2016 IEEE 55th Conference on Decision and Control (CDC) 2016
DOI: 10.1109/cdc.2016.7799367
|View full text |Cite
|
Sign up to set email alerts
|

A semi-global model-based state observer for the quadrotor using only inertial measurements

Abstract: We propose a nonlinear observer to estimate the state (orientation and in-plane velocity vector) of the quadrotor, based on a drag-force-enhanced model. It is a simpler and more robust alternative to recent works using a similar model together with an Extended Kalman Filter (EKF). A particular state over-parameterization leads to a linear time-varying model with a nonlinear state-constraint that serves for the observer design. The proposed observer is able to ensure the uniform semi-global asymptotic stability… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1

Citation Types

0
5
0

Year Published

2017
2017
2020
2020

Publication Types

Select...
5
2

Relationship

1
6

Authors

Journals

citations
Cited by 8 publications
(5 citation statements)
references
References 11 publications
(18 reference statements)
0
5
0
Order By: Relevance
“…In this subsection we will consider the problem of localization of each agent with respect to its neighbors by incorporating local, noiseless measurements, and considering a static target. This will be achieved by means of a designed nonlinear observer based on the invariant-manifold observer methodology, see Astolfi et al 27 and Karagiannis and Astolfi 18 for the general setting and Martin and Sarras, 28 Martin and Sarras, 29 and Sarras et al 12 for recent applications on MAVs. Proposition 1.…”
Section: Single Vehicle Localization From Direct Local Measurements: mentioning
confidence: 99%
“…In this subsection we will consider the problem of localization of each agent with respect to its neighbors by incorporating local, noiseless measurements, and considering a static target. This will be achieved by means of a designed nonlinear observer based on the invariant-manifold observer methodology, see Astolfi et al 27 and Karagiannis and Astolfi 18 for the general setting and Martin and Sarras, 28 Martin and Sarras, 29 and Sarras et al 12 for recent applications on MAVs. Proposition 1.…”
Section: Single Vehicle Localization From Direct Local Measurements: mentioning
confidence: 99%
“…A dynamical model of the system can be used to predict the accelerations and compensate for them. This prediction can be based on the forces models, either in the case of unmanned aerial vehicles [14,15] or legged robots [4,17]. However this solution is specific to every dynamical system and requires to identify many dynamical parameters.…”
Section: Introductionmentioning
confidence: 99%
“…Classical approaches for state estimation are typically based on filtering techniques such as extended Kalman filters (EKF), unscented Kalman filters or particle filters. However, nonlinear observers have increasingly become an alternative to these classical techniques, starting with the work of Salcudean on attitude observer [20] and subsequent contributions by other researchers [1], [5], [6], [8], [10], [15]- [19]. Full pose observer design has recently attracted some particular attention [2]- [4], [9], [11], [13]- [15], [21]- [23].…”
Section: Introductionmentioning
confidence: 99%