Van Niekerk, J.A.Le Roux, Johan DerikCraig, Ian Keith2022-11-232022-11-232022Van Niekerk, J.A. , Le Roux, J.D. & Craig, I.K. 2022, 'On-line automatic controller tuning using Bayesian optimisation - a bulk tailings treatment plant case study', IFAC-PapersOnLine, vol. 55, no. 21, pp. 126-131, doi: 10.1016/j.ifacol.2022.09.255.2405-8963 (online)10.1016/j.ifacol.2022.09.255https://repository.up.ac.za/handle/2263/88456The automatic tuning problem of multiple-input-multiple-output (MIMO) controllers is considered within the framework of Bayesian optimisation and applied in simulation to a bulk tailings treatment process. The aim is to develop a model free, on-line, automatic tuner which can optimise the performance of a given controller to the task at hand. The automatic tuning procedure can be conducted during commissioning, when poor controller performance is observed or when the process has changed. Simulations indicate that the method is able to locate the optimal tuning parameters for the bulk tailings treatment process as compared to a de-coupled controller developed from a model of the process. The parameters were obtained from an objective function which was balanced and weighted according to the response required.en© 2022 The Authors. This is an open access article under the CC BY-NC-ND license.Bayesian optimisationGaussian processesAcquisition functionAuto tuningBulk tailings treatmentMultiple-input-multiple-output (MIMO)Article