Control Engineering and Applied Informatics最新文献_第2页

Extension of the clustering identification by extending the Density Based Spatial Clustering of Applications with Noise approach to Multi-Input Multi-Output Piece Wise Affine systems: Application to an industrial robot 多输入多输出片仿射系统中基于噪声的密度空间聚类应用的聚类识别扩展:在工业机器人上的应用

4区计算机科学

Control Engineering and Applied Informatics Pub Date : 2023-06-28 DOI: 10.61416/ceai.v25i2.8523

Zeineb Lassoued, Kamel Abderrahim

{"title":"Extension of the clustering identification by extending the Density Based Spatial Clustering of Applications with Noise approach to Multi-Input Multi-Output Piece Wise Affine systems: Application to an industrial robot","authors":"Zeineb Lassoued, Kamel Abderrahim","doi":"10.61416/ceai.v25i2.8523","DOIUrl":"https://doi.org/10.61416/ceai.v25i2.8523","url":null,"abstract":"In this paper the problem of clustering based identificationof a Multi-Input Multi-Output (MIMO) PieceWise Affinesystems (PWA) is considered. This approach, originallydesigned for systems with a Multiple-Input Single-Output(MISO) structure, is carried out by three main steps whichare data clustering, parameters vectors estimation and regionscomputing. Data clustering is the most important stepbecause the two other steps depend on the results given bythe used clustering algorithm. In case of MIMO PWA systems,we should cluster matrices of parametres which areconsidered high dimensionnal data. However, most of theconventional clustering algorithms do not work well in termsof effectiveness and efficiency since the similarity assessmentwhich is based on the distances between objects is fruitlessin high dimension space. Therefore, we propose an extensionof the DBSCAN (Density Based Spatial Clusteringof Applications with Noise) clustering approach for the identificationof MIMO PWA systems. The simulation resultspresented in this paper prouve the performance of the suggestedapproach. An application of the proposed approachto an industrial robot manipulator is also presented in orderto validate the simulation results. DOI: 10.61416/ceai.v25i2.8523","PeriodicalId":50616,"journal":{"name":"Control Engineering and Applied Informatics","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135354263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Study on Fuzzy Sliding Mode Active Disturbance Rejection Control Method for Horizontal Vibration of High-Speed Elevator Car System 高速电梯轿厢系统水平振动的模糊滑模自抗扰控制方法研究

4区计算机科学

Control Engineering and Applied Informatics Pub Date : 2023-06-28 DOI: 10.61416/ceai.v25i2.8336

Qinghua Ge, Lulu Zhang, Hua Li, Qin He, Ruijun Zhang

{"title":"Study on Fuzzy Sliding Mode Active Disturbance Rejection Control Method for Horizontal Vibration of High-Speed Elevator Car System","authors":"Qinghua Ge, Lulu Zhang, Hua Li, Qin He, Ruijun Zhang","doi":"10.61416/ceai.v25i2.8336","DOIUrl":"https://doi.org/10.61416/ceai.v25i2.8336","url":null,"abstract":"To effectively control the horizontal vibration of high-speed elevator car system caused by the factors such as the irregularity of the guide rail and the nonlinearity of spring-damping in guide shoes, this paper proposes an active disturbance rejection (ADR) control method based on fuzzy sliding mode. Firstly, considering the nonlinear characteristics of the spring-damping in the guide shoes, the horizontal vibration dynamic model of the elevator car system is established. Then, the guide rail excitation and the linear and nonlinear disturbances of the car are summarized into the total disturbances of the car system, which can be estimated by the designed extended state observer. On this basis, a sliding mode active disturbance rejection (SADR) control is presented, which makes the anti-vibration and anti-disturbance control of the car system highly robust. For the chattering problem caused by sliding mode control, the fuzzy control method is designed to eliminate it, and the fuzzy sliding mode active disturbance rejection (FSADR) control for the horizontal vibration of the car system is further realized. Finally, MATLAB/Simulink is utilized for simulation tests. The simulation results show that, compared with ADR and SMADR, the root mean square value, maximum value and A95 peak value of horizontal vibration acceleration through FSADR are significantly reduced. Therefore, the FSARC control method designed in this paper can effectively suppress the horizontal vibration generated during the operation of high-speed elevators. DOI: 10.61416/ceai.v25i2.8336","PeriodicalId":50616,"journal":{"name":"Control Engineering and Applied Informatics","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135354260","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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 Automaton and Super-Twisting Sliding-Mode Control for Wall Following 一种自动超扭滑模随墙控制方法

4区计算机科学

Control Engineering and Applied Informatics Pub Date : 2023-06-28 DOI: 10.61416/ceai.v25i2.8352

Edgar Martinez, Rafael Murrieta-Cid, Hector Becerra

引用次数: 0

Prediction-based Optimization of Service Capacity with Robotic Process Automation 基于机器人过程自动化的服务能力预测优化

4区计算机科学

Control Engineering and Applied Informatics Pub Date : 2023-06-28 DOI: 10.61416/ceai.v25i2.8439

Radu Florin Negoita, Theodor Borangiu, Silviu Raileanu

{"title":"Prediction-based Optimization of Service Capacity with Robotic Process Automation","authors":"Radu Florin Negoita, Theodor Borangiu, Silviu Raileanu","doi":"10.61416/ceai.v25i2.8439","DOIUrl":"https://doi.org/10.61416/ceai.v25i2.8439","url":null,"abstract":"The research described in this paper concerns the automation of back-office workflows for the capacity management of hospitality services: continuously monitoring clients’ reservations and hotel registrations and automatically updating the decisions that establish optimal staffing levels to assure dependable and accurate services with minimum personnel cost, and maintaining a minimal stable workforce level. The service capacity management workflows connect multiple instances of online reservation and front-office customer registration processes (booking, check-in taxation, check-out invoicing according to the back-office strategy) with a combination of marketing- and operations-oriented back-office processes that: a) best match capacity and demand for quality services, and b) optimize the staffing levels and personnel workshift schedules. These workflows with many operations and complex timing are automated with the Robotic Process Automation (RPA) technology that uses AI techniques for seasonality prediction of confirmed service demand. A case study of optimal hotel staff assignment with RPA using the Blue Prism scheduler is included, and the gains of using RPA solutions are presented. DOI: 10.61416/ceai.v25i2.8439","PeriodicalId":50616,"journal":{"name":"Control Engineering and Applied Informatics","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135354258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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

Efficient Trajectory Planning and Tracking Control for Underactuated Crane 欠驱动起重机的高效轨迹规划与跟踪控制

4区计算机科学

Control Engineering and Applied Informatics Pub Date : 2023-06-28 DOI: 10.61416/ceai.v25i2.8307

Xinyu Long, Mingwei Sun, Zengqiang Chen

引用次数: 0

Supercapacitor module quality prewarning based on the improved whale optimization algorithm and GM (1,1) gray prediction model 基于改进鲸鱼优化算法和GM(1,1)灰色预测模型的超级电容模块质量预警

4区计算机科学

Control Engineering and Applied Informatics Pub Date : 2023-06-28 DOI: 10.61416/ceai.v25i2.8343

Baochen Liu, Xiaobang Sun, Conghao Liu, Jun Xiang

{"title":"Supercapacitor module quality prewarning based on the improved whale optimization algorithm and GM (1,1) gray prediction model","authors":"Baochen Liu, Xiaobang Sun, Conghao Liu, Jun Xiang","doi":"10.61416/ceai.v25i2.8343","DOIUrl":"https://doi.org/10.61416/ceai.v25i2.8343","url":null,"abstract":"This paper proposes an algorithm combining the improved whale optimization algorithm (WOA) and GM (1,1) to predict the number of qualified products in the test batches of supercapacitor modules. Based on this algorithm, a quality prewarning system is developed on LabVIEW software. First, the GM (1,1) gray prediction model is established with the number of qualified products in the test batch as the original sequence, and then a nonlinear iterative parameter is proposed to improve the WOA. The improved WOA is used to optimize the background value sequence in the GM (1,1) gray prediction model, to obtain the optimal prediction algorithm. Then, on the LabVIEW software platform, the simulation of the GM (1,1) gray prediction model, the algorithm combining WOA and GM (1,1) and the algorithm combining the improved WOA and GM (1,1) are carried out for fifty groups of original data series. Taking one group of simulation data results as an example, the relative error of the prediction value of the algorithm combining the improved WOA and GM (1,1) is 0.0004%, which is better than 0.0112% of the algorithm combining the WOA and GM (1,1) and 1.5429% of the GM (1,1) gray prediction model. Finally, the quality prewarning system of the supercapacitor module is developed by using LabVIEW software, which provides a more accurate quality prewarning function for the test process of the supercapacitor module. DOI: 10.61416/ceai.v25i2.8343","PeriodicalId":50616,"journal":{"name":"Control Engineering and Applied Informatics","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135354261","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"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