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<i title="Walter de Gruyter GmbH">
<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/gtmb6i7f4nafrasuvcrl3t5ahe" style="color: black;">International Journal of Applied Mathematics and Computer Science</a>
This paper proposes two different health-aware economic predictive control strategies that aim at minimizing the damage of components in a pasteurization plant. The damage is assessed with a rainflow-counting algorithm that allows estimating the components' fatigue. By using the results obtained from this algorithm, a simplified model that characterizes the health of the system is developed and integrated into the predictive controller. The overall control objective is modified by adding an<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2478/amcs-2018-0007">doi:10.2478/amcs-2018-0007</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tnrhkf3sunffpl3gkgttsld2u4">fatcat:tnrhkf3sunffpl3gkgttsld2u4</a> </span>
more »... a criterion that takes into account the accumulated damage. The first strategy is a single-layer predictive controller with an integral action to eliminate the steady-state error that appears when adding the extra criterion. In order to achieve the best minimal accumulated damage and operational costs, the single-layer approach is improved with a multi-layer control scheme, where the solution of the dynamic optimization problem is obtained from the model in two different time scales. Finally, to achieve the advisable trade-off between minimal accumulated damage and operational costs, both control strategies are compared in simulation over a utility-scale pasteurization plant.
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