Journal of Process Control最新文献_第2页

Multivariable soft sensor with a predictor of mutually dependent errors applied to an industrial fractionator 具有相互依赖误差预测器的多变量软传感器应用于工业分馏器

IF 3.9 2区计算机科学

Journal of Process Control Pub Date : 2025-09-22 DOI: 10.1016/j.jprocont.2025.103555

Oleg Snegirev , Vladimir Klimchenko , Denis Shtakin , Andrei Torgashov , Fan Yang

{"title":"Multivariable soft sensor with a predictor of mutually dependent errors applied to an industrial fractionator","authors":"Oleg Snegirev , Vladimir Klimchenko , Denis Shtakin , Andrei Torgashov , Fan Yang","doi":"10.1016/j.jprocont.2025.103555","DOIUrl":"10.1016/j.jprocont.2025.103555","url":null,"abstract":"<div><div>This paper addresses the development of a multivariable soft sensor (SS) with a predictor designed to handle mutual dependencies within multivariate error series. Typically, the mutual influence in vector time series is characterized using cross-correlation. The proposed multivariable cross-correlated error predictor (MCCEP) framework effectively manages such dependencies and is compatible with any data-driven SS model. Forecasted error values are fed back into the SS output as corrections, refining the final predictions of quality indicators. The MCCEP model is constructed through statistical analysis to minimize the generalized variance – defined as the determinant of the covariance matrix – of multivariate forecast errors. Unlike conventional approaches such as bias update techniques, the MCCEP model is chosen from a broad class of predictors for multivariate linear processes, explicitly considering the dynamic relationships among the univariate components of the SS error process. For the <em>n</em>-dimensional case, it is analytically demonstrated that MCCEP minimizes the generalized variance of multivariate errors by leveraging the cross-correlation functions among the univariate components of the time series, thereby enhancing SS accuracy. Analytical methods for constructing MCCEP using the autocovariance generating function and the squared SS error coherence spectrum are developed. The framework’s superiority is highlighted through a case study involving an industrial fractionator, where the SS with MCCEP outperforms conventional SSs employing dynamic partial least squares and bias updates or developed sequentially without considering interdependencies among univariate components of multi-output model errors.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"155 ","pages":"Article 103555"},"PeriodicalIF":3.9,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145106723","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

Advances in modeling and control of nonlinear distributed parameter systems and their applications: A review 非线性分布参数系统的建模与控制及其应用研究进展

IF 3.9 2区计算机科学

Journal of Process Control Pub Date : 2025-09-20 DOI: 10.1016/j.jprocont.2025.103549

Bowen Xu , Weiqi Yang , Xinjiang Lu , Yunxu Bai , Yajun Wang

{"title":"Advances in modeling and control of nonlinear distributed parameter systems and their applications: A review","authors":"Bowen Xu , Weiqi Yang , Xinjiang Lu , Yunxu Bai , Yajun Wang","doi":"10.1016/j.jprocont.2025.103549","DOIUrl":"10.1016/j.jprocont.2025.103549","url":null,"abstract":"<div><div>Numerous processes in various fields including engineering, physics, and chemistry, etc., belong to distributed parameter systems (DPSs). These systems are strongly spatiotemporal coupled, possessing complex time-varying dynamics and infinite-dimensional spatial distribution characteristics. Additionally, there are unknown initial/ boundary conditions and parameter variation during the interaction of information or energy exchange, especially in complex application scenarios (i.e., large operation range, large spatial region, etc.). These factors make the modeling, prediction and control of spatiotemporal dynamics extremely difficult and challenging. With the enrichment of computational resources and data-driven/ intelligent methods, many new frameworks and strategies are designed and applied for nonlinear DPSs, which promotes the research diversity and maturity of DPS theory. Meanwhile, the development also gives rise to new problems. From the perspective of review, this paper starts from the practical modeling and control problems in combination with several application cases of nonlinear DPSs, and summarizes the research and application progress, including traditional methods, data-driven methods, intelligent modeling methods etc., and looks forward to the future development trends, providing guidance for related research and practical problem-solving of nonlinear DPSs.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"155 ","pages":"Article 103549"},"PeriodicalIF":3.9,"publicationDate":"2025-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097511","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

Maximum extrem biogas yield prediction based tracking control for two-stage anaerobic digestion using CKF robust observer feedback 基于CKF鲁棒观测器反馈的两级厌氧消化最大极值沼气产量预测跟踪控制

IF 3.9 2区计算机科学

Journal of Process Control Pub Date : 2025-09-19 DOI: 10.1016/j.jprocont.2025.103558

Hongxuan Li , Haoping Wang , Yang Tian , Nicolai Christov

{"title":"Maximum extrem biogas yield prediction based tracking control for two-stage anaerobic digestion using CKF robust observer feedback","authors":"Hongxuan Li , Haoping Wang , Yang Tian , Nicolai Christov","doi":"10.1016/j.jprocont.2025.103558","DOIUrl":"10.1016/j.jprocont.2025.103558","url":null,"abstract":"<div><div>Two-stage anaerobic digestion process, recognized as a promising microbiological technology, can effectively converts organic pollutants into renewable energy gases. However, practical implementation faces two fundamental challenges: the critical process states (for example, concentrations of anaerobic microorganisms) are not directly measurable through conventional sensors, and the gas production efficiency remains suboptimal under current operational paradigms. To address these challenges, this study proposed a robust observer-based biogas yield extremum prediction tracking controller (RO-EPTC). The proposed RO-EPTC controller integrates a cubature Kalman filter robust observer and an artificial neural network-based prediction tracking controller. The RO-EPTC enables dynamic extremum prediction of biogas yield while ensuring real-time convergence of actual gas production to the identified optimal trajectory. Additionally, the proposed scheme provides accurate estimation of unmeasurable system states. Finally, through simulation comparison experiments, the effects of proposed RO-EPTC method were verified.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"155 ","pages":"Article 103558"},"PeriodicalIF":3.9,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097510","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

Output consensus for interconnected systems via the internal model principle and a model predictive control based strategy 基于内模原理和模型预测控制策略的互联系统输出一致性

IF 3.9 2区计算机科学

Journal of Process Control Pub Date : 2025-09-18 DOI: 10.1016/j.jprocont.2025.103551

Ye Zhang , Fei Li , Dongya Zhao , Xing-Gang Yan , Sarah K. Spurgeon

引用次数: 0

Deep learning-based model predictive control with exponential weighting strategy and its application in energy management systems 基于深度学习的指数加权模型预测控制及其在能源管理系统中的应用

IF 3.9 2区计算机科学

Journal of Process Control Pub Date : 2025-09-17 DOI: 10.1016/j.jprocont.2025.103542

Dan Cui , Yanfang Mo , Xiaofeng Yuan , Lingjian Ye , Kai Wang , Feifan Shen , Yalin Wang , Chunhua Yang , Weihua Gui

{"title":"Deep learning-based model predictive control with exponential weighting strategy and its application in energy management systems","authors":"Dan Cui , Yanfang Mo , Xiaofeng Yuan , Lingjian Ye , Kai Wang , Feifan Shen , Yalin Wang , Chunhua Yang , Weihua Gui","doi":"10.1016/j.jprocont.2025.103542","DOIUrl":"10.1016/j.jprocont.2025.103542","url":null,"abstract":"<div><div>Building energy management plays an important role in improving the overall system efficiency and reducing energy consumption. To achieve this goal, it is significant and challenging for the optimization of energy consumption and the utilization of renewable energy sources. This work presents a deep learning-based model predictive control with exponential weighting (DLEMPC) strategy to control and optimize Energy Management Systems (EMS). First, an exponential weighting technique with decreasing characteristic is introduced to the cost function over the timeslots in the receding horizon of the MPC to improve the control performance of the system, which aims to obtain the control actions by paying more importance on recent timeslots in the finite time-horizon. Second, a controller based on the deep belief network (DBN) model is proposed to reduce computational complexity of the rolling horizon optimization in practical applications. The deep learning controller is obtained by training it with a large number of input and output data pairs that are generated from a well-defined MPC designed with the new cost function. Finally, the DLEMPC strategy is used to control and optimize an EMS, connected to a grid, battery, HVAC, and solar panel. The results demonstrate that DLEMPC strategy can significantly improve the energy efficiency of buildings and reduce energy consumption compared to the traditional MPC formula.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"155 ","pages":"Article 103542"},"PeriodicalIF":3.9,"publicationDate":"2025-09-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145097508","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

Excitation-free closed-loop identification based on adaptive hysteresis loop width adjustment strategy 基于自适应磁滞环宽度调整策略的无激励闭环辨识

IF 3.9 2区计算机科学

Journal of Process Control Pub Date : 2025-09-13 DOI: 10.1016/j.jprocont.2025.103552

Chonggao Hu , Ridong Zhang , Furong Gao

{"title":"Excitation-free closed-loop identification based on adaptive hysteresis loop width adjustment strategy","authors":"Chonggao Hu , Ridong Zhang , Furong Gao","doi":"10.1016/j.jprocont.2025.103552","DOIUrl":"10.1016/j.jprocont.2025.103552","url":null,"abstract":"<div><div>Aiming at the problem that the traditional system identification methods are not adaptive enough when the system model parameters change significantly, this paper proposes an excitation-free closed-loop identification method based on an adaptive hysteresis loop width adjustment (AHLWA) strategy. Firstly, the AHLWA strategy is proposed according to the direction of change of the mean value of the power spectrum (MVPS) of the input signal, which can respond to the trend of the system's dynamic characteristics and dynamically adjust the hysteresis loop width parameters in real time. Secondly, an excitation-free closed-loop identification method based on the AHLWA strategy was developed by integrating the AHLWA strategy with the prediction error method. In addition, to accurately quantify the model error and detect model parameter variations, an improved model error detection method is proposed to quantify the model error by using the unexcited closed-loop identification technique. The numerical example simulation results indicate that the MVPS of the proposed identification method increases from 0.01 to 0.25 compared to the relay feedback identification method, which ensures the continuous excitation of the input signals and significantly improves the identification accuracy when the system model parameters change significantly. Meanwhile, the proposed identification method is further validated by applying it to the temperature control system of industrial coking furnaces. In addition, the proposed identification method can update the benchmark model on time, which makes the system model error significantly lower than 30%, providing an effective solution for model error detection in industrial closed-loop systems.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"155 ","pages":"Article 103552"},"PeriodicalIF":3.9,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050181","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 cross-layer cooperative optimization framework for optimal scheduling of multi-grade PET fiber production 多级聚酯纤维生产优化调度的跨层协同优化框架

IF 3.9 2区计算机科学

Journal of Process Control Pub Date : 2025-09-11 DOI: 10.1016/j.jprocont.2025.103540

Jiale Zhang, Wenli Du, Xin Dai

{"title":"A cross-layer cooperative optimization framework for optimal scheduling of multi-grade PET fiber production","authors":"Jiale Zhang, Wenli Du, Xin Dai","doi":"10.1016/j.jprocont.2025.103540","DOIUrl":"10.1016/j.jprocont.2025.103540","url":null,"abstract":"<div><div>The fluctuations in the supply chain market of polyethylene terephthalate (PET) fibers have been intensifying in recent years. Existing research on the production scheduling of PET plants is usually based on the assumption of a stationary supply chain market. However, these works ignore supply chain fluctuations and market competition, and the schedule obtained may become sub-optimal or infeasible in the real market. This paper considers using the game to represent the competition and cooperation relationships in the market among enterprises with limited supply capacity to obtain equilibrium supplies. Meanwhile, changes in the market prices will cause changes in the equilibrium supplies of the game. In addition, price prediction and supply decisions support the production schedule to achieve high economic efficiency. Therefore, we propose a cross-layer cooperative optimization framework between the supply chain layer and production chain layer for production scheduling optimization. In the supply chain layer, price trends are predicted by synchronous spatio-temporal relationship network, and equilibrium supplies are obtained through a multi-firm multi-product game. In the production chain layer, a production scheduling optimization model that integrates predicted prices and equilibrium supplies from the supply chain layer is established. The effectiveness of the proposed method is verified on a real-world PET plant.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"155 ","pages":"Article 103540"},"PeriodicalIF":3.9,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145050180","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

Novel observer-based fault-tolerant tracking control of input-constrained polymerization reactor with statistical analysis 基于观测器的统计分析输入约束聚合反应器容错跟踪控制

IF 3.9 2区计算机科学

Journal of Process Control Pub Date : 2025-09-10 DOI: 10.1016/j.jprocont.2025.103541

Zahra Ahangari Sisi , Mehdi Mirzaei , Sadra Rafatnia , Somayeh Jamshidi , Maryam Farbodi

{"title":"Novel observer-based fault-tolerant tracking control of input-constrained polymerization reactor with statistical analysis","authors":"Zahra Ahangari Sisi , Mehdi Mirzaei , Sadra Rafatnia , Somayeh Jamshidi , Maryam Farbodi","doi":"10.1016/j.jprocont.2025.103541","DOIUrl":"10.1016/j.jprocont.2025.103541","url":null,"abstract":"<div><div>The polymerization reaction within a continuous stirred tank reactor is modeled as a multivariable, nonlinear control process with input constraints. This study proposes a novel optimization-based approach for fault diagnosis and compensation, despite the uncertainties and disturbances present in the dynamic model of the polymerization reactor. This approach facilitates the design of a reliable model-based controller through the estimation of system perturbations. The proposed strategy mitigates external disturbances, time-varying uncertainties, and faults by incorporating complementary terms, calculated in real-time from output measurements, into the initial process model. To ensure robust performance of the fault detection mechanism, the threshold bounds for external disturbances and other uncertainties are determined stochastically using the Monte Carlo simulation approach. A continuous predictive controller is designed in closed form based on the updated reactor model, accounting for the presence of control input limitations. The constrained controller is formulated by solving an optimization problem using the Karush–Kuhn–Tucker (KKT) conditions. The boundedness of the tracking errors is established under the constrained multivariable controller. The results demonstrate that the proposed method exhibits high sensitivity, accuracy, and robustness in fault detection and isolation for a nonlinear uncertain reactor. Simulations confirm the superior performance of the proposed observer-based fault-tolerant control system over existing passive and active actuator fault-tolerant control methods.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"155 ","pages":"Article 103541"},"PeriodicalIF":3.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145027379","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

Observer based dual-layer sliding mode fault-tolerant control for dissolved oxygen concentration in wastewater treatment process 基于观测器的废水处理过程溶解氧浓度双层滑模容错控制

IF 3.9 2区计算机科学

Journal of Process Control Pub Date : 2025-09-09 DOI: 10.1016/j.jprocont.2025.103538

Hongyan Yang, Qi Zou, Honggui Han

{"title":"Observer based dual-layer sliding mode fault-tolerant control for dissolved oxygen concentration in wastewater treatment process","authors":"Hongyan Yang, Qi Zou, Honggui Han","doi":"10.1016/j.jprocont.2025.103538","DOIUrl":"10.1016/j.jprocont.2025.103538","url":null,"abstract":"<div><div>Fault-tolerant control (FTC) of dissolved oxygen concentration is the core technology to ensure the robustness of wastewater treatment process (WWTP). However, the dynamic characteristics of microbial community are difficult to be modeled accurately, and external disturbances such as fluctuations in influent water quality and equipment failures further increase the control difficulty. Therefore, how to effectively compensate for the unmodeled dynamics and improve the system robustness is still a key problem to be solved in the field of WWTP control. In order to address this problem, this paper proposes an FTC method for dissolved oxygen concentration that integrates a dual sliding mode observation mechanism and an intelligent optimization strategy. Firstly, a state observer with an adaptive compensation mechanism is constructed based on the sliding mode control (SMC) method to realize the simultaneous estimation of dissolved oxygen concentration and unmodeled dynamics. Secondly, an adaptive robust fault-tolerant controller is designed by combining the Lyapunov stability theory. Then, a double sliding mode surface containing observation error and control error is established. Thirdly, a differential evolutionary algorithm is introduced to perform a global optimization of the robust gain parameters, which transforms the complex robustness problem into an optimal gain solving problem. Simulation experiments are conducted to compare the fault-tolerant control effect of different control methods with the proposed method, and the results verify the superiority of the method proposed in this paper.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"155 ","pages":"Article 103538"},"PeriodicalIF":3.9,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145021014","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

Align knowledge with time-series: Cross-modal domain knowledge activation for LLM-enabled zero-shot fault diagnosis 将知识与时间序列对齐：跨模态领域知识激活用于llm支持的零故障诊断

IF 3.9 2区计算机科学

Journal of Process Control Pub Date : 2025-09-09 DOI: 10.1016/j.jprocont.2025.103534

Jiancheng Zhao , Chunhui Zhao , Jiaqi Yue

{"title":"Align knowledge with time-series: Cross-modal domain knowledge activation for LLM-enabled zero-shot fault diagnosis","authors":"Jiancheng Zhao , Chunhui Zhao , Jiaqi Yue","doi":"10.1016/j.jprocont.2025.103534","DOIUrl":"10.1016/j.jprocont.2025.103534","url":null,"abstract":"<div><div>The existing zero-shot fault diagnosis methods identify unseen categories that have no training samples by predicting fault attributes from samples. Although these methods alleviated the data scarcity issue, they raised a new challenge, i.e., professional fault attributes annotation. We recognize that the essence of fault attributes lies in describing the connections and differences between categories. Therefore, we propose a novel LLM-enabled zero-shot fault diagnosis paradigm, and the large language models (LLMs) fine-tuned based on domain-specific knowledge can capture similar information to replace manual annotation. It unlocks the potential of LLMs to handle zero-shot tasks related to industrial time-series data in a cross-modal manner. It aims to address the burden of semantic knowledge annotation posed by the existing attribute-enabled paradigm. Moreover, the domain shift problem (DSP) arising from the shortage of training samples for unseen faults is also tackled by leveraging the cross-modal activation of relevant knowledge that has been learned from domain-specific documents. Firstly, to address the issue that LLMs pretrained on general knowledge are lacking in the knowledge of the industrial field, we design prompts for industrial faults and fine-tune the LLM with domain knowledge from diagnosis reports. Subsequently, considering that LLMs lack the ability to process time-series data, we design a cross-modal transformation module to align the time-series modality with the text modality. Moreover, we propose a knowledge distillation strategy to further align these two modalities, so the unseen fault text descriptions can serve as substitutes for the unavailable samples to address the DSP. We conduct experiments on a real thermal power plant, and the proposed method achieves an average improvement of 9.83% in terms of the diagnosis accuracy of unseen faults.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"155 ","pages":"Article 103534"},"PeriodicalIF":3.9,"publicationDate":"2025-09-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145021013","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