An interacting multiple-model based fault detection, diagnosis and fault-tolerant control approach

In this paper, an interacting multiple-model (IMM) based fault detection, diagnosis and reconfigurable control approach for discrete-time stochastic systems is proposed. Fault detection and diagnosis (FDD) is carried out using the IMM estimator. The linear quadratic regulator (LQR) and an eigenstructure assignment (EA) techniques have been used for nominal and reconfigurable control laws design, respectively. To achieve zero steady-state tracking error, a set of feedforward control gains is also designed using an input weighting approach. The paper has considered not only actuator and sensor faults, but also system component faults. To achieve fast and reliable fault detection, diagnosis and controller reconfiguration, new fault diagnosis and reconfiguration mechanisms have been proposed using appropriate combination of the information provided by the mode probabilities from the IMM algorithm and an index related to the closed-loop system performance. The proposed approach is evaluated using an aircraft example in the presence of system component, actuator and sensor faults