Abstract
This paper presents an application of particle swarm optimisation (PSO) for system identification and tuning of the proportional integral (PI) controller in pH process. Two independent swarms are used sequentially for system identification and PI controller tuning. The proposed PSO utilises self tuning regulator to search for the changes in system parameters and to calculate the corresponding controller parameters. The self tuning regulator has a parameter identification function and requires neither prior knowledge nor training data for learning. Once the process parameters are identified, another PSO is applied to find the optimal controller setting. The performance of the proposed PSO approach is compared with the traditional Ziegler Nichols tuning and internal model control for various set point and trajectory response of the pH process. The simulation results show that the cascaded PSOs are very effective to adapt the controller to dynamic plant characteristic changes in pH process.
Published Version
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