Event-Based Sequential Prognosis for Uncertain Hybrid Systems With Intermittent Faults

This paper addresses the prognosis problem for hybrid systems with intermittent faults and uncertain parameters. First, a diagnostic hybrid bond graph in linear fractional form is used to model the uncertain hybrid system to generate the mode-dependent adaptive thresholds for fault detection purpose. Then, a global combinative fault signature matrix integrating independent and dependent augmented global analytical redundancy relations is proposed to improve the system fault isolability under the multiple-fault condition. After the possible fault set is isolated, an adaptive reinforcement unscented Kalman filter is introduced to identify the intermittent fault magnitude, where an auxiliary indicator is used to capture the fault appearing and disappearing time steps. To describe the degradation trend of the intermittent fault, a dynamic model with a mode-dependent degradation coefficient is used. Taking the variation of the degradation coefficient into account, an event-based sequential prognosis method is proposed, where the prognoser is only reactivated if the discrete event representing mode change is observed and its associated conditions are satisfied. Finally, the key concept of the proposed method is verified by experimental studies.