Model and data-driven combination: a fault diagnosis and localization method for unknown fault size of quadrotor uav actuator based on extended state observer and deep forest

HIGHLIGHTS

• who: Jia Song and colleagues from the School of Astronautics, Beihang University, Beijing, China have published the research work: Model and Data-Driven Combination: A Fault Diagnosis and Localization Method for Unknown Fault Size of Quadrotor UAV Actuator Based on Extended State Observer and Deep Forest, in the Journal: Sensors 2022, 22, 7355. of /2022/
• what: The authors propose a fault diagnosis and localization scheme the (ESO) and_(DF). The residual signal is the difference between the observed of ESO and the true fault Then the authors design the residual feature analysis method by considering . . .
  

   

  

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