Carrier rocket load shedding control method based on inverse reinforcement learning

Abstract

The invention provides a carrier rocket load shedding control method based on inverse reinforcement learning. The carrier rocket load shedding control method comprises the following specific steps: 1, establishing a carrier rocket dynamic model considering a wind field condition; 2, generating a passive load shedding expert demonstration; 3, training an inverse reinforcement learning load shedding control strategy; and 4, migrating the load shedding controller, that is, load shedding control strategy network parameters obtained through training are solidified, a closed loop is achieved through input and output interfaces of carrier rocket dynamics, and the load shedding controller serves as the load shedding controller. Through the above steps, the method can achieve the load shedding control of the carrier rocket, solves a problem that the existing method depends on precise wind field information and cannot guarantee the guidance precision, and achieves better stability and universality. The guidance control method is scientific and good in manufacturability and has wide application and popularization value.

Description

technical field [0001] The invention provides a carrier rocket load reduction control method based on inverse reinforcement learning, which is a guidance control method for autonomously adjusting the attitude of the carrier rocket ascending section in a dense atmosphere to reduce the aerodynamic load, applicable to general carrier rockets, and belongs to aviation Aerospace; Guidance, navigation and control technology; Reinforcement learning control field; Background technique [0002] During the ascent flight of the launch vehicle, the rocket body flying at high speed interacts with the airflow, causing the rocket body to be subjected to aerodynamic force and aerodynamic moment, which is called aerodynamic load. Moment balance, thereby generating internal force bending moment in the rocket body; due to the high slenderness ratio of the launch vehicle, the above internal force bending moment is likely to cause instability or even destruction of the launch vehicle structure; ...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to solve the above problems, and propose a load reduction control method based on inverse reinforcement learning, that is, a load reduction control method for the ascent of a launch vehicle, through inverse reinforcement learning load reduction index deduction and load reduction control strategy Training, to obtain a load reduction control strategy that is adaptable to the wind field and can guarantee the guidance accuracy, so as to solve the problems existing in the existing technology that rely on accurate wind field information and cannot guarantee the guidance accuracy, and improve the reliability of the launch vehicle;

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