Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

A method of aircraft attitude control based on deep learning

An attitude control and deep learning technology, applied in the field of deep learning and flight control, can solve the problems of inability to intelligently control the aircraft attitude, fixed single calculation method, many steps, etc., to achieve good development prospects, fast convergence speed, parameter less effect

Active Publication Date: 2020-11-03
北京元晨华盛科技有限公司
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The existing technology is to classify and calculate the due aircraft attitude control amount according to certain rules according to the aircraft parameters. The calculation method is fixed and single, with many steps, and it is impossible to intelligently control the aircraft attitude.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • A method of aircraft attitude control based on deep learning
  • A method of aircraft attitude control based on deep learning
  • A method of aircraft attitude control based on deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0052] A specific embodiment of the present invention will be described in detail below in conjunction with the accompanying drawings, but it should be understood that the protection scope of the present invention is not limited by the specific embodiment.

[0053] This example provides an aircraft attitude control method based on deep learning, and its flow chart is as follows figure 1 As shown, the specific steps are as follows:

[0054] S1. Collect the status data of the aircraft in real time, and normalize the data.

[0055] S2. Input the normalized data into the aircraft attitude control network to obtain the control amount of the aircraft attitude. Among them, the aircraft attitude control amount is the rate of change of the angle of attack and rate of change of tilt angle Among them, a represents the angle of attack, θ represents the angle of inclination, represents the rate of change of the angle of attack, Indicates the rate of change of the tilt angle, t indic...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

PUM

No PUM Login to View More

Abstract

The invention discloses an aircraft attitude control method based on deep learning, comprising the steps of S1, acquiring 47 pieces of state data of an aircraft in real time and normalizing the data;S2, inputting the normalized data into an aircraft attitude control network to obtain two aircraft attitude control quantities including an angle of attack change rate and an angle of inclination change rate which are described in the specification; and S3, after the aircraft attitude control quantities are obtained, calculating attitude parameters, including an angle of attack at+[delta]t and anangle of inclination [theta]t+[delta]t, required by the aircraft. Compared with an existing aircraft attitude control method, the method of the invention directly inputs the aircraft parameters into the constructed aircraft attitude control network, thereby obtaining the attitude parameters. The method constructs a network for extracting a relationship between data by using an intelligent manner,and eliminates a calculation steps in the prior art, and achieves high accuracy.

Description

technical field [0001] The invention relates to the fields of deep learning and flight control, in particular to an aircraft attitude control method based on deep learning. Background technique [0002] With the development of combat aircraft in the direction of informatization, integration, and intelligence, the information provided to pilots has exploded, and it is almost impossible for pilots to make timely and correct flight decisions. Therefore, it is particularly important to establish an aircraft attitude control method and use it in the auxiliary decision-making of pilots in today's battlefield environment. [0003] However, most of the currently existing aircraft attitude control methods use certain formulas to calculate the attitude parameters. The existing technology is to initialize the relative situation, position and speed information, attitude information, weapon state, experimental simulation time and maneuvering scheme of both sides before the simulation ca...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to View More

Application Information

Patent Timeline
no application Login to View More
Patent Type & Authority Patents(China)
IPC IPC(8): G05D1/08
CPCG05D1/0808
Inventor 李波梁诗阳李曦彤高晓光高佩忻
Owner 北京元晨华盛科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com