Model-Based Control Allocation Strategies for Predictive Maintenance of Saturated Actuators

Abstract

Predictive maintenance techniques are getting increasing interest in industry because instrumental to determine suitable reliability conditions of in-service equipment aimed at smartly establishing when a maintenance operation should take place. This approach presents economic benefits when compared to more traditional routines or time-based preventive maintenance because tasks are performed only when warranted. Within this context, this work presents a control allocation scheme based on Model Predictive Control ideas to deal with actuator loss of effectiveness related to their usage. These undesired events occur when the associated degradation effects, whose evolution is assumed to be measurable and/or predictable, overcome a given threshold. The proposed scheme consists of two modules: a prognostic unit in charge of monitoring the actuators’ health and a reconfigurable control allocation module whose action is based on the current actuators’ degradation level. Its main goal is to establish a suitable time interval during which a maintenance service can occur without affecting the stability of the controlled system and the feasibility properties of the control allocation scheme.