With the ongoing trend in moving the upper levels of the automation hierarchy to the cloud, there
has been investigation into supplying industrial automation as a cloud based service. There are many
practical considerations which pose limitations on the feasibility of the idea. This research investigates
some of the requirements which would be needed to implement a platform which would facilitate
competition between different controllers which would compete to control a process in real-time. This
work considers only the issues relating to implementation of the philosophy from a control theoretic
perspective, issues relating to hardware/communications infrastructure and cyber security are beyond
the scope of this work.
A platform is formulated and all the relevant control requirements of the system are discussed. It is
found that in order for such a platform to determine the behaviour of a controller, it would need to
simulate the controller on a model of the process over an extended period of time. This would require
a measure of the disturbance to be available, or at least an estimate thereof. This therefore increases
the complexity of the platform. The practicality of implementing such a platform is discussed in terms
of system identification and model/controller maintenance. A model of the surge tank from SibanyeStillwater’s Platinum bulk tailings treatment (BTT) plant,
the aim of which is to keep the density of the tank outflow constant while maintaining a steady tank
level, was derived, linearised and an input-output controllability analysis performed on the model.
Six controllers were developed for the process, including four conventional feedback controllers
(decentralised PI, inverse, modified inverse and H¥) and two Model Predictive Controllers (MPC)
(one linear and another nonlinear). It was shown that both the inverse based and H¥ controllers fail to
control the tank level to set-point in the event of an unmeasured disturbance. The competing concept
was successfully illustrated on this process with the linear MPC controller being the most often selected
controller, and the overall performance of the plant substantially improved by having access to more
advanced control techniques, which is facilitated by the proposed platform.
A first appendix presents an investigation into a previously proposed switching philosophy  in
terms of its ability to determine the best controller, as well as the stability of the switching scheme. It
is found that this philosophy cannot provide an accurate measure of controller performance owing to
the use of one step ahead predictions to analyse controller behaviour. Owing to this, the philosophy
can select an unstable controller when there is a stable, well tuned controller competing to control the
A second appendix shows that there are cases where overall system performance can be improved
through the use of the proposed platform. In the presence of constraints on the rate of change of the
inputs, a more aggressive controller is shown to be selected so long as the disturbance or reference
changes do not cause the controller to violate these input constraints. This means that switching back
to a less aggressive controller is necessary in the event that the controller attempts to violate these
constraints. This is demonstrated on a simple first order plant as well as the surge tank process.
Overall it is concluded that, while there are practical issues surrounding plant and system identification
and model/controller maintenance, it would be possible to implement such a platform which would
allow a given plant access to advanced process control solutions without the need for procuring the
services of a large vendor.
Dissertation (MEng)--University of Pretoria, 2020.
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