Integrated Model-Based Control Allocation Strategies Oriented to Predictive Maintenance of Saturated Actuators

Predictive Maintenance approaches are gaining popularity in the new Industry 4.0 paradigm as they offer superior benefits in terms of time and money savings when it is required to assess the current working capabilities of operating equipment to carefully schedule maintenance operations. This work deals with a control allocation strategy inspired by Model Predictive Control ideas and able to address the loss of effectiveness of actuating equipment arising from their continuous usage. The scheme here presented comprises two modules: a prognostic unit for monitoring the reliability conditions of the actuators and a re-configurable control allocation block that operates according to the deterioration degree of the present actuators. The benefits of the proposed approach are testified by the numerical simulations carried out on both an unstable system and a tanks network. In particular, it can be observed that the proposed method is capable of suggesting a time-window for maintenance interventions that prevents either stability or feasibility issues.