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A stochastic hybrid system (SHS) is a type of model describing real-world systems, who are both dynamic and hybrid. System performance evaluation is a key technology related to mission accomplishment and safety, where a rational selection of performance indicators is an important guarantee of truly and accurately evaluating system performance. This paper proposes a performance evaluation algorithm of SHS. First, the concept of fuzzy health degree is proposed and the SHS model studied in this paper is established. Then, the procedure of the algorithm is presented in detail, including hybrid state estimation based on a modified interacting-multiple-model algorithm, discretization of continuous variables, and quantitative calculation of fuzzy health degree. In order to validate the effectiveness of the proposed algorithm, an experiment of a quadrotor with sensor anomalies is made where the system performance is quantitatively described by using the fuzzy health degree. Comparative studies are also made and discussed.

A Performance Evaluation Algorithm of Stochastic Hybrid Systems Based on Fuzzy Health Degree and Its Application to Quadrotors