Abstract In this paper, we present a computationally efficient economic NMPC formulation, where we propose to adaptively update the length of the prediction horizon in order to reduce the problem size. This is based on approximating an infinite horizon economic NMPC problem with a finite horizon optimal control problem with terminal region of attraction to the optimal equilibrium point. Using the nonlinear programming (NLP) sensitivity calculations, the minimum length of the prediction horizon required to reach this terminal region is determined. We show that the proposed adaptive horizon economic NMPC (AH-ENMPC) has comparable performance to standard economic NMPC (ENMPC). We also show that the proposed adaptive horizon economic NMPC framework is nominally stable. Two benchmark examples demonstrate that the proposed adaptive horizon economic NMPC provides similar performance as the standard economic NMPC with significantly less computation time.

中文翻译：

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自适应水平经济非线性模型预测控制

摘要在本文中，我们提出了一种计算效率高的经济 NMPC 公式，我们建议自适应地更新预测范围的长度以减少问题的规模。这是基于将无限范围经济 NMPC 问题与有限范围最优控制问题逼近，该问题具有对最优平衡点的吸引力终端区域。使用非线性规划 (NLP) 灵敏度计算，确定到达该终端区域所需的预测范围的最小长度。我们表明，提出的自适应水平经济 NMPC (AH-ENMPC) 具有与标准经济 NMPC (ENMPC) 相当的性能。我们还表明，提议的自适应水平经济 NMPC 框架名义上是稳定的。