Input Design Minimizing the  -gap in Cross-Directional Models of Paper Machines

TitleInput Design Minimizing the  -gap in Cross-Directional Models of Paper Machines
Publication TypeConference Paper
Year of Publication2006
AuthorsAmmar, M., and G. Dumont
Conference NameAmerican Control Conference, 2006
Pagination3795 -3800
Date Publishedjun.
Keywordsclosed loop, closed loop systems, control system synthesis, cross-directional models, input-output identification, modeling uncertainties, noncausal transfer function, nu-gap metric, nu-gap minimization, nu-gap stability, paper machines, paper making machines, robust control, robustness, spatial domain, spatial response modeling, static spatial model, temporal transfer functions, transfer functions, uncertain systems

Modeling uncertainties resulting from input-output identification are inevitable. In this paper, input design minimizing the uncertainties in the static spatial model of paper machines is presented. A technique that was developed for temporal transfer functions was adapted to the spatial domain. The spatial response is modeled by a non-causal transfer function as it propagates in both the forward and backward directions of space. As the robustness of the closed loop is a crucial issue, the uncertainties are quantified using the nu-gap metric and the worst case nu-gap resulting from a prediction error experiment over all plants in the uncertainty region is minimized. The nu-gap stability criterion is extended to accommodate the non-causal system. Simulation results illustrate the advantage of using the designed input and the significance of the spatial nu-gap


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