Predictive maintenance of actuators in linear systems: A receding horizon set-theoretic approach

This work is focused on a model predictive control (MPC) based approach for the regulation of systems whose actuators are subject to loss of effectiveness. Such a degradation process, whose evolution is assumed to be measurable and predictable, can lead to actuators breakdown whenever certain thresholds are exceeded. Within this context, if the control problem is defined with ad hoc operational constraints and/or running costs, the intrinsic MPC capability of mitigating faulty events arises. To this end, the proposed control scheme consists of two modules: the former is in charge of performing a prognostic activity on actuators' health, while the second one reconfigures the control law on the basis of actuators' degradation information. The core of the proposed method relies on modeling healthy and faulty plant configurations via a switching systems paradigm that is instrumental to offline determine sequences of precomputed inner approximations of one-step ahead controllable sets. Such regions are online selected by a switching logic in order to determine a control signal properly weighted on the basis of the measured actuators degradation level.