Abstract
This paper is concerned with the design of an adaptive observer which would identify the parameters and estimate the state of singleinput single-output discrete-time linear system with measurement noise.
The observer design is done by using the parametric representation of original system to separate the parameter identification process and the state estimation one. Parameter identification is carried out by using a method similar to RML (Recursive Maximum Likelihood) identifier. The main difference from RML method is the estimation of measurement vector. Since the proposed method utilizes the full available information in this estimation, the improvement of parameter estimation accuracy can be expected as compared with RML method. Once obtained the parameter estimate, the state estimate is obtained by simple manipulation of the parameter estimate.
A simulation result for two order system indicates the acceptable performance of the proposed method in both deterministic and stochastic environments.
