Advanced Control Engineering: Academia - Industry

Contribution List

8. CERN Industrial Control

Dr Philippe Gayet (CERN)

10. Control and simulation of cryogenic plants at CERN

Dr Benjamin Bradu (CERN)

CERN is operating the largest helium cryogenic installations of the world to maintain the 40 000 tons of the LHC at 1.9 K. To control these industrial plants, around 80 PLC (programmable Logic Controllers) are used handling more than 40 000 Inputs/Outputs. The PLC are also embedding around 5 000 PID regulation loops to maintain temperatures, pressures and flows at desired values. In these...

12. Design and Performance of the LHC beam-based Feedback Systems

Dr Ralph Steinhagen (CERN)

The LHC deploys a comprehensive suite of beam-based feedbacks for safe and reliable machine operation. More than 3500 devices, distributed over the 27 km circumference, are involved in these feedbacks, making them one of the largest and most complex systems at any present or previous high-energy accelerator. This contribution evaluates the underlying feedback control loop architecture, its...

13. Formal methods applied to PLC code verification

Mr Borja Fernandez Adiego (Universidad de Oviedo (ES))

PLCs are the most widely used control devices for industrial processes. Ensuring that PLC programs are compliant with the specifications is a challenging task and a highly recommended practice, especially for Safety Critical Systems. We propose a methodology for applying automated model checking to PLC programs hiding completely the complexity of using formal methods to PLC developers

11. High precision current control of the LHC Power Converters

Mr Hugues Thiesen (CERN)

The LHC requires a very high precision (a few ppm) in the control of the superconducting magnet currents. To reach this challenge a digital RST current loop has been developed to control the LHC power converters. This talk presents the RST theory and its application to the power converter control.

9. Model Predictive Control applied to the LHC magnets temperature control

Dr Enrique Blanco Vinuela (CERN)

The LHC superconducting magnets are operated below a temperature of 1.9 K along a circumference of 27 kilometers. The temperature of these magnets is a control parameter with very strict operating constraints. The presentation addresses the different approaches taken to overcome the complexity of the process and introducing a nonlinear control approach based on a predictive control technique...

7. Multiobjective optimization for engineering design

Prof. Xavier Blasco (Universitat Politècnica de Valencia - Spain)

Engineering design problems usually require the satisfaction of several objectives. In most cases there exists conflict among design requirements and, thus, the solution to the problem is not either unique or trivial. In fact finding a tradeoff solution for these multiobjetive optimization problems (MOP) is a crucial and time consuming task that the designer must carry out. Obtaining a design...

6. Overview of Model Predictive Control

Prof. Cesar de Prada (Universidad de Valladolid - Spain)

Model Predictive control (MPC) is a modern control technique that has gained high acceptance in industry due to its capability of dealing with large multivariable processes where demanding specifications and constraints must be met in spite of disturbances and operation changes. The talk gives an introduction to the fundamentals of this control technology, covering from basic concepts and...

5. Recent advances in PI/PID tuning

Prof. Ramon Vilanova (Universitat Autònoma de Barcelona - Spain)

PID control is well known as the dominant field feedback controller. Its simplicity, low number of parameters and acceptable performance levels even with “hand tunning” has made it the preferable option by most of the plant operators. During the last decade, some new perspectives o PI/PID tuning have raised that provide a more holistic and global view of the controller tuning procedure. The...

14. Visual data analytics applied to industrial processes

Dr Ignacio Diaz Blanco

The emerging field of visual analytics (VA) relies on combining intelligent data algorithms (IDA), visualization principles and interactive interfaces, amplifying human cognition to tackle problems that involve large datasets and non-explicit problem domain knowledge. We believe that the VA is a powerful approach for process analysis and optimization thanks to its ability to communicate...