Real-time embedded sliding mode observer for quadcopter UAVs
Firdaus, AR and Tokhi, MO (2017). Real-time embedded sliding mode observer for quadcopter UAVs. CLAWAR 2017: 20th International Conference on Climbing and Walking Robots and the Support Technologies for Mobile Machines. Porto, Portugal 11 - 13 Sep 2017 London South Bank University.
|Authors||Firdaus, AR and Tokhi, MO|
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.
|Keywords||Nonlinear systems; quadcopter; sliding mode observer; extended Kalman filter.|
|Publisher||London South Bank University|
|Accepted author manuscript|
CC BY 4.0
|11 Sep 2017|
|Publication process dates|
|Deposited||15 Dec 2017|
|Accepted||01 Jul 2017|
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