Real-time, non-linear optimization for industrial applications

(Actualized on 20-12-2012)

Non-linear Model Predictive Control directly adresses many aspects of complex industrial plant dynamics, like strong non-linearities, inverse responses, variable dead times and complex couplings between process vars. The controler uses a non-linear plant model to make predictions of future plant behaviour and optimize closed loop plant dynamics in real-time. The computational cost of such optimizations is high, hovever with modern computers and algorithms it is now applicable to a wider range of systems.

The aim of the project is to develop a real-time non-linear optimization platform for wide range of industrial control applications. This framework is based on a novel, low computational cost formulation of a Non-linear Programming Problem with inequality constraints and one step Newton-type method. It has been originally developed for application of the Nonlinear Model Predictive Control (NMPC) for the Superfluid Helium Cryogenic Circuit at the Large Hadron Collider (LHC) Arcs, see the homepage of that project at www.predictive-control.com/lhc.

Rafal Noga

Bibliography

[1] R Noga. "PhD Thesis description: Non-linear Model based Predictive Control (NMPC)of the Large Hydron Collider's (LHC) Super fluid Helium Cryogenic Circuit". University of Valladolid, CERN. 2008 (Download)
[2] R Noga. Modeling and control of the String2 LHC Prototype at CERN. Master's thesis, Gdansk University of Technology, University of Karlsruhe, Grenoble Institute of Technology, 2007. (Download)
[3]R Noga, C de Prada. First principles modeling of the Large Hadron Colliders (LHC) Super Fluid Helium Cryogenic Circuit. In Proceedings of 20th European Modeling and Simulation Symposium (EMSS08), 2008. (Download)
[4] R Noga, T Ohtsuka, C de Prada, E Blanco, and J Casas. Nonlinear Model Predictive Control for the Superfluid Helium Cryogenic Circuit of the Large Hadron Collider. In Proceedings of the 2010 IEEE International Conference on Control Applications, 2010. (Download)
[5] R Noga, T Ohtsuka, C de Prada, E Blanco, and J Casas. Simulation Study on Application of Nonlinear Model Predictive Control to the Superfluid Helium Cryogenic Circuit. Accepted to IFAC WC2011, 2010. (Download)
[6] R Noga, T Ohtsuka. NMPC for stiff, distributed parameter system: Semi-Automatic Code Generation and optimality condition evaluation. Submitted to PC2011, 2010. (Download Paper,Download Presentation)