Real-time Process Optimization with Simple Control Structures, Economic MPC or Machine Learning

Dear Colleagues,

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):

1. High cost of developing and updating the model structure (offline)
2. Inaccurate values of model parameters and disturbances (online)
3. 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

Prof. Dr. Sigurd Skogestad
Dr. Dinesh Krishnamoorthy
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Processes is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.