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The performance of a three-way catalytic converter under transient operation can be improved by controlling the level of oxygen stored on ceria at some optimal level. A model-based controller, with the model estimating the level of ceria coverage by oxygen, can achieve this goal. A simple, dynamic model is based on step responses of the converter and is used to train the controller off-line. The controller is a neuro-fuzzy approximation of a model predictive controller. Thus, it retains a high performance while being less computationally involving. The system performance has been experimentally tested by a specially designed, highly transient test cycle.