Design of an optimal PI controller for a non-linear process using genetic algorithm Online publication date: Thu, 30-Sep-2010
by D. Rathikarani, D. Sivakumar
International Journal of Automation and Control (IJAAC), Vol. 4, No. 4, 2010
Abstract: Many industrial processes have to satisfy different criteria to achieve better quality product and performance. These multiple performance criteria need to be optimised simultaneously. However, a suitable optimal solution meeting the entire criteria can hardly be found since these criteria are conflicting. Compared to conventional optimisation techniques, genetic algorithms (GAs) are well suited to solve optimisation problems that involve multiple performance criteria. This paper presents the application of GA to optimise the PI controller parameters for a non-linear process. Least square estimation (LSE) method is used to estimate the parameters of the process. All the PI controllers which stabilise the given plant in the specified ranges are designed using the estimated plant parameters. GA searches the optimal controller parameters within this stabilising set. Experimental results are provided, showing the effectiveness of the multiple performance criteria tuned controller for a nonlinear process.
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