Control parameter tuning for aircraft crosswind landing via multi-solution particle swarm optimization |
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| Authors: | Qi Bian Brett Nener Xinmin Wang |
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| Affiliation: | 1. School of Automation, Northwestern Polytechnical University, Xi’an, People's Republic of China;2. School of Electrical, Electronic, and Computer Engineering, The University of Western Australia, Perth, Australia;3. School of Electrical, Electronic, and Computer Engineering, The University of Western Australia, Perth, Australia |
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| Abstract: | Crosswind landing is one of the most complex and challenging landing manoeuvres; an aircraft can drift laterally or could even be blown off the runway under extreme crosswind conditions. This article proposes an improved multi-group swarm-based optimization method that can not only optimize the parameters of the lateral flight control system, but also find diversity solutions of the underlying optimization problem. During the optimizing process, several swarm groups are generated to search potential areas for the optimal solution. These groups exchange information with each other during the searching process and focus on their different but continuous spaces. Finally, a diverse range of solutions is presented to the engineer for the flight control system design. A nonlinear 6 degrees-of-freedom rigid model of a Boeing 747 is used as a test bed to verify the robustness and feasibility of the proposed method. |
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| Keywords: | Crosswind landing control parameter optimization multi-solution particle swarm optimization |
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