Abstract
This paper proposes the data-driven method named Fictitious Correlation-based Tuning (FCbT) for the tuning of Linear Time Invariant (LTI) multivariable controllers. The parameters of the controller are updated directly using the data acquired in closed-loop operation. This approach allows one to tune diagonal elements of the controller transfer function matrix to satisfy the desired closed-loop performance, while the other elements are tuned to mutually decouple the closed-loop outputs. Moreover, FCbT requires only one-shot experimental data for an off-line nonlinear optimization in order to obtain the optimal parameter minimizing a “fictitious” crosscorrelation function. FCbT is compared with standard Correlation-based Tuning (CbT) for MIMO systems in some simulations.
