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Advanced predictive control of a distillation column with neural models

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This paper describes application of linear and nonlinear Model Predictive Control (MPC) algorithms to a cyclohexane-heptane distillation column. Two nonlinear MPC techniques are compared in terms of control accuracy and computational complexity: MPC with Nonlinear Optimization (MPC-NO) and MPC with Nonlinear Prediction and Linearization (MPC-NPL). In nonlinear MPC a feedforward neural model is used rather than significantly complicated and causing numerical problems fundamental model of the process.
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Bibliogr. 33 poz., rys., tab.
  • Institute of Control and Computation Engineering, Faculty of Electronics and Information Technology, Warsaw University of Technology, Warszawa, Poland,
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