Suspended load path tracking control based on zonotopic state estimation using a tilt-rotor UAV

2016 ◽  
Author(s):  
Brenner S. Rego ◽  
Guilherme V. Raffo
Keyword(s):  
State Estimation ◽  
Tracking Control ◽  
Suspended Load ◽  
Path Tracking ◽  
Load Path ◽  
Tilt Rotor

scholarly journals Suspended Load Path Tracking Control Strategy Using a Tilt-Rotor UAV

2017 ◽  
Vol 2017 ◽  
pp. 1-22 ◽  
Author(s):  
M. A. Santos ◽  
B. S. Rego ◽  
G. V. Raffo ◽  
A. Ferramosca
Keyword(s):  
Control Strategy ◽  
Degrees Of Freedom ◽  
Unscented Kalman Filter ◽  
Equations Of Motion ◽  
Suspended Load ◽  
Path Tracking ◽  
Total System ◽  
Load Path ◽  
Tilt Rotor ◽  
Lagrange Formulation

This work proposes a control strategy to solve the path tracking problem of a suspended load carried by a tilt-rotor unmanned aerial vehicle (UAV). Initially, the equations of motion for the multibody mechanical system are derived from the load’s perspective by means of the Euler-Lagrange formulation, in which the load’s position and orientation are chosen as degrees of freedom. An unscented Kalman filter (UKF) is designed for nonlinear state estimation of all the system states, assuming that available information is provided by noisy sensors with different sampling rates that do not directly measure the load’s attitude. Furthermore, a model predictive control (MPC) strategy is proposed for path tracking of the suspended load with stabilization of the tilt-rotor UAV when parametric uncertainties and external disturbances affect the load, the rope’s length and total system mass vary during taking-off and landing, and the desired yaw angle changes throughout the trajectory. Finally, numerical experiments are presented to corroborate the good performance of the proposed strategy.

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