Simultaneous Design of Reference Model and Controller for VRFT using Closed-loop Step Response Data

Abstract

This paper proposes a simultaneous reference model and controller design for Virtual Reference Feedback Tuning (VRFT) using closed-loop response data. In the proposed approach, a parametrized reference model is considered, and a modified cost criterion is introduced taking account of the trade-off relation between model-matching properties and fast tracking properties. The proposed cost criterion is optimized using a sequential least squares algorithm that solves the optimization of reference model parameters and controller parameters alternately. In addition, the paper proposes a pre-filter design that suits the given cost criterion in case that collected input and output data are generated from step response data. Finally, through a numerical simulation, the effectiveness of a prefilter design is shown for two weighting parameters of the cost criterion.