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Predictive maintenance of actuators in linear systems: A receding horizon set‐theoretic approach
Author(s) -
Tedesco Francesco,
Akram Waseem,
Forouzanfar Mehdi,
Casavola Alessandro,
Famularo Domenico
Publication year - 2022
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.6148
Subject(s) - actuator , control theory (sociology) , model predictive control , context (archaeology) , computer science , process (computing) , set (abstract data type) , basis (linear algebra) , control (management) , control engineering , engineering , mathematics , artificial intelligence , paleontology , biology , programming language , operating system , geometry
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.