Depending on the amount of data to process, file generation may take longer.

If it takes too long to generate, you can limit the data by, for example, reducing the range of years.

Chapter

Download BibTeX

Title

An Efficient PSO-Based Method for an Identification of a Quadrotor Model Parameters

Authors

[ 1 ] Instytut Automatyki i Inżynierii Informatycznej, Wydział Elektryczny, Politechnika Poznańska | [ D ] phd student | [ P ] employee

Year of publication

2015

Chapter type

chapter in monograph

Publication language

english

Keywords
EN
  • mathematical modeling
  • identication
  • particle swarm optimization
Abstract

EN This paper considers the method of Quadrotor’s model parameters identification. Nowadays, restrictions are being imposed on the drons, forcing their control algorithms to be robust and faultless. This can be partially ensured by Model Reference Adaptive Control (MRAC) as well as dedicated state estimators (e.g. Extended Kalman Filter). Although those methods can be easy implemented and used, in all scenario, the parameterized model is needed. In this work we proposed the identification method for parameters of the quadrotor’s orientation model, based on the PSO (Particle Swarm Optimization). We also add different physical aspects to model, so it can characterize the real Quadrotor more precisely. The conducted experiments shows that the PSO, can provide fast and reliable estimation of the model parameters. It also reveals interesting nature of the proposed models.

Pages (from - to)

95 - 104

DOI

10.1007/978-3-319-15847-1_10

URL

https://link.springer.com/chapter/10.1007/978-3-319-15847-1_10

Book

Progress in Automation, Robotics and Measuring Techniques : Volume 2 Robotics

Presented on

International Conference on Automation, ICA 2015, 18-20.03.2015, Warsaw, Poland

This website uses cookies to remember the authenticated session of the user. For more information, read about Cookies and Privacy Policy.