Abstract
The combination of pursuit and line of sight guidance laws, called PLOS, is used to steer an unmanned aerial vehicle along a desired path. In the previous studies, the parameters of this guidance law are tuned by trial and error and are constant, during the flight. In this research, it will be shown that the optimal value of these parameters depends on the initial conditions of the problem and the wind conditions. For this reason, a fuzzy system is proposed to generate the instantaneous optimal value of these parameters, in such a way that the flying vehicle converges to the desired path in less time and follows it more accurately, in the presence of wind. For this purpose, a cost function is defined to penalize the distance from the desired path and the control effort. Then, the parameters of the fuzzy system are optimized for different initial and wind conditions. During the flight, the optimized fuzzy systems determine the parameters of the guidance algorithm in an online manner, in such a way that the desired path is better followed. The obtained results show that online adjustment of the PLOS guidance law improves its performance in the presence of wind by about 20%.
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Data Availability
The codes generated during the current study are available from the corresponding author on reasonable request. All data generated for analysis during this study are included in this published article
All data generated for analyzed during this study are included in this published article.
Javad Asghari]; Writing - original draft preparation: [Javad Asghari]; Writing - review and editing: [Hadi Nobahari]; Supervision: [Hadi Nobahari].
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Conceptualization: [Hadi Nobahari]; Data curation: [Javad Asghari]; Formal analysis and investigation: [Javad Asghari]; Methodology: [Hadi Nobahari, Javad Asghari]; Software: [Javad Asghari]; Validation: [Hadi Nobahari, Javad Asghari]; Visualization: [Hadi Nobahari,
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Nobahari, H., Asghari, J. A Fuzzy-PLOS Guidance Law for Precise Trajectory Tracking of a UAV in the Presence of Wind. J Intell Robot Syst 105, 18 (2022). https://doi.org/10.1007/s10846-022-01635-y
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DOI: https://doi.org/10.1007/s10846-022-01635-y