Optimization of mode discerning control for nonlinear hybrid systems subject to unknown inputs with applications to active fault diagnosis.

Mode identification for hybrid systems with unknown inputs has important applications to multiple-model approaches for health monitoring of cyber-physical systems. Active mode discerning applies a certain auxiliary control signal or reconfigures the controller to excite the hybrid system such that modes of the system are guaranteed to be distinguished, which is associated with the idea of active fault diagnosis in fault detection and isolation (FDI). The mode discerning auxiliary control design for nonlinear hybrid systems subject to unknown-but-constrained inputs with applications to active fault diagnosis has rarely been considered in existing works, and is far from being thoroughly addressed yet due to its nonlinear, nonconvex, bi-level, and multi-objective nature. To tackle the problem, a novel optimization scheme presenting a bi-level structure is proposed in this paper for the formulated active mode discerning problem for smooth nonlinear hybrid systems with unknown inputs. The proposed scheme can solve the local optimization problem of active mode discerning in a numerically stable manner without conservative convex relaxations. The effectiveness of the proposed scheme is demonstrated using an example of active fault detection for an aircraft control surface driven by an electro-mechanical actuator.