The problem of parameter recursive identification for minimum variance control was studied from the point of system identification.For the unknown parameter vector of the ARMAX model in the minimum variance closed loop control, we proposed a multi-innovation recursive least-squares identification method and a separable iterative recursive least-squares identification method to identify and estimate the unknown parameters vector in the ARMAX model on line.When excited by the white noise, both the methods could give the unbiased estimation about the unknown parameter vector.When excited by the colored noise, only the separable iterative recursive least-squares identification method could give the unbiased estimation.Finally, the effectiveness and feasibility of the proposed strategy was verified by the simulation results.