Health-aware model predictive control of pasteurization plant
European Workshop on Advanced Control and Diagnosis (ACD)
In order to optimize the trade-off between components life and energy consumption, the integration of a system health management and control modules is required. This paper proposes the integration of model predictive control (MPC) with a fatigue estimation approach that minimizes the damage of the components of a pasteurization plant. The fatigue estimation is assessed with the rainflow counting algorithm. Using data from this algorithm, a simplified model that characterizes the health of the system is developed and integrated with MPC. The MPC controller objective is modified by adding an extra criterion that takes into account the accumulated damage. But, a steady-state offset is created by adding this extra criterion. Finally, by including an integral action in the MPC controller, the steady-state error for regulation purpose is eliminated. The proposed control scheme is validated in simulation using a simulator of a utility-scale pasteurization plant.
F. Karimi, V. Puig and C. Ocampo-Martínez. Health-aware model predictive control of pasteurization plant, 13th European Workshop on Advanced Control and Diagnosis, 2016, Lille, Vol 783 of Journal of Physics: Conference Series, pp. 012030, 2017.