This paper presents the empirical modeling of the
gaseous pilot plant which is a kind of interacting series process
with presence of non linearities. In this study, the discrete-time identification approach based on subspace method with N4SIDalgorithm 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.
Index Terms—Gaseous pilot plant, Serial interacting process,
Empirical modeling, Model predictive control (MPC)
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