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Abstract <p>Unmanned aerial vehicles (UAVs) have made a significant impact on both industry and academics due to their many applications. It is convenient to exchange data, decision making, and control attitude/altitude of UAV systems with the establishment of a cloud communication network. There is a chance of data packet dropout and data packet delay during cloud communication. In this proposed work, the stochastic model of networked UAV is developed with network induced delay and packet loss using Bernoulli random variables. Also, discrete event triggered technique is implemented in sensor node and controller node that restricts unuseful information. Cloud network bandwidth and energy consumption are decreased as a result of limited data transmission. A predicted measurement is used to handle cloud network inefficiencies and during untriggered scenarios. For the developed stochastic UAV model, an estimator/filter is developed using orthogonal projection methods. An anomaly detection algorithm is proposed for a networked UAV system using estimator information to identify the fault and cyber-attack.</p>

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Event-Triggered Orthogonal Estimator Design for Cloud Communication Based Unmanned Aerial Vehicle System

  • 期刊论文

  • 发表日期：

    2025年2月1日

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  • Vasanthakumar Sekar,
  • K. Senthilkumar,
  • K. Srinivasan

摘要

Abstract

Unmanned aerial vehicles (UAVs) have made a significant impact on both industry and academics due to their many applications. It is convenient to exchange data, decision making, and control attitude/altitude of UAV systems with the establishment of a cloud communication network. There is a chance of data packet dropout and data packet delay during cloud communication. In this proposed work, the stochastic model of networked UAV is developed with network induced delay and packet loss using Bernoulli random variables. Also, discrete event triggered technique is implemented in sensor node and controller node that restricts unuseful information. Cloud network bandwidth and energy consumption are decreased as a result of limited data transmission. A predicted measurement is used to handle cloud network inefficiencies and during untriggered scenarios. For the developed stochastic UAV model, an estimator/filter is developed using orthogonal projection methods. An anomaly detection algorithm is proposed for a networked UAV system using estimator information to identify the fault and cyber-attack.