ONLINE FREQUENCY-DOMAIN AND TIME-DOMAIN IDENTIFICATION OF A LINEAR-MULTIVARIABLE SYSTEM

A method for the on-line identification of a linear multivariable plant subject to both deterministic and stochastic disturbances is proposed. The identification scheme rests on the employment of sinusoids of distinct frequencies as probing-signal inputs and on the employment of linear time-varying filters to filter the plant inputs and the plant outputs. The time-varying filters are essentially banks of narrow-band filters tuned to the probing-signal frequencies. The filtered plant inputs and the filtered plant outputs yield an estimate of the plant transfer function matrix at the probing-signal frequencies. The filtered data are further processed using a recursive least-squares algorithm and a time-domain model estimate is obtained in terms of the coefficients of the difference equation relating each input-output pair. The identification algorithm is decoupled in the sense that the estimate of the transfer function or difference equation between the ith input and jth output is unaffected by other inputs or outputs. Simulation results on the performance of the time-varying filter and the identification scheme are given.