Data-driven Output-feedback Predictive Control: Unknown Plant's Order and Measurement Noise
Systems and Control
2022-01-11 v1 Systems and Control
Abstract
The aim of this paper is to propose a new data-driven control scheme for multi-input-multi-output linear time-invariant systems whose system model are completely unknown. Using a non-minimal input-output realization, the proposed method can be applied to the case where the system order is unknown, provided that its upper bound is known. A workaround against measurement noise is proposed and it is shown through simulation study that the proposed method is superior to the conventional methods when dealing with input/output data corrupted by measurement noise.
Cite
@article{arxiv.2201.03136,
title = {Data-driven Output-feedback Predictive Control: Unknown Plant's Order and Measurement Noise},
author = {Nam H. Jo and Hyungbo Shim},
journal= {arXiv preprint arXiv:2201.03136},
year = {2022}
}