Fast error whitening algorithms for system identification and control

Linear system identifcation with noisy inputs is a critical problem in signal processing and control. Conventional techniques based on the Mean Squared-Error (MSE) criterion can at best provide a biased estimate of the unknown system being modeled. Recently, we proposed a new criterion called the Error Whitening Criterion (EWC) to solve the problem of linear parameter estimation in the presence of additive white noise. In this paper, we present a fmed-point type algorithm with Om’) complexity for EWC, called the Recursive Error Whitening (REW) algorithm. We will also show that the EWC solution can he solved by using the computational principles of Total Least-Squares (TLS). A novel EWC-TLS algorithm with Om’) complexity is derived. We will then apply the EWC methods for adaptive inverse control and show the superiority over existing methods.