Estimation of Markov parameters and time-delay/interactor matrix

The ARRMarkov-least squares method is extended to multivariable systems. Th is method explicitly determines the Markov parameters (impulse response coe fficients) of a process using process input-output data and a standard leas t-squares (LS) algorithm. The parameter estimates are consistent and have t ighter confidence bounds than those produced by other linear regression met hods. The Interactor matrix, which defines the time delays in multivariable systems, can be directly estimated from the Markov parameters. From simula tion results it is observed that the Markov parameters estimated by the ARM arkov-LS method an the closest to the actual Markov parameters irrespective of the system order and lead to a better estimate of the interactor matrix than other linear regression methods such as Correlation Analysis, ARX, FI R, etc. The identified Markov parameters and/or the time-delay/interactor m atrix can be used directly in the design of model predictive controllers an d control loop performance assessment. (C) 2000 Elsevier Science Ltd. All r ights reserved.