth and accurate estimating results when sensor noise exists. The optimal controller can receive desired control performance both in steady and transition control tasks within the engine working states above the idle, verifying the effectiveness of the proposed DTC architecture s application in thrust direct control problem.