A two-step algorithm for identification of linear plants

A noise-immune recurrence form of a two step algorithm for adaptive identification of linear plants is derived. For stationary plants the algorithm is proved to be monotonically convergent and the rate of convergent is found to be at least as good as that of the optimal single-step algorithm. The results of experimental computer studies of algorithm characteristics and an example of application to identification of a tube rolling mill are given.