Fuzzy health degree-based dynamic performance evaluation of quadrotors in the presence of actuator and sensor faults


This paper proposes a fuzzy health degree-based dynamic performance evaluation algorithm of quadrotors in the presence of actuator and sensor faults. First, an augmented stochastic hybrid system (SHS) model for quadrotors is established. In the SHS model, the discrete modes are assigned with sensor normal mode and other senor anomalous modes. In each mode, a process equation and an observation equation are provided to describe the continuous behavior of quadrotors, where the process equation is augmented to model actuator fault by introducing effectiveness coefficients, and different observation equations are built to model different sensor faults. Then, a modified interacting multiple model algorithm is used to estimate the hybrid state of the SHS model, and a concept of fuzzy health degree is introduced to measure dynamic performance of the quadrotor based on the state estimation result. Finally, a simulation of a quadrotor suffering from successive actuator and sensor faults is presented to validate the effectiveness of the proposed algorithm.

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This work was supported in part by the Beijing Municipal Natural Science Foundation under Grant 4194074, in part by the National Key R&D Program of China under Grant 2017YFC1600605, in part by the Shandong Provincial Natural Science Foundation, China under Grant ZR2018BF016, and in part by the Beijing Municipal Education Commission Research Program-General Project under Grant KM201910011011.

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Correspondence to Xiaoyi Wang.

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Zhao, Z., Wang, X., Yao, P. et al. Fuzzy health degree-based dynamic performance evaluation of quadrotors in the presence of actuator and sensor faults. Nonlinear Dyn 95, 2477–2490 (2019). https://doi.org/10.1007/s11071-018-4711-2

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  • Dynamic performance
  • Quadrotor
  • Actuator fault
  • Sensor fault
  • Fuzzy health degree