摘要：AbstractIn this paper we study the contraction properties of the recently introduced Advanced Step Real-Time Iteration (AS-RTI) under active-set changes. Compared to the well-known Real-Time Iteration, in order to improve optimality, in the AS-RTI some extra calculations on a problem with a predicted state are carried out. This enables us to trade off controller performance for computational load in a simple manner. Under standard assumptions, we prove the contraction of the iterates and boundedness of the numerical error. To achieve these goals we use generalized equations, Robinson’s strong regularity and recently presented results for abstract real-time algorithms. Finally, we present a numerical benchmark, where the performance of different variants of the AS-RTI is demonstrated on an industrial case study.
关键词：Keywordsnonlinear model predictive controlnumerical methodsnonlinear optimization
