State estimation for descriptor systems via the unknown input filtering method

This paper addresses the optimal unbiased minimum-variance state estimation of descriptor systems in the framework of unknown input filtering. It is shown that any descriptor system can be equivalently transformed into a standard state-space system with unknown inputs; the existing globally optimal state estimators can then be readily used to facilitate the optimal filter design. This research highlights the relationship between descriptor state estimation and unknown input filtering for standard state-space systems with unknown inputs. A direct application to the state estimation of descriptor systems with unknown inputs via the proposed results is also addressed. An illustrative example is given to show the novelty of the proposed results.