Adaptive dynamic matrix control for a multivariable training plant.
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Date
2001
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Abstract
Dynamic Matrix Control (DMC) has proven to be a powerful tool for optimal regulation of
chemical processes under constrained conditions. The internal model of this predictive
controller is based on step response measurements at an average operating point. As the process
moves away from this point, however, control becomes sub-optimal due to process
non-linearity. If DMC is made adaptive, it can be expected to perform well even in the presence
of uncertainties, non-linearities and time-vary ing process parameters.
This project examines modelling and control issues for a complex multivariable industrial
operator training plant, and develops and applies a method for adapting the controller on-line to
account for non-linearity. A two-input/two-output sub-system of the Training Plant was
considered. A special technique had to be developed to deal with the integrating nature of this
system - that is, its production of ramp outputs for step inputs.
The project included the commissioning of the process equipment and the addition of
instrumentation and interfacing to a SCADA system which has been developed in the School of
Chemical Engineering.
Description
Thesis (M.Sc.Eng.)-University of Natal, Durban, 2001.
Keywords
Chemical process control., Predictive control., Adaptive control systems., Theses--Chemical engineering.