Data-Driven State-Space Identification with Correlated Fuzzy Parametric Uncertainty for Prediction and Integral Control
Data-driven models for embedded control must account for acquisition filtering and experimental uncertainty while retaining dependence among identified parameters. This work develops a framework connecting identification in filtered-state coordinates, joint fuzzy uncertainty propagation, and fixed-gain stability assess...