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In this paper we provide the first solution to the challenging problem ofdesigning a globally exponentially convergent estimator for the parameters ofthe standard model of a continuous stirred tank reactor. Because of thepresence of non-separable exponential nonlinearities in the system dynamicsthat appear in Arrhenius law, none of the existing parameter estimators is ableto deal with them in an efficient way and, in spite of many attempts, theproblem was open for many years. To establish our result we propose a novelprocedure to obtain a suitable nonlinearly parameterized regression equationand introduce a radically new estimation algorithm - derived applying theImmersion and Invariance methodology - that is applicable to these regressionequations. A further contribution of the paper is that parameter convergence isguaranteed with weak excitation requirements.

A Globally Convergent Estimator of the Parameters of the Classical Model of a Continuous Stirred Tank Reactor