Dual-loop control and state prediction analysis of QUAV trajectory tracking based on biological swarm intelligent optimization algorithm

Quadrotor unmanned aerial vehicles (QUAVs) have attracted significant research focus due to their outstanding Vertical Take-Off and Landing (VTOL) capabilities. This research addresses the challenge of maintaining precise trajectory tracking in QUAV systems when faced with external disturbances by i...

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Veröffentlicht in:	Scientific reports Jg. 14; H. 1; S. 19091 - 25
Hauptverfasser:	Zou, Zuoming, Yang, Shuming, Zhao, Liang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	London Nature Publishing Group UK 17.08.2024 Nature Publishing Group Nature Portfolio
Schlagworte:	639/166 639/705 Control systems Data-driven Deep learning Humanities and Social Sciences Long short-term memory multidisciplinary Particle swarm optimization Quadrotor unmanned aerial vehicles Science Science (multidisciplinary) Sliding mode control Systems stability Vertical take-off and landing Long short-term memory Data-driven Vertical take-off and landing Particle swarm optimization Quadrotor unmanned aerial vehicles Sliding mode control
ISSN:	2045-2322, 2045-2322
Online-Zugang:	Volltext
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