Trajectory tracking of under-actuated quadcopter using Lyapunov-based optimum adaptive controller

In this article, optimum adaptive sliding mode controller (ASMC) optimized by particle swarm optimization (PSO) algorithm is designed to solve the trajectory tracking control problems of a quadcopter with model parameter uncertainties. Quadcopters have nonlinear, multi-input multi-output, coupled an...

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Bibliographic Details
Published in:Proceedings of the Institution of Mechanical Engineers. Part G, Journal of aerospace engineering Journal of aerospace engineering, 2022-01, Vol.236 (1), p.202-215
Main Authors: Navabi, M, Davoodi, Ali, Mirzaei, Hamidreza
Format: Article
Language:English
Subjects:
Adaptive control
Algorithms
Control systems design
Controllers
Feedback control
Helicopters
Mathematical models
Parameter uncertainty
Particle swarm optimization
Reference signals
Sliding mode control
Tracking control
Trajectory control
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Summary:In this article, optimum adaptive sliding mode controller (ASMC) optimized by particle swarm optimization (PSO) algorithm is designed to solve the trajectory tracking control problems of a quadcopter with model parameter uncertainties. Quadcopters have nonlinear, multi-input multi-output, coupled and under-actuated dynamics. For comparison with the designed controller, an adaptive integral backstepping controller approach is applied to compensate mass and inertia uncertainties of the flying robot. These methods guarantee stability of closed-loop system and force the states to track desired reference signals. The performance of both controllers is evaluated by numerical simulations. The obtained results demonstrate the better effectiveness of the designed PSO ASMC in stabilization of tracking particularly with parameter uncertainties.
ISSN:0954-4100
2041-3025
DOI:10.1177/09544100211010852