Multi-UAV tracking target in urban environments by model predictive control and improved whale optimizer

Yongheng Zhao; Xuzhao Chai; Cuicui He; Yiming Lu; Pengwei Wen; Li Yan; Zhao Li

doi:10.1117/12.3032000

8 June 2024 Multi-UAV tracking target in urban environments by model predictive control and improved whale optimizer

Yongheng Zhao, Xuzhao Chai, Cuicui He, Yiming Lu, Pengwei Wen, Li Yan, Zhao Li

Proceedings Volume 13171, Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024); 1317112 (2024) https://doi.org/10.1117/12.3032000
Event: 3rd International Conference on Algorithms, Microchips and Network Applications (AMNA 2024), 2024, Jinan, China

Abstract

In this work, the method of Model Predictive Control (MPC) and Improved Whale Optimization Algorithm (IWOA) has been proposed to solve multiple unmanned aerial vehicles (UAVs) tracking a moving target in urban environment. The problem models are established, including the UAV model, target model, environment model and cost function model. Adopting MPC as a control framework for UAV target tracking, WOA is chosen as the solver of MPC. To further improve the optimized efficiency, the introduced strategies include bootstrap initialization strategy, double-difference variational strategy, adaptive weighting strategy and elite selection strategy. The compared experiments show the control method in this paper has better tracking performance and is a reliable technique for UAV tracking the moving target.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yongheng Zhao, Xuzhao Chai, Cuicui He, Yiming Lu, Pengwei Wen, Li Yan, and Zhao Li "Multi-UAV tracking target in urban environments by model predictive control and improved whale optimizer", Proc. SPIE 13171, Third International Conference on Algorithms, Microchips, and Network Applications (AMNA 2024), 1317112 (8 June 2024); https://doi.org/10.1117/12.3032000

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