In the context of direct data-driven design, we propose a controller design procedure on the basis of a set of experimental input/output data, with no identification of the plant model. The objective of the control problem is to make the closed-loop system to match the behavior of an assigned reference model as close as possible. As is well known, the presence of one of more non-minimum phase zeros in the plant transfer function makes the direct data-driven design procedure significantly harder since, no matter what is the considered approach among the ones proposed in the literature, the designed controller commonly leads to an unstable closed-loop system due to unstable pole-zero cancellations. In this paper we propose a new approach for performing the design of direct data-driven controller when the unknown plant may or may not have non-minimum phase zeros. The problem is formulated in the context of the set-membership estimation theory, and previous results from some ot the authors on errors-in-variables identification are exploited to compute the controller parameters. The effectiveness of the presented technique is demonstrated by means of two simulation examples. 

العنوان

2017 IEEE 56th Annual Conference on Decision and Control (CDC)

الناشر

IEEEE

بلد الناشر

الولايات المتحدة الأمريكية

Indexing

Scopus

معامل التأثير

None

نوع المنشور

إلكتروني فقط

المجلد

--

السنة

2019

الصفحات

1284-1290