公开(公告)号：US11721219B2

公开(公告)日：2023-08-08

申请号：US16652457

申请日：2018-10-26

Applicant: South China University of Technology

Inventor： Zhijun Zhang ,  Lu'nan Zheng ,  Dongyu Ji

IPC: G08G5/00 ,  B64C39/02 ,  G05D1/08 ,  G05D1/00 ,  B64U30/20 ,  B64U101/00

CPC classification number: G08G5/003 ,  B64C39/024 ,  G05D1/0088 ,  G05D1/0816 ,  B64U30/20 ,  B64U2101/00

Abstract: Disclosed is a method for controlling stable flight of an unmanned aircraft, comprising the following steps: acquiring real-time flight operation data of the aircraft itself by means of an attitude sensor, a position sensor and an altitude sensor mounted to the unmanned aircraft, performing corresponding analysis on a kinematic problem of the aircraft by a processor mounted thereto, and establishing a dynamics model of the aircraft (S1); designing a controller of the unmanned aircraft according to a multi-layer zeroing neurodynamic method (S2); solving output control quantities of motors of the aircraft by the designed multi-layer zeroing neural network controller using the acquired real-time operation data of the aircraft and target attitude data (S3); and transferring solution results to a motor governor of the aircraft, and controlling powers of the motors according to a relationship between the control quantities solved by the controller and the powers of the motors of the multi-rotor unmanned aircraft, so as to control the motion of the unmanned aircraft (S4). Based on the multi-layer zeroing neurodynamic method, a correct solution to the problem can be approached rapidly, accurately and in real time, and a time-varying problem can be significantly solved.

公开(公告)号：US20220036739A1

公开(公告)日：2022-02-03

申请号：US16652457

申请日：2018-10-26

Applicant: South China University of Technology

Inventor： Zhijun Zhang ,  Lu'nan Zheng ,  Dongyu Ji

IPC: G08G5/00 ,  G05D1/08 ,  B64C39/02

Abstract: Disclosed is a method for controlling stable flight of an unmanned aircraft, comprising the following steps: acquiring real-time flight operation data of the aircraft itself by means of an attitude sensor, a position sensor and an altitude sensor mounted to the unmanned aircraft, performing corresponding analysis on a kinematic problem of the aircraft by a processor mounted thereto, and establishing a dynamics model of the aircraft (S1); designing a controller of the unmanned aircraft according to a multi-layer zeroing neurodynamic method (S2); solving output control quantities of motors of the aircraft by the designed multi-layer zeroing neural network controller using the acquired real-time operation data of the aircraft and target attitude data (S3); and transferring solution results to a motor governor of the aircraft, and controlling powers of the motors according to a relationship between the control quantities solved by the controller and the powers of the motors of the multi-rotor unmanned aircraft, so as to control the motion of the unmanned aircraft (S4). Based on the multi-layer zeroing neurodynamic method, a correct solution to the problem can be approached rapidly, accurately and in real time, and a time-varying problem can be significantly solved.