Abstract
Abstract Often only some aspect of the state needs to be estimated, not the whole state. This problem is referred to as output estimation Also, there may be disturbances other than Gaussian noise. In such situations a Kalman filter may not be the most appropriate estimator. Two alternative approaches are to reduce the H 2 or H ∞ output estimation error. A derivation of both types of estimators for output estimation of linear infinite-dimensional systems is provided. A practical framework for constructing finite-dimensional estimators that provide performance arbitrarily close to optimal is developed.
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