Special Issue "Optimization-Driven Methods for Optimal Operation and Control Strategies"

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Computational Methods".

Deadline for manuscript submissions: 30 April 2020.

Special Issue Editor

Prof. Dr. Johannes Jäschke
E-Mail Website
Guest Editor
Department Chemical Engineering, Norwegian University of Science and Technology (NTNU)
Interests: combining optimization and control; real-time optimization; economic model predictive control; health-aware control and operation; control-structure design; modeling for optimization; energy storage

Special Issue Information

Dear Colleagues,

It is my pleasure to invite contributions to this Special Issue on Optimization-Driven Methods for Optimal Operation and Control Strategies.

Numerical optimization approaches have improved significantly in recent years. They enable us to find optimal operation and control strategies that trade-off many aspects of process operation while taking constraints into account. This has made optimization-based approaches attractive for industrial practitioners as well as academic research.

This Special Issue will collect contributions that apply and develop optimization concepts for realizing optimal process operation and control. This includes online-optimization methods, such as model predictive control (MPC) and real-time optimization (RTO), as well as developments that use optimization off-line for designing an optimal control structure, or controllers, including tuning. Applications of optimizations and new developments of optimization algorithms and methods are both welcome.

Topics include

  • Model predictive control
  • Dynamic real-time optimization / economic model predictive control
  • Real-time optimization / modifier adaptation / self-optimizing control
  • Optimization-based controller design and controller tuning methods
  • Learning-based optimization for optimal operation
  • Data-based optimization of operations
  • Plant-wide control approaches and control structure design

We welcome especially contributions in which optimization-based methods have been applied in industrial or pilot systems.

Prof. Dr. Johannes Jäschke
Guest Editor

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 papers will be 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 100 words) can be sent to the Editorial Office for announcement on this website.

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-blind 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 monthly 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 1400 CHF (Swiss Francs). Please note that for papers submitted after 30 June 2020 an APC of 1500 CHF applies. 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.

Keywords

  • Real-time optimization (RTO) 
  • Modifier-adaptation schemes 
  • Dynamic RTO and model predictive control 
  • Repeated identification and optimization 
  • Control structure design 
  • Controller tuning
  • Plantwide control 
  • Model-based and model-free approaches 
  • Classical process control
  • Simplified implementation of optimal operation

Published Papers (2 papers)

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Research

Open AccessArticle
A Control-Performance-Based Partitioning Operating Space Approach in a Heterogeneous Multiple Model
Processes 2020, 8(2), 215; https://doi.org/10.3390/pr8020215 - 11 Feb 2020
Abstract
An operating space partition method with control performance is proposed, where the heterogeneous multiple model is applied to a nonlinear system. Firstly, the heterogeneous multiple model is obtained from a nonlinear system at the given equilibrium points and transformed into a homogeneous multiple [...] Read more.
An operating space partition method with control performance is proposed, where the heterogeneous multiple model is applied to a nonlinear system. Firstly, the heterogeneous multiple model is obtained from a nonlinear system at the given equilibrium points and transformed into a homogeneous multiple model with auxiliary variables. Secondly, an optimal problem where decision variables are composed of control input and boundary conditions of sub-models is formulated with the hybrid model developed from the homogeneous multiple model. The computational implementation of an optimal operating space partition algorithm is presented according to the Hamilton–Jacobi–Bellman equation and numerical method. Finally, a multiple model predictive controller is designed, and the computational implementation of the multiple model predictive controller is addressed with the auxiliary vectors. Furthermore, a continuous stirred tank reactor (CSTR) is used to confirm the effectiveness of the developed method as well as compare with other operating space decomposition methods. Full article
Open AccessArticle
The Application of a New PID Autotuning Method for the Steam/Water Loop in Large Scale Ships
Processes 2020, 8(2), 196; https://doi.org/10.3390/pr8020196 - 06 Feb 2020
Abstract
In large scale ships, the most used controllers for the steam/water loop are still the proportional-integral-derivative (PID) controllers. However, the tuning rules for the PID parameters are based on empirical knowledge and the performance for the loops is not satisfying. In order to [...] Read more.
In large scale ships, the most used controllers for the steam/water loop are still the proportional-integral-derivative (PID) controllers. However, the tuning rules for the PID parameters are based on empirical knowledge and the performance for the loops is not satisfying. In order to improve the control performance of the steam/water loop, the application of a recently developed PID autotuning method is studied. Firstly, a ‘forbidden region’ on the Nyquist plane can be obtained based on user-defined performance requirements such as robustness or gain margin and phase margin. Secondly, the dynamic of the system can be obtained with a sine test around the operation point. Finally, the PID controller’s parameters can be obtained by locating the frequency response of the controlled system at the edge of the ‘forbidden region’. To verify the effectiveness of the new PID autotuning method, comparisons are presented with other PID autotuning methods, as well as the model predictive control. The results show the superiority of the new PID autotuning method. Full article
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