Improved robust energy-to-peak filtering for uncertain linear systems

This paper investigates the problem of energy-to-peak filtering for both discrete-time and continuous-time systems with polyhedral uncertainties in the state-space equations. By increasing the flexible dimensions in the solution space for the energy-to-peak optimization, less conservative results on the robust energy-to-peak filtering are obtained. The filter parameters can be readily designed by solving a set of parameter-dependent linear matrix inequalities (LMIs). In comparison with the existing methods, the improvement of the proposed method over the existing results is shown via two numerical examples.