In this paper,a reinforced gradient-type iterative learning control pro file is proposed by making use of system matrices and a proper learning step to improve the tracking performance of batch processes disturbed by external Gaussian white noise.The robustness is analyzed and the range of the step is speci fied by means of statistical technique and matrix theory.Compared with the conventional one,the proposed algorithm is more ef ficient to resist external noise.Numerical simulations of an injection molding process illustrate that the proposed scheme is feasible and effective. In this paper, an reinforced gradient-type iterative learning control pro file is proposed by making use of system matrices and a proper learning step to improve the tracking performance of batch processes disturbed by external Gaussian white noise. The robustness is analyzed and the range of the step is speci fied by means of statistical technique and matrix theory. Compared with the conventional one, the proposed algorithm is more ef ficient to resist external noise. Numerical simulations of an injection molding process that that proposed scheme is feasible and effective.