Fuzzy adaptive PID controller design method of aero-engine based on RBF neural network feedforward

Abstract

The invention discloses a fuzzy PID adaptive controller design method of an aero-engine based on RBF neural network feedforward and belongs to the aero-engine numerical control system field. The method is used for improving acceleration and deceleration work states of the aero-engine and components under effects of an extraneous condition and internal control so that the engine possesses a good acceleration and deceleration characteristic. The technical scheme is characterized by based on an aero-engine steady state test data sample, using an RBF neural network to carry out off-line training so as to form a feedforward controller; and based on that, adding a fuzzy adaptive PID controller. In the invention, through carrying out acceleration and deceleration control on each state of the aero-engine, the controller possesses a good tracking effect and a good controller parameter online setting capability, control quality of the system in a large range can be further increased and a control difficulty brought by a non-linear characteristic of the engine can be effectively solved.

Description

technical field [0001] The invention discloses a fuzzy self-adaptive PID controller design method based on RBF neural network feedforward for an aero-engine, which belongs to the field of aero-engine numerical control systems and is used to improve the acceleration and deceleration of aero-engines and their components under the influence of external conditions and internal control The working state makes the engine have good acceleration and deceleration characteristics. Background technique [0002] Aeroengines and their components have a wide operating range under the influence of external conditions and internal controls. The external conditions mainly include: the total temperature and total pressure of the engine inlet determined by the flight M number and flight altitude. Its internal control functions mainly include: the amount of fuel in the main combustion chamber and the afterburner, the throat area of ​​the reaction nozzle, the installation angle of the blades (f...

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Problems solved by technology

[0009] The technical problem to be solved by the present invention is to consider that the aeroengine and its components have a wide operating range under the influence of external conditions and internal control, so that the characteristics of the engine in this operating range vary greatly, and the process is complicated. The working process of aerodynamic thermodynamics has strong nonlinear characteristics, and the design method of fuzzy adaptive PID controller based on RBF neural network feedforward is designed to improve the acceleration and deceleration work of aeroengines and their components under the influence of external conditions and internal control state, so that the engine has good acceleration and deceleration characteristics

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