LQ-based set-point constrained regulation of uncertain systems via dynamic inversion

In this paper we present a now methodology, based on dynamic inversion, for the set-point constrained regulation of a scalar linear system with structured uncertainties. The approach basically relies on the combined design of the controller and of the reference command input. The first is based on LQR methodology whilst the latter is determined by means of a stable dynamic inversion. An illustrative example, in which optimization has been performed by means of genetic algorithms, shows that the overall method is effective for a wide class of scalar systems, including nonminimum-phase ones.