The problem of minimax design of linear observers and regulators for linear time-vqhg multivariable stochastic systems with uncertain models of their second-order statistics is treated in this paper. General classes of allowable covariance matrices and means of the process and observation noises and of the random initial condition are considered. A game formulation of the problem is adopted and it is shown that the optimal fiier for the least favorable set of covariances is minimax robust for each of the filtering situations analyzed. Conditions satisfied by the saddle-point solutions are given, and their utility for finding the worst case covariances is illustrated by way of several examples of uncertainty classes of practical interest.
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Computer Science Applications
- Electrical and Electronic Engineering