关键词: 两阶段递推算法, 递推贝叶斯算法, 最小二乘算法, 协方差重置

Abstract: In order to obtain unbiased estimates in the presence of colored noise, a two-stage recursive Bayesian identification algorithm is proposed based on auxiliary model principle and decomposing technique. In this algorithm, the original model is decomposed into two fictional sub-models firstly, and then identified respectively; the estimated noise variance and a new covariance resetting method are also integrated into the algorithm to obtain improved estimates. Compared with recursive least squares algorithm, the proposed algorithm can reduce the computational burden. According to the simulation, the estimation error of the proposed algorithms is smaller than that of the recursive least squares. An industrial application validates the proposed algorithm.

Key words: two-stage recursive algorithm, recursive Bayesian algorithm, the least squares algorithm, covariance resetting