1
|
Xu J. Efficiency-Oriented Model Predictive Control: A Novel MPC Strategy to Optimize the Global Process Performance. SENSORS (BASEL, SWITZERLAND) 2024; 24:5732. [PMID: 39275643 PMCID: PMC11397815 DOI: 10.3390/s24175732] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2024] [Revised: 09/01/2024] [Accepted: 09/02/2024] [Indexed: 09/16/2024]
Abstract
Existing control strategies, such as Real-time Optimization (RTO), Dynamic Real-time Optimization (DRTO), and Economic Model Predictive Control (EMPC) cannot enable optimal operation and control behavior in an optimal fashion. This work proposes a novel control strategy, named the efficiency-oriented model predictive control (MPC), which can fully realize the potential of the optimization margin to improve the global process performance of the whole system. The ideas of optimization margin and optimization efficiency are first proposed to measure the superiority of the control strategy. Our new efficiency-oriented MPC innovatively uses a nested optimization structure to optimize the optimization margin directly online. To realize the computation, a Periodic Approximation technique is proposed, and an Efficiency-Oriented MPC Type I is constructed based on the Periodic Approximation. In order to alleviate the strict constraint of Efficiency-Oriented MPC Type I, the zone-control-based optimization concept is used to construct an Efficiency-Oriented MPC Type II. These two well-designed efficiency-oriented controllers were compared with other control strategies over a Continuous Stirred Tank Reactor (CSTR) application. The simulation results show that the proposed control strategy can generate superior closed-loop process performance, for example, and the Efficiency-Oriented MPC Type I can obtain 7.11% higher profits than those of other control strategies; the effectiveness of the efficiency-oriented MPC was, thereby, demonstrated.
Collapse
Affiliation(s)
- Jiahong Xu
- Robotics Institute, Ningbo University of Technology, Ningbo 315211, China
| |
Collapse
|
2
|
Ławryńczuk M, Nebeluk R. Beyond the quadratic norm: Computationally efficient constrained nonlinear MPC using a custom cost function. ISA TRANSACTIONS 2023; 134:336-356. [PMID: 36153191 DOI: 10.1016/j.isatra.2022.09.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 09/05/2022] [Accepted: 09/05/2022] [Indexed: 06/16/2023]
Abstract
A new approach to nonlinear Model Predictive Control (MPC) is discussed in this work. A custom user-defined cost function is used in place of the typically considered quadratic norm. An approximator of the cost function is applied to obtain a computationally simple procedure and linearization of two trajectories is carried out online. The predicted output trajectory of the approximator and the predicted trajectory of the manipulated variable, both over the prediction horizon, are repeatedly linearized online. It yields a simple quadratic programming task. The algorithm is implemented for a simulated neutralization benchmark modeled by a neural Wiener model. The resulting control quality is excellent, identical to that observed in the MPC scheme with nonlinear optimization. Validity of the described MPC algorithms is demonstrated when only simple box constraints are considered on the process input variable and in a more demanding case when additional soft limitations are put on the predicted output. Two structures of the approximator are compared: polynomial and neural; the advantages of the latter one are shown and stressed.
Collapse
Affiliation(s)
- Maciej Ławryńczuk
- Warsaw University of Technology, Faculty of Electronics and Information Technology, Institute of Control and Computation Engineering, ul. Nowowiejska 15/19, 00-665 Warsaw, Poland.
| | - Robert Nebeluk
- Warsaw University of Technology, Faculty of Electronics and Information Technology, Institute of Control and Computation Engineering, ul. Nowowiejska 15/19, 00-665 Warsaw, Poland.
| |
Collapse
|
3
|
Fan Z, Ren Z, Chen A. Multi-objective predictive control based on the cutting tobacco outlet moisture priority. Sci Rep 2023; 13:199. [PMID: 36604460 PMCID: PMC9814934 DOI: 10.1038/s41598-022-26694-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Accepted: 12/19/2022] [Indexed: 01/06/2023] Open
Abstract
In this paper, we propose a new priority multi-objective optimization strategy of system output variables in cutting tobacco process. The proposed strategy focuses on the cutting tobacco moisture-controlled output variables optimization in feasible regions with two levels according to the priority. This study aims to provide a novel technical support for the chemical industry contained drying process. In order to alleviate the lack of degree of freedom of the system, strict set-point control is given, meanwhile, other output variables adopt zone control. Firstly, the system control output variables are optimized in ascending order of priority. Secondly, the specific lower-level target constraints are first relaxed. Finally, the relaxation of other high-priority target constraints is stopped when the optimization is feasible. Thus, the system control output variables move along the optimal target trajectory. From the perspective of practical application of engineering, under the condition of disturbance existing in the cutting tobacco drying process, the simulation shows that the proposed approach has good robustness when there is disturbance, and the previous method cannot meet the control requirement. The proposed strategy meanwhile has better tracking effect through single and multiple output variables simulation, which compared with traditional predictive control in real cutting tobacco drying process.
Collapse
Affiliation(s)
- Zhiping Fan
- School of Electrical and Electronic Engineering, Anhui Science and Technology University, Bengbu, 233000, China. .,College of Information Science and Technology, Donghua University, Shanghai, 201620, China.
| | - Zhengyun Ren
- grid.255169.c0000 0000 9141 4786College of Information Science and Technology, Donghua University, Shanghai, 201620 China
| | - Angang Chen
- Guotai Junan Securities Co., Ltd., Shanghai, 200041 China
| |
Collapse
|
4
|
Gupta N, De R, Kodamana H, Bhartiya S. Batch-to-Batch Adaptive Iterative Learning Control-Explicit Model Predictive Control Two-Tier Framework for the Control of Batch Transesterification Process. ACS OMEGA 2022; 7:41001-41012. [PMID: 36406504 PMCID: PMC9670101 DOI: 10.1021/acsomega.2c04255] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Accepted: 09/29/2022] [Indexed: 06/16/2023]
Abstract
To harness energy security and reduce carbon emissions, humankind is trying to switch toward renewable energy resources. To this extent, fatty acid methyl esters, also known as biodiesel, are popularly used as a green fuel. Fatty acid methyl esters can be produced by a batch transesterification reaction between vegetable oil and alcohol. Being a batch process, fatty acid methyl esters production is beset with issues such as uncertainties and unsteady state behavior, and therefore, adequate process control measures are necessitated. In this study, we have proposed a novel two-tier framework for the control of the fatty acid methyl esters production process. The proposed approach combines the constrained batch-to-batch iterative learning control technique and explicit model predictive control to obtain the desired concentration of the fatty acid methyl esters. In particular, the batch-to-batch iterative learning control technique is used to generate reactor temperature set-points, which is further utilized to obtain an optimal coolant flow rate by solving a quadratic objective cost function, with the help of explicit model predictive control. Our simulation results indicate that the fatty acid methyl esters concentration trajectory converges to the desired batch trajectory within four batches for uncertainty in activation energy and six batches for uncertainty in both inlet concentration of triglyceride and in activation energy even in the presence of process disturbances. The proposed approach was compared to the heuristic-based approach and constraint iterative learning control approach to showcase its efficacy.
Collapse
Affiliation(s)
- Nikita Gupta
- Department
of Chemical Engineering, IIT Delhi, New Delhi110016, India
| | - Riju De
- Department
of Chemical Engineering, BITS Pilani, K.
K. Birla Goa Campus, Zuarinagar, Goa403726, India
| | - Hariprasad Kodamana
- Department
of Chemical Engineering & Yardi School of Artificial Intelligence, IIT Delhi, New
Delhi110016, India
| | - Sharad Bhartiya
- Department
of Chemical Engineering, IIT Bombay, Mumbai, Maharashtra400 076, India
| |
Collapse
|
5
|
Efficiency-Oriented MPC: Using Nested Structure to Realize Optimal Operation and Control. MATHEMATICS 2022. [DOI: 10.3390/math10132324] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Optimal operation and control, which can result in the global optimal operation performance of industrial processes, has been a hot topic in recent control strategy designs. However, existing control strategies, such as real-time optimization (RTO), dynamic real-time optimization (DRTO), and economic model predictive control (EMPC), have their own limitations, and they can only generate sub-optimal operation performance. In order to further improve online global operation performance, a new kind of control strategy named efficiency-oriented model predictive control (EfiMPC) is proposed in this paper. The aim of the EfiMPC is discussed first, and then, the ideal EfiMPC strategy with a nested structure is proposed, where the inner layer is the offline construction of an efficiency-oriented terminal region, and the outer layer is the direct optimization of the transient operation performance. This efficiency-oriented terminal region can guarantee a dynamic operation performance in the closed-loop perspective, and a better global operation performance can thus be obtained. A practical EfiMPC strategy, which replaces the offline construction of the efficiency-oriented terminal region with the online optimization of the average dynamic operation performance in the inner layer, is also proposed, and the recursive feasibility as well as the closed-loop stability of practical EfiMPC are discussed. Finally, a CSTR application was used to test the superiority of the proposed EfiMPC strategy, and the simulation results show that EfiMPC can obtain the best global operation performance compared with the other three control strategies; thus, the effectiveness of EfiMPC is demonstrated.
Collapse
|
6
|
Multi-Objective-Based Tuning of Economic Model Predictive Control of Drinking Water Transport Networks. WATER 2022. [DOI: 10.3390/w14081222] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
In this paper, the tuning of economic model predictive control (EMPC) applied to drinking water transport networks (DWTNs) is addressed using multi-objective optimization approaches. The tuning strategies are based on Pareto front calculations of the underlying multi-objective problem. This feature represents an improvement with respect to the standard EMPC approach for weight tuning based on trial and error. Different multi-objective optimization methods with corresponding normalization approaches of the controller objectives are first studied to explore the dynamic nature of the Pareto fronts. An automated decision-making strategy is proposed to select the preferred controller parameters as a function of different disturbance values. The tuning requires an offline training phase and an online application phase. During the offline phase, the controller parameters are selected for different disturbances using the decision-making strategy. During the online phase, two approaches are evaluated: (i) exploiting the controller parameters with the highest frequency in the resulting histogram or (ii) using a regression model between the controller parameters and the disturbances. The proposed tuning strategies are applied to a real-life simulation case study based on the Barcelona DWTN. The simulation results show that the proposed tuning strategies outperform the baseline results by exploiting the periodicity of the water demands profile.
Collapse
|
7
|
Multi Set-Point Explicit Model Predictive Control for Nonlinear Process Systems. Processes (Basel) 2021. [DOI: 10.3390/pr9071156] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
In this article, we introduce a novel framework for the design of multi set-point nonlinear explicit controllers for process systems engineering problems where the set-points are treated as uncertain parameters simultaneously with the initial state of the dynamical system at each sampling instance. To this end, an algorithm for a special class of multi-parametric nonlinear programming problems with uncertain parameters on the right-hand side of the constraints and the cost coefficients of the objective function is presented. The algorithm is based on computed algebra methods for symbolic manipulation that enable an analytical solution of the optimality conditions of the underlying multi-parametric nonlinear program. A notable property of the presented algorithm is the computation of exact, in general nonconvex, critical regions that results in potentially great computational savings through a reduction in the number of convex approximate critical regions.
Collapse
|
8
|
Zangina JS, Wang W, Qin W, Gui W, Zhang Z, Xu S, Yang C, Wang Y, Liu X. Model Predictive Control of a High‐Purity Internal Thermally Coupled Distillation Column. Chem Eng Technol 2021. [DOI: 10.1002/ceat.202000617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Ja'afar Sulaiman Zangina
- Zhejiang University Zhejiang University NGICS Platform State Key Laboratory of Industrial Control Technology College of Control Science & Engineering 310027 Hangzhou China
| | - Wenhai Wang
- Zhejiang University Zhejiang University NGICS Platform State Key Laboratory of Industrial Control Technology College of Control Science & Engineering 310027 Hangzhou China
| | - Weizhong Qin
- China Petroleum Chemical Co. Jiujiang Branch 332004 Jiujiang China
| | - Weihua Gui
- Central South University School of Information Science & Engineering 410083 Changsha China
| | - Zeyin Zhang
- Zhejiang University Zhejiang University NGICS Platform State Key Laboratory of Industrial Control Technology College of Control Science & Engineering 310027 Hangzhou China
| | - Shenghu Xu
- China Petroleum Chemical Co. Jiujiang Branch 332004 Jiujiang China
| | - Chunhua Yang
- Central South University School of Information Science & Engineering 410083 Changsha China
| | - Yalin Wang
- Central South University School of Information Science & Engineering 410083 Changsha China
| | - Xinggao Liu
- Zhejiang University Zhejiang University NGICS Platform State Key Laboratory of Industrial Control Technology College of Control Science & Engineering 310027 Hangzhou China
| |
Collapse
|
9
|
Wan X, Luo XL. Economic Optimization in the Non-Steady-State Periodic Orbit under Zone Model Predictive Control for the Chemical Process: A Case Study of a Heavy-Oil Fractionator. Ind Eng Chem Res 2021. [DOI: 10.1021/acs.iecr.1c01168] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Xin Wan
- Department of Automation, China University of Petroleum Beijing, 102249 Beijing, China
| | - Xiong-Lin Luo
- Department of Automation, China University of Petroleum Beijing, 102249 Beijing, China
| |
Collapse
|
10
|
Sharikov YV, Tkachev IV, Snegirev NV. Modeling Optimal Control over a Nonlinear Object. THEORETICAL FOUNDATIONS OF CHEMICAL ENGINEERING 2020. [DOI: 10.1134/s0040579520050425] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
|
11
|
Model-Free Extremum Seeking Control of Bioprocesses: A Review with a Worked Example. Processes (Basel) 2020. [DOI: 10.3390/pr8101209] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Uncertainty is a common feature of biological systems, and model-free extremum-seeking control has proved a relevant approach to avoid the typical problems related to model-based optimization, e.g., time- and resource-consuming derivation and identification of dynamic models, and lack of robustness of optimal control. In this article, a review of the past and current trends in model-free extremum seeking is proposed with an emphasis on finding optimal operating conditions of bioprocesses. This review is illustrated with a simple simulation case study which allows a comparative evaluation of a few selected methods. Finally, some experimental case studies are discussed. As usual, practice lags behind theory, but recent developments confirm the applicability of the approach at the laboratory scale and are encouraging a transfer to industrial scale.
Collapse
|
12
|
One-layer gradient-based MPC + RTO strategy for unstable processes: a case study of a CSTR system. BRAZILIAN JOURNAL OF CHEMICAL ENGINEERING 2020. [DOI: 10.1007/s43153-020-00018-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
|
13
|
Nguyen VB, Tran SBQ, Khan SA, Rong J, Lou J. POD-DEIM model order reduction technique for model predictive control in continuous chemical processing. Comput Chem Eng 2020. [DOI: 10.1016/j.compchemeng.2019.106638] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
|
14
|
An Optimal Feedback Control Strategy for Nonlinear, Distributed-Parameter Processes. Processes (Basel) 2019. [DOI: 10.3390/pr7100758] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
In this work, an optimal state feedback control strategy is proposed for non-linear, distributed-parameter processes. For different values of a given parameter susceptible to upsets, the strategy involves off-line computation of a repository of optimal open-loop states and gains needed for the feedback adjustment of control. A gain is determined by minimizing the perturbation of the objective functional about the new optimal state and control corresponding to a process upset. When an upset is encountered in a running process, the repository is utilized to obtain the control adjustment required to steer the process to the new optimal state. The strategy is successfully applied to a highly non-linear, gas-based heavy oil recovery process controlled by the gas temperature with the state depending non-linearly on time and two spatial directions inside a moving boundary, and subject to pressure upsets. The results demonstrate that when the process has a pressure upset, the proposed strategy is able to determine control adjustments with negligible time delays and to navigate the process to the new optimal state.
Collapse
|
15
|
Huang M, Zheng Y, Li S, Xu S. Enhancing Transient Event Trigger Real-Time Optimization for Fluid Catalytic Cracking Unit Operation with Varying Feedstock. Ind Eng Chem Res 2019. [DOI: 10.1021/acs.iecr.9b03557] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Meng Huang
- Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China
| | - Yi Zheng
- Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China
| | - Shaoyuan Li
- Department of Automation, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai 200240, China
| | - Shenghu Xu
- Sinopec Jiujiang Company, Jiujiang 332004, China
| |
Collapse
|
16
|
Faulwasser T, Pannocchia G. Toward a Unifying Framework Blending Real-Time Optimization and Economic Model Predictive Control. Ind Eng Chem Res 2019. [DOI: 10.1021/acs.iecr.9b00782] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Timm Faulwasser
- Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology (KIT), 76131 Karlsruhe, Germany
| | - Gabriele Pannocchia
- Department of Civil and Industrial Engineering, Chemical Engineering Section, University of Pisa, 56122 Pisa, Italy
| |
Collapse
|
17
|
Economic operation of a fluid catalytic cracking process using self-optimizing control and reconfiguration. J Taiwan Inst Chem Eng 2019. [DOI: 10.1016/j.jtice.2019.01.004] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
|
18
|
Valluru J, Patwardhan SC. An Integrated Frequent RTO and Adaptive Nonlinear MPC Scheme Based on Simultaneous Bayesian State and Parameter Estimation. Ind Eng Chem Res 2019. [DOI: 10.1021/acs.iecr.8b05327] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Jayaram Valluru
- Department of Chemical Engineering, Indian Institutue of Technology Bombay, Mumbai, 400076, India
| | - Sachin C. Patwardhan
- Department of Chemical Engineering, Indian Institutue of Technology Bombay, Mumbai, 400076, India
| |
Collapse
|
19
|
Wang X, Han D, Lin Y, Du W. Recent progress and challenges in process optimization: Review of recent work at ECUST. CAN J CHEM ENG 2018. [DOI: 10.1002/cjce.23250] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
- Xiaoqiang Wang
- Key Laboratory of Advanced Control and Optimization for Chemical Processes; East China University of Science and Technology, Ministry of Education; Shanghai 200237 China
| | - Dong Han
- Key Laboratory of Advanced Control and Optimization for Chemical Processes; East China University of Science and Technology, Ministry of Education; Shanghai 200237 China
| | - Yuefeng Lin
- Key Laboratory of Advanced Control and Optimization for Chemical Processes; East China University of Science and Technology, Ministry of Education; Shanghai 200237 China
| | - Wenli Du
- Key Laboratory of Advanced Control and Optimization for Chemical Processes; East China University of Science and Technology, Ministry of Education; Shanghai 200237 China
| |
Collapse
|
20
|
Abstract
This paper introduces GEKKO as an optimization suite for Python. GEKKO specializes in dynamic optimization problems for mixed-integer, nonlinear, and differential algebraic equations (DAE) problems. By blending the approaches of typical algebraic modeling languages (AML) and optimal control packages, GEKKO greatly facilitates the development and application of tools such as nonlinear model predicative control (NMPC), real-time optimization (RTO), moving horizon estimation (MHE), and dynamic simulation. GEKKO is an object-oriented Python library that offers model construction, analysis tools, and visualization of simulation and optimization. In a single package, GEKKO provides model reduction, an object-oriented library for data reconciliation/model predictive control, and integrated problem construction/solution/visualization. This paper introduces the GEKKO Optimization Suite, presents GEKKO’s approach and unique place among AMLs and optimal control packages, and cites several examples of problems that are enabled by the GEKKO library.
Collapse
|
21
|
One Layer Nonlinear Economic Closed-Loop Generalized Predictive Control for a Wastewater Treatment Plant. APPLIED SCIENCES-BASEL 2018. [DOI: 10.3390/app8050657] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
|
22
|
Aydin E, Bonvin D, Sundmacher K. NMPC using Pontryagin’s Minimum Principle-Application to a two-phase semi-batch hydroformylation reactor under uncertainty. Comput Chem Eng 2018. [DOI: 10.1016/j.compchemeng.2017.08.010] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
|
23
|
Hinojosa AI, Ferramosca A, González AH, Odloak D. One-layer gradient-based MPC + RTO of a propylene/propane splitter. Comput Chem Eng 2017. [DOI: 10.1016/j.compchemeng.2017.06.006] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
|
24
|
Wang X, Mahalec V, Qian F. Globally optimal dynamic real time optimization without model mismatch between optimization and control layer. Comput Chem Eng 2017. [DOI: 10.1016/j.compchemeng.2017.04.006] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
|
25
|
Nease J, Monteiro N, Adams TA. Application of a two-level rolling horizon optimization scheme to a solid-oxide fuel cell and compressed air energy storage plant for the optimal supply of zero-emissions peaking power. Comput Chem Eng 2016. [DOI: 10.1016/j.compchemeng.2016.08.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
|
26
|
Economic model predictive control designs for input rate-of-change constraint handling and guaranteed economic performance. Comput Chem Eng 2016. [DOI: 10.1016/j.compchemeng.2016.04.026] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
|
27
|
On the Use of Nonlinear Model Predictive Control without Parameter Adaptation for Batch Processes. Processes (Basel) 2016. [DOI: 10.3390/pr4030027] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
|
28
|
Aydın E, Arkun Y, Is G, Mutlu M, Dikbas M. Plant-wide optimization and control of an industrial diesel hydro-processing plant. Comput Chem Eng 2016. [DOI: 10.1016/j.compchemeng.2016.01.016] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
|
29
|
Hinojosa AI, Capron B, Odloak D. REALIGNED MODEL PREDICTIVE CONTROL OF A PROPYLENE DISTILLATION COLUMN. BRAZILIAN JOURNAL OF CHEMICAL ENGINEERING 2016. [DOI: 10.1590/0104-6632.20160331s20140102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
|
30
|
Singh R, Sen M, Ierapetritou M, Ramachandran R. Integrated Moving Horizon-Based Dynamic Real-Time Optimization and Hybrid MPC-PID Control of a Direct Compaction Continuous Tablet Manufacturing Process. J Pharm Innov 2015. [DOI: 10.1007/s12247-015-9221-x] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
|
31
|
A novel interactive preferential evolutionary method for controller tuning in chemical processes. Chin J Chem Eng 2015. [DOI: 10.1016/j.cjche.2014.09.020] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
|
32
|
Nease J, Adams TA. Application of rolling horizon optimization to an integrated solid-oxide fuel cell and compressed air energy storage plant for zero-emissions peaking power under uncertainty. Comput Chem Eng 2014. [DOI: 10.1016/j.compchemeng.2014.06.001] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
|
33
|
Kluge A, Nazir S, Manca D. Advanced Applications in Process Control and Training Needs of Field and Control Room Operators. ACTA ACUST UNITED AC 2014. [DOI: 10.1080/21577323.2014.920437] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
|
34
|
Martins MA, Zanin AC, Odloak D. Robust model predictive control of an industrial partial combustion fluidized-bed catalytic cracking converter. Chem Eng Res Des 2014. [DOI: 10.1016/j.cherd.2013.08.005] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/26/2022]
|
35
|
Pinheiro CIC, Fernandes JL, Domingues L, Chambel AJS, Graça I, Oliveira NMC, Cerqueira HS, Ribeiro FR. Fluid Catalytic Cracking (FCC) Process Modeling, Simulation, and Control. Ind Eng Chem Res 2011. [DOI: 10.1021/ie200743c] [Citation(s) in RCA: 88] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Carla I. C. Pinheiro
- Institute for Biotechnology and Bioengineering (IBB), Department of Chemical Engineering, Instituto Superior Técnico/Universidade Técnica de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal
| | - Joana L. Fernandes
- Process Design and Modeling Division, IFP Energies Nouvelles − Lyon, Rond-point de l’échangeur de Solaize, B.P. 3, 69360 Solaize, France
| | - Luís Domingues
- Institute for Biotechnology and Bioengineering (IBB), Department of Chemical Engineering, Instituto Superior Técnico/Universidade Técnica de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal
| | - Alexandre J. S. Chambel
- Institute for Biotechnology and Bioengineering (IBB), Department of Chemical Engineering, Instituto Superior Técnico/Universidade Técnica de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal
| | - Inês Graça
- Institute for Biotechnology and Bioengineering (IBB), Department of Chemical Engineering, Instituto Superior Técnico/Universidade Técnica de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal
| | - Nuno M. C. Oliveira
- Centre for Chemical Processes Engineering and Forest Products (CIEPQPF), Department of Chemical Engineering, Universidade de Coimbra, R. Sílvio Lima − Pólo II, 3030-790 Coimbra, Portugal
| | - Henrique S. Cerqueira
- ATP Engenharia, Rua São José 90/2201-C, 20010-020 Centro, Rio de Janeiro, RJ, Brazil
| | - Fernando Ramôa Ribeiro
- Institute for Biotechnology and Bioengineering (IBB), Department of Chemical Engineering, Instituto Superior Técnico/Universidade Técnica de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa, Portugal
| |
Collapse
|