IDENTIFICATION OF NONLINEAR SYSTEMS USING GAUSSIAN MIXTURE OF LOCAL MODELS

Abstract

Identification of operating regime based models of nonlinear dynamic systems is addressed. The operating regimes and the parameters of the local linear models are identified directly and simultaneously based on the Expectation Maximization (EM) identification of Gaussian Mixture Model (GMM). The proposed technique is demonstrated by means of the identification of a neutralization reaction in a continuously stirred tank reactor.