Improving the choice of disturbance reference model in data-driven control methods

Virgínia Bordignon¹; Lucíola Campestrini¹

¹ Universidade Federal do Rio Grande do Sul

Baixar PDF doi:10.20906/CPS/CBA2018-1052

Resumo

This work aims to study and address the problem of choosing the reference model within a model reference control design problem for disturbance rejection. Existing theory on the design of the reference model for disturbance is revisited, and adaptations for data-based applications, in which the process' mathematical model is unknown, are proposed. Finally, this paper presents an alternative way of accounting for this choice directly in a data-based control tuning method. Simulation results show that a sensible choice of reference model improve controller tuning and that the proposed strategy is able to manage this choice in a systematic manner without using the process' model.

Palavras-chave: Data-driven control; Model reference control; Disturbance rejection; PID control