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In this paper, we propose a data-driven economic model predictive control(EMPC) scheme with generalized terminal constraint to control an unknown lineartime-invariant system. Our scheme is based on the Fundamental Lemma to predictfuture system trajectories using a persistently exciting input-outputtrajectory. The control objective is to minimize an economic cost objective. Byemploying a generalized terminal constraint with artificial equilibrium, thescheme does not require prior knowledge of the optimal equilibrium. We provethat the asymptotic average performance of the closed-loop system can be madearbitrarily close to that of the optimal equilibrium. Moreover, we extend ourresults to the case of an unknown linear stage cost function, where theFundamental lemma is used to predict the stage cost directly. The effectivenessof the proposed scheme is shown by a numerical example.

Linear Data-Driven Economic MPC with Generalized Terminal Constraint