Identification of multi-input systems based on correlation techniques

Abstract

This article proposes a correlation analysis-based identification method for multi-input single-output systems. The basic idea is to estimate the equivalent FIR model parameters with the orders increasing, and to compute the parameter estimates of the original systems (i.e. each fictitious subsystem) using the system inputs and the outputs of the estimated FIR models and using the least squares optimisation. Simulation results indicate that the proposed algorithm can work well.

Keywords:

• system identification
• parameter estimation
• correlation methods
• least squares
• structure determination
• multivariable systems