Fault-Tolerant Subspace Predictive Control Applied to a Boeing 747 Model

Abstract

This paper presents a fault-tolerant control system based on a combination of predictive control and subspace identification called subspace predictive control. In this control method, the mathematical model used by conventional predictive controllers to predict the future output is replaced by a subspace predictor. Because the subspace predictor is continuously updated in a closed-loop setting based on new input-output data, it can naturally adapt the controller after a fault has occurred. This property is very useful for fault-tolerant control because faults might be unanticipated. A novel feature of the presented subspace predictive control algorithm is that the predictor is recursively updated in a computationally efficient way. A multiple-model fault classification scheme is used to distinguish between anticipated and unanticipated faults. For anticipated faults the control system is configured such that it can accommodate these faults more quickly. The proposed fault-tolerant control system is evaluated on a detailed model of a Boeing 747.