School of electrical and electronic engineering

https://seee.hust.edu.vn

Professor from Dortmund Technical University to give a presentation at SEE

As part of ELITECH, the ELITECH Coordination Team collaborated with the School of Electrical Engineering to invite Professor Sebastian Engell from Dortmund Technical University to teach the Advanced Program and give a presentation on the development trend in the field. Process control and optimization problems in real time.

GS. Sebastian Engell is a world-renowned professor in process control. He has published over 150 articles in magazines and 300 prestigious conference papers in the field. He used to hold the position of Vice Principal in Scientific Research at Dortmund Technical University (Germany), Dean of Chemistry - Biochemistry Department. Currently, Prof. is the Chairman of the Strategic Development Council of the Association of Engineering and Process Engineering Faculties in Germany, National Council Member of the Faculty of Technical and Information Technology training of German universities. Professor is the president of the European Control Association (EUCA) in the period 2015-2017.

Time: Saturday, September 22, 2018 begins at 9:00

Location: Hall 301, C1, Hanoi University of Science and Technology
Presentation name: New developments in process control and real-time optimization
The teachers and students and students come together !!

Presentation Sumary: The economics and energy and resource efficiency of chemical production processes can be significantly improved by employing model-based optimizing control and model-based real-time optimization. We will discuss new developments in this area, focusing on how to cope with the inevitable deficiencies of model and the optimization of large production sites by distributed optimization and coordination.

We will first discuss the real-time optimization of the operating points of processing plants using a combination of models and measured data that was obtained at previous operating points. The measured data is used to iteratively correct the optimization model by means of the so-called modifier adaptation principle. In this context, we propose a novel way of estimating the modifiers – the empirical plant gradients- which is based on ideas from derivative-free optimization: MAWQA – Modifier Adaptation with Quadratic Approximation.

Secondly, we discuss the advantage of economics optimizing model predictive control and introduce multi-stage optimizing control which is a systematic way to achieve optimal performance and robust constraint satisfaction in the presence of model uncertainties. In contrast to other approaches, the presence of feedback in the control loop which enables corrections of the predicted control moves after new information has been obtained is taken into account in the optimization by computing so-called recourse actions.

 

Finally, for a number of reasons in large production sites an integrated optimization of the overall site is not feasible. We propose to use distributed optimization and coordination by market-like mechanisms and explain the principle by means of a case study of a Petrochemical plant.

 
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