Journal of Process Control最新文献_第2页

A unified GPR model based on transfer learning for SOH prediction of lithium-ion batteries 基于迁移学习的统一 GPR 模型用于锂离子电池的 SOH 预测

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-11-16 DOI: 10.1016/j.jprocont.2024.103337

Li Cai

{"title":"A unified GPR model based on transfer learning for SOH prediction of lithium-ion batteries","authors":"Li Cai","doi":"10.1016/j.jprocont.2024.103337","DOIUrl":"10.1016/j.jprocont.2024.103337","url":null,"abstract":"<div><div>State of health (SOH) acts as a qualitative capability measure in lithium-ion batteries’ management systems. Accurate SOH prediction is a critical issue for lithium-ion batteries. Most existing techniques always extract features from the tested batteries’ historical charging/discharging curves to achieve SOH prediction. However, the charging or discharging curves may be incomplete in the real-world application. Also, it is necessary to provide effective and dependable SOH predictions for both one-step-ahead and multi-step-ahead scenarios simultaneously, catering to diverse requirements. In order to achieve a unified SOH prediction without a prediction lag, a Gaussian process regression (GPR) model based on transfer learning is proposed. In this article, a non-zero mean function along with a compound covariance function are designed to describe the capacity attenuation. The hyper-parameter set of this model can be transferred and pre-determined from some readily available batteries in the same processes. The proposed method is verified on several batteries from NASA dataset. Results illustrate that our approach with both superior prediction performance and stronger robustness outperforms the counterparts.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"144 ","pages":"Article 103337"},"PeriodicalIF":3.3,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142664020","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

Control of Production-Inventory systems of perennial crop seeds 控制多年生作物种子的生产-库存系统

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-11-10 DOI: 10.1016/j.jprocont.2024.103330

Robbert van der Kruk , René van de Molengraft , Herman Bruyninckx , Eldert J. van Henten

{"title":"Control of Production-Inventory systems of perennial crop seeds","authors":"Robbert van der Kruk , René van de Molengraft , Herman Bruyninckx , Eldert J. van Henten","doi":"10.1016/j.jprocont.2024.103330","DOIUrl":"10.1016/j.jprocont.2024.103330","url":null,"abstract":"<div><div>Production planning and inventory control are essential for the logistic performance of breeding companies. In this paper, we discuss such a system for perennial crop seeds in which production during multiple years and a number of growth cycles before production starts are characteristic. Large variations in yield and demand are typical and could easily lead to shortages or excess in seed stock. Both are costly phenomena. For these reasons, production planning as currently done by seed breeders without much technical support is extremely challenging. This paper describes and models the seed production process of a breeding company and examines its impact on inventory levels. The approach involves developing a time-discrete model parameterised with historical data. Subsequently, three control schemes are formulated: a classical feedback–feedforward PID controller, a feedback–feedforward PID controller with a Smith Predictor and a Model Predictive Control scheme. The goal of this paper is to present and validate a novel seed production–inventory model. Only aged plants are destroyed after a fixed number of production cycles. The ordering of new plants is the input control variable. The model represents the multi-year seed production of perennial crop seeds and expands upon the dead-time delay model, which typically does not account for production level uncertainty in production–inventory systems. The parameters of the model create a general approach; for both annual and perennial crop seeds.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"144 ","pages":"Article 103330"},"PeriodicalIF":3.3,"publicationDate":"2024-11-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142664018","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Model-predictive fault-tolerant control of safety-critical processes based on dynamic safe set 基于动态安全集的安全关键过程模型预测容错控制

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-11-07 DOI: 10.1016/j.jprocont.2024.103329

Ritu Ranjan, Costas Kravaris

{"title":"Model-predictive fault-tolerant control of safety-critical processes based on dynamic safe set","authors":"Ritu Ranjan, Costas Kravaris","doi":"10.1016/j.jprocont.2024.103329","DOIUrl":"10.1016/j.jprocont.2024.103329","url":null,"abstract":"<div><div>Industrial systems and chemical plants heavily rely on automation and control systems for seamless operations. However, the susceptibility of these systems to various faults poses threats to processes, leading to economic losses and safety risks. Here, a robust fault-tolerant control (FTC) strategy is developed that can take proactive measures during faults involving in-time activation of a backup controller, to ensure that the system remains within safe operational limits. It is based on the Dynamic Safe Set (DSS) which is the set of initial process states that meet safety constraints at all times, and the dynamic safety margin (DSM) which is the minimum distance from the DSS boundary. For just-in-time corrective action, a critical fault function is introduced, defined as the time required by the system to cross the DSS boundary under the nominal controller only. This critical fault function is calculated offline and is integrated with a real-time fault size estimation to formulate the controller reconfiguration logic to keep system within DSS. A linear functional observer is used to estimate fault size, combined with a predictive scheme, to enhance robustness during the transient period of fault estimation. This configuration avoids unnecessary control actions while ensuring timely intervention. The proposed FTC strategy is tested on an exothermic Continuous Stirred Tank Reactor (CSTR) case study. The results demonstrate the strategy's effectiveness in handling process faults, ensuring both stability and safety constraints are met. Thus, this paper contributes to the advancement of FTC ensuring the resilience of industrial systems in the face of unforeseen challenges.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"144 ","pages":"Article 103329"},"PeriodicalIF":3.3,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142664021","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

Numerical solution of nonlinear periodic optimal control problems using a Fourier integral pseudospectral method 用傅立叶积分伪谱法数值求解非线性周期优化控制问题

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-11-04 DOI: 10.1016/j.jprocont.2024.103326

Kareem T. Elgindy

{"title":"Numerical solution of nonlinear periodic optimal control problems using a Fourier integral pseudospectral method","authors":"Kareem T. Elgindy","doi":"10.1016/j.jprocont.2024.103326","DOIUrl":"10.1016/j.jprocont.2024.103326","url":null,"abstract":"<div><div>Many real-world systems exhibit cyclical behavior and nonlinear dynamics. Optimal control theory provides a framework for determining the best periodic control strategies for such systems. These strategies achieve the desired goals while minimizing the costs, energy use, or other relevant metrics. This study addresses this challenge by introducing the Fourier integral pseudospectral (FIPS) method. This method is applicable to a general class of nonlinear periodic process control problems with equality and/or inequality constraints, assuming sufficiently smooth solutions. The FIPS method performs collocation of the problem’s integral form at an equidistant set of nodes. Furthermore, it utilizes highly accurate Fourier integration matrices (FIMs) to approximate all necessary integrals. This approach transforms the original problem into a nonlinear programming problem (NLP) with algebraic constraints. We employed a direct numerical optimization method to solve this NLP effectively. This study establishes rigorous convergence properties and derives error estimates for the Fourier series, interpolants, and quadratures employed within the context of process control applications, focusing on smooth and continuous periodic functions. Finally, the accuracy and efficiency of the FIPS method are demonstrated through two illustrative nonlinear process-control problems.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"144 ","pages":"Article 103326"},"PeriodicalIF":3.3,"publicationDate":"2024-11-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142579014","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

FPGA-embedded optimization algorithm to maximize the acetate productivity in a dark fermentation process 在黑暗发酵过程中最大限度提高醋酸生产率的 FPGA 嵌入式优化算法

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-11-01 DOI: 10.1016/j.jprocont.2024.103323

José de Jesús Colín-Robles , Ixbalank Torres-Zúñiga , Mario A. Ibarra-Manzano , J. Gabriel Aviña-Cervantes , Víctor Alcaraz-González

{"title":"FPGA-embedded optimization algorithm to maximize the acetate productivity in a dark fermentation process","authors":"José de Jesús Colín-Robles , Ixbalank Torres-Zúñiga , Mario A. Ibarra-Manzano , J. Gabriel Aviña-Cervantes , Víctor Alcaraz-González","doi":"10.1016/j.jprocont.2024.103323","DOIUrl":"10.1016/j.jprocont.2024.103323","url":null,"abstract":"<div><div>This paper presents an optimization strategy to online maximize the acetate productivity rate in a dark fermentation (DF) process. The Golden Section Search algorithm is used to compute the maximum acetate productivity rate as a function of the inlet chemical oxygen demand (COD) and the dilution rate, selected as a manipulated variable. Such maximum productivity is considered as a reference by a Super-Twisting controller to regulate the real acetate productivity rate of the DF process. Due to the lack of sensors to measure the COD online, the optimization strategy includes an unknown input observation strategy integrated by a Luenberger observer interconnected to a Super-Twisting observer to estimate the inlet COD concentration. The optimization algorithm is embedded in an FPGA (Field Programmable Gate Array) device to minimize hardware resources and power consumption. The feasibility of the online optimization strategy embedded in an FPGA, using a digital architecture designed with a fixed-point format representation, is demonstrated by numerical simulations. Results show that the optimization strategy requires 53% of the logic elements and 100% of 8-bit multipliers of an FPGA Cyclone II and the power consumption estimated is only <span><math><mrow><mn>190</mn><mspace></mspace><mi>m</mi><mi>W</mi></mrow></math></span>.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"144 ","pages":"Article 103323"},"PeriodicalIF":3.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Data Science and Model Predictive Control: 数据科学与模型预测控制

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-11-01 DOI: 10.1016/j.jprocont.2024.103327

Marcelo M. Morato , Monica S. Felix

{"title":"Data Science and Model Predictive Control:","authors":"Marcelo M. Morato , Monica S. Felix","doi":"10.1016/j.jprocont.2024.103327","DOIUrl":"10.1016/j.jprocont.2024.103327","url":null,"abstract":"<div><div>Model Predictive Control (MPC) is an established control framework, based on the solution of an optimisation problem to determine the (optimal) control action at each discrete-time sample. Accordingly, major theoretical advances have been provided in the literature, such as closed-loop stability and recursive feasibility certificates, for the most diverse kinds of processes descriptions. Nevertheless, identifying <em>good</em>, trustworthy models for complex systems is a task heavily affected by uncertainties. As of this, developing MPC algorithms <strong>directly from data</strong> has recently received a considerable amount of attention over the last couple of years. In this work, we review the available <strong>data-based MPC</strong> formulations, which range from reinforcement <strong>learning</strong> schemes, <strong>adaptive</strong> controllers, and novel solutions based on behavioural theory and <strong>trajectory</strong> representations. In particular, we examine the recent research body on this topic, highlighting the main features and capabilities of available algorithms, while also discussing the fundamental connections among approaches and, comparatively, their advantages and limitations.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"144 ","pages":"Article 103327"},"PeriodicalIF":3.3,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142572464","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 error feedback regulation for a 1-D anti-stable wave equation subject to harmonic disturbances 受谐波干扰的一维反稳定波方程的自适应误差反馈调节

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-10-28 DOI: 10.1016/j.jprocont.2024.103324

Shuangxi Huang , Qing-Qing Hu

引用次数: 0

Enhanced predictive PDF control of stochastic distribution systems with neural network compensation and its application 采用神经网络补偿的随机配电系统的增强型预测性 PDF 控制及其应用

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-10-24 DOI: 10.1016/j.jprocont.2024.103328

Ping Zhou, Xiaoyang Sun, Lixiang Zhang, Mingjie Li

{"title":"Enhanced predictive PDF control of stochastic distribution systems with neural network compensation and its application","authors":"Ping Zhou, Xiaoyang Sun, Lixiang Zhang, Mingjie Li","doi":"10.1016/j.jprocont.2024.103328","DOIUrl":"10.1016/j.jprocont.2024.103328","url":null,"abstract":"<div><div>Compared to the conventional control algorithms that use mean and variance as indicators, predictive probability density function (PDF) control can effectively handle the output PDF control problem of non-Gaussian stochastic distribution systems. However, the existing predictive PDF control method does not consider the construction error between output PDF and weight, thus the control performance is still unsatisfactory. Therefore, this paper proposes a new Enhanced Predictive PDF control method (En-PDF) to improve the output PDF control performance of stochastic distribution systems. The proposed method mainly consists of two parts: the predictive PDF control part and the neural network compensation control part aiming to reduce the bias of output PDF. First, the Radical Basis Functions (RBFs) are used to approximate the PDF of the stochastic systems output, and then a prediction model representing the relationship between input and weight is established using the subspace identification algorithm to design the predictive PDF control for the stochastic systems. Next, the Kullback-Leibler (KL) divergence is used to measure the similarity between the output PDF and the set PDF, combined with the weight error and compensation to design a new performance index. Based on this, the parameters of the neural network are adjusted using the gradient descent algorithm to obtain the optimal compensation, and the stability and tracking performance of the proposed algorithm are analyzed using inductive reasoning method. Finally, the predictive PDF control input with the compensation work together on the controlled plant to achieve high-performance control of the output PDF of non-Gaussian stochastic distribution systems. Both simulation experiments and physical control experiments validate the effectiveness and superiority of the proposed method.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"143 ","pages":"Article 103328"},"PeriodicalIF":3.3,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528045","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

Fixed-time active fault-tolerant control for a class of nonlinear systems with intermittent faults and input saturation 一类具有间歇性故障和输入饱和的非线性系统的固定时间主动容错控制

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-10-24 DOI: 10.1016/j.jprocont.2024.103319

Xuanrui Cheng, Ming Gao, Li Sheng, Yongli Wei

{"title":"Fixed-time active fault-tolerant control for a class of nonlinear systems with intermittent faults and input saturation","authors":"Xuanrui Cheng, Ming Gao, Li Sheng, Yongli Wei","doi":"10.1016/j.jprocont.2024.103319","DOIUrl":"10.1016/j.jprocont.2024.103319","url":null,"abstract":"<div><div>In this paper, the problem of fixed-time active fault-tolerant control is studied for systems with sector-bounded nonlinearities, intermittent faults, and input saturation. Since intermittent faults appear and disappear randomly, a fixed-time scheme is considered in the active fault-tolerant control algorithm, composed of detection, isolation, estimation, and the control unit. Utilizing homogeneity-based observers, the fixed-time state estimation is available in the presence of unknown but bounded disturbances, and a fault diagnosis unit is proposed. An input saturation compensator is introduced to analyze the effect of input saturation, and its auxiliary variables are used in the reconfigurable control law. The fault-tolerant controller, which is constructed via the information provided by the fault diagnosis unit and saturation compensator, has two switching modes. As a consequence, intermittent faults are compensated via the designed active fault-tolerant control method and the system reaches practical stability with the entire convergence time bounded in a fixed time. Finally, the example of a heat control system is exploited to demonstrate the effectiveness of the developed active fault-tolerant control scheme.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"143 ","pages":"Article 103319"},"PeriodicalIF":3.3,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528048","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

Pre-connected and trainable adjacency matrix-based GCN and neighbor feature approximation for industrial fault diagnosis 用于工业故障诊断的基于邻接矩阵和邻近特征近似的预连接和可训练邻接矩阵

IF 3.3 2区计算机科学

Journal of Process Control Pub Date : 2024-10-24 DOI: 10.1016/j.jprocont.2024.103320

Hao-Yang Qing, Ning Zhang, Yan-Lin He, Qun-Xiong Zhu, Yuan Xu

{"title":"Pre-connected and trainable adjacency matrix-based GCN and neighbor feature approximation for industrial fault diagnosis","authors":"Hao-Yang Qing, Ning Zhang, Yan-Lin He, Qun-Xiong Zhu, Yuan Xu","doi":"10.1016/j.jprocont.2024.103320","DOIUrl":"10.1016/j.jprocont.2024.103320","url":null,"abstract":"<div><div>Industrial fault diagnosis methods based on graph convolution network (GCN) becomes a hot topic for its great feature extraction ability to multivariate time-series data. However, GCNs ignore inter-sample temporality when constructing the adjacency matrix (AM), leading to low prediction accuracy. A novel fault diagnosis method based on pre-connected and trainable AM-based GCN and neighbor feature approximation (PTGCN-FA) is proposed at the node-level task. Firstly, PTGCN-FA introduces the temporal nearest neighbors into spatial nearest neighbors to pre-connect and construct the AM. Then, the AM is trained only where the samples are connected, which makes the best weights obtained and reduces the time complexity of the model. Finally, after the GCN layers, the trained AM is introduced into the approximation of features, which are neighbors in the original sample space. Two process industry cases are carried out, and the simulation results including diagnosis accuracy, confusion matrix, study to the ratio of labeled data and an ablation experiment verify PTGCN-FA has more efficient and accurate diagnostic performance than related methods. Additionally, the analysis of the temporal neighborhood weight parameter shows that the performance of fault diagnosis can be improved by considering both temporal and spatial information between samples.</div></div>","PeriodicalId":50079,"journal":{"name":"Journal of Process Control","volume":"143 ","pages":"Article 103320"},"PeriodicalIF":3.3,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142528046","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