Analysis of stochastically disturbed industrial plants within short measuring time

For the analysis of heavily stochastically disturbed, linearizable control systems by means of predetermined test signals, measuring strategies are derived which ensure a short measuring time for the analysis with a prescribed accuracy and given technical limitations. The time favourable analysis strategy is obtained by resolving an isoperimetric variation problem with inequality constraints and a super-ordinated optimizing problem. A digital computer is utilized to calculate the optimum analysis strategy. An example is given which demonstrates the application of the programmed ALGOL algorithms.