Decentralized closed-loop parameter identification for multivariable processes from step responses Original Research Article

This paper presents a novel technique for on-line decentralized closed-loop parameter identification of multivariable processes from step responses. Based on simple sequential step tests, the coupled closed-loop n-inputs and n-outputs (n × n) multivariable process is decoupled equivalently into n2 independent single open-loop processes with an unit step input signal acting on the n2 transfer functions. By using virtual step response signals, the parameters of each element in the transfer function matrix can be directly identified by the well-developed least squares methods. The significance of the proposed method is that it relaxes most restrictions of existing multivariable process identification methods, it is universally applicable to closed-loop identification for cross-coupling multivariable processes. Simulation examples are given to show both effectiveness and practicality of the identification method for a wide range of multivariable processes.