Structure Determination of a Criterion Function by Dynamic Inverse Optimization

Abstract

Dynamic inverse optimization generates a quadratic criterion function under which given input and output sequences become optimal for a known state equation model. In this paper we propose to use statistical test to decide which state variables are included in a criterion function. To evaluate the effectiveness of the proposed method, simulation experiments are carried out. Statistical test successfully determines which state variables are included in a criterion function.