Control Engineering Practice最新文献_第4页

Global–local preserving method of quality-related maximization and its application for process monitoring 质量相关最大化的全局-局部保存法及其在过程监控中的应用

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2024-11-01 DOI: 10.1016/j.conengprac.2024.106143

Jiandong Yang, Xuefeng Yan

{"title":"Global–local preserving method of quality-related maximization and its application for process monitoring","authors":"Jiandong Yang, Xuefeng Yan","doi":"10.1016/j.conengprac.2024.106143","DOIUrl":"10.1016/j.conengprac.2024.106143","url":null,"abstract":"<div><div>Common multivariate statistical quality-related process monitoring methods often separate feature extraction from quality-related process modeling, which can lead to insufficient extraction of quality-related information. In this paper, a quality-related maximization model with global and local preservation constraints is proposed. The process data are mapped to a high-dimensional feature space using kernel projection, which better linearizes the nonlinear data. Kernel sparse representation local linear embedding is applied to adaptively determine local relationships. Based on these local relationships, global-local constraints are constructed, and quality-related features are extracted according to the principle of maximizing correlation with quality indicators, resulting in a low-dimensional embedding matrix. This embedding matrix is used for process monitoring by dividing the quality-related and quality-independent subspaces and constructing a monitoring statistical strategy. The effectiveness of the proposed method is verified using the Tennessee-Eastman process, and it is further applied to a fluid catalytic cracking process.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106143"},"PeriodicalIF":5.4,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142571576","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

Synchronous DTC for torque sub-harmonic reduction in low switching frequency induction motor drives 用于降低低开关频率感应电机驱动器转矩次谐波的同步 DTC

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2024-11-01 DOI: 10.1016/j.conengprac.2024.106133

A. Benevieri, M. Marchesoni, M. Passalacqua, P. Pozzobon, L. Vaccaro

引用次数: 0

Bayesian optimization with embedded stochastic functionality for enhanced robotic obstacle avoidance 具有嵌入式随机功能的贝叶斯优化技术，用于增强机器人的避障能力

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2024-10-30 DOI: 10.1016/j.conengprac.2024.106141

Catalin Stefan Teodorescu, Andrew West, Barry Lennox

{"title":"Bayesian optimization with embedded stochastic functionality for enhanced robotic obstacle avoidance","authors":"Catalin Stefan Teodorescu, Andrew West, Barry Lennox","doi":"10.1016/j.conengprac.2024.106141","DOIUrl":"10.1016/j.conengprac.2024.106141","url":null,"abstract":"<div><div>Designing an obstacle avoidance algorithm that incorporates the stochastic nature of human–robot-environment interactions is challenging. In high risk activities, such as those found in nuclear environments, a comprehensive approach towards handling uncertainty is essential. In this article, in the context of safe teleoperation of robots, an automated iterative sampling procedure based on Bayesian optimization is proposed, where the robot is trained to predict the behaviour of a human operator. Specifically, a Gaussian process regression model is used to learn an effective representation of a safe stop manoeuvre, required for implementing an obstacle avoidance shared control algorithm. This model is then used to predict the future time duration to execute a safe stop manoeuvre, given the current real-world circumstances. The control algorithm expects this value to be reasonably high; if not, it will gradually reduce the human operator’s authority. A distinctive attribute of the proposed method is the use of statistical confidence metrics as tuning parameters, intended to provide a statistical indication of whether or not an obstacle will be avoided. The proof-of-concept experiments were carried out using three robotic platforms suited for use in nuclear robotics, an amphibious SuperDroid HD2 robot equipped with a Velodyne VLP16 (a 3D lidar), an AgileX Scout Mini R&D Pro land robot fitted with a Realsense D435 depth camera, and a Husarion ROSBot 2.0 Pro supplied with an RPLIDAR A3 (a 2D lidar). The test results show that the proposed Bayesian optimization method uses 8 times less data compared to an exhaustive grid approach, and that it provides a robot-agnostic, robust obstacle avoidance.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106141"},"PeriodicalIF":5.4,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142553443","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

Aerial teleoperation for quadrotors based on gaze-guidance 基于凝视导航的四旋翼飞行器空中遥控操作

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2024-10-30 DOI: 10.1016/j.conengprac.2024.106138

Jiahui Hu , Yonghua Lu , Jing Li , Haibo Yang , Jingjing Liu

引用次数: 0

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2024-10-29 DOI: 10.1016/j.conengprac.2024.106140

Liujiayi Zhao, Pengyu Song, Chunhui Zhao

{"title":"Causal similarity learning with multi-level predictive relation aggregation for grouped root cause diagnosis of industrial faults","authors":"Liujiayi Zhao, Pengyu Song, Chunhui Zhao","doi":"10.1016/j.conengprac.2024.106140","DOIUrl":"10.1016/j.conengprac.2024.106140","url":null,"abstract":"<div><div>Existing root cause diagnosis (RCD) methods infer causal relationships among abnormal variables by decomposing causal graphs into intra-group and inter-group levels, reducing redundancy according to direct causality. However, the indirect causality trigged by wide-range fault propagation may be ignored when inferring within groups, leading to the mismatch between causality distribution and grouping results. To overcome the challenge, we propose a causal similarity learning method with multi-level predictive relation aggregation, which contains a complementary similarity measurement framework covering both single-level and high-level causal relationships. First, an attention mechanism with temporal misalignment is designed, which can convert the undirected correlations of features into directed high-level causal similarity by extracting lagged predictive relations. Further, a graph-cutting penalty term is proposed to promote causality distribution to exhibit intra-group denseness and inter-group sparsity, so that single-level causal similarity can be considered during grouping. Finally, a dual RCD method is proposed to search root causes from the causal graph with intra-group and inter-group causality. In this way, numerous redundant causations caused by complex fault propagation can be succinctly described by inter-group causation, and the search for root cause variables can be limited to subgroups to improve diagnosis efficiency. The validity of the proposed method is illustrated through both the Tennessee Eastman benchmark example and a real industrial process.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106140"},"PeriodicalIF":5.4,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539824","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

Multiple-model iterative learning control with application to stroke rehabilitation 多模型迭代学习控制在中风康复中的应用

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2024-10-29 DOI: 10.1016/j.conengprac.2024.106134

Junlin Zhou , Christopher T. Freeman , William Holderbaum

{"title":"Multiple-model iterative learning control with application to stroke rehabilitation","authors":"Junlin Zhou , Christopher T. Freeman , William Holderbaum","doi":"10.1016/j.conengprac.2024.106134","DOIUrl":"10.1016/j.conengprac.2024.106134","url":null,"abstract":"<div><div>Model-based iterative learning control (ILC) algorithms achieve high accuracy but often exhibit poor robustness to model uncertainty, causing divergence and long-term instability as the number of trials increases. To address this, an estimation-based multiple-model switched ILC (EMMILC) approach is developed based on novel theorem results which guarantee stability if the true plant lies within a uncertainty space defined by the designer. Using gap metric analysis, EMMILC eliminates restrictive assumptions on the uncertainty structure assumed in existing multiple-model ILC methods. Our design framework minimises computational load while maximising tracking accuracy. Applied to a common rehabilitation scenario, EMMILC outperforms the standard ILC approaches that have been previously employed in this setting. This is confirmed by experimental tests with four participants where performance increased by 28%. EMMILC is the first model-based ILC framework that can guarantee high performance while not requiring any model identification or tuning, and paves the way for effective, home-based rehabilitation systems.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106134"},"PeriodicalIF":5.4,"publicationDate":"2024-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142539825","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

Bounded control of PMLSM servo system based on fractional order barrier function adaptive super-twisting approach 基于分数阶障碍函数自适应超扭曲方法的 PMLSM 伺服系统有界控制

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2024-10-25 DOI: 10.1016/j.conengprac.2024.106131

XinYu Zhao, LiMei Wang

{"title":"Bounded control of PMLSM servo system based on fractional order barrier function adaptive super-twisting approach","authors":"XinYu Zhao, LiMei Wang","doi":"10.1016/j.conengprac.2024.106131","DOIUrl":"10.1016/j.conengprac.2024.106131","url":null,"abstract":"<div><div>The performance of permanent magnet linear synchronous motor in tracking is influenced by payload uncertainty and unknown disturbances. Traditional constant-gain super-twisting control typically use a high control gain exceeding the total disturbances to maintain the stability of the system. However, these controllers may lead to control input oversaturation when disturbances decrease and the control gain is not appropriately chosen. To address this issue, this paper proposes a new Fractional Order Barrier Function Adaptive Super-Twisting (FOBFAST) control strategy. The advantages of FOBFAST include: (1) mitigation of system chattering through the design of the super-twisting algorithm and the fractional-order integral terminal sliding mode manifold; (2) achieving convergence of system error to a predetermined zero-neighborhood without requiring information about the disturbance upper bound; (3) dynamic adjustment of control gain to a smaller value as tracking error converges to the origin. Furthermore, an improved barrier function is proposed to address the issue of large control amplitudes, limiting the maximum allowable control gain and ensuring system stability. Experimental results demonstrate that the proposed control strategy not only enhances position tracking performance but also exhibits superior robustness.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106131"},"PeriodicalIF":5.4,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532939","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

Integral predictive sliding mode control for high-speed trains: A dynamic linearization and input constraint-based data-driven scheme 高速列车的积分预测滑动模式控制：基于数据驱动的动态线性化和输入约束方案

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2024-10-25 DOI: 10.1016/j.conengprac.2024.106139

Liang Zhou, Zhong-Qi Li, Hui Yang, Chang Tan

{"title":"Integral predictive sliding mode control for high-speed trains: A dynamic linearization and input constraint-based data-driven scheme","authors":"Liang Zhou, Zhong-Qi Li, Hui Yang, Chang Tan","doi":"10.1016/j.conengprac.2024.106139","DOIUrl":"10.1016/j.conengprac.2024.106139","url":null,"abstract":"<div><div>A control scheme with high reliability and excellent tracking performance is essential for the automatic operation of high-speed trains (HSTs). In this study, a novel discrete-time data-driven predictive sliding mode control (DDPSMC) scheme is proposed for multi-power unit HSTs. Initially, a nonlinear integral terminal sliding mode surface was designed to replace the traditional linear sliding mode function, thereby achieving a rapid system error convergence and alleviating chattering. Then, receding horizon optimization was integrated into predictive control, which allowed the predicted sliding mode state to follow the expected trajectory of a predefined continuous convergence law. This scheme enabled the system to obtain higher output error accuracy and explicitly handle input constraints. Moreover, to enhance robustness, a parameter update law and disturbance delay estimation algorithm were introduced to calculate the control gain and total uncertainty, respectively. Finally, a comparative test of the proposed control scheme was conducted using a CRH380A HST simulation experimental platform in a laboratory setting. Simulation results demonstrate that the velocity error range of each power unit of the HST under the proposed control scheme is within [<span><math><mo>−</mo></math></span>0.176 km/h, 0.152 km/h], while the control force and acceleration are within [<span><math><mo>−</mo></math></span>55.7 kN, 44.8 kN] and [<span><math><mo>−</mo></math></span>0.564 m/s<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>, 0.496 m/s<span><math><msup><mrow></mrow><mrow><mn>2</mn></mrow></msup></math></span>], respectively, with stable variation, and other performance indicators are also better than other comparison methods. These results satisfy the safety, stability, and punctuality requirements of the train.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106139"},"PeriodicalIF":5.4,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532940","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

Corrective variational mode decomposition to detect multiple oscillations in process control systems 纠正变分模式分解以检测过程控制系统中的多重振荡

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2024-10-24 DOI: 10.1016/j.conengprac.2024.106123

Songhua Liu , Xun Lang , Jiande Wu , Yufeng Zhang , Cong Lei , Hongye Su

{"title":"Corrective variational mode decomposition to detect multiple oscillations in process control systems","authors":"Songhua Liu , Xun Lang , Jiande Wu , Yufeng Zhang , Cong Lei , Hongye Su","doi":"10.1016/j.conengprac.2024.106123","DOIUrl":"10.1016/j.conengprac.2024.106123","url":null,"abstract":"<div><div>Monitoring oscillatory behavior in industrial control systems is essential to ensure process safety and enhance productivity, but unfortunately, current decomposition-based monitoring methods struggle to extract and accurately detect multiple oscillations. This struggle is primarily due to the level of noise susceptibility in current monitoring methods and the intermittent nature of multiple oscillations in industrial control systems. As a potential solution, variational mode decomposition (VMD) shows promising advantages in processing non-stationary industrial signals with a significant amount of interference. Nevertheless, improperly configuring the number of modes in the VMD can lead to mode mixing and degrade the oscillation extraction accuracy. To overcome this challenge, we propose a corrective VMD approach that automatically adjusts the mode number to create a robust and automated framework for monitoring multiple oscillations. Our framework excels in detecting oscillatory behavior and quantifying the number of oscillations, even in the presence of noisy, intermittent, and irregular disturbances. To validate its effectiveness and practicality, we applied the framework to both a benchmark industrial dataset and a self-constructed industrial dataset, comparing its performance against state-of-the-art oscillation detection methods. The framework demonstrated superior accuracy, achieving 93.90% in detecting oscillations and 85.37% in quantifying the number of oscillations within the benchmark dataset, with similarly excellent results observed in the self-constructed industrial dataset.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"154 ","pages":"Article 106123"},"PeriodicalIF":5.4,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142532937","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

Hierarchical grouping and visualization of correlated alarms using time-augmented word embedding 利用时间增强词嵌入对相关警报进行分层分组和可视化处理

IF 5.4 2区计算机科学

Control Engineering Practice Pub Date : 2024-10-24 DOI: 10.1016/j.conengprac.2024.106130

Aliakbar Davoodi, Ahmad W. Al-Dabbagh

引用次数: 0