Detail publikace

Model-Based Attitude Estimation for Multicopters

BARÁNEK, R. ŠOLC, F.

Originální název

Model-Based Attitude Estimation for Multicopters

Anglický název

Model-Based Attitude Estimation for Multicopters

Jazyk

en

Originální abstrakt

The paper deals with model-based attitude estimation for multicopters and is mainly focused on investigation of accuracy degradation due to wind and inaccurate model parameters which are conditions always present when using in real world. At first the need for model-base estimation is motivated. Then the multicopter model is described. Based on the mathematical model of multicopter, the estimation algorithm utilizing the extended Kalman filter is constructed. The main contribution of the paper is the investigation of the negative impact of the wind and of inaccurate knowledge of the model parameters.

Anglický abstrakt

The paper deals with model-based attitude estimation for multicopters and is mainly focused on investigation of accuracy degradation due to wind and inaccurate model parameters which are conditions always present when using in real world. At first the need for model-base estimation is motivated. Then the multicopter model is described. Based on the mathematical model of multicopter, the estimation algorithm utilizing the extended Kalman filter is constructed. The main contribution of the paper is the investigation of the negative impact of the wind and of inaccurate knowledge of the model parameters.

Dokumenty

BibTex


@article{BUT111346,
  author="Radek {Baránek} and František {Šolc}",
  title="Model-Based Attitude Estimation for Multicopters",
  annote="The paper deals with model-based attitude estimation for multicopters and is mainly focused on investigation of accuracy degradation due to wind and inaccurate model parameters which are conditions always present when using in real world. At first the need for model-base estimation is motivated. Then the multicopter model is described. Based on the mathematical model of multicopter, the estimation algorithm utilizing the extended Kalman filter is constructed. The main
contribution of the paper is the investigation of the negative impact of the wind and of inaccurate knowledge of the model parameters.",
  chapter="111346",
  doi="10.15598/aeee.v12i5.1151",
  howpublished="online",
  number="5",
  volume="2014",
  year="2014",
  month="december",
  pages="501--510",
  type="journal article in Scopus"
}