Abstract

The stability margin and the gap metric are powerful tools for closed-loop robust stability analysis in control system designs. In order to develop a data-driven framework for the real-time evaluation of the closed-loop stability, this paper presents a study on data-driven estimation of the closed-loop stability margin using time domain measurements. The core of the study is to find an estimation of the multiplication operator of the closed-loop transfer function matrices, where a data-driven stable image representation (SIR) of the system is identified using closed-loop data sets based on the orthogonal projection technique. The contributions of this paper efficiently bridge the gap between robustness analysis/design and data-driven techniques for the future research. The main results of this paper are verified and demonstrated through randomly generated systems and designed closed-loops.

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