Data-Driven IQC-Based Robust Control Design for Hybrid Micro-Disturbance Isolation Platform

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Klauser, Elias
Gupta, Vaibhav
Karimi, Alireza
A novel approach for robust controller synthesis, which models uncertainty as an elliptical set, is proposed in the paper. Given a set of frequency response functions of linear time-invariant (LTI) multiple-input multiple-output (MIMO) systems, the approach determines the ‘best’ linear nominal model and the corresponding elliptical uncertainty set, which is consistent with the data. Using a novel split representation, the uncertainty set is represented as an equivalent integral quadratic constraint (IQC). Finally, this IQC is integrated into a data-driven frequency-domain controller synthesis method using convex optimisation. The proposed method is used to design a controller, which is robust against mechanical uncertainties for a hybrid micro-disturbance isolation platform for space applications. The experimental results show that the proposed method provides a less conservative uncertainty set and improves attenuation performance compared to classical methods that use disk uncertainty.
Publication Reference
62nd IEEE Conference on Decision and Control, Singapore (SG)