Title
Position control of a quadrotor MAV while compensating for discrete jumps in the pose estimate
Author
van Namen, Rick (TU Delft Mechanical, Maritime and Materials Engineering; TU Delft Biomechanical Engineering)
Contributor
de Visser, C.C. (mentor)
Wisse, M. (graduation committee)
Anil Meera, A. (graduation committee)
Degree granting institution
Delft University of Technology
Programme
Biomedical Engineering
Date
2019-11-21
Abstract
The trajectory tracking efficiency of a quadrotor Micro Aerial Vehicle (MAV) position controller is decreased by discrete jumps in the pose estimate provided by a localization algorithm. This paper presents a solution to this problem by first introducing a new quadrotor MAV position control architecture followed by two methods that can compensate for the jumps in the pose estimate. The new control architecture consists of Model Predictive Control (MPC) for the outer position control loop and Incremental Nonlinear Dynamic Inversion (INDI) to control the inner angular accelerations. The attitude itself is controlled with a Proportional-Derivative (PD) controller. The first method that compensates for the jumps in the pose estimate considers an adaptive control law that changes the weights in the MPC cost function when the quadrotor's position is known to be uncertain. The second method applies a filter to the reference signal before providing it to the controller. Simulations validate the proposed controller architecture and show that the adaptive controller and the controller with reference filter decrease the covered distance during a flight mission by 6.7% and 7.0%, respectively, compared to the controller without these enhancements. Therefore, the efficiency of the trajectory tracking is increased.
Subject
Micro Aerial Vehicle
position control
Model Predictive Control
Incremental Nonlinear Dynamic Inversion
localization uncertainty
pose estimate
To reference this document use:
http://resolver.tudelft.nl/uuid:ef3c588b-b801-4256-9e06-cba8299cc726
Embargo date
2024-11-06
Part of collection
Student theses
Document type
master thesis
Rights
© 2019 Rick van Namen