Abstract
Abstract It is well-know that the use of an inaccurate model in any model-based control scheme might lead to a suboptimal operation and to violation of the constraints. In this contribution, an economics optimizing control scheme is proposed with the aim of achieving closed-loop optimality despite the presence of structural model-plant mismatch. Model uncertainties are handled by augmenting the nominal model with bias and gradients correction terms which are iteratively updated using plant information. The basic idea is to enforce the matching of the optimality conditions between the plant and the augmented model by linear correction terms similar to modifier adaptation. The proposed scheme is discussed and illustrated by simulation studies of a benchmark problem.
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