EFFECTIVE DECENTRALIZED TITO PROCESS IDENTIFICATION FROM CLOSED‐LOOP STEP RESPONSES

Abstract

In this paper, a new identification method performed in the time domain based on the decentralized step-test is proposed for two inputs and two outputs (TITO) processes with significant interactions. In terms of parameter identification, the coupled closed-loop TITO system is decoupled to obtain four individual single open-loop systems with the same input signal. As in the SISO case, new linear regression equations are derived, from which the parameters of a first- or second-order plus dead-time model can be obtained directly. The proposed method outperforms the existing estimation methods for multivariable control systems that use step-test responses. Furthermore, the method is robust in the presence of high levels of measurement noise. Simulation examples are given to show both effectiveness and practicality of the identification method for a wide range of multivariable processes. The usefulness of the identified method in multivariable process modeling and controller design is demonstrated.