Adaptive nonlinear model predictive path-following control for a fixed-wing unmanned aerial vehicle

2013 ◽  
Vol 11 (1) ◽  
pp. 65-74 ◽  
Author(s):  
Kwangjin Yang ◽  
Yeonsik Kang ◽  
Salah Sukkarieh
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Nonlinear Model ◽  
Path Following ◽  
Path Following Control ◽  
Aerial Vehicle

Collision Avoidance and Path Following Control of Unmanned Aerial Vehicle in Hazardous Environment

2018 ◽  
Vol 95 (1) ◽  
pp. 193-210 ◽  
Author(s):  
Zhixiang Liu ◽  
Youmin Zhang ◽  
Chi Yuan ◽  
Laurent Ciarletta ◽  
Didier Theilliol
Keyword(s):  
Collision Avoidance ◽  
Unmanned Aerial Vehicle ◽  
Path Following ◽  
Path Following Control ◽  
Aerial Vehicle

scholarly journals Path Following Control for Miniature Fixed Wing Unmanned Aerial Vehicle Under Uncertainties and Disturbances：A Two-Layered Framework

2021 ◽  
Author(s):  
Weinan Wu ◽  
Yao Wang ◽  
Chunlin Gong ◽  
Dan Ma
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Feedback Linearization ◽  
Vector Fields ◽  
Control Level ◽  
Path Following ◽  
Control Effort ◽  
Path Following Control ◽  
Straight Line ◽  
Control Scheme ◽  
Aerial Vehicle

Abstract In this paper a solution to the path following control problem for miniature fixed wing unmanned aerial vehicle (MAV) in the presence of inaccuracy modelling parameters and environmental disturbances is presented. We introduce a two-layered framework to collaborate guidance level with control level. A modified vector fields based path following methodology is proposed in the kinematics phase to track a Dubins path with straight line segments and circle ones. Then a Proportional-Integral-Derivative (PID) controller based on feedback linearization and gain scheduling techniques is designed such that the MAV can reject nonlinear dynamics, system uncertainties and disturbances by using a robust fuzzy control scheme. Eventually, by giving comparison test with control effort and track error as assessment metrics, both the practicality of the framework and the outperformance of the proposed algorithm are well demonstrated.

scholarly journals Implementation of Nonlinear Model Predictive Path-Following Control for an Industrial Robot

2017 ◽  
Vol 25 (4) ◽  
pp. 1505-1511 ◽  
Author(s):  
Timm Faulwasser ◽  
Tobias Weber ◽  
Pablo Zometa ◽  
Rolf Findeisen
Keyword(s):  
Nonlinear Model ◽  
Industrial Robot ◽  
Path Following ◽  
Path Following Control

scholarly journals Nonlinear Model Predictive Control for the Stabilization of a Wheeled Unmanned Aerial Vehicle on a Pipe

2019 ◽  
Vol 4 (4) ◽  
pp. 4314-4321
Author(s):  
Suping Zhao ◽  
Fabio Ruggiero ◽  
Giuseppe Andrea Fontanelli ◽  
Vincenzo Lippiello ◽  
Zhanxia Zhu ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Unmanned Aerial Vehicle ◽  
Predictive Control ◽  
Nonlinear Model ◽  
Nonlinear Model Predictive Control ◽  
Aerial Vehicle

scholarly journals Improved Area Covering in Dynamic Environments by Nonlinear Model Predictive Path Following Control

2019 ◽  
Vol 52 (15) ◽  
pp. 418-423
Author(s):  
M. Ibrahim ◽  
J. Matschek ◽  
B. Morabito ◽  
R. Findeisen
Keyword(s):  
Nonlinear Model ◽  
Path Following ◽  
Dynamic Environments ◽  
Path Following Control
Sign in / Sign up

Export Citation Format

Share Document