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A Hybrid Strategy Enhanced Sub-Sampled Recursive Second Order Algorithm for Chemical process Intelligent Identification

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INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS 2023年第1期16卷 117-117页

作者： Wang, Yaxin Xu, Baochang China Univ Petr Coll Informat Sci & Engn Beijing 102249 Peoples R China

The accurate dynamic model of the chemical process is an important condition for the successful implementation of advanced control in the plant. In this paper, an efficient second order algorithm for long short-term memory (LSTM) network training is proposed for chemical process intelligent identification. A novel Hessian inverse recursion method is adopted to achieve fast convergence and avoid the high-cost operation of the classic second order optimization method. Besides, more information is back propagated since the proposed method retains the real curvature information of the neural network. Considering the large amount of chemical process data, a sub-sampled recursive second order-stochastic gradient descent (SRSO-SGD) algorithm which uses sub-sampling method and hybrid strategy is proposed. The identification experiment on a delayed coker fractionator shows that the proposed sub-sampled neural network second order training algorithm has better performance than other learning algorithms in terms of model identification accuracy and convergence speed. By adopting a hybrid strategy that performing Hessian inverse estimation every 3 training epochs, the expensive Hessian inverse calculation cost in the identification process is further reduced while low training and testing errors are maintained.

关键词： Chemical process modeling Deep learning Intelligent identification Second order learning algorithm advanced process control

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Nonlinear hybrid control model for accurate steady-state predictions

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COMPUTERS & CHEMICAL ENGINEERING 2023年第1期178卷

作者： Krespach, Valentin Blum, Nicolas Pottmann, Martin Rehfeldt, Sebastian Klein, Harald Tech Univ Munich Inst Plant & Proc Technol TUM Sch Engn & Design Dept Energy & Proc Engn Boltzmannstr 15 D-85748 Garching Germany Linde GmbH Linde Engn Dr Carl von Linde Str 6-14 D-82049 Pullach Germany

Since the industrial sector accounts for a considerable share of total energy consumption, industrial plants must be improved in terms of their energy efficiency. Improved process control can be seen as one approach towards achieving this goal. These controllers are based on a control model and thus are able to optimize future plant performance. Mostly linear control models are used, though, especially for highly nonlinear processes, nonlinear control models are advantageous. While physical modeling of those can be challenging, data-driven control models can also be used. However, it is shown that even these lead to slightly inaccurate predictions especially for steady-state operation. Therefore, a hybrid model is developed starting from a data-driven control model before a physical model component is introduced. As a result, the hybrid model is able to reproduce the correct steady-state plant behavior, thus improving the overall prediction quality of the control model.

关键词： Hybrid modeling Grey box Nonlinear control model advanced process control Air separation

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Lyapunov-Based Cyberattack Detection for Distinguishing Between Sensor and Actuator Attacks

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IFAC-PapersOnLine 2024年第14期58卷 604-609页

作者： Dominic Messina Helen Durand Wayne State University Detroit MI 48202 USA

control-theoretic cyberattack detection strategies are control strategies where control theory can be used in the design of the detection policies and analysis of stability properties with and without cyberattacks. This work provides a step toward understanding how to diagnose cyberattacks using control-theoretic cyberattack detection mechanisms. Specifically, we analyze the conditions under which a control-theoretic cyberattack detection strategy developed in our prior work to handle detection of simultaneous actuator and sensor attacks can be extended to distinguish between whether attacks are occurring on sensors or actuators. We present and evaluate heuristic concepts for attempting to diagnose sensor attacks; these again demonstrate the utility of control-theoretic diagnosis policies and lead to further suggestions for such control-theoretic policies.

关键词： Cyber physical system advanced process control Model predictive optimization-based control Nonlinear predictive control Sensors actuators

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Model-based feedback control of filament geometry in extrusion-based additive manufacturing ⁎

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IFAC-PapersOnLine 2024年第14期58卷 403-408页

作者： Carlos J.G. Rojas Christian Portilla Leyla Özkan Eindhoven University of Technology The Netherlands Delft University of Technology The Netherlands

control of extrusion-based printing is fundamental to improving the traditional open-loop operation of commercial machines. However, the literature on feedback control based on nozzle motion is still limited in comparison with the developments for extrusion dynamics. In this work, we propose a model-based control strategy where the effects of the nozzle speed on the filament width are described by a first-order model, and the model uncertainty is used for robust synthesis. The feedback employs the internal model controller (IMC) to get an approximate inversion of the dynamics and the IMC filter is tuned based on robust performance criteria. The controller was experimentally tested and provided satisfactory results, especially when the parameters were refined depending on the speed regime.

关键词： Additive manufacturing Time delay systems advanced process control Robust control applications process control applications

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control invariant set enhanced safe reinforcement learning: Improved sampling efficiency, guaranteed stability and robustness

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COMPUTERS & CHEMICAL ENGINEERING 2023年 179卷

作者： Bo, Song Agyeman, Bernard T. Yin, Xunyuan Liu, Jinfeng Univ Alberta Dept Chem & Mat Engn Edmonton AB T6G 1H9 Canada Nanyang Technol Univ Sch Chem Chem Engn & Biotechnol Singapore 637459 Singapore

Reinforcement learning (RL) is an area of significant research interest, and safe RL in particular is attracting attention due to its ability to handle safety-driven constraints that are crucial for real-world applications. This work proposes a novel approach to RL training, called control invariant set (CIS) enhanced RL, which leverages the advantages of utilizing the explicit form of CIS to improve stability guarantees and sampling efficiency. Furthermore, the robustness of the proposed approach is investigated in the presence of uncertainty. The approach consists of two learning stages: offline and online. In the offline stage, CIS is incorporated into the reward design, initial state sampling, and state reset procedures. This incorporation of CIS facilitates improved sampling efficiency during the offline training process. In the online stage, RL is retrained whenever the predicted next step state is outside of the CIS, which serves as a stability criterion, by introducing a Safety Supervisor to examine the safety of the action and make necessary corrections. The stability analysis is conducted for both cases, with and without uncertainty. To evaluate the proposed approach, we apply it to a simulated chemical reactor. The results show a significant improvement in sampling efficiency during offline training and closed-loop stability guarantee in the online implementation, with and without uncertainty.

关键词： advanced process control Robustness control invariant set Reinforcement learning Closed-loop stability Sampling efficiency

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Estimating APC Model Parameters for Dynamic Intervals Determined Using Change-Point Detection in Continuous processes in the Petrochemical Industry

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processES 2023年第8期11卷 2229页

作者： Yu, Yoseb Lee, Minyeob Lee, Chaekyu Cheon, Yewon Baek, Seungyun Kim, Youngmin Kim, Kyungmin Jung, Heechan Lim, Dohyeon Byun, Hyogeun Jeong, Jongpil Sungkyunkwan Univ Dept Smart Factory Convergence 2066 Seobu Ro Suwon 16419 South Korea Infotrol Technol 159-1 Mokdongseo Ro Seoul 07997 South Korea Sungkyunkwan Univ Dept Stat 25-2 Sungkyunkwan Ro Seoul 03063 South Korea Sungkyunkwan Univ Dept Chem Engn 2066 Seobu Ro Suwon 16419 South Korea Sungkyunkwan Univ Dept Mech Engn 2066 Seobu Ro Suwon 16419 South Korea Sungkyunkwan Univ Dept Syst Management Engn 2066 Seobu Ro Suwon 16419 South Korea Sungkyunkwan Univ Dept Comp Sci & Engn 2066 Seobu Ro Suwon 16419 South Korea

Several papers have proven that advanced process controller (APC) systems can save more energy in the process than proportional-integral-differential (PID) controller systems. Therefore, implementing an APC system is ultimately beneficial for saving energy in the plant. In a typical APC system deployment, the APC model parameters are calculated from dynamic data intervals obtained through the plant test. However, depending on the proficiency of the APC engineer, the results of the plant test and the APC model parameters are implemented differently. To minimize the influence of the APC engineer and calculate universal APC model parameters, a technique is needed to obtain dynamic data without a plant test. In this study, we utilize time-series data from a real petrochemical plant to determine dynamic intervals and estimate APC model parameters, which have not been investigated in previous studies. This involves extracting the data of the dynamic intervals with the smallest mean absolute error (MAE) by utilizing statistical techniques such as pruned exact linear time, linear kernel, and radial basis function kernel of change-point detection (CPD). After that, we fix the hyper parameters at the minimum MAE value and estimate the APC model parameters by training with the data from the dynamic intervals. The estimated APC model parameters are applied to the APC program to compare the APC model fitting rate and verify the accuracy of the APC model parameters in the dynamic intervals obtained through CPD. The final validation of the model fitting rates demonstrates that the identification of the dynamic intervals and the estimation of the APC model parameters through CPD show high accuracy. We show that it is possible to estimate APC model parameters from dynamic intervals determined by CPD without a plant test.

关键词： petrochemical continuous process advanced process control change-point detection model parameter estimation

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Development of Mix-and-Match Overlay for Multiple Metrology Platforms Utilization by using the Cross-Layer Overlay Simulation Method

Development of Mix-and-Match Overlay for Multiple Metrology ...

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Metrology, Inspection, and process control XXXIX 2025

作者： Lin, Chia-Chung Zhang, Qiqi Huang, Yu-Chen Chu, Hsiao-Lun Liu, John Hsieh, Chris Lin, Penny Tsou, Chao-Jen Demirer, Onur Chu, Wilbur Yang, York Yang, Cheng-Wei Huang, Foster Nanya Technology Corp. No. 98 Nanlin Rd. Taishan Dist New Taipei City243 Taiwan KLA Corporation No. 79-80 Zuchongzhi Road LANE 887 Shanghai China KLA Corporation Tai Yuen Hi-Tech Industrial Park No. 22 Taiyuan Street Na Zhubei302 Taiwan KLA Corporation Dr.-Kuelz-Ring 15 Dresden01067 Germany KLA Corporation One Technology Drive MilpitasCA95035 United States

ISBN: (纸本)9781510686380

With stricter overlay requirements in advanced technology nodes, new overlay metrology solutions have been introduced, offering enhanced precision, accuracy, and measurement speed. To improve overlay performance, different metrology tools may sometimes be utilized on the same layer. This strategy, however, can degrade the stability of both statistical process control (SPC) and advanced process control (APC) compared to overlay control with a single metrology platform. In our study, we evaluated the overlay impact when using two metrology platforms within a single run-to-run control loop, i.e., mix-and-match overlay (MMO) metrology. We will highlight the key factors for successful MMO implementation in high-volume manufacturing (HVM). We evaluated two critical factors that could influence the performance of mix-and-match overlay metrology control. Firstly, we studied controlling high-order correction per exposure (HO-CPE) and metrology target design (MTD) on after etch Inspection (AEI) overlay (OVL) stability. Secondly, we simulated the run-to-run overlay performance of the target layer when using multiple metrology platforms and confirmed the lithography's key performance indicators (KPIs), such as the stability of process correction and the out-of-control rate using statistical process control (SPC). Finally, we simulated the overlay impact on the subsequent layer using the cross-layer overlay simulation method, based on the process correction changes in the target layer resulting from mix-and-match overlay metrology control. © 2025 SPIE.

关键词： Overlay metrology Metrology Optical alignment Semiconducting wafers advanced process control High volume manufacturing Etching Lithography control systems Inspection

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BioDT: An Integrated Digital-Twin-Based Framework for Intelligent Biomanufacturing

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processES 2023年第4期11卷 1213页

作者： Zhao, Beichen Li, Xueliang Sun, Wanqiang Qian, Juntao Liu, Jin Gao, Minjie Guan, Xin Ma, Zhenwu Li, Jianghua Jiangnan Univ Key Lab Ind Biotechnol Minist Educ Wuxi 214122 Peoples R China Jiangnan Univ Sci Ctr Future Foods Wuxi 214122 Peoples R China T&J Bioengn Shanghai Co Ltd Shanghai 201611 Peoples R China Jiangnan Univ Sch Biotechnol Key Lab Carbohydrate Chem & Biotechnol Minist Educ Wuxi 214122 Peoples R China Suzhou Univ Sci & Technol Coll Mech Engn Suzhou 215009 Peoples R China

The field of industrial biotechnology has shown an increasing interest in adopting digital twins for improving process productivity and management efficiency. Despite its potential benefits, digital-twin-based biomanufacturing has not been fully implemented. As a preliminary undertaking, we developed an open-source digital twin framework for cell culture. The core models of the digital twin were coded in C++ and compiled as a reusable Python library. A web-based, cloud-native HMI application that links the physical and virtual systems was developed. A microbioreactor digital twin system was implemented using the framework as a proof of concept. The system features a 3D-printed rocking platform that is customized to fit T25 flasks, enabling automated rocking rate and angle control and in-place optical cell density measurement. The digital twin was validated using Chinese Hamster Ovary (CHO) cells and was found to be able to predict the changes in cell density, glucose consumption, lactic acid production, and oxygen uptake rate (OUR). Finally, we performed a case study to demonstrate the system's practical applicability in advanced process control (APC) by constructing real-time glucose and lactic acid soft sensors, which are in turn used to alert the operator for manual media change or for automated feeding.

关键词： digital twin advanced process control process analytical technology Chinese hamster ovary (CHO) cells soft-sensor 3D-printing open-source software

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Free-form Bending control using Optimal Residual Strategies

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IFAC-PapersOnLine 2023年第2期56卷 2671-2676页

作者： Ahmed Ismail Daniel Maier Sophie Stebner Sebastian Münstermann Wolfram Volk Boris Lohmann Chair of Automatic Control Technical University of Munich Boltzmannstr. 15 85748 Garching Germany Chair of Metal Forming and Casting Technical University of Munich Walther-Meißner-Str. 4 85748 Garching Germany Integrity of Materials and Structures RWTH Aachen University Intzestr. 1 52072 Aachen Germany

Free-form bending is a bending technique, whereas the bending tool head combines both linear and rotary motions. One problem with free-form bending is that an incorrectly bent tube section can no longer be corrected. Therefore, if a defect is detected during bending, a strategy for bending the remaining tube sections must be determined in such a way that the overall shape of the tube is as close as possible to the desired one. In this paper, a solution based on optimal recalculation of the residual trajectories of the bending tool head is presented and different cost functions are discussed in terms of their effect on the overall shape. Simulation results have shown a significant improvement of the resulting end shape of the workpiece upon subjecting it to perturbation.

关键词： process modelling advanced process control process Optimization Soft sensors Freeform bending

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Add-on Harmonic Disturbance Cancellation control in Continuous Hot-Dip Galvanizing Lines

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IFAC-PapersOnLine 2023年第2期56卷 6181-6186页

作者： L. Marko A. Kugi A. Steinboeck Christian Doppler Laboratory for Intelligent Process Control for High-Quality Steel Products Automation and Control Institute TU Wien Austria Automation and Control Institute TU Wien Austria

In continuous hot-dip galvanizing of steel strips, unwanted vibrations of the processed strip can significantly degrade the coating uniformity and quality. Thus, an increasing number of hot-dip galvanizing lines are equipped with electromagnetic strip stabilization devices to enable active strip-shape and vibration control. Typically, commercial strip stabilizers achieve adequate broad-band vibration attenuation. However, their disturbance rejection capabilities are usually insufficient in case of persistently exciting harmonic disturbances. This work proposes a new multivariable harmonic disturbance cancellation control strategy which can be used as add-on to the position control loop of an existing strip stabilization device. The unknown amplitude, phase angle, and disturbance frequency are estimated during online operation. The systematic consideration of controller-output and estimator constraints in the design guarantees a reliable and safe operation in the challenging industrial environment. The devised control system works well even in the case of non-persistently exciting harmonic disturbances. The effectiveness of the proposed control scheme is demonstrated by short- and long-term measurement results from an industrial hot-dip galvanizing line.

关键词： Steel industry advanced process control Vibration control Disturbance rejection Constrained control

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