Real-time embedded sliding mode observer for quadcopter UAVs

Mohammad osman Tokhi; Mohammad Osman

Real-time embedded sliding mode observer for quadcopter UAVs

Mohammad osman Tokhi, Mohammad Osman

Electrical and Electronic Engineering (302)

Research output: Contribution to conference › Paper › peer-review

Abstract

Sliding mode observer (SMO) as a nonlinear and robust observer, is believed to be able to provide all required states information for control process of quadcopter UAVs. In this paper, a comparative assessment through numerical simulation is conducted between SMO and Extended Kalman Filter (EKF) to demonstrate the performance of both estimators. The results obtained demonstrate good performance of SMO in dealing with noise and uncertainty. Furthermore, experiments are carried out to validate the performance of SMO in real-time. The results show that estimated states can track true states fast with small estimation steady state errors and the observer estimates the unmeasured states smoothly.

Original language	English
Publication status	Published - 11 Sept 2017
Event	20th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines - School of Engineering of the Porto Polytechnic, Porto, Portugal Duration: 11 Sept 2017 → 13 Sept 2017

Conference

Conference	20th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines
Abbreviated title	CLAWAR 2017
Country/Territory	Portugal
City	Porto
Period	11/09/17 → 13/09/17
Other	The 20th International Conference on Climbing and Walking Robots and Support Technologies for Mobile Machines (CLAWAR 2017), will be held within the premises of the School of Engineering of the Porto Polytechnic, Portugal, during 11 – 13 September 2017, continuing a series of successful events all over the world. CLAWAR 2017 will feature technical and social programs. The technical program will comprise plenary, regular and special/invited sessions. All articles submitted for inclusion in the conference will be peer reviewed before acceptance. It is envisaged that all accepted papers will appear in the conference proceedings, to be published by World Scientific Publishing Company, as well as on CD/flash drive, subject to registration of at least one author for presenting the work. A selection of presented papers will also be recommended for possible publication in reputable international journals.

Keywords

Nonlinear systems; quadcopter; sliding mode observer; extended Kalman filter.

Cite this

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title = "Real-time embedded sliding mode observer for quadcopter UAVs",

abstract = "Sliding mode observer (SMO) as a nonlinear and robust observer, is believed to be able to provide all required states information for control process of quadcopter UAVs. In this paper, a comparative assessment through numerical simulation is conducted between SMO and Extended Kalman Filter (EKF) to demonstrate the performance of both estimators. The results obtained demonstrate good performance of SMO in dealing with noise and uncertainty. Furthermore, experiments are carried out to validate the performance of SMO in real-time. The results show that estimated states can track true states fast with small estimation steady state errors and the observer estimates the unmeasured states smoothly.",

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T1 - Real-time embedded sliding mode observer for quadcopter UAVs

AU - Tokhi, Mohammad osman

AU - Osman, Mohammad

PY - 2017/9/11

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N2 - Sliding mode observer (SMO) as a nonlinear and robust observer, is believed to be able to provide all required states information for control process of quadcopter UAVs. In this paper, a comparative assessment through numerical simulation is conducted between SMO and Extended Kalman Filter (EKF) to demonstrate the performance of both estimators. The results obtained demonstrate good performance of SMO in dealing with noise and uncertainty. Furthermore, experiments are carried out to validate the performance of SMO in real-time. The results show that estimated states can track true states fast with small estimation steady state errors and the observer estimates the unmeasured states smoothly.

AB - Sliding mode observer (SMO) as a nonlinear and robust observer, is believed to be able to provide all required states information for control process of quadcopter UAVs. In this paper, a comparative assessment through numerical simulation is conducted between SMO and Extended Kalman Filter (EKF) to demonstrate the performance of both estimators. The results obtained demonstrate good performance of SMO in dealing with noise and uncertainty. Furthermore, experiments are carried out to validate the performance of SMO in real-time. The results show that estimated states can track true states fast with small estimation steady state errors and the observer estimates the unmeasured states smoothly.

KW - Nonlinear systems; quadcopter; sliding mode observer; extended Kalman filter.

M3 - Paper

T2 - 20th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines

Y2 - 11 September 2017 through 13 September 2017

ER -

Real-time embedded sliding mode observer for quadcopter UAVs

Abstract

Conference

Keywords

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