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Robust stable economic MPC with applications in engine control

Economic Model Predictive Controllers have shown to improve a plant's economic performance using state dependant economic stage costs. Recent extensions have provided continual feasibility guarantees, despite changes in economic parameters, however, perfect plant models have been assumed. This assumption is invalid in practise due to modelling errors or un-modelled disturbances and can therefore lead to infeasibility of the optimisation problem. This paper proposes a robust economic model predictive controller, which takes advantage of constraint tightening techniques to guarantee feasibility despite modelling errors. Input-to-state stability is proven using a Lyapunov function. The advantages of this method are highlighted against alternative control structures in the application of power tracking for diesel engines in series hybrid type applications.