In this paper we construct an infinite horizon minimax state observer for a
linear stationary differential-algebraic equation (DAE) with uncertain but
bounded input and noisy output. We do not assume regularity or existence of a
(unique) solution for any initial state of the DAE. Our approach is based on a
generalization of Kalman's duality principle. The latter allows us to transform
minimax state estimation problem into a dual control problem for the adjoint
DAE: the state estimate in the original problem becomes the control input for
the dual problem and the cost function of the latter is, in fact, the
worst-case estimation error. Using geometric control theory, we construct an
optimal control in the feed-back form and represent it as an output of a stable
LTI system. The latter gives the minimax state estimator. In addition, we
obtain a solution of infinite-horizon linear quadratic optimal control problem
for DAEs.Comment: This is an extended version of the paper which is to appear in the
proceedings of the 52nd IEEE Conference on Decision and Control, Florence,
Italy, December 10-13, 201