Robust control of discrete minimum and non‐minimum phase systems via data‐driven virtual reference feedback tuning and IMC

Abstract

AbstractIn this paper, we develop a novel robust control approach for discrete minimum and non‐minimum phase systems via a combined data‐driven virtual reference feedback tuning () and internal model control (IMC) scheme. The first step in the conventional method controller design is the selection of the closed‐loop reference model (), and selection is still an open problem. The integration of the scheme and the VRFT method provides the advantage of flexibility in controller design due to the incorporation of the filter. As a result, the proposed design method begins with the selection of and filter. Unlike the standard method, the proposed combined and design approach has the unique feature of taking into account a robustness property of dynamics, namely, maximum sensitivity () as the design specification for the and IMC filter selection. Moreover, the proposed approach includes a robustness specification that resolves the trade‐off between performance and robustness in real‐time controller design. Furthermore, the robustness guarantee with plant uncertainties and controller fragility is elucidated. The proposed approach is validated using numerical simulations and experimental validation through the temperature control process. Compared to conventional controllers, experimental and simulation results show that the proposed controllers have less tracking error, minimize control effort, and improve robustness.