Strictly Positive Real Condition Establishment in Feedback Error Learning Control

Feedback error learning (FEL) is a useful tool for designing two-degree-of-freedom (2DOF) control systems. FEL consists of a fixed feedback block for stability and a feedforward block tuned online for tracking. Recently the author’s group has proposed a new FEL tuning law which requires a certain strictly positive real (SPR) condition in the feedback loop. In this paper we discuss relaxation of this requirement by means of filter selection in the feedforward controller.