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Adaptive Communication and Control Co-Design for Remote UAV Systems

  • Harbin Institute of Technology Shenzhen
  • Pengcheng Laboratory

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we present a remote UAV control framework to achieve the tasks of trajectory tracking while avoiding collision. We utilize short-packet communication to transmit the control commands. Following this framework, we develop an improved self-triggered stochastic model predictive control (ST-SMPC) to adaptively adjust the control length, which greatly affects the control and communication performance. Moreover, chance constraints are considered to realize collision avoidance. Consequently, we decouple this co-design problem into a SMPC problem and a communication power optimization problem to jointly determine the control length. Simulation results demonstrate that the proposed control method can adaptively adjust the control length under various environments, achieving better communication efficiency compared to traditional MPC approaches.

Original languageEnglish
Title of host publication2025 IEEE 101st Vehicular Technology Conference, VTC 2025-Spring 2025 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798331531478
DOIs
StatePublished - 2025
Externally publishedYes
Event101st IEEE Vehicular Technology Conference, VTC 2025-Spring 2025 - Oslo, Norway
Duration: 17 Jun 202520 Jun 2025

Publication series

NameIEEE Vehicular Technology Conference
ISSN (Print)1550-2252

Conference

Conference101st IEEE Vehicular Technology Conference, VTC 2025-Spring 2025
Country/TerritoryNorway
CityOslo
Period17/06/2520/06/25

Keywords

  • UAV
  • collision avoidance
  • self-triggered control
  • stochastic model predictive control
  • trajectory tracking

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