Parameter dependent reduced order estimators

In this paper we consider the optimal reduced order estimation problem where the plant model depends on parameters that are measurable. Such cases occur in many applications and the question that arises is how to update the reduced order estimator without complete re-solution of the problem. A method of approximation of the updated estimator, which is based on its series expansion is given. A similar approach is used to develop a new algorithm for the numerical solution of the nominal problem.