ISA transactionsPub Date : 2024-08-01DOI: 10.1016/j.isatra.2024.05.049
{"title":"Observer-based hierarchical distributed model predictive control for multi-linear motor traction systems","authors":"","doi":"10.1016/j.isatra.2024.05.049","DOIUrl":"10.1016/j.isatra.2024.05.049","url":null,"abstract":"<div><p>This paper proposes an observer-based hierarchical distributed model predictive control (MPC) strategy for ensuring speed consistency in multi-linear motor traction systems. First, a communication topology is considered to ensure information exchange. Secondly, the control architecture of each agent is divided into upper layers and lower layers. The upper layer utilizes a distributed MPC method to track the leader’s speed. The lower layer uses a decentralized MPC method to track the command signals sent by its upper layer controller. In addition, to eliminate the negative impact of disturbance, a nonlinear disturbance observer is designed. We then prove the asymptotic stability of the entire system by properly designing the Lyapunov equation. Finally, the feasibility of the proposed strategy is verified based on several simulations.</p></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"151 ","pages":"Pages 131-142"},"PeriodicalIF":6.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141328245","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}
ISA transactionsPub Date : 2024-08-01DOI: 10.1016/j.isatra.2024.06.003
{"title":"Membership-dependent polynomial fuzzy control of a positive discrete time system: A symbol transfer technique","authors":"","doi":"10.1016/j.isatra.2024.06.003","DOIUrl":"10.1016/j.isatra.2024.06.003","url":null,"abstract":"<div><p>This work explores the polynomial fuzzy stabilization for positive systems. The traditional quadratic Lyapunov function and basic stability analysis may not be favourable for stability investigation due to the absence of the positivity property and membership functions. Therefore, a fuzzy co-positive polynomial Lyapunov–Krasovskii (FCPL) function which considers the positivity is proposed firstly through an imperfect premise matching (IPM) approach. Secondly, the symbol transfer technique which takes into account fuzzy membership knowledge relaxes the stability conditions. The number of symbols is reduced by two constraints: (1) the last and next moments of the membership functions of the FCPL function; (2) membership functions of the fuzzy model and the controller. Finally, the polynomial fuzzy controller with symbols is obtained. Two examples are implemented to verify the proposed methods.</p></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"151 ","pages":"Pages 212-220"},"PeriodicalIF":6.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141392508","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}
ISA transactionsPub Date : 2024-08-01DOI: 10.1016/j.isatra.2024.05.030
{"title":"Dynamic event-triggered control for CPSs under QoS-based variable sampling approach","authors":"","doi":"10.1016/j.isatra.2024.05.030","DOIUrl":"10.1016/j.isatra.2024.05.030","url":null,"abstract":"<div><p>In this article, a quality of service (QoS) dependent variable sampling dynamic event-triggered control method is designed for a cyber–physical system (CPS) with delays and packets dropout to cope with non-ideal network environments, maintain the desired control performance and improve the communication efficiency. To achieve the variable period sampling, a sampler is designed based on the QoS of the wireless network by using the delta operator discretization method. Then, a variable period sampling scheme for the delta operator system converted from the CPS is designed. Furthermore, a dynamic event-triggered mechanism (DETM) is proposed using the variable period sampling signal, which can reduce event triggered data calculations and increase event triggered intervals. By utilizing the average dwell time (ADT) approach, sufficient conditions contains the explicit variable sampling period are derived for the derived switched CPS. Finally, the effectiveness of the designed method is verified by numerical examples.</p></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"151 ","pages":"Pages 12-18"},"PeriodicalIF":6.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141142680","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}
ISA transactionsPub Date : 2024-08-01DOI: 10.1016/j.isatra.2024.05.041
{"title":"Remote path-following control for a holonomic Mecanum-wheeled robot in a resource-efficient networked control system","authors":"","doi":"10.1016/j.isatra.2024.05.041","DOIUrl":"10.1016/j.isatra.2024.05.041","url":null,"abstract":"<div><p>This paper introduces a novel resource-efficient control structure for remote path-following control of autonomous vehicles based on a comprehensive combination of Kalman filtering, non-uniform dual-rate sampling, periodic event-triggered communication, and prediction-based and packet-based control techniques. An essential component of the control solution is a non-uniform dual-rate extended Kalman filter (NUDREKF), which includes an h-step ahead prediction stage. The prediction error of the NUDREKF is ensured to be exponentially mean-square bounded. The algorithmic implementation of the filter is straightforward and triggered by periodic event conditions. The main goal of the approach is to achieve efficient usage of resources in a wireless networked control system (WNCS), while maintaining satisfactory path-following behavior for the vehicle (a holonomic Mecanum-wheeled robot). The proposal is additionally capable of coping with typical drawbacks of WNCS such as time-varying delays, and packet dropouts and disorder. A Simscape Multibody simulation application reveals reductions of up to 93% in resource usage compared to a nominal time-triggered control solution. The simulation results are experimentally validated in the holonomic Mecanum-wheeled robotic platform.</p></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"151 ","pages":"Pages 377-390"},"PeriodicalIF":6.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S001905782400243X/pdfft?md5=56690d28ec6668476670def6daee72ca&pid=1-s2.0-S001905782400243X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141249161","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}
ISA transactionsPub Date : 2024-08-01DOI: 10.1016/j.isatra.2024.05.050
{"title":"Sliding mode observer-based model predictive tracking control for Mecanum-wheeled mobile robot","authors":"","doi":"10.1016/j.isatra.2024.05.050","DOIUrl":"10.1016/j.isatra.2024.05.050","url":null,"abstract":"<div><p>This paper proposes a novel adaptive variable power sliding mode observer-based model predictive control (AVPSMO-MPC) method for the trajectory tracking of a Mecanum-wheeled mobile robot (MWMR) with external disturbances and model uncertainties. First, in the absence of disturbances and uncertainties, a model predictive controller that considers various physical constraints is designed based on the nominal dynamics model of the MWMR, which can transform the tracking problem into a constrained quadratic programming (QP) problem to solve the optimal control inputs online. Subsequently, to improve the anti-jamming ability of the MWMR, an AVPSMO is designed as a feedforward compensation controller to suppress the effects of external disturbances and model uncertainties during the actual motion of the MWMR, and the stability of the AVPSMO is proved via Lyapunov theory. The proposed AVPSMO-MPC method can achieve precise tracking control while ensuring that the constraints of MWMR are not violated in the presence of disturbances and uncertainties. Finally, comparative simulation cases are presented to demonstrate the effectiveness and robustness of the proposed method.</p></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"151 ","pages":"Pages 51-61"},"PeriodicalIF":6.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141281586","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}
ISA transactionsPub Date : 2024-08-01DOI: 10.1016/j.isatra.2024.05.051
{"title":"A periodic-modulation-oriented noise resistant correlation method for industrial fault diagnostics of rotating machinery under the circumstances of limited system signal availability","authors":"","doi":"10.1016/j.isatra.2024.05.051","DOIUrl":"10.1016/j.isatra.2024.05.051","url":null,"abstract":"<div><p>The periodical impulses caused by localized defects of components are the vital characteristic information for fault detection and diagnosis of rotating machines. In recent years, multitudinous spectrum analysis-based signal processing methods have been developed and authenticated as the powerful tools for excavating fault-related repetitive transients from the measured complex signals. Nonetheless, in practice, their applications can be severely confined by the constraints of limited system signal availability and incomplete information extraction under intricate noise interferences. To tackle the aforementioned issues, this paper proposes a periodic-modulation-oriented noise resistant correlation (PMONRC) method for target period detection and fault diagnosis of rotating machinery. Firstly, the envelope of raw signal is obtained via a novel sequential procedure of signal element-wise squaring, spectral Gini index-guided adaptive low-pass filtering, and signal element-wise square root computation, to highlight the modulated wave component that is more likely to be related to the potential fault-induced periods. Subsequently, a series of sub-signals, which can encode the fault-related repetitive information and enhance noise resistance, are constructed utilizing the envelope signal. Based upon the envelope signal and the obtained sub-signals, a weighted envelope noise resistant correlation function can be derived with the assistance of the L-moment ratio-based indicator and Sigmoid transformation. Finally, the specific fault type of the rotating machinery can be identified and affirmed accordingly. The proposed PMONRC method, which is nonparametric and completely adaptive to the signal being processed itself, overcomes the deficiencies of spectral analysis-based approaches, and is applicable for the engineering circumstances of system signal limitation and low signal-to-noise ratio (SNR), possessing immense practical merit. Both simulation analyses and experimental validations profoundly demonstrate that the proposed method is superior to other existing state-of-the-art time-domain correlation methods. Moreover, as an attempt as well as exemplar to apply this method, the PMONRC-based incipient fault diagnostic results of rolling bearing data from the well-known experimental platform PRONOSTIA are presented and discussed as well, to further elucidate the effectiveness and practical engineering significance of the proposed method.</p></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"151 ","pages":"Pages 258-284"},"PeriodicalIF":6.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141294081","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}
ISA transactionsPub Date : 2024-08-01DOI: 10.1016/j.isatra.2024.05.040
{"title":"Research on spatial-temporal synergistic sensor fault diagnosis method for top-blowing furnace","authors":"","doi":"10.1016/j.isatra.2024.05.040","DOIUrl":"10.1016/j.isatra.2024.05.040","url":null,"abstract":"<div><p>Top-blowing furnace systems, characterized by a large number of sensors and harsh working environments, are prone to sensor failures due to factors like component aging and external interference. These failures can significantly impact the system's safe and reliable operation. However, traditional sensor fault diagnosis methods often neglect the exploration of spatial-temporal characteristics and focus solely on learning temporal relationships between sensors, failing to effectively consider their spatial relationships. In this study, we propose a spatial correlation model based on the maximal information-based graph convolutional network (MI-GCN) by constructing a sensor network knowledge graph using maximal mutual information. The MI-GCN leverages the graph convolution mechanism to extract multi-scale spatial features and capture the spatial relationships between sensors. Additionally, we develop a spatial-temporal graph-level prediction model, known as the spatial-temporal graph transformer (STGT), to extract temporal features. By combining the spatial features extracted by the MI-GCN with the temporal features captured by the STGT, accurate predictions can be achieved. Sensor fault diagnosis is conducted by analysing the normalized residuals between the predicted values and the ground truth. Finally, the feasibility and effectiveness of the proposed method are validated using test data from a top-blowing furnace system in the nickel smelting process.</p></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"151 ","pages":"Pages 221-231"},"PeriodicalIF":6.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141261702","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}
ISA transactionsPub Date : 2024-08-01DOI: 10.1016/j.isatra.2024.05.042
{"title":"Zebrafishtracker3D: A 3D skeleton tracking algorithm for multiple zebrafish based on particle matching","authors":"","doi":"10.1016/j.isatra.2024.05.042","DOIUrl":"10.1016/j.isatra.2024.05.042","url":null,"abstract":"<div><p>Zebrafish are considered as model organisms in biological and medical research because of their high degree of homology with human genes. Automatic behavioral analysis of multiple zebrafish based on visual tracking is expected to improve research efficiency. However, vision-based multi-object tracking algorithms often suffer from data loss owing to mutual occlusion. In addition, simply tracking zebrafish as points is not sufficient-more detailed information, which is required for research on zebrafish behavior. In this paper, we propose Zebrafishtracker3D, which utilizes a skeleton stability strategy to reduce detection error caused by frequent overlapping of multiple zebrafish effectively and estimates zebrafish skeletons using head coordinates in the top view. Further, we transform the front- and top-view matching task into an optimization problem and propose a particle-matching method to perform 3D tracking. The robustness of the algorithm with respect to occlusion is estimated on the dataset comprising two and three zebrafish. Experimental results demonstrate that the proposed algorithm exhibits a multiple object tracking accuracy (MOTA) exceeding 90% in the top view and a 3D tracking matching accuracy exceeding 90% in the complex videos with frequent overlapping. It is noteworthy that each instance in the trace saves its skeleton. In addition, Zebrafishtracker3D is applied in the zebrafish courtship experiment, establishes the stability of the method in applications of life science, and proves that the data can be used for behavioral analysis. Zebrafishtracker3D is the first algorithm that realizes 3D skeleton tracking of multiple zebrafish simultaneously.</p></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"151 ","pages":"Pages 363-376"},"PeriodicalIF":6.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141261863","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}
ISA transactionsPub Date : 2024-08-01DOI: 10.1016/j.isatra.2024.05.032
{"title":"Active disturbance rejection control based on a cascade estimator composed of reduced-order and full-order extended state observers","authors":"","doi":"10.1016/j.isatra.2024.05.032","DOIUrl":"10.1016/j.isatra.2024.05.032","url":null,"abstract":"<div><p>This paper presents a pioneering cascade estimator, CRESO, which merges reduced-order and full-order extended state observers (ESO) in a novel manner. CRESO is designed to navigate the trade-off between robustness, estimation accuracy, and noise amplification inherent in active disturbance rejection control (ADRC) schemes. An analysis in the frequency domain substantiates CRESO’s performance and robustness capabilities compared to those of single-level ESO and cascade ESO (CESO). These features are quantified using practical metrics, such as stability margins, sensitivity bandwidth, and estimation error at low frequencies. Additionally, the discussion encompasses the impact of selecting bandwidths for the cascade levels of CRESO on noise suppression. Experimental validation on a synchronous buck converter demonstrates the effectiveness of CRESO-based ADRC against control gain uncertainties, frequency-varying external disturbances, and sensor noise. The results highlight the advantages of the proposed approach over ADRC strategies employing singular ESO, two-level CESO, and two independent ESOs, as evidenced by several quality indices derived from the tracking errors and control signals.</p></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"151 ","pages":"Pages 296-311"},"PeriodicalIF":6.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141136720","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}
ISA transactionsPub Date : 2024-08-01DOI: 10.1016/j.isatra.2024.05.028
{"title":"Joint unknown input observer for descriptor system based on interval observer","authors":"","doi":"10.1016/j.isatra.2024.05.028","DOIUrl":"10.1016/j.isatra.2024.05.028","url":null,"abstract":"<div><p>In this paper, a novel joint unknown input observer (JUIO) is proposed for a class of descriptor systems. The unknown input (UI) to be estimated injects additively into both the state and output equations in a state space model. To the best of our knowledge, only a few contributions in existing work address this problem directly. To begin with, by introducing an auxiliary UI, the original system is transformed into a normal form in which the output is no longer affected by UI. In this way, the negative effect brought by the UI occurring in the output measurement is removed. An interval observer is developed to obtain upper and lower boundary estimates of the output of the reformulated system. After that, an algebraic relationship between the auxiliary UI and the states is established, and a UI reconstruction (UIR) method is developed. Based on the UIR, a JUIO comprising the UIR and a Luenberger-like state observer is developed to achieve asymptotic estimations of the UI and state simultaneously. Verifiable conditions for the existence of the proposed JUIO are given with respect to the original descriptor system. Finally, a simulation example is presented to verify the effectiveness of the proposed method.</p></div>","PeriodicalId":14660,"journal":{"name":"ISA transactions","volume":"151 ","pages":"Pages 153-163"},"PeriodicalIF":6.3,"publicationDate":"2024-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141028060","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}