Accession Number : AD0753704

Title :   Minimax Design of Kalman-Like Filters in the Presence of Large Parameter Uncertainties.

Descriptive Note : Research rept.,

Corporate Author : MASSACHUSETTS UNIV AMHERST DEPT OF ELECTRICAL AND COMPUTER ENGINEERING

Personal Author(s) : Hutchinson,C. E. ; D'Appolito,J. A. ; Bongiovanni,P. L.

Report Date : 16 AUG 1972

Pagination or Media Count : 11

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)

Descriptors :   (*ADAPTIVE CONTROL SYSTEMS, MATHEMATICAL MODELS), LINEAR SYSTEMS, WHITE NOISE, STOCHASTIC PROCESSES, MATRICES(MATHEMATICS), MINIMAX TECHNIQUE, STATISTICAL ANALYSIS

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE