Advanced Cryogenics Process Control: Nonlinear Predictive Control

by Enrique Blanco (LHC Division)

Thursday 26 Apr 2001, 14:15 → 15:15 Europe/Zurich

Bldg. 112 / Room R-018 UNUSUAL PLACE

Most of the industrial processes are typically operated using linear controllers, although it is well known that many of these processes are highly nonlinear. Proportional, Integral and Derivative (PID) regulation is still the preferred control method in industry but 'modern' advanced control techniques are emerging and have already proven significant improvements over PID performance in processes where dynamics are highly complex and/or profit maximization is an issue. Cryogenic processes dynamics are inherently very nonlinear and present a fertile ground for applying modern control algorithms. These algorithms are intended to be better at handling undesirable features such us inverse response, variable dead time and non-self regulating behaviour. A nonlinear predictive controller for the superconducting magnet temperature regulation has been developed, commissioned and fully validated on the LHC String Test and the Inner Triplet (IT-HXTU). The followed methodology is a very illustrative procedure of how to successfully apply these optimization techniques to other areas of interest.