Open AccessA Nonlinear UAV Control Tuning Under Communication Delay using HPC Strategies in Parameters Space
Author(s) -
Leonardo A. Fagundes-Júnior,
Michael Canesche,
Ricardo Ferreira,
Alexandre Santos Brandão
Publication year - 2021
Language(s) - English
Resource type - Conference proceedings
DOI - 10.5753/wscad.2021.18526
Subject(s) - computer science , matlab , convergence (economics) , speedup , task (project management) , stability (learning theory) , robot , set (abstract data type) , nonlinear system , control theory (sociology) , real time computing , control engineering , simulation , control (management) , artificial intelligence , engineering , parallel computing , physics , systems engineering , quantum mechanics , machine learning , economics , programming language , economic growth , operating system
In practical applications, the presence of delays can deteriorate the performance of the control system or even cause plant instability. However, by properly controlling these delays, it is possible to improve the performance of the mechanism. The present work is based on a proposal to analyze the asymptotic stability and convergence of a quadrotor robot, an unmanned aerial vehicle (UAV), on the performance of a given task, under time delay in the data flow. The effects of the communication delay problem, as well as the response-signal behavior of the quadrotors in the accomplishment of positioning mission are presented and analyzed from the insertion of fixed time delay intervals in the UAVs' data collected by its sensors system. Due to the large search space in the set of parameter combinations and the high computational cost required to perform such an analysis by sequentially executing thousands of simulations, this work proposes an open source GPU-based implementation to simulate the robot behavior. Experimental results show a speedup up to 4900x in comparison to MATLAB® implementation. The implement is available in Colab Google platform.