The initial objective of the work was to update the reactor pilot-scale rig command and control system. This enabled a variety of self-tuning control strategies [self-tuning PID (STPID), generalised minimum variance (GMV) and generalised predictive control (GPC)] to be applied in an attempt to achieve the desired control objectives. The different self-tuning control procedures were designed, then tested by simulation, and finally implemented on the experimental rig. It has been found that GPC gives superior control (in comparison to STPID and GMV) when the system dead-time varies and or has been poorly estimated. The GPC strategy is demonstrated further to cope well with system non-linearities. The preheater outlet temperature on the pilot plant is shown to be successfully controlled using all three self-tuning strategies. Generalised predictive control is found to give excellent results when employed to control the inlet temperature and the position and temperature of the hot-spot of the fixed-bed reactor where poorly known and variable dead-times are present. The hot-spot temperature on the rig is shown to be well controlled also by employing a new version of the generalised predictive controller, viz. extremum GPC. Finally both STPID and GPC strategies are found to be successful when based on a design which employs a neural network for system identification and prediction instead of the normal least squares procedure.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:638037 |
| Date | January 1995 |
| Creators | Mazana, N. |
| Publisher | Swansea University |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
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