A Recursive Algorithm by using Eigenvector Method for Identifying Multivariable Linear Time-Invariant Systems

This paper discusses the identification of multivariable linear time-invariant systems, under the condition that colored noise disturbance exists both in the input and output observation data simultanuously. A recursive algorithm is developed by using eigenvector method for identifying multivariable systems, and also the problem of convergence is discussed. The result of simulation on digital computer shows that the convergence of the algorithm is assured, even under the condition that the noise to signal ratio is up to 33% in the output and up to 20% in the input, satisfactory result can still be obtained by using the recursive algorithm given in this paper.