Prescribed-Time Attitude Control for Hypersonic Morphing Vehicles Using Morphing Information-Driven Events

An event-triggered practical prescribed time control (PPTC) strategy is proposed for hypersonic morphing vehicles (HMVs) with system uncertainties and limited computation resources. HMVs can frequently change the aerodynamic profile to keep the desired aerodynamic properties. Attitude stabilization is essential for HMVs in continuous morphing stages. First of all, the HMV model is established and investigated to support the control system design. As a result, the complete morphing process will lead to significant improvements in aerodynamic coefficients, requiring fast-tracking and adaptation. Then, an appointed-time prescribed performance function (ATPPF) is proposed. Based on the ATPPF and the HMV model, the PPTC technique is induced for HMVs. Third, the event-triggered PPTC is presented based on morphing information-driven (MI-driven) events, which are a part of the actual flight status. The developed MI-driven event-triggering mechanism could lead to a lower triggering number than the conventional time-triggering mechanism and the commonly used relative-threshold event-triggering mechanism. Finally, the prescribed time stability is theoretically proven via Lyapunov thesis while excluding the Zeno behavior. The simulations validated the effectiveness and the properties of the proposed control scheme for HMVs.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Aerospace and Electronic Systems
Published
2024-11-25
DOI
https://doi.org/10.1109/taes.2024.3506512
Citations
6
Primary Topic
Advanced Control Systems Optimization
Type
article
Field-Weighted Citation Impact
1.97
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prescribed-Time Attitude Control for Hypersonic Morphing Vehicles Using Morphing Information-Driven Events

Cunyu Bao, Weimin Bao, Wenhui Ma, Guojian Tang et al.
6 citations
IEEE Transactions on Aerospace and Electronic Systems
Advanced Control Systems Optimization
1.97
article

Prescribed-Time Attitude Control for Hypersonic Morphing Vehicles Using Morphing Information-Driven Events

Cunyu Bao, Weimin Bao, Wenhui Ma, Guojian Tang, Hao Zhang, Peng Wang
article en
6 citations

Abstract

An event-triggered practical prescribed time control (PPTC) strategy is proposed for hypersonic morphing vehicles (HMVs) with system uncertainties and limited computation resources. HMVs can frequently change the aerodynamic profile to keep the desired aerodynamic properties. Attitude stabilization is essential for HMVs in continuous morphing stages. First of all, the HMV model is established and investigated to support the control system design. As a result, the complete morphing process will lead to significant improvements in aerodynamic coefficients, requiring fast-tracking and adaptation. Then, an appointed-time prescribed performance function (ATPPF) is proposed. Based on the ATPPF and the HMV model, the PPTC technique is induced for HMVs. Third, the event-triggered PPTC is presented based on morphing information-driven (MI-driven) events, which are a part of the actual flight status. The developed MI-driven event-triggering mechanism could lead to a lower triggering number than the conventional time-triggering mechanism and the commonly used relative-threshold event-triggering mechanism. Finally, the prescribed time stability is theoretically proven via Lyapunov thesis while excluding the Zeno behavior. The simulations validated the effectiveness and the properties of the proposed control scheme for HMVs.

IEEE Transactions on Aerospace and Electronic SystemsVol. 61(3)
Harbin Engineering University (CN), National University of Defense Technology (CN), Northwestern Polytechnical University (CN), China Aerospace Science and Technology Corporation (CN), Xi'an Technological University (CN)
Climate action
Openalex Percentile: Top 13%
Advanced Control Systems Optimization
1.97
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.