Data-driven robust feedback-feedforward controller design for discrete minimum and non-minimum phase systems via novel combined VRFT and IMC approach

Abstract In this work, a novel robust controller design is proposed by integrating the Internal Model Control (IMC) and Virtual Reference Feedback Tuning (VRFT) strategy. The distinctive aspect of this case is the robust controller design that is produced by choosing the reference model M(z) and IMC filter while taking Maximum Sensitivity ( M s ) into account as the design criteria. This paradigm enables the resolution of the trade-off between overall performance and robustness, as well as the tracking of a possible output trajectory. The VRFT, IMC scheme with IMC filter integration provides flexibility and makes the proposed framework to be robust to disturbances, model uncertainties, and unknown measurement noise. Also, an employed non-measurable disturbance signal enhances the presumed advantage of feedback plus feedforward (FB + FF) structure in improving disturbance rejection. The simulation is employed on numerical examples of minimum phase, non-minimum phase, and time delayed systems to verify the proposed approach also validated through experimental results.