Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.7
3.5
Journals
Processes
Special Issues
Optimization-Driven Methods for Optimal Operation and Control Strategies
share announcement

Optimization-Driven Methods for Optimal Operation and Control Strategies

A special issue of Processes (ISSN 2227-9717). This special issue belongs to the section "Process Control and Monitoring".

Deadline for manuscript submissions: closed (30 May 2020) | Viewed by 21059

Special Issue Editor

Prof. Dr. Johannes Jäschke

E-Mail Website
Guest Editor
Department Chemical Engineering, Norwegian University of Science and Technology (NTNU), Trondheim, Norway
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 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 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 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.

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 (7 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

28 pages, 7445 KiB  
Article
Research on Improved Intelligent Control Processes Based on Three Kinds of Artificial Intelligence
by Jingwei Liu, Tianyue Li, Jiaming Chen and Fangling Zuo
Processes 2020, 8(9), 1042; https://doi.org/10.3390/pr8091042 - 26 Aug 2020
Cited by 1 | Viewed by 1737
Abstract
Autotuning and online tuning of control parameters in control processes (OTP) are widely used in practice, such as in chemical production and industrial control processes. Better performance (such as dynamic speed and steady-state error) and less repeated manual-tuning workloads in bad environments for [...] Read more.
Autotuning and online tuning of control parameters in control processes (OTP) are widely used in practice, such as in chemical production and industrial control processes. Better performance (such as dynamic speed and steady-state error) and less repeated manual-tuning workloads in bad environments for engineers are expected. The main works are as follows: Firstly, a change ratio for expert system and fuzzy-reasoning-based OTP methods is proposed. Secondly, a wavelet neural-network-based OTP method is proposed. Thirdly, comparative simulations are implemented in order to verify the performance. Finally, the stability of the proposed methods is analyzed based on the theory of stability. Results and effects are as follows: Firstly, the proposed control parameters of online tuning methods of artificial-intelligence-based classical control (AI-CC) systems had better performance, such as faster speed and smaller error. Secondly, stability was verified theoretically, so the proposed method could be applied with a guarantee. Thirdly, a lot of repeated and unsafe manual-based tuning work for engineers can be replaced by AI-CC systems. Finally, an upgrade solution AI-CC, with low cost, is provided for a large number of existing classical control systems. Full article
(This article belongs to the Special Issue Optimization-Driven Methods for Optimal Operation and Control Strategies)
►▼ Show Figures

Figure 1

36 pages, 1150 KiB  
Article
Robust Multi-Stage Nonlinear Model Predictive Control Using Sigma Points
by Sakthi Thangavel, Radoslav Paulen and Sebastian Engell
Processes 2020, 8(7), 851; https://doi.org/10.3390/pr8070851 - 16 Jul 2020
Cited by 4 | Viewed by 2960
Abstract
We address the question of how to reduce the inevitable loss of performance that is incurred by robust multi-stage NMPC due to the lack of knowledge compared to the case where the exact plant model (no uncertainty) is available. Multi-stage NMPC in the [...] Read more.
We address the question of how to reduce the inevitable loss of performance that is incurred by robust multi-stage NMPC due to the lack of knowledge compared to the case where the exact plant model (no uncertainty) is available. Multi-stage NMPC in the usual setting over-approximates a continuous parametric uncertainty set by a box and includes the corners of the box and the center point into the scenario tree. If the uncertainty set is not a box, this augments the uncertainty set and results in a performance loss. In this paper, we propose to mitigate this problem by two different approaches where the scenario tree of the multi-stage NMPC is built using sigma points. The chosen sigma points help to capture the true mean and covariance of the uncertainty set more precisely. The first method computes a box over-approximation of the reachable set of the system states whereas the second method computes a box over-approximation of the reachable set of the constraint function using the unscented transformation. The advantages of the proposed schemes over the traditional multi-stage NMPC are demonstrated using simulation studies of a simple semi-batch reactor and a more complex industrial semi-batch polymerization reactor benchmark example. Full article
(This article belongs to the Special Issue Optimization-Driven Methods for Optimal Operation and Control Strategies)
►▼ Show Figures

Figure 1

16 pages, 1466 KiB  
Article
Real-Time Optimization of Pulp Mill Operations with Wood Moisture Content Variation
by Wipawadee Nuengwang, Thongchai R. Srinophakun and Matthew J. Realff
Processes 2020, 8(6), 651; https://doi.org/10.3390/pr8060651 - 30 May 2020
Cited by 3 | Viewed by 2454
Abstract
In tropical countries, such as Thailand, the variation of tree moisture content can be significant based on seasonal variations in rainfall. Pulp mill operation optimization accounting for wood moisture variation was used to determine optimal operation conditions and minimize production cost. The optimization [...] Read more.
In tropical countries, such as Thailand, the variation of tree moisture content can be significant based on seasonal variations in rainfall. Pulp mill operation optimization accounting for wood moisture variation was used to determine optimal operation conditions and minimize production cost. The optimization models were built using empirical modeling techniques with simulated data from the IDEAS software package. Three case studies were performed. First, a base case of nominal annual operation at a fixed production rate was used to calculate production cost that varies with wood moisture content. The second case is annual optimization where production was allowed to vary monthly over an annual cycle to minimize production cost. For the third case, real-time optimization (RTO) was used to determine optimal production rate with the wood moisture content varying every 3 days. The rolling horizon approach was used to schedule production to keep inventory levels within bounds and with a penalty applied to deviations from the annual expected values of inventory. The advantage of RTO in accounting for moisture content variation was confirmed by annual production costs results simulated for 20 years. These results statistically demonstrated that the overall cost was reduced compared to the second case of monthly production targets. Full article
(This article belongs to the Special Issue Optimization-Driven Methods for Optimal Operation and Control Strategies)
►▼ Show Figures

Figure 1

21 pages, 6362 KiB  
Article
Leak Detection in Gas Mixture Pipelines under Transient Conditions Using Hammerstein Model and Adaptive Thresholds
by Syed Muhammad Mujtaba, Tamiru Alemu Lemma, Syed Ali Ammar Taqvi, Titus Ntow Ofei and Seshu Kumar Vandrangi
Processes 2020, 8(4), 474; https://doi.org/10.3390/pr8040474 - 17 Apr 2020
Cited by 19 | Viewed by 4471
Abstract
Conventional leak detection techniques require improvements to detect small leakage (<10%) in gas mixture pipelines under transient conditions. The current study is aimed to detect leakage in gas mixture pipelines under pseudo-random boundary conditions with a zero percent false alarm rate (FAR). Pressure [...] Read more.
Conventional leak detection techniques require improvements to detect small leakage (<10%) in gas mixture pipelines under transient conditions. The current study is aimed to detect leakage in gas mixture pipelines under pseudo-random boundary conditions with a zero percent false alarm rate (FAR). Pressure and mass flow rate signals at the pipeline inlet were used to estimate mass flow rate at the outlet under leak free conditions using Hammerstein model. These signals were further used to define adaptive thresholds to separate leakage from normal conditions. Unlike past studies, this work successfully detected leakage under transient conditions in an 80-km pipeline. The leakage detection performance of the proposed methodology was evaluated for several leak locations, varying leak sizes and, various signal to noise ratios (SNR). Leakage of 0.15 kg/s—3% of the nominal flow—was successfully detected under transient boundary conditions with a F-score of 99.7%. Hence, it can be concluded that the proposed methodology possesses a high potential to avoid false alarms and detect small leaks under transient conditions. In the future, the current methodology may be extended to locate and estimate the leakage point and size. Full article
(This article belongs to the Special Issue Optimization-Driven Methods for Optimal Operation and Control Strategies)
►▼ Show Figures

Figure 1

11 pages, 1082 KiB  
Article
Investigating Data-Driven Systems as Digital Twins: Numerical Behavior of Ho–Kalman Method for Order Estimation
by Alexios Papacharalampopoulos
Processes 2020, 8(4), 431; https://doi.org/10.3390/pr8040431 - 05 Apr 2020
Cited by 7 | Viewed by 2682
Abstract
System identification has been a major advancement in the evolution of engineering. As it is by default the first step towards a significant set of adaptive control techniques, it is imperative for engineers to apply it in order to practice control. Given that [...] Read more.
System identification has been a major advancement in the evolution of engineering. As it is by default the first step towards a significant set of adaptive control techniques, it is imperative for engineers to apply it in order to practice control. Given that system identification could be useful in creating a digital twin, this work focuses on the initial stage of the procedure by discussing simplistic system order identification. Through specific numerical examples, this study constitutes an investigation on the most “natural” method for estimating the order from responses in a convenient and seamless way in time-domain. The method itself, originally proposed by Ho and Kalman and utilizing linear algebra, is an intuitive tool retrieving information out of the data themselves. Finally, with the help of the limitations of the methods, the potential future outlook is discussed, under the prism of forming a digital twin. Full article
(This article belongs to the Special Issue Optimization-Driven Methods for Optimal Operation and Control Strategies)
►▼ Show Figures

Figure 1

13 pages, 1119 KiB  
Article
A Control-Performance-Based Partitioning Operating Space Approach in a Heterogeneous Multiple Model
by Bing Wu, Ximei Liu and Yaobin Yue
Processes 2020, 8(2), 215; https://doi.org/10.3390/pr8020215 - 11 Feb 2020
Viewed by 1681
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
(This article belongs to the Special Issue Optimization-Driven Methods for Optimal Operation and Control Strategies)
►▼ Show Figures

Figure 1

20 pages, 7110 KiB  
Article
The Application of a New PID Autotuning Method for the Steam/Water Loop in Large Scale Ships
by Shiquan Zhao, Sheng Liu, Robain De Keyser and Clara-Mihaela Ionescu
Processes 2020, 8(2), 196; https://doi.org/10.3390/pr8020196 - 06 Feb 2020
Cited by 4 | Viewed by 4487
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
(This article belongs to the Special Issue Optimization-Driven Methods for Optimal Operation and Control Strategies)
►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-7
Back to TopTop