System identification of an interacting series process for real-time model predictive control

• Main Authors: M.N., Karsiti, T.C.S., Wibowo, N., Saad
• Format: Conference or Workshop Item
• Published: 2009
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utp.edu.my/471/1/paper.pdf; http://www.scopus.com/inward/record.url?eid=2-s2.0-70449640063&partnerID=40&md5=65767b2aefe9805894163de7267fb35b; http://eprints.utp.edu.my/471/
• Institution: Universiti Teknologi Petronas

This paper presents the empirical modeling of the gaseous pilot plant which is a kind of interacting series process with presence of nonlinearities. In this study, the discrete-time identification approach based on subspace method with N4SID algorithm is applied to construct the state space model around a given operating point, by probing the system in open-loop with variation of input signals. Three practical approaches are used and their performances are compared to obtain the most suitable approach for modeling of such a system. The models are also tested in the real-time implementation of a linear model predictive control. The selected model is able to well reproduce the main dynamic characteristics of gaseous pilot 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 MIMO state space model are discussed. © 2009 AACC.