Minimax Design of Kalman-Like Filters in the Presence of Large Parameter Uncertainties.
Abstract
The Kalman filter has been used in many applications, however, practical implementation of the filter has required exact knowledge of the various system parameters (input and measurement noise covariance) so as to yield optimum performance. The paper develops a minimax technique for the direct synthesis of Kalman-like estimators when there are large uncertainties in the a priori statistics of the plant and measurement noises. Both continuous and discrete estimators are considered. General properties of the filters that satisfy the various minimax performance indices are discussed and a number of examples of both continuous and discrete applications are then presented to demonstrate the technique. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 16, 1972
- Accession Number
- AD0753704
Entities
People
- C. E. Hutchinson
- J. A. D'appolito
- P. L. Bongiovanni
Organizations
- University of Massachusetts Amherst