A Direct Design of 2DOF Controller Based on FCbT and an Application to Closed-Loop Identification

Abstract

This paper proposes a data-driven method named Fictitious Correlation-based Tuning (FCbT) for 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” cross-correlation function. In this paper, we enhanced FCbT to tuning of 2DOF controllers, which are often adopted in various control problems. In model-based control synthesis, a feedforward controller is generally synthesized as a product of a reference model and an inverse model of the plant. It means that closed-loop identification of MIMO system can be performed by FCbT. The effectiveness of FCbT and application to closed-loop identification are shown by simulations and experiments.