{"title":"Predictive dq Current Control of an Induction Motor","authors":"M. Costin, C. Lazar","doi":"10.1109/ICSTCC52150.2021.9607241","DOIUrl":"https://doi.org/10.1109/ICSTCC52150.2021.9607241","url":null,"abstract":"In this paper, a predictive control algorithm for the current system of an induction machine (CS-IM) is presented, developed by using the field orientation control (FOC). The CS-IM is modeled in the dq rotor reference frame. By adopting the hypothesis of considering the synchronous angular speed as a known parameter, the CS-IM may be approached by the linear multivariable generalized predictive control (MV-GPC) algorithm. The aim of the paper is to provide a suitable control algorithm that leads to improve the close loop performances of CS-IM. To perform a proper evaluation of the MV-GPC controller, it has been carried out a comparison with the classical linear controllers, which are mainly developed by single-input single-output (SISO) controllers. The obtained results for current tracking have been evaluated by using a performance index and conclude that MV-GPC controller is a usefulness multivariable approach that leads to improve the dynamic performances.","PeriodicalId":413433,"journal":{"name":"2021 25th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125837795","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"The main benefits-risks of adopting Robotic Process Automation in Big Four Companies from Romania. A Case Study.","authors":"Banta Viorel Costin, Anca Tănasie, D. Cojocaru","doi":"10.1109/ICSTCC52150.2021.9607188","DOIUrl":"https://doi.org/10.1109/ICSTCC52150.2021.9607188","url":null,"abstract":"The last period has changed a lot the way of thinking of the companies that use ERP type systems as - core systems. The worldwide pandemic, in the last year, has greatly accelerated the adoption of new technologies - in this case - RPA - Robotic Process Automation. Thus, more and more companies have adopted the part of re-modeling existing economic processes, introducing steps that can be performed by software robots. Perhaps, this has been originally thought to replace human labor, but in some places, it did not prove as such, so the authors of this article conducted research aiming to highlight several critical factors residing in the implementation projects, which finally highlighted a record of the benefits but also of the risks that these companies decided to assume. The case studies were carried out in the first 4 companies in Romania (subsidiaries of some external companies), aiming to point out how many steps could be automated, for two frequently used economic processes - O2C (order-to-cash: sales division) and P2P (procure-to-pay: procurement division), using UiPath tools (development of the bots), near to the ERP - SAP computer system, and if the use of automation was useful.","PeriodicalId":413433,"journal":{"name":"2021 25th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122326736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A comprehensive simulation framework for modeling a dynamic multi-agent emergency system","authors":"Adrian-Costin Tundrea","doi":"10.1109/ICSTCC52150.2021.9607235","DOIUrl":"https://doi.org/10.1109/ICSTCC52150.2021.9607235","url":null,"abstract":"The software world is in the midst of a computing paradigm shift, transitioning on-premise software to the efficiency and almost endless scalability offered by cloud solutions. While some simulation models are by design better prepared than others for this transition, relatively little progress has been done on the architectural side of software to fully harness the new possibilities offered by cloud computing. This paper aims to review the various simulation models with emphasis on agent-based ones, highlighting their advantages and present a short review of state-of-art software implementing those models. Finally, this paper will focus on an innovative way of applying an agent-based model to a variety of emergency simulations, while showcasing a lightweight and flexible software architecture capable of distributing workload in a cloud-based environment.","PeriodicalId":413433,"journal":{"name":"2021 25th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126205876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Global Sensitivity Analysis for the input parameters of a Perfusion Bioreactor System in Tissue Engineering","authors":"I. Nascu, Taofei Chen, Wenli Du, I. Nascu","doi":"10.1109/ICSTCC52150.2021.9607196","DOIUrl":"https://doi.org/10.1109/ICSTCC52150.2021.9607196","url":null,"abstract":"This paper uses the method of high-dimensional model representation (HDMR) to present a global sensitivity analysis and simulations of a perfusion bioreactor operation. This method enables the analysis of the input–output relationships of a complex model containing a high dimensional input space focusing on the parameters that could be used in the control of a perfusion bioreactor process. The model used in this work is a comprehensive mathematical model for diffusion and convection for a perfusion bioreactor, which is combined with cell growth kinetics that describes the spatio-temporal glucose concentration, oxygen concentration, lactate concentration and cell density evolution in a 3D polymeric scaffold. To investigate the important features of the perfusion bioreactor process as well as possible factors underlying qualitative discrepancies a quantitative analysis of the complex kinetic mechanisms using recent development of advanced mathematical approaches to global sensitivity and uncertainty analysis through HDMR is used. Assessing the effect of the model inputs on the model’s predicted outputs is an important step especially when trying to develop control strategies","PeriodicalId":413433,"journal":{"name":"2021 25th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120976662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Stoean, R. Stoean, M. Hotoleanu, D. Iliescu, C. Patru, R. Nagy
{"title":"An assessment of the usefulness of image pre-processing for the classification of first trimester fetal heart ultrasound using convolutional neural networks","authors":"C. Stoean, R. Stoean, M. Hotoleanu, D. Iliescu, C. Patru, R. Nagy","doi":"10.1109/ICSTCC52150.2021.9606852","DOIUrl":"https://doi.org/10.1109/ICSTCC52150.2021.9606852","url":null,"abstract":"Convolutional neural networks have obtained note-worthy results in various fields of medicine, giving an objective, virtual second opinion to the physicians concerning the presence of disease indicators. Usually, it is believed that the performance of the model arises when it can concentrate on the exact region of interest of the examination within the entire larger scan available. A prior processing of the medical images is thus usually helpful towards a better prediction by eliminating background information that is not of interest to the classification process. But what if this information is actually helpful when the problem needs the reference to an extra Other class that represents the samples containing nothing important from the detection point of view? Or what if the processing itself leads to artefacts misleading the model? In this respect, the paper investigates the effect of an image processing step to precede the deep learning model. The medical problem treated regards the identification of the four principal views in first trimester fetal echocardiography scans towards an early indication of possible congenital heart defects.","PeriodicalId":413433,"journal":{"name":"2021 25th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124106910","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sparse Filtering Under Non-Random Bounded Exogenous Disturbances","authors":"M. Khlebnikov","doi":"10.1109/ICSTCC52150.2021.9607287","DOIUrl":"https://doi.org/10.1109/ICSTCC52150.2021.9607287","url":null,"abstract":"We propose a simple and universal approach to the solution of a sparse filtering problem via use of a reduced number of outputs under arbitrary bounded exogenous disturbances using an observer. The approach is based on the LMI technique and the method of invariant ellipsoids. Application of this concept made it possible to reduce the original problem to SDP that can be easily solved numerically. The approach is simple and easy to implement and equally covers both continuous- and discrete-time cases.","PeriodicalId":413433,"journal":{"name":"2021 25th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"136 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115907917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fusing Convolutional Neural Networks with Segmentation for Brain Tumor Classification","authors":"L. Ferariu, Emil-Daniel Neculau","doi":"10.1109/ICSTCC52150.2021.9607260","DOIUrl":"https://doi.org/10.1109/ICSTCC52150.2021.9607260","url":null,"abstract":"Early diagnosis is crucial for treating cerebral cancer. Significant progress has been made using noninvasive imaging methods combined with convolutional neural networks (CNN). Primarily, CNNs can extract relevant features from medical images, without requesting preliminary segmentations. However, additional ready-to-use information can be helpful for improving the accuracy of medical diagnostics. This paper compares different brain tumor classification methods based on CNNs. The proposed configurations consider an input-level fusion with two types of segmentation methods. One map is obtained via region-growing technique, from super-pixel partition; its role is to provide a ready-to-use simplified layout of the MRI scan. The other segmented image is a Class Activation Map (CAM), which incorporates the most relevant knowledge gained by a previously trained CNN. The experimental results indicate improved classification performance for the configurations that combine the original MRI scan with the segmented images into the input neural arrays.","PeriodicalId":413433,"journal":{"name":"2021 25th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127530662","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Linearized Model Identification for Quadcopter Vertical Translation Dynamics","authors":"V. Alexandrov, I. Rezkov, D. V. Shatov","doi":"10.1109/ICSTCC52150.2021.9607314","DOIUrl":"https://doi.org/10.1109/ICSTCC52150.2021.9607314","url":null,"abstract":"Frequency domain identification can be used to find the linearized model of a nonlinear system for an operating point. The methods to identify transfer function coefficients from estimates of the frequency response function obtained from experimental data are studied using the example of a quadcopter vertical translation dynamics. Continuous and discrete time models are identified via linear least squares approach and optimization procedures.","PeriodicalId":413433,"journal":{"name":"2021 25th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"399 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124243315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Canonical form observers for non-integrable nonlinear single-output systems using flat inputs and dynamic compensators","authors":"Klemens Fritzsche, Yuhang Guo, K. Röbenack","doi":"10.1109/ICSTCC52150.2021.9607105","DOIUrl":"https://doi.org/10.1109/ICSTCC52150.2021.9607105","url":null,"abstract":"We investigate the design of observers for non-integrable nonlinear single-output systems, i.e., systems that cannot be transformed into observer canonical form. Inspired by flat input based methods, we use dynamic compensation to alter the original dynamics such that the modified system can be transformed into observer canonical form. We construct a canonical form observer for the modified system. Utilizing the compensators, we can then deduce the state of the original dynamics. The method is demonstrated on well-known non-integrable examples.","PeriodicalId":413433,"journal":{"name":"2021 25th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114549521","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Water pipes leak prediction in QWAT databases","authors":"Bogdan Văduva, H. Valean","doi":"10.1109/ICSTCC52150.2021.9607191","DOIUrl":"https://doi.org/10.1109/ICSTCC52150.2021.9607191","url":null,"abstract":"Romanian water supplying companies are involved in a daily activity that consumes resources, both hardware and man power. That activity(ies), is finding hardware failures (mostly leaks) and repairing them. Such activities are not specific to Romanian companies but to all water supplying companies in all the countries. Researches in this field had been done before and highlights that companies are better to prevent leaks than to stop them, but to prevent leaks they need a way of predicting them prior their occurrence. This study wants to present a way of predicting leaks in open source databases specific for water supplying companies. The article focuses on preparing the QWAT (Acronym from Quantum GIS Water Plugin) data to be neural network friendly and how to use that data to make predictions. Other purpose of this article is to show that a web-based prediction tool can be built using open source resources.","PeriodicalId":413433,"journal":{"name":"2021 25th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124040325","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}