A dynamic inversion approach to robust set-point regulation of TITO systems

In this paper we present a novel methodology, based on dynamic inversion, for the set-point regulation of a two-inputs-two-outputs (TITO) system with structured uncertainties. The approach first consists in decoupling the systems by considering its nominal model. Then, polynomial functions are chosen as output functions and both the controller and the command inputs are designed in order to minimize the worst-case settling-time of the set-point regulation, with constraints on the absolute value of the control variables and on the maximum overshoot and undershoot of the outputs. A worked example shows the effectiveness of the method. Optimization has been performed by means of genetic algorithms.