Optimum Control of Linear, Sampled Data Systems with Inaccessible State Variables.
Some new results in the optimum control of linear systems with respect to a quadratic performance criterion. It is assumed that the system is subject to additive random disturbances and that some state variables cannot be measured or can only be measured with additive noise. It is well known that when the disturbance and noise are normal random variables, the optimum controller is a linear function of the minimum mean squared estimates for the state variables. In this study the result is shown to hold without qualification. 22 pp. Ref.