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.