ACTIVE DISTURBANCE REJECTION CONTROL AND MODEL-FREE CONTROL TUNED VIA FICTITIOUS REFERENCE ITERATIVE TUNING

This paper presents a comparative analysis of two data-driven algorithm combinations: the first-order Active Disturbance Rejection Control-Fictitious Reference Iterative Tuning (ADRC-FRIT) and the first-order Model-Free Control-Fictitious Reference Iterative Tuning (MFC-FRIT). The objective of both data-driven combinations is to ascertain the tunable parameters through the resolution of an optimization problem and to streamline the heuristic procedures involved. The data-driven algorithms are empirically validated through experimental trials utilizing the 3D laboratory equipment in which the x-, y-, and z-axes are controlled.