The stochastic approximation type algorithm with input disturbance is proposed. The algorithm enables to form consistent estimates of unknown function point of minima which depend on random parameter in the presence of correlated noises. The algorithm convergence is proved under assumption that disturbance and noises are independent. The algorithm is illustrated for the example of identification of mean values of parameters of non-stationary moving average process.