Recursive identification algorithms for right matrix fraction description models

Multivariable identification algorithms are usually designed only for left matrix fraction description (LMFD) models. In this paper we consider recursive identification algorithms for right matrix fraction description (RMFD) models with diagonal denominator matrices. The algorithms are of prediction error (PE) and model reference (MR) type. Convergence analysis results give a positive realness condition for the convergence of the MR algorithm to the true RMFD of the system. The PE scheme converges to a local minimum of the criterion with probability 1. Results from simulations illustrate the convergence of the algorithms.

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