Adaptive internal model control research in autonomous landing phase for a fixed-wing UAV

Abstract

utonomous landing is a very complex phase of flight for unmanned aerial vehicle (UAV). Adaptive internal model control (AIMC) is proposed and applied on autonomous landing control system in this paper. Controllers are designed based on the decoupled and linearized models of a sample UAV. Estimation of process model is carried out to enhance system robustness, and filter parameter adjustment is proposed to achieve a good dynamic performance. Control effects are compared and analyzed between IMC and AIMC in different wind conditions which demonstrate that AIMC has better performances than IMC. At last, Monte Carlo simulations prove the system stability.

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• http://dx.doi.org/10.1007/s13272-016-0216-1 under the license https://creativecommons.org/licenses/by

• https://link.springer.com/content/pdf/10.1007/s13272-016-0216-1.pdf under the license http://creativecommons.org/licenses/by/4.0

• http://link.springer.com/content/pdf/10.1007/s13272-016-0216-1.pdf,

http://link.springer.com/article/10.1007/s13272-016-0216-1/fulltext.html,

http://dx.doi.org/10.1007/s13272-016-0216-1 under the license cc-by

• https://link.springer.com/article/10.1007/s13272-016-0216-1,

https://paperity.org/p/77962528/adaptive-internal-model-control-research-in-autonomous-landing-phase-for-a-fixed-wing-uav,

https://trid.trb.org/view/1456257,

https://link.springer.com/content/pdf/10.1007%2Fs13272-016-0216-1.pdf,

https://academic.microsoft.com/#/detail/2530912536 under the license http://creativecommons.org/licenses/by/4.0