Auto-tuning of dual mode controllers using genetic algorithms

The techniques adopted in this paper involves firstly collecting experimental data to identify the simplified process model using genetic algorithm. The identified model, the GA and simulation methods, are then used to off-line tune the dual mode controller, so as to minimise a time-domain based cost function. Finally, the genetically tuned controller is implemented online on the real process. The results of the auto-tuning of the dual mode controller technique are illustrated on a laboratory heat exchanger, and a comparison between this and the Åstrom PI auto-tuning technique are made