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Invitation to submit papers to Special issue of the open access journal Processes on 
"Real-time optimization of processes using simple control structures, economic MPC or machine learning."
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Dear Colleagues,

I think Processes is the best open access journal in our field and I’m happy
to announce that we are planning a special issue of  'Processes' on "Real-time
optimization of processes using simple control structures, economic MPC or
machine learning." The main motivation behind the special issue, is the
realization that real-time optimization is not used as much in practice as one
would expect, so there is a need for new approaches, of which some are listed
in the above title. Other approaches than the one listed in the title of the
special issue may be also be included.  

The deadline for the manuscripts is November 15. 

However, for further planning please tell me if you are considering to contribute 
and provide a preliminary title of your planned contribution(s).

Note that this is an open access journal and the publication fee will be about 1200 USD.

Best regards,
Sigurd Skogestad
skoge@ntnu.no

For more information see here:

https://www.mdpi.com/journal/processes/special_issues/real_time_process


MORE INFORMATION:


The main motivation behind the Special Issue is the realization that real-time optimization is not used as much in practice as one would expect. Some of the reasons and challenges for this are (in expected order of importance):

- High cost of developing and updating the model structure (offline)
- Inaccurate values of model parameters and disturbances (online)
- Computational issues of solving numerical optimization problems

Therefore, there is a need for new approaches to address these challenges, some of which are indicated in the title of the Special Issue. In summary, the main goal of this Special Issue is to take a new look at the possibilities and advantages of exploiting process data more efficiently to address these challenges, may it be by using “traditional” optimal control methods like MPC and simple feedback controllers or advanced machine learning-based approaches. Other approaches than those listed may also be included.

The special issue calls for novel advances in theoretical development as well as applications of online process
optimization tools for large-scale process systems. The deadline for the manuscripts is November 15. For further
planning, we would like to know by June 5 whether you consider contributing and, if so, we would need a
preliminary title of your planned contribution(s). Please also let us know if you are not planning to contribute.
Topics include, but are not limited to: 

- Real-time optimization (RTO)
- Dynamic RTO and Economic MPC
- Machine learning and expert systems approaches
- Self-optimizing control
- Plantwide control
- Classical advanced control structures including cascade control, split range control, feedforward control, selectors, valve position control
- Extremum-seeking control/hill climbing/NCO tracking
- Combination of model- and data-based approaches, including modifier adaptation

Guest Editor
Prof. Sigurd Skogestad
skoge@ntnu.no
Department of Chemical Engineering, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway
Interests: Use of feedback as a tool to reduce uncertainty, change the system dynamics, and make the system more well-behaved, including self-optimizing control; Limitations on performance in linear systems, Real-time optimization; Control structure design and plantwide control; Interactions between process design and control. Distillation column design, control and dynamics

Guest Editor 
Dr. Dinesh Krishnamoorthy
dinesh.krishnamoorthy@ntnu.no
Department of Chemical Engineering, Norwegian University of Science and Technology (NTNU), 7491 Trondheim, Norway 
Interests: Real-time optimization and plantwide control; model-predictive control under uncertainty; measurement and learning-based optimization and control