Recursive Least Squares Algorithm for Nonlinear Dual-rate Systems Using Missing-Output Estimation Model

In this paper, a recursive least squares algorithm is proposed for a class of nonlinear dual-rate systems. By using the missing-output estimation model, the unavailable outputs can be estimated. Then, the unknown parameters can be estimated from all the inputs and outputs. Compared with the polynomial transformation technique and the lifting technique, the unknown parameters can be estimated directly by using the missing-output estimation model, without increasing the number of parameters. The convergence analysis and the simulation results indicate that the proposed method is effective.