Aviation engine direct thrust control method based on composite model predictive control

Abstract

The invention discloses an aviation engine direct thrust control method based on composite model predictive control. A nonlinear predictive model control method is used for directly controlling enginethrust; a predictive model used in the nonlinear predictive model control method is a composite predictive model established on the basis of an engine state variable model, a Kalman filter and an engine nonlinear model, and the Kalman filter calculates an engine degradation quantity by using the difference between an engine measurement parameter value and an engine nonlinear model calculation value and feeds the engine degradation quantity back to the engine nonlinear model; and the engine nonlinear model calculates an engine unmeasurable parameter and feeds the engine unmeasurable parametertogether with the engine degradation quantity back to the engine state variable model, and the engine state variable model obtains a predicted control quantity through real-time rolling optimization.Compared with the prior art, the real-time performance of the engine model predictive control can be effectively improved.

Description

technical field [0001] The invention belongs to the technical field of system control and simulation in aerospace propulsion theory and engineering, and in particular relates to an aeroengine direct thrust control method based on composite model predictive control. Background technique [0002] How to quickly and accurately provide thrust to aircraft is an important performance index of aero-engines. Traditional aeroengine controllers control thrust indirectly by controlling engine measurable parameters that are specifically related to thrust, such as rotor speed and engine boost ratio. However, due to the degradation of the aero-engine due to natural wear, corrosion and other reasons during the service cycle, and tolerances will be produced in the manufacturing and installation, these will cause deviations in the mapping relationship between these measurable parameters and the required thrust. If we continue to Control errors are unavoidable using measurable parameters rel...

AI Technical Summary

Problems solved by technology

Due to the high control precision of EKF-based NMPC and the application of engine degradation, it has attracted much attention. However, EKF is linearized online through the component-level model. Due to the high computational complexity of the component-level model, the engine is a strongly nonlinear object. , so the single-step calculation time requirement must be short, so it is difficult to guarantee the real-time performance of EKF

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