摘要：AbstractModifier-Adaptation methodologies have been widely used to overcome plant-model mismatch and control a system to its steady-state optimal setpoint. They use gradient information of the real plant to design modifiers that correct the model, so that the first order necessary conditions for optimality of the model-based problem converge to those of the optimal one. In this paper, we get rid of the hypothesis that the plant optimum needs to be an equilibrium point. Instead, we only require it to be a periodic trajectory. We show the behaviour of the proposed approach by means of a motivating example that highlights the necessity of this formulation in cases where the system changes periodically through time.
关键词：KeywordsModel predictive control (MPC)Dynamic real-time optimization (DRTO)Economic designModifier-adaptationUncertaintyNonlinear systemsPeriodic references
