Model-Free Fuzzy Adaptive Control of the Heading Angle of Fixed-Wing Unmanned Aerial Vehicles
Publication: Journal of Aerospace Engineering
Volume 30, Issue 4
Abstract
In this paper, a novel model-free fuzzy adaptive control (MFFAC) scheme is developed to control the heading angle of fixed-wing unmanned aerial vehicles (UAVs). It is common knowledge that the aerodynamics of the heading angle of fixed-wing UAVs are difficult to accurately model and are subject to wind disturbances. Therefore, it is difficult to implement conventional model-based control to the heading angle control problem. To overcome this difficulty, the authors propose a novel data-driven control approach. First, an adaptive neuro-fuzzy inference system (ANFIS) is designed to estimate the pseudo partial derivative (PPD), which is described as an equivalent dynamic linearization (EDL) technique for unknown nonlinear systems. Secondly, an extended model-free adaptive control (MFAC) strategy is proposed to control the heading angle of fixed-wing UAVs with wind disturbances. Finally, a discrete Lyapunov-based stability analysis is presented to prove the globally asymptotic stability of the proposed control scheme. The high-fidelity semiphysical simulations illustrate that accurate and stable control is achieved in this designed control strategy.
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Acknowledgments
This work is supported by the National Natural Science Foundation (NNSF) of China under Grant 61403406.
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Published In
Journal of Aerospace Engineering
Volume 30 • Issue 4 • July 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Jan 12, 2016
Accepted: Dec 12, 2016
Published ahead of print: Feb 22, 2017
Published online: Feb 23, 2017
Published in print: Jul 1, 2017
Discussion open until: Jul 23, 2017
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