A NEURO-FUZZY MODEL PREDICTIVE CONTROLLER APPLIED TO A PH-NEUTRALIZATION PROCESS
Jonas B. Waller and Hannu T. Toivonen
Department of Chemical Engineering, Åbo Akademi University, FI-20500 Åbo, Finland
This paper addresses the issue of controlling nonlinear processes by the use of the nonlinear model predictive control formulation. To handle the nonlinearities, a neuro-fuzzy process model is suggested as a means to model processes with strong nonlinearities depending on the operating region. In this paper the neuro-fuzzy approach is used for the modelling and control of a strongly nonlinear pH neutralization process, both in the face of set-point changes and in the face of unmodelled disturbances.
Keywords: Process control, pH control, nonlinear control, neural network models, nonlinear models
Session slot T-Tu-E11: Nonlinear Process Control II/Area code 7a : Chemical Process Control

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