Tolerance assignment in linear networks using nonlinear programming

Abstract

Tolerance assignment in linear networks on a worstcase basis is treated as a nonlinear programming problem. The sequential unconstrained minimization technique of Fiacco and McCormick is employed as a solution mechanism with network behavior being evaluated by means of a large-change sensitivity model. The solution mechanism also yields worst-case responses at the constraint frequencies. Examples are presented and a comparison is made with the method proposed by Karafin.