The Global Error Approach to the Convergence and Accuracy of Complex Recursive Identification Algorithms

Abstract

The global error is the identification error expressed expiIcItly as a function of all unknown system parameters, model parameters and external system inputs. It is used to transform the difficult problem of mean-square convergence and accuracy testing for recursive identification algorithms into a relatively simple problem of determining the properties of the solution for a polynomial equation. The method is introduced for the simple problem of closed-loop identification of time-discrete systems. Its full power is demonstrated for the case of the self-tuning regulator and self-tuning predictor.