A multiple model-based decentralized system for accommodation of failures in second-order flight control actuators

In this paper effective failure detection, identification and reconfiguration (FDIR) algorithms are developed for a class of nonlinear systems characterized by significant actuator dynamics. Assuming that the actuator dynamics are fast, a baseline controller is designed and, using the singular perturbation arguments, shown to achieve the control objective. Typical failures in flight control actuators are considered next, and multiple model-based failure detection and identification (FDI) algorithms are derived for the case of measurable and non-measurable actuator rates. The FDI subsystem is decentralized in that an observer is run at each of the actuators, and the parameter estimates are adjusted using only the local information. The major issue of how to use this information to reconfigure the control law and assure the stability of the resulting closed-loop control system is addressed. Adaptive re-configurable controllers using the parameter estimates from the FDI subsystem are designed next. It is demonstrated that all the signals in the system are bounded and that the tracking error converges to zero asymptotically despite multiple simultaneous actuator failures in the case of second order actuator dynamics. The properties of the proposed FDIR algorithms are evaluated through numerical simulations of the F/A-18 aircraft