A prognostics enhanced reconfigurable control architecture

This paper introduces a control architecture incorporating prognostic information to extend the Remaining Useful Life (RUL) of a system while ensuring stability and performance requirements. A Model Predictive Control (MPC) framework is chosen to utilize the existing production controller by adjusting its reference points, thereby lowering its impact on the system. The MPC arrives at a control law by minimizing a quadratic cost function of control effort and tracking error while enforcing hard and soft constraints. Prognostic information is included in the cost function through the use of soft constraints whereas absolute boundary conditions (eg. input limits, tracking error) are incorporated as hard constraints. A relationship is provided between the terminal cost associated with the prognostic constraints and the quadratic costs. Asymptotic stability of the control architecture is demonstrated for the case of nominal system dynamics. The proposed fault-tolerant control design is applicable to a variety of application domains. An EMA is used to illustrate the efficacy of the proposed approach.