Four-rotor aircraft adaptive neural network positioning control method based on visual feedback

Abstract

The invention discloses a four-rotor aircraft adaptive neural network positioning control method based on visual feedback. The method comprises the following steps of S1, determining a kinetic model equation of a four-rotor aircraft (QAR) according to the principles of aerodynamics and rigid mechanics, S2, establishing equivalent transformation between a position error and a projection image error by adopting a spherical projection method according to the kinetic model equation, S3, determining a linear velocity error differential equation of the QAR according to the spherical projection method and the kinetic model equation, S4, constructing a backstepping virtual attitude controller according to the linear velocity error differential equation of the QAR, S5, according to the backstepping controller, determining an operation equation of the adaptive controller based on the neural network, S6, according to the operation equation of the adaptive controller, constructing an inertia matrix estimator based on the Jorleski decomposition, and S7, calculating the position of the QAR according to the operation equation of the adaptive controller and the adaptive law equation, thereby realizing QAR visual position tracking control.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to a visual feedback-based adaptive neural network positioning control method for a quadrotor aircraft. Background technique [0002] In the past few decades, with the development of computer technology and camera equipment, visual servoing, which aims to control the movement of robots through visual feedback signals, has gradually developed into an independent discipline across the technical fields of robotics, automatic control and image processing. technology. In general, visual servoing can be divided into two types, namely position-based visual servoing (PBVS) and image-based visual servoing (IBVS). The IBVS method solves the servo problem by directly controlling the position error in image planning, which is more robust to disturbances and parameter deviations than the PBVS method. In the classic IBVS framework, the depth information of each feature point needs to be estim...

AI Technical Summary

Problems solved by technology

[0005] In view of the problems existing in the prior art, the purpose of the present invention is to provide a visual feedback-based adaptive neural network positioning control method for quadrotor aircraft, which solves the difficulty of high-precision positioning of quadrotor aerial robots, and the robot is under-actuated. The problem of large amount of calculation and lack of displayed inertia matrix realizes QAR visual position tracking control

Images