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The paper describes a hybrid air-fuel mixture control system that uses neural network and the direct adaptive algorithm. The A/F ratio stabilization to the stoichiometric value is required to obtain maximum efficiency of the three-way catalytic converter operation. The issues of the algorithm synthesis of the adaptive control of the fuel injection have been formulated. This was supplemented by the presentation of the state-of-the-art in the adaptive control theory as applied to non-stationary random object identification. The control algorithms of the fuel injection have been reviewed and classified. The fuel injection algorithms in the SI engine have been described and differentiated in terms of the used engine model and regulator structure. The algorithms comprise elements of the object modeling as well as adaptive coefficients for the control quality of the air-fuel ratio in the steady and non-steady conditions.