Adaptive actuator fault compensation for linear systems with matching and unmatching uncertainties

The problem of process systems subject to actuator faults (partial loss of actuator effectiveness) is considered. An active fault compensation control law is designed that utilizes compensation in a way that accounts for matching and unmatching uncertainties and the occurrence of actuator faults. The main idea is designing the robust compensation controller to guarantee closed-loop stability in the presence of faults, based on a neural network representation of the fault dynamics. Changes in the system due to faults are modeled as unknown nonlinear functions. The updating control law is derived such that all the parameters of the closed-loop system are bounded. An output feedback controller is used to the “healthy” system and the adaptive feedback controller is used to compensate for the effect of the dynamics caused by the fault. The advantage of fault compensation is the dynamics caused by faults can be accommodated online. The proposed design method is illustrated on a three-tank system.