system identification of an interacting process for a real time model preditive control 1.0

This paper presents the empirical modeling of thegaseous pilot plant which is a kind of interacting series processwith 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 Termsd-deOCLGaseous pilot plant, Serial interacting process,Empirical modeling, Model predictive control (MPC)

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	Approaches,  Control,  Implementation,  Linear,  Models,  Predictive,  Realtime,  Selected,  Suitable,  Tested
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