An auxiliary-model-based improved stochastic Newton recursive algorithm is utilized to identify the output-error model for the dual-rate system. The output estimations at the time between two slow-sampled periods will diverge when the unstable estimated system arises and the identification process will cease. Therefore, a nonlinear model is proposed as the sub-auxiliary model. Together with the general auxiliary model, the proposed model provides estimated information for the next recursion. When the input is not general enough, the Hessian matrix will be singular or nearly singular. A positive definite symmetric matrix is added to the recursion for Hessian matrix to ensure it positive definite. Finally, the uniform convergence of the proposed algorithm is proved.