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An improved dynamic matrix control with output penalty for industrial processes

CANADIAN JOURNAL OF CHEMICAL ENGINEERING 2025年第0期

作者： Hong, Sen Bai, Jianjun Zou, Hongbo Hangzhou Dianzi Univ Informat & Control Inst Hangzhou 310018 Peoples R China

For plants with complex dynamics, traditional dynamic matrix control (DMC), which includes output errors and control increments in the cost function, usually exhibits limited control performance. To obtain a better performance in system overshoot, we propose a novel DMC method with an output penalty term without increasing the computational complexity. First, we design a quadratic term for output increments and integrate it into the cost function. This term is used to penalize the system output, thereby reducing system overshoot. Considering that the cost function already contains three performance indexes, we propose a fast DMC algorithm to reduce the computational burden of the controller. The main idea of the proposed fast DMC is to move part of the control computation offline to reduce the cost of online computation. Finally, the proposed DMC strategy is applied to the oxygen content system of the coke furnace. The results show that the proposed DMC method is superior to the conventional DMC method in terms of reducing system overshoot. In addition, the proposed method achieves a significant improvement in computational efficiency.

关键词： dynamic matrix control industrial coke furnace output penalty reduced computational burden system overshoot

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Adaptive Tuning of dynamic matrix control for Uncertain Industrial Systems With Deep Reinforcement Learning

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2025年 22卷 8695-8708页

作者： Zhang, Yang Wang, Peng Yu, Liying Li, Ning Shanghai Jiao Tong Univ Dept Automat Shanghai 200240 Peoples R China

dynamic matrix control (DMC) has been field-validated in many industrial practices, highlighting the critical importance of fine-tuning parameters for optimal performance. However, the tuning of well-performed parameters is challenging because the relationship between parameters and the performance of DMC is intricate to characterize for industrial systems with uncertainty. An adaptive tuning approach based on deep reinforcement learning (DRL) is proposed to optimize the performance of DMC for uncertain systems in this paper. The approach can online tune the horizons and weighting matrices of DMC in real time adaptive to the state and uncertainty of the systems. Compared with offline tuning approaches, the proposed approach does not need to tradeoff optimality for robustness. The proposed approach utilizes various state-of-the-art DRL algorithms, e.g., value-based and actor-critic-based, to develop online parameter tuning policies that can adapt to system uncertainty. A piecewise reward function is designed to improve the performance and stability of the agent. A novel predictor-switching criterion is developed to address the horizon inconsistency in the receding optimization process. The proposed approaches are validated by the moisture control task in industrial cigarette drying process.

关键词： Tuning Prediction algorithms Predictive models Uncertainty Optimization Adaptation models Heuristic algorithms Adaptive systems Predictive control Performance analysis dynamic matrix control deep reinforcement learning adaptive parameter tuning predictor-switching criterion moisture control

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dynamic matrix control OF AN AUTOGENOUS GRINDING CIRCUIT

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MINERALS ENGINEERING 1994年第1期7卷 105-114页

作者： VALENZUELA, J BOURASSA, M NAJIM, K DELVILLAR, R CTR RECH MINERALES QUEBEC CITYPQCANADA ECOLE NATL SUPER INGENIEURS GENIE CHIM GRECO SARTACNRSURA 192F-31078 TOULOUSEFRANCE

Autogenous grinding is characterized by non-linearities, time-varying dynamics and a high level of uncertainties, conditions which usually originate from the variability of the ore feed characteristics (hardness and grade). These characteristics make this grinding operation particularly appealing for some type of knowledge-based control. This paper discusses the application of the dynamic matrix control algorithm to an autogenous grinding operation. This control algorithm is a long-range predictive control algorithm which has been successfully applied to other processes. The study was carried out using an empirical simulator calibrated with industrial data. The simulation results were compared to those obtained using PID and learning controllers. The ability of the dynamic matrix control to improve the efficiency of this complex and highly sensitive process is clearly demonstrated.

关键词： AUTOGENOUS GRINDING dynamic matrix control DMC, PROCESS control LEARNING control

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dynamic matrix control of a High-Purity Internal Thermally Coupled Distillation Column

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CANADIAN JOURNAL OF CHEMICAL ENGINEERING 2014年第4期92卷 696-702页

作者： Cong, Lin Liu, Xinggao Wang, Chengyu Zhejiang Univ Control Dept State Key Lab Ind Control Technol Hangzhou 310027 Peoples R China

The internal thermally coupled distillation column (ITCDIC) is a frontier in the energy-saving distillation research. The process inside a high-purity ITCDIC is of great nonlinear dynamics, high sensitivity to disturbances and inverse response, which prevent the process from being commercialised. To obtain a satisfactory control performance, a dynamic matrix control (DMC) is presented. The benzene/toluene system is studied as a simulation example. The results are compared with a traditional PID and an adaptive multivariable generalised predictive control (AM-GPC) in detail. The performances in both servo and regulatory control confirm the accuracy and validity of the DMC for the high-purity ITCDIC process.

关键词： internal thermally coupled distillation column high purity dynamic matrix control

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dynamic matrix control and generalized predictive control, comparison study with IMC-PID

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2017年第28期42卷 17561-17570页

作者： Ramdani, Ammar Grouni, Said Univ Boumerdes Fac Oil & Chem Appl Automat Lab Av Independance Boumerdes 35000 Algeria Univ Boumerdes Fac Sci Engn Ind Maintenance Dept Av Independance Boumerdes 35000 Algeria

Two of control techniques of the Model Predictive control (MPC) methodology, which are dynamic matrix control (DMC) and Generalized Predictive control (GPC), with IMC-PID are disputed in this paper. The main characteristics of these important control techniques, widely used in industry, are presented. The optimum solution of the predicted control inputs and outputs are obtained by minimizing a cost function that contains the squared errors between the reference trajectory and predictions output on the prediction horizon. These controllers are applied on a Process control Module (PCM), a system with pure time delay, and tested in the light of disturbance rejection and tracking performance for the constant and variable trajectory. (C) 2017 Hydrogen Energy Publications LLC. Published by Elsevier Ltd. All rights reserved.

关键词： dynamic matrix control Generalized predictive control IMC-PID

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dynamic matrix control of a Bubble-Column Reactor for Microbial Synthesis Gas Fermentation

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CHEMICAL ENGINEERING & TECHNOLOGY 2017年第4期40卷 727-736页

作者： Fu, Yao Chang, Liang Henson, Michael A. Liu, Xing Gao Zhejiang Univ Dept Control Sci & Engn Inst Ind Proc Control Zheda Rd 38 Hangzhou 310027 Zhejiang Peoples R China Univ Massachusetts Dept Chem Engn 686 North Pleasant St159 Goessmann Lab Amherst MA 01003 USA

A spatiotemporal metabolic model of a representative syngas bubble-column reactor was applied to design and evaluate dynamic matrix control (DMC) schemes for regulation of the desired by-product ethanol and the undesired by-product acetate. This model was used to develop linear step response models for controller design and also served as the process in closed-loop simulations. A 2x2 DMC scheme with manipulation of the liquid and gas feed flows to the column provided a superior performance to proportional integral (PI) control due to slow process dynamics combining the multivariable and constrained nature of the control problem. Ethanol concentration control for large disturbances was further improved by adding the flow of a pure hydrogen stream as a third manipulated variable. The advantages of DMC for syngas bubble-column reactor control are demonstrated and a design strategy for future industrial applications is provided.

关键词： Bubble-column reactors dynamic matrix control Metabolic modeling Microbial syngas fermentation Model predictive control

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dynamic matrix control applied to emission control of a diesel engine

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INTERNATIONAL JOURNAL OF ENGINE RESEARCH 2016年第5期17卷 556-575页

作者： Kozlik, Christian Geringer, Bernhard Schirrer, Alexander Jakubek, Stefan Vienna Univ Technol Christian Doppler Lab Model Based Calibrat Method Getreidemarkt 9 A-1060 Vienna Austria

In this paper we suggest a hierarchical control scheme, applicable to engine control. The chosen setup facilitates the simultaneous control of emissions and torque. On the top level a standard PID controller is installed, setting the injection quantity in order to reach the demand torque, which is a prerequisite to follow a given load profile. The second level is dedicated to the emission control. We apply dynamic matrix control (DMC), which is a specific form of model predictive control. DMC stands out by a very simple way of modeling the controlled process which is represented by step responses. Constraints on the absolute values and maximum rates of change are applied to the manipulable system inputs to cope with given hardware limitations. Moreover, we incorporate so-called operational constraints, thus constraining the input variables to certain polytopic operating regions. Thereby areas with high HC emissions can be excluded in advance. Furthermore we include the predefined demand torque as input to the DMC. With the known impact of transient torque changes on the emissions, the DMC can act in an optimal way with respect to the given load profile. To cope with the nonlinearities of a combustion engine, we apply a network of several DMCs, scheduled by engine speed and load as well as by the manipulable actuators. We also propose a procedure to reduce the amount of modeling data, by introducing a parameterized formulation of the measured step responses. The proposed control concept is then evaluated on a realistic, physically-based engine model for several representative driving sequences, amongst them the well-known New European Driving Cycle (NEDC) and the highly dynamic Worldwide Harmonized Light Duty Test Cycle (WLTC). The advantages of DMC against a conventional PID control are finally summarized and demonstrated on a typical load step.

关键词： dynamic matrix control predictive control emission control diesel engine constrained optimization

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dynamic matrix control OF DIAPHRAGM-TYPE CHLORINE CAUSTIC ELECTROLYSERS

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JOURNAL OF PROCESS control 1995年第3期5卷 131-136页

作者： NIKRAVESH, M FARELL, AE LEE, CT VANZEE, JW UNIV S CAROLINA DEPT CHEM ENGNCOLUMBIASC 29208

dynamic matrix control (DMC) is now widely used in industrial control, and when properly applied results in significant savings due to improved efficiency and reduced off-spec product. The objective of this paper is to implement MIMO DMC on a simulated diaphragm-type chlorine/caustic electrolyser. A comparison between the MIMO DMC and traditional multi-loop SISO PID control strategy shows greatly improved controller performance and cell efficiency using DMC, which will result in reduced operating costs and increase cell diaphragm lifespan.

关键词： dynamic matrix control CHLORINE CAUSTIC ELECTROLYZER ELECTROCHEMICAL CELL

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dynamic matrix control optimization based new PIPD type control for outlet temperature in a coke furnace

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CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 2015年 142卷 245-254页

作者： Li, Haisheng Zhou, Hongbo Zhang, Jianming Zhejiang Univ Inst Cyber Syst & Control State Key Lab Ind Control Technol Hangzhou 310027 Zhejiang Peoples R China Zhejiang Supeon Co Ltd Hangzhou 310053 Zhejiang Peoples R China

Proportional-integral-derivative (PID) control is widely applied to various kinds of industrial processes with its simple structure and convenient implementation. However, for processes with complex behavior and uncertainties, PID control may not always satisfy the higher requirements. Compared with PID control, proportional-integral-proportional-derivative (PI-PD) control can provide improved control performance but is now used in a limited scope because its controller parameter tuning is a little bit more inconvenient than PID. In view of the above facts, this paper proposed a new PI-PD control design based on dynamic matrix control (DMC) optimization, which bears the advantages of improved control performance under DMC optimization and at the same time, simple structure of PI-PD control for implementation. The proposed PI-PD controller is tested on the outlet temperature of an industrial coke furnace, where results show that the controller shows improved control performance compared with traditional PID control and PI-PD control in terms of set-point tracking and disturbance rejection. (C) 2015 Elsevier B.V. All rights reserved.

关键词： dynamic matrix control PI-PD control PID control Outlet temperature control Coke furnace

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dynamic matrix control of a Reactive Distillation Process for Biodiesel Production

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INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH IN AFRICA 2019年 45卷 132-147页

作者： Giwa, Abdulwahab Owolabi, John Olusoji Giwa, Saidat Olanipekun Afe Babalola Univ Coll Engn Chem & Petr Engn Dept Afe Babalola Way Ado Ekiti Ekiti State Nigeria Abubakar Tafawa Balewa Univ Fac Engn & Engn Technol Chem Engn Dept Tafawa Balewa Way Bauchi Nigeria

This study has been carried out to demonstrate the control of a reactive distillation process in which the production of biodiesel was taken as the case study using an advanced control method, which is known as dynamic matrix control. The control was accomplished by employing the transfer function model of the reactive distillation process developed, using the System Identification Toolbox of MATLAB, from the dynamic data generated when the prototype plant of the process was simulated with the aid of ChemCAD process simulator. The results obtained from the dynamic matrix control were compared with those of a proportional-integral-derivative (PID) control system tuned with Ziegler-Nichols and Cohen-Coon methods, and it was discovered that the dynamic matrix control was able to perform best among the three (dynamic matrix control method, PID tuned with Ziegler-Nichols method and PID tuned with Cohen-Coon method) because it (the dynamic matrix control) was able to make the biodiesel mole fraction response not to exceed the maximum limit value of 1 in addition to having the lowest sum of absolute errors (SAE) and sum of squared errors (SSE) from the control systems that were simulated.

关键词： Reactive distillation biodiesel dynamic matrix control conventional control MATLAB

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