The unknown nonlinear process is approximated by a Volterra series model which is a nonparametric description. The parameters of the Volterra series can be approximated recursively. Because of the large number of the parameters the usage of scalar convergence coefficients is recommended. The control algorithm is an extension of Brujin's predictive control algorithm, based on the weighting function series of linear systems, to the Volterra weighting function series model. The control signal is assumed constant during the control horizon and the calculation is repeated in every control interval. The above strategy results in a very robust algorithm