%V 49
%T MIMO model of an interacting series process for Robust MPC via System Identification
%O cited By 9
%D 2010
%R 10.1016/j.isatra.2010.02.005
%N 3
%J ISA Transactions
%L scholars1388
%I ISA - Instrumentation, Systems, and Automation Society
%A T.C.S. Wibowo
%A N. Saad
%P 335-347
%X This paper discusses the empirical modeling using system identification technique with a focus on an interacting series process. The study is carried out experimentally using a gaseous pilot plant as the process, in which the dynamic of such a plant exhibits the typical dynamic of an interacting series process. Three practical approaches are investigated and their performances are evaluated. The models developed are also examined in real-time implementation of a linear model predictive control. The selected model is able to reproduce the main dynamic characteristics of the plant in open-loop and produces zero steady-state errors in closed-loop control system. Several issues concerning the identification process and the construction of a MIMO state space model for a series interacting process are deliberated. © 2010 ISA. Published by Elsevier Ltd. All rights reserved.
%K Closed loop control systems; Dynamics; Identification (control systems); Mathematical models; MIMO systems; Pilot plants; Predictive control systems; Real time control; Religious buildings; State space methods, Dynamic characteristics; Identification process; Interacting process; Linear modeling; Mimo state-space models; Real-time implementations; System identification techniques; Zero steady state error, Model predictive control, algorithm; article; computer system; forecasting; gas; industry; methodology; pilot study; reproducibility; statistical model, Algorithms; Computer Systems; Forecasting; Gases; Industry; Linear Models; Models, Statistical; Pilot Projects; Reproducibility of Results