Jednostavna neizrazita identifikacija implementirana u naprednom regulatoru

The paper focuses on identification issues of the advanced controller ASPECT* that is implemented on a simple PLC platform with an extra mathematical coprocessor and is intended for the advanced control of complex plants. The model of the controlled plant is obtained by means of experimental modelling using an online learning procedure that combines model identification with pre- and post-identification steps that provide reliable operation. It is shown that acceptable performance of the system is obtained despite difficult conditions that may arise during operation.Ovaj se rad usredotočuje na problematiku identifikacije na osnovi naprednog regulatora ASPECT* implementiranog na jednostavnoj PLC platformi s dodatnim matematičkim koprocesorom, koji se želi koristiti za naprednu regulaciju složenih postrojenja. Model reguliranog postrojenja dobiva se eksperimentalnim modeliranjem, pri čemu se koristi on-line procedura učenja s pred- i post-identifikacijskim koracima koji osiguravaju pouzdan rad. Pokazano je da se prihvatljive performance sustava dobivaju unatoč teškim uvjetima koji se mogu pojaviti tijekom rada

Jednostavna neizrazita identifikacija implementirana u naprednom regulatoru

The paper focuses on identification issues of the advanced controller ASPECT* that is implemented on a simple PLC platform with an extra mathematical coprocessor and is intended for the advanced control of complex plants. The model of the controlled plant is obtained by means of experimental modelling using an online learning procedure that combines model identification with pre- and post-identification steps that provide reliable operation. It is shown that acceptable performance of the system is obtained despite difficult conditions that may arise during operation.Ovaj se rad usredotočuje na problematiku identifikacije na osnovi naprednog regulatora ASPECT* implementiranog na jednostavnoj PLC platformi s dodatnim matematičkim koprocesorom, koji se želi koristiti za naprednu regulaciju složenih postrojenja. Model reguliranog postrojenja dobiva se eksperimentalnim modeliranjem, pri čemu se koristi on-line procedura učenja s pred- i post-identifikacijskim koracima koji osiguravaju pouzdan rad. Pokazano je da se prihvatljive performance sustava dobivaju unatoč teškim uvjetima koji se mogu pojaviti tijekom rada

ITER plasma current and shape control using MPC

In plasma magnetic control schemes, comprising a cascade control scheme with a plasma current and shape controller (CSC) in the outer loop and a vertical stabilisation (VS) controller in the inner loop, the main challenges are: the suppression of plasma shape transients after disturbances specific to tokamak reactors; the robustness to changes of the local dynamics; using the available chamber volume in the best possible way, so that the plasma is placed as close as possible to the plasma facing components; and tight control near power supply and gap constraints. Model predictive control (MPC) is an advanced process control approach for dealing with constraints, already established in a range of industries involving multivariable processes with slower dynamics. In this work we present an MPC controller for the ITER CSC in order to assess the feasibility of its practical implementation, and a performance evaluation in comparison to a CSC based on singular perturbation decomposition (SPD)