Design a Robust RST Controller for Stabilization of a Tri-Copter UAV

Research on the tri-rotor aerial robot is due to extra efficiency over other UAV’s regarding stability, power and size requirements. We require a controller to achieve 6-Degree Of Freedom (DOF), for such purpose, we propose the RST controller to operate our tri-copter model. A MIMO model of a tri-copter aerial robot is challenged in the area of control engineering. Ninestates of output control dynamics are treated individually. We designed dynamic controllers to stabilize the parameters of an UAV. The resulting system control algorithm is capable of stabilizing our UAV to perform numerous operations autonomously. The estimation and simulation implemented inMATLAB, Simulink to verify the results. All real flight test results are presented to prove the success of the planned control structure.

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Cognitive Multi-UAV Formation Flight: Principle, Low-Cost UAV Testbed, Controller Tuning and Experiments

Volume 3: 2011 ASME/IEEE International Conference on Mechatronic and Embedded Systems and Applications, Parts A and B ◽

10.1115/detc2011-47848 ◽

2011 ◽

Cited By ~ 8

Author(s):

Long Di ◽

Haiyang Chao ◽

Jinlu Han ◽

YangQuan Chen

Keyword(s):

Real Time ◽

Control Structure ◽

Low Cost ◽

Flight Test ◽

Formation Flight ◽

Experimental Setup ◽

Test Results ◽

Test Protocol ◽

Multi Agent ◽

Multi Uav

Cooperative UAV systems can have great advantages over isolated UAV systems, regarding application, safety, efficiency and many other perspectives. Motivated by challenges from practical multiple UAV formation flight, this paper presents our approaches towards cognitive formation flight. It introduces the principle ofmulti-UAV cognitive formation flight and the control structure utilized in our development, describes a low-cost UAV testbed developed by ourselves, and details the tuning procedures of the implemented multi-agent flight controller for stable and consistent formation flights. Different formation flight scenarios are also discussed and the experimental setup is presented including real-time issues and the formation flight test protocol. Routinized comprehensive flight test results are also shown at the end.

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Supersonic flight test results of a performance seeking control algorithm on a NASA-15 spacecraft

10.2514/6.1994-3210 ◽

1994 ◽

Cited By ~ 3

Author(s):

John Orme ◽

Timothy Conners

Keyword(s):

Control Algorithm ◽

Flight Test ◽

Test Results ◽

Supersonic Flight ◽

A Performance

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Flight test results for a high-capacity single-groove heat pipe

10.2514/6.1992-2887 ◽

1992 ◽

Author(s):

J. AMBROSE ◽

H. HOLMES ◽

R. CIMA ◽

M. KAPOLNEK

Keyword(s):

Heat Pipe ◽

High Capacity ◽

Flight Test ◽

Test Results

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Mission Adaptive Compliant Wing: Design, Performance and Flight Test Results

50th AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference ◽

10.2514/6.2009-2126 ◽

2009 ◽

Cited By ~ 8

Author(s):

Russell Osborn ◽

Sridhar Kota ◽

Greg Ervin ◽

Hal Youngren ◽

Peter Flick

Keyword(s):

Flight Test ◽

Test Results ◽

Wing Design ◽

Design Performance

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Advanced Fighter Technology Integration (AFTI)/F-16 Automated Maneuvering Attack System Final Flight Test Results

10.4271/871348 ◽

1987 ◽

Author(s):

Donald J. Dowden ◽

Denis E. Bessette

Keyword(s):

Technology Integration ◽

Flight Test ◽

Test Results

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Optical Navigation Sensor for Runway Relative Positioning of Aircraft during Final Approach

Sensors ◽

10.3390/s21062203 ◽

2021 ◽

Vol 21 (6) ◽

pp. 2203

Author(s):

Antal Hiba ◽

Attila Gáti ◽

Augustin Manecy

Keyword(s):

Optical Sensors ◽

Inertial Sensor ◽

Image Data ◽

Flight Test ◽

Image Features ◽

Wide Field ◽

Test Results ◽

Wide Field Of View ◽

Final Approach ◽

Marker Detection

Precise navigation is often performed by sensor fusion of different sensors. Among these sensors, optical sensors use image features to obtain the position and attitude of the camera. Runway relative navigation during final approach is a special case where robust and continuous detection of the runway is required. This paper presents a robust threshold marker detection method for monocular cameras and introduces an on-board real-time implementation with flight test results. Results with narrow and wide field-of-view optics are compared. The image processing approach is also evaluated on image data captured by a different on-board system. The pure optical approach of this paper increases sensor redundancy because it does not require input from an inertial sensor as most of the robust runway detectors.

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