Non-linear Model-based Predictive Control for Trajectory Tracking and Control Effort Minimization in a Smartphone-based Quadrotor
DOI:
https://doi.org/10.14313/JAMRIS/4-2022/28Keywords:
Quadrotor, Model-based Predictive Control, Smartphone, Trajectory Tracking, Energy ConsumptionAbstract
In this paper, the design and implementation of a non-linear model-based predictive controller (NMPC) for predefined trajectory tracking and to minimize the control effort of a smartphone-based quadrotor is carried out. The optimal control actions are calculated in each iteration by means of an optimal control algorithm based on the non-linear model of the quadrotor, considering some aerodynamic effects. Control algorithm implementation and simulation tests are executed on a smartphone using the CasADi framework. In addition, a technique for estimating the energy consumed based on control signals is presented. NMPC controller performance is compared to an H-infinity controller and an LQI controller, using three predefined trajectories, where the NMPC average tracking error was around 50\% lower, and average estimated power and energy consumption slightly higher, with respect to the H-infinity and LQI controllers.
Downloads
Published
Issue
Section
License
Copyright (c) 2022 Journal of Automation, Mobile Robotics and Intelligent Systems

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.


