A clarifying analysis of feedback error learning in an LTI framework

Journal article, 2008

Feedback error learning (FEL) is a proposed technique for reference-feedforward adaptive control. FEL in a linear and time-invariant (LTI) framework has been studied recently; the studies can be seen as proposed solutions to a feedforward MRAC problem. This paper reanalyzes two suggested schemes with new interpretations and conclusions. It motivates the suggestion of an alternative scheme for reference-feedforward adaptive control, based on a certainty-equivalence approach. The suggested scheme differs from the analyzed ones by a slight change in both the estimator and the control law. Boundedness and error convergence are then guaranteed when the estimator uses normalization combined with parameter projection onto a convex set where stability of the estimated closed-loop system holds.