An off-line Model Reduction-based Technique for On-line Linear MPC Applications for Nonlinear Large- Scale Distributed Systems

نویسندگان

  • Weiguo Xie
  • Constantinos Theodoropoulos
چکیده

Linear Model Predictive Control (MPC) has been effectively applied for many process systems. However, linear MPC is often inappropriate for controlling nonlinear largescale systems. To overcome this, model reduction methodology has been exploited to enable the efficient application of linear MPC for nonlinear distributed-parameter systems. An implementation of the proper orthogonal decomposition method combined with a finite element Galerkin projection is first used to extract accurate non-linear loworder models from the large-scale ones. Then a Trajectory Piecewise-Linear method is developed to construct a piecewise linear representation of the reduced nonlinear model. Linear MPC, based on quadratic programming, can then be efficiently performed on the resulting system. The stabilisation of the oscillatory behaviour of a tubular reactor with recycle is used as an illustrative example to demonstrate our methodology.

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تاریخ انتشار 2010