Optimal attitude tracking control for an unmanned aerial quadrotor under lumped disturbances

The robust control problem in attitude tracking of an unmanned aerial vehicle quadrotor is a challenging task due to strong parametric uncertainties, large nonlinearities and high couplings in flight dynamics. In this paper, a continuous nonsingular fast terminal sliding mode controller based on lin...

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Bibliographic Details
Published in:International journal of micro air vehicles Vol. 12
Main Authors: Ding, Li, Li, Yangmin
Format: Journal Article
Language:English
Published: London, England SAGE Publications 2020
Sage Publications Ltd
Subjects:
Adaptive algorithms
Adaptive control
Aerodynamics
Attitude control
Control methods
Controllers
Couplings
Disturbances
Optimization
Robust control
Sliding mode control
State observers
Tracking control
Uncertainty
Unmanned aerial vehicles
Unmanned helicopters
terminal sliding mode
attitude tracking control
fruit fly optimization algorithm
linear extended state observer
Quadrotor
ISSN:1756-8293, 1756-8307
Online Access:Get full text
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Summary:The robust control problem in attitude tracking of an unmanned aerial vehicle quadrotor is a challenging task due to strong parametric uncertainties, large nonlinearities and high couplings in flight dynamics. In this paper, a continuous nonsingular fast terminal sliding mode controller based on linear extended state observer is proposed for attitude tracking control of a quadrotor under lumped disturbances. The proposed control method requires no prior knowledge of the attitude dynamics. It can ensure rapid convergence rate and high tracking precision due to terminal sliding mode surface and fast reaching law. The controller uses the linear extended state observer to reject the influence of both parametric uncertainties and external disturbances. Meanwhile, the nonsingular fast terminal sliding mode control strategy is designed to ensure the state variables to slide to desired points in finite time. To enhance the control performance, a self-adaptive fruit fly optimization algorithm is applied to parameters tuning of the proposed controller. The effectiveness of the proposed control approach is illustrated through numerical simulations and experimental verification.
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ISSN:1756-8293
1756-8307
DOI:10.1177/1756829320923563