Abstract
A key problem in the fixed-wing UAVs control with constraints is the time consumption of objective function optimization. In this paper, considering multiple constraints, an improved model predictive control algorithm for the path planning problem of fixed-wing UAVs is proposed to reduce the computer storage requirements and enhance the calculation efficiency. The improved MPC and the inner loop controller are combined in Matlab and Simulink for verification, which shows that our method has a faster convergence of the fixed-wing UAVs positions into a desired formation.
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Acknowledgements
This work is supported by the National Natural Science Foundation of China (61803309, 61703343), Fundamental Research Funds for the Central Universities (3102019ZDHKY02, 3102018JCC003), China Postdoctoral Science Foundation (2018M633574), Key Research and Development Project of Shaanxi Province (2020ZDLGY06-02), and Natural Science Foundation of Shaanxi Province (2018JQ6 070, 2019JM-254).
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Su, M. et al. (2022). Path Planning Based on Improved MPC for Fixed Wing UAVs with Collision Avoidance. In: Yan, L., Duan, H., Yu, X. (eds) Advances in Guidance, Navigation and Control . Lecture Notes in Electrical Engineering, vol 644. Springer, Singapore. https://doi.org/10.1007/978-981-15-8155-7_192
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DOI: https://doi.org/10.1007/978-981-15-8155-7_192
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