Persons at STU
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Basic information about a final thesisAdditional informationAdditional information about the final thesis follows. Click on the language link to display the information in the desired language.
|Language of final thesis:||English|
|Title of the thesis:||Tracking of Necessary Conditions of Optimality in Real-time Dynamic Optimisation of Batch Processes|
|Summary:||This work deals with optimal control of batch processes in the presence of uncertainty. An integrated two-time-scale control is proposed, whereby a run-to-run adaptation strategy with adaptation of the terminal constraints is implemented at the slow time scale, and is integrated with a neighbouring-extremal controller that operates at the fast time scale and performs further on-line corrections. This control scheme is especially suitable for repeatable batch processes with the fast changes in process dynamics. In addition, this scheme can be easily realised in real batch processes as the required computational power is low. Particularly, the only computation performed in real-time at each sampling time is a solution of a linear two-point boundary value problem. By sacrificing a bit of accuracy, all the required controlled designs and an accompanying computations might by done off-line. In the presence of uncertainty, the necessary conditions of optimality no longer hold. The core idea is to use the so called NCO-tracking approach that pushes the gradients caused by an uncertainty to zero. Neighbouring-extremal controller is approximated controller, i.e. it is based on linearisation of the nominal solution. Because of a lower performance of such control solution in chemical applications, the need for a supplementary adaptation is obvious. Our proposed control scheme thus corrects approximated control by another control. Run-to-run adaptation strategy updates the model between batches according to the latest constraints measurements and re-optimises the nominal solution. This solution then provides the reference trajectories for neighbouring-extremal controller. The thesis describes essentials to understand the basic building blocks of the proposed control scheme. In particular, the first part introduces the nominal optimisation, i.e optimisation under ideal circumstances without the influence of the uncertainty. Next part discusses the efficient algorithms that deals with the uncertainty. The proposed control is verified on real process. It is shown that the integrated two-time-scale control scheme has faster convergence rate and better performance in comparison to the other tested approaches.|
|Key words:||optimal control, necessary conditions of optimality, batch process|
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