Unbiased estimation of the Hessian for iterative feedback tuning (IFT)

Iterative feedback tuning (IFT) is a data-based method for the optimal tuning of a low order controller. The tuning of the controller parameters is performed iteratively, using a generalized Robbins-Monro type gradient descent scheme. An update step of the controller parameters is performed at each iteration on the basis of data obtained partly during normal operating conditions and partly from some special experiments. These data come from the closed loop system with the current controller. This paper presents a simple improvement to the IFT scheme: it is shown that one can compute an unbiased estimate of the Hessian on the basis of additional experiments on the closed loop system.Anglai