Iterative Feedback Tuning for cascade systems

Iterative Feedback Tuning (IFT) is a data-driven method used to tune parameters of feedback controllers minimising an H-2 criterion. The method uses data from experiments to estimate the gradient of the criterion, and uses iterative quasi newton algorithms to adjust the controllers. When the method is used in cascade systems, usually the inner loop is firstly adjusted, and after the outer loop. In this article we describe an extension to the IFT method that adjusts both inner and outer loop at the same time using only data from closed-loop experiments at each iteration.