To reduce the negative impact of stochastic noise in iterative learning control system, an iterative learning controller design method based on the Infinite Impulse Response (ⅡR) digital filter was proposed. For the first batch, the output errors from two repeated experiments were filtered by wavelet transform. Then the input/output data during the wavelet filtering process were used to obtain an equivalent ⅡR filter, which would be used to reconstruct the error objective function and optimize the iterative learning controller. Finally, the obtained ⅡR filter was applied to filter out the stochastic noise from subsequent batches until the convergence condition was met. Through simulation, compared with wavelet filtering, it could be demonstrated that by applying the proposed method, the 2-norm of output error could be reduced by nearly 15% and the ringing caused by setting the wavelet filter threshold too small was also avoided. The cumulative noise between the batches could be reduced by about 9%. The simulation results show that the proposed algorithm not only significantly reduces the negative effect of stochastic noise, but also effectively improves the accuracy of the tracking system.