Journal of Process Control最新文献_第8页

Prediction model of burn-through point with data correction based on feature matching of cross-section frame at discharge end 基于放电端截面框架特征匹配的烧穿点预测模型及数据校正

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-06-26 DOI: 10.1016/j.jprocont.2024.103265

Huihang Li, Min Wu, Sheng Du, Jie Hu, Wen Zhang, Luefeng Chen, Xian Ma, Hongxiang Li

{"title":"Prediction model of burn-through point with data correction based on feature matching of cross-section frame at discharge end","authors":"Huihang Li, Min Wu, Sheng Du, Jie Hu, Wen Zhang, Luefeng Chen, Xian Ma, Hongxiang Li","doi":"10.1016/j.jprocont.2024.103265","DOIUrl":"https://doi.org/10.1016/j.jprocont.2024.103265","url":null,"abstract":"<div><p>Accurately predicting the burn-through point (BTP) is crucial for achieving stable control of the sintering process. However, accurately measuring the raw BTP is difficult due to the harsh production environment and poor thermocouple measurement accuracy of the temperature of exhaust gas in bellows. This paper proposes a prediction model of the BTP with data correction based on the feature matching of cross-section frame at discharge end. Firstly, a feature extraction method of cross-section frames at discharge end is designed. Next, the cross-section frame at discharge end features matching method is used to correct the raw BTP, and this method corrects anomalous data resulting from sensor failures. Finally, the temporal convolutional neural network and gated recurrent unit are used to predict the corrected BTP. The prediction model considers the cross-section frame feature at discharge end and state parameters as inputs, and it can achieve accurate prediction of the corrected BTP. A series of comparative experiments are conducted to verify the feasibility and effectiveness of the proposed model. At the same time, this paper also designs industrial implementation plan,and use actual operation data to verify the feasibility of the designed industrial implementation plan.</p></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"140 ","pages":"Article 103265"},"PeriodicalIF":3.3,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141487386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Self-tunable approximated explicit MPC: Heat exchanger implementation and analysis 自调整近似显式 MPC：热交换器的实现与分析

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-06-22 DOI: 10.1016/j.jprocont.2024.103260

Lenka Galčíková, Juraj Oravec

{"title":"Self-tunable approximated explicit MPC: Heat exchanger implementation and analysis","authors":"Lenka Galčíková, Juraj Oravec","doi":"10.1016/j.jprocont.2024.103260","DOIUrl":"https://doi.org/10.1016/j.jprocont.2024.103260","url":null,"abstract":"<div><p>The tunable approximated explicit model predictive control (MPC) comes with the benefits of real-time tunability without the necessity of solving the optimization problem online. This paper provides a novel self-tunable control policy that does not require any interventions of the control engineer during operation in order to retune the controller subject to the changed working conditions. Based on the current operating conditions, the autonomous tuning parameter scales the control input using linear interpolation between the boundary optimal control actions. The adjustment of the tuning parameter depends on the current reference value, which makes this strategy suitable for reference tracking problems. Furthermore, a novel technique for scaling the tuning parameter is proposed. This extension provides to exploit different ranges of the tuning parameter assigned to specified operating conditions. The self-tunable explicit MPC was implemented on a laboratory heat exchanger with nonlinear and asymmetric behavior. The asymmetric behavior of the plant was compensated by tuning the controller’s aggressiveness, as the negative or positive sign of reference change was considered in the tuning procedure. The designed self-tunable controller improved control performance by decreasing sum-of-squared control error, maximal overshoots/undershoots, and settling time compared to the conventional control strategy based on a single (non-tunable) controller.</p></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"140 ","pages":"Article 103260"},"PeriodicalIF":3.3,"publicationDate":"2024-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141444385","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adaptive temperature control of a reverse flow process by using reinforcement learning approach 利用强化学习方法对逆向流动过程进行自适应温度控制

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-06-20 DOI: 10.1016/j.jprocont.2024.103259

A. Binid , I. Aksikas , M.A. Mabrok , N. Meskin

引用次数: 0

A stochastic approach for the solution of single and multi–objective optimisation problems of biological processes in sequencing batch reactor 解决序批式反应器中生物过程的单目标和多目标优化问题的随机方法

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-06-20 DOI: 10.1016/j.jprocont.2024.103266

Tomasz Ujazdowski, Robert Piotrowski, Michał Banach

{"title":"A stochastic approach for the solution of single and multi–objective optimisation problems of biological processes in sequencing batch reactor","authors":"Tomasz Ujazdowski, Robert Piotrowski, Michał Banach","doi":"10.1016/j.jprocont.2024.103266","DOIUrl":"https://doi.org/10.1016/j.jprocont.2024.103266","url":null,"abstract":"<div><p>This paper investigates the impact of implementing single and multi-optimisation solutions on the biological treatment process in a sequencing batch reactor (SBR). The research is based on a case study of the water resource recovery facility (WRRF) in Swarzewo, Northern Poland. The paper introduces the adaptive extremum seeking control (ESC) method for dissolved oxygen (DO) concentration control and places it in a layered control structure. Further, it presents the introduction of an optimisation layer for the structure and parameters of the SBR cycle, through the synthesis of stochastic methods: single-objective optimisation (SOO) using a genetic algorithm (GA) and multi-objective optimisation (MOO) using the NSGA-II algorithm. The results were compared to a classical approach with fixed cycle parameters. The paper shows the advantages of optimising cycle parameters, including the number of phases as well as the DO value, on the process flow. These control structures underwent simulation tests in the MATLAB environment with the Simba package. The biochemical processes occurring in the reactor are based on the Activated Sludge Model No. 2d (ASM2d). The optimising control system demonstrates tangible improvements in operational efficiency and significant reductions in electrical energy consumption, highlighting the effectiveness of the proposed methodologies. © 2017 Elsevier Inc. All rights reserved.</p></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"140 ","pages":"Article 103266"},"PeriodicalIF":3.3,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141434794","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A novel interactive prognosis framework with nonlinear Wiener process and multi-sensor fusion for remaining useful life prediction 利用非线性维纳过程和多传感器融合预测剩余使用寿命的新型互动预报框架

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-06-20 DOI: 10.1016/j.jprocont.2024.103264

Wenyi Lin , Xiaolong Chen , Haoran Lu , Yutao Jiang , Linchuan Fan , Yi Chai

{"title":"A novel interactive prognosis framework with nonlinear Wiener process and multi-sensor fusion for remaining useful life prediction","authors":"Wenyi Lin , Xiaolong Chen , Haoran Lu , Yutao Jiang , Linchuan Fan , Yi Chai","doi":"10.1016/j.jprocont.2024.103264","DOIUrl":"https://doi.org/10.1016/j.jprocont.2024.103264","url":null,"abstract":"<div><p>Accurate remaining useful life (RUL) prediction plays a vital role in increasing the system operation safety and reducing maintenance costs. In industrial applications, there is usually a large amount of multi-sensor data generated. Therefore, how to construct an appropriate health index (HI) based on multi-sensor signals is very important for the RUL prediction. However, existing works treat sensor selection, HI construction, and degradation modeling independently as unrelated parts, which may result in the combination of sensors selected not constituting an optimal HI or the constructed HI not matching the degradation model. In addition, most existing works treat prior units as a whole to obtain a unique set of sensor combinations and fusion coefficients, which cannot reflect unit-to-unit heterogeneity, thus affecting the accuracy of RUL prediction. Therefore, a novel interactive feedback framework is established to construct HI, where the sensor selection, fusion coefficient calculation, and nonlinear Wiener process degradation modeling are incorporated into the feedback. Furthermore, an adaptive weight selection method based on particle swarm optimization and leave-one-out cross-validation (PSO-LV) is proposed to adjust the fusion coefficients in real-time. Then, the RUL is estimated by updating model parameters online, detecting degradation trends, and deriving the probability density function (PDF) of the RUL. Finally, two examples of engine datasets are provided to verify the effectiveness of the proposed method.</p></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"140 ","pages":"Article 103264"},"PeriodicalIF":3.3,"publicationDate":"2024-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141434804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Finite-time stabilization output-feedback control of Schrödinger’s equation 薛定谔方程的有限时间稳定输出反馈控制

IF 4.2 2区计算机科学

Journal of Process Control Pub Date : 2024-06-19 DOI: 10.1016/j.jprocont.2024.103258

Ruicheng Li, Feng-Fei Jin

引用次数: 0

Monitoring the operating state of crystal growth process based on digital twin model 基于数字孪生模型监控晶体生长过程的运行状态

IF 4.2 2区计算机科学

Journal of Process Control Pub Date : 2024-06-19 DOI: 10.1016/j.jprocont.2024.103261

Yu-Yu Liu , Ling-Xia Mu , Ding Liu

{"title":"Monitoring the operating state of crystal growth process based on digital twin model","authors":"Yu-Yu Liu , Ling-Xia Mu , Ding Liu","doi":"10.1016/j.jprocont.2024.103261","DOIUrl":"https://doi.org/10.1016/j.jprocont.2024.103261","url":null,"abstract":"<div><p>The reliable assessment of the operational status during the silicon single crystal growth process is a prerequisite for ensuring system safety and improving crystal quality. However, in the actual silicon single crystal growth process, due to limitations in manpower, material resources, financial resources, and current technical methods, the establishment of monitoring models is still in its infancy. To address this issue, this paper proposes a hybrid deep belief network (HDBN) algorithm aided by the digital twin (DT) model to achieve real-time monitoring of equipment operational status. Firstly, this study constructs the DT model based on the basic principles of crystal growth, mainly to achieve high-precision simulation of the actual silicon single crystal growth process and generate abnormal data for the equipment. This operation can expand the sample set, enhance the diversity and coverage of data, and effectively solve the problem of insufficient sample size. Secondly, this study uses the variational mode decomposition (VMD) algorithm to decompose the dataset composed of obtained abnormal and normal data, and constructs sub-deep belief network (DBN) for the decomposed subsequences to capture deep feature information at different frequencies of the data. Subsequently, based on the concept of ensemble learning, the outputs of each sub-DBN network are used as inputs to construct the overall DBN network, achieving monitoring of the equipment operational status. Through the combination of VMD decomposition and DBN networks, this algorithm can better capture the frequency characteristics and time-domain features of the signal, enhancing monitoring accuracy. Experimental results show that this algorithm can accurately identify abnormal equipment states, effectively improve monitoring performance, and is of significant importance for the optimization and control of the semiconductor-grade silicon single crystal growth process, contributing to increased production efficiency and product quality.</p></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"140 ","pages":"Article 103261"},"PeriodicalIF":4.2,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141429769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An adaptive control system based on spatial–temporal graph convolutional and disentangled baseline-volatility prediction of bellows temperature for iron ore sintering process 基于时空图卷积和分解基线-波动预测的铁矿石烧结过程风箱温度自适应控制系统

IF 4.2 2区计算机科学

Journal of Process Control Pub Date : 2024-06-18 DOI: 10.1016/j.jprocont.2024.103254

Zhengwei Chi, Xiaoxia Chen, Hanzhong Xia, Chengshuo Liu, Zhen Wang

{"title":"An adaptive control system based on spatial–temporal graph convolutional and disentangled baseline-volatility prediction of bellows temperature for iron ore sintering process","authors":"Zhengwei Chi, Xiaoxia Chen, Hanzhong Xia, Chengshuo Liu, Zhen Wang","doi":"10.1016/j.jprocont.2024.103254","DOIUrl":"https://doi.org/10.1016/j.jprocont.2024.103254","url":null,"abstract":"<div><p>The temperature within the sintering furnace is a decisive factor influencing the quality of the sintered ore in the iron ore sintering process. In practical operations, the temperature at the bellows directly linked to the bed layer indirectly signifies the internal furnace temperature. Maintaining a stable temperature at the bellows, particularly at the burn-through point, is vital for minimizing gas emissions, improving carbon efficiency, and enhancing the quality of the sintered ore. This paper proposes an intelligent temperature control system based on Spatial–Temporal Graph Convolutional and Disentangled Baseline-Volatility (STGCDBV) prediction. The STGCDBV network comprises three parallel modules: Adaptive Graph Convolution Network (AGCN), Baseline and Volatility Disentangler (BVD), and a residual link, along with a Temporal–Nodal Encoder–Decoder (TNED) module. The AGCN constructs a graph reflecting the characteristics of bellows temperature, effectively merging static spatial data with dynamic thermal information. The BVD module captures the nonlinear trend data inherent in the sintering process. In contrast, the TNED synergizes the insights from the parallel modules using cross encoding and decoding functionalities. For controlling the sintering gas flow rate, a Model Reference Adaptive Control (MRAC) system is implemented, which utilizes a control scheme founded on a temperature reference model and iterative parameter adjustments. Extensive experiments using actual time-series data from a steel plant have been conducted. Moreover, comparisons between the performance of pre- and post-control interventions demonstrate that the STGCDBV-MRAC system can stabilize temperature fluctuations and exhibit exemplary control proficiency.</p></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"140 ","pages":"Article 103254"},"PeriodicalIF":4.2,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141424546","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Manifold embedding stationary subspace analysis for nonstationary process monitoring with industrial applications 面向工业应用的非稳态过程监控的流形嵌入静态子空间分析

IF 4.2 2区计算机科学

Journal of Process Control Pub Date : 2024-06-18 DOI: 10.1016/j.jprocont.2024.103262

Chunhua Yang , Zhihong Lin , Keke Huang , Dehao Wu , Weihua Gui

{"title":"Manifold embedding stationary subspace analysis for nonstationary process monitoring with industrial applications","authors":"Chunhua Yang , Zhihong Lin , Keke Huang , Dehao Wu , Weihua Gui","doi":"10.1016/j.jprocont.2024.103262","DOIUrl":"https://doi.org/10.1016/j.jprocont.2024.103262","url":null,"abstract":"<div><p>Industrial processes frequently exhibit nonstationary characteristics due to factors like load fluctuations and external interference. Accurate monitoring of nonstationary industrial processes is of vital importance in ensuring production stability and safety. Unfortunately, most existing monitoring methods overlook the manifold structure presented in nonstationary data due to nonstationary features, causing the loss of critical information and poor interpretability. As a consequence, monitoring performance is compromised. To address this issue, this paper proposes a manifold embedding stationary subspace analysis (MESSA) algorithm. By embedding a neighborhood preservation term into the objective function of SSA, MESSA effectively mitigates the impact of nonstationarity on manifold structure. The extracted features incorporate both global stationarity and local manifold characteristics, facilitating a more comprehensive reconstruction of the intricate underlying mechanisms in industrial processes. This contributes to a substantial enhancement in the accuracy and reliability of process monitoring. A set of nonstationary swiss-roll dataset is designed to visually demonstrate the capability of MESSA in extracting manifold structure. Case studies including a numerical case, a continuous stirred tank reactor system and a real industrial roasting process validate the superior monitoring performance of the proposed method.</p></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"140 ","pages":"Article 103262"},"PeriodicalIF":4.2,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141423219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modified active disturbance rejection control based on gain scheduling for circulating fluidized bed units 基于增益调度的循环流化床装置改进型主动干扰抑制控制

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-06-14 DOI: 10.1016/j.jprocont.2024.103253

Zhenlong Wu , Donghai Li , Yanhong Liu , YangQuan Chen

{"title":"Modified active disturbance rejection control based on gain scheduling for circulating fluidized bed units","authors":"Zhenlong Wu , Donghai Li , Yanhong Liu , YangQuan Chen","doi":"10.1016/j.jprocont.2024.103253","DOIUrl":"10.1016/j.jprocont.2024.103253","url":null,"abstract":"<div><p>Circulating fluidized bed (CFB) units are extensively operated in China due to their wide fuel adaptability, low emissions and high combustion efficiency. Nevertheless, CFB units are facing many control challenges due to their strong nonlinearity and large lag characteristics. To handle these control challenges, a modified active disturbance rejection control based on gain scheduling is structured in this paper. Firstly, a decentralized active disturbance rejection control strategy based on gain scheduling is designed by analyzing control difficulties of CFB units. Then, the parameter tuning and scheduling methods are provided, and the convergence of the extended state observer during the scheduling process is derived theoretically. The advantages of the proposed method in tracking performance, disturbance rejection performance, and ability to reject fuel quality fluctuation and uncertain heat transfer coefficients are illustrated by comparative simulations. Finally, the proposed control strategy is practically applied to the main steam pressure system of a 300 MW CFB unit. Running data demonstrate that it has a faster tracking performance and better disturbance rejection ability in [50<span><math><mo>∼</mo></math></span>100]% of the rated load, where the hourly average integral absolute error index has decreased obviously, and it shows a good field application prospect.</p></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"140 ","pages":"Article 103253"},"PeriodicalIF":3.3,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141400552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0