Turbofan engine thrust prediction method and controller based on neural network

Abstract

The invention discloses a turbofan engine thrust prediction method and a turbofan engine thrust prediction controller based on a neural network. The turbofan engine thrust prediction method comprisesthe steps of: establishing a steady-state multiple-input multiple-output neural network model of turbofan engine key gas path measurement parameters; using the neural network model as a prediction model for designing a thrust model prediction controller; designing a certain type of turbofan engine closed-loop control system by using the model prediction controller, and studying tracking performance and constraint performance of a thrust control system. On the basis of considering the existing control constraint conditions of an engine, the turbofan engine thrust prediction method utilizes thesteady-state neural network model combined with an SQP optimization algorithm, regards the minimum error of unmeasurable thrust performance parameters of the engine as a target, designs the thrust prediction controller, calculates a control quantity of the engine, is simple in structure, and has a positive promoting effect on reduction of the workload of designing the controller and suppression ofthrust performance degradation of the controller.

Description

technical field [0001] The invention belongs to the field of aero-engine simulation and control, and in particular relates to a neural network-based turbofan engine thrust prediction method and a controller. Background technique [0002] Due to the continuous improvement of aero-engine technology, the performance requirements of the engine control system are also getting higher and higher. The traditional control method satisfies all constraints at the expense of engine performance, and it is difficult to meet the increasingly higher performance requirements of the engine. Compared with traditional control methods, model predictive control (Model Predictive Control, MPC) can not only deal with the problems of time delay and limit constraints of the system, but also realize optimal control based on the predictive model, so that the control system has good control performance, and Meet control needs. [0003] The coupling of mechanical, fluid and thermal effects in an aeroen...

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Problems solved by technology

[0005] The technical problem to be solved by the present invention is to aim at the defects of the background technology, design a turbofan engine thrust prediction controller based on a steady-state multiple-input multiple-output neural network model, and use it to solve the problems of engine constraints, nonlinear characteristics and dynamic model-based Problems with long response times for predictive controllers with good tracking and constraint performance

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