Pub Date : 2022-10-19DOI: 10.1109/ICSTCC55426.2022.9931791
Amelia Chindrus, D. Copot, C. Caruntu
Continuous manufacturing represents a flow production method in which the processed materials are in continuous movement between the interconnected operating units involved in the production process. This method has been adopted in many industries, e.g., electrical components, automotive or food production due to increased needs and higher quality of the resulting products. Continuous manufacturing is a first step towards transforming industrial processes into cyber-physical systems (CPSs). In case of pharma industry, recent studies revealed the benefits of transforming batch production into continuous manufacturing, related to product quality, lower fabrication costs and reduced production times. Among the advantages of continuous manufacturing, regardless of industry, is an increase in efficiency, enabled by maximum automation through the interconnection of operation units. As such, this paper proposes a control strategy based on Linear Quadratic Regulator (LQR) with Integral action (LQI) for the production of pharmaceutical tablets. Moreover, the control architecture has been extended by using an observer to estimate the unknown states of the system. The simulation results obtained on a Matlab/Simulink-based pilot plant and the performance analysis prove that this method is suitable for the dry granulation process.
{"title":"Continuous Manufacturing using Linear Quadratic Regulator in the Context of Cyber-Physical Systems","authors":"Amelia Chindrus, D. Copot, C. Caruntu","doi":"10.1109/ICSTCC55426.2022.9931791","DOIUrl":"https://doi.org/10.1109/ICSTCC55426.2022.9931791","url":null,"abstract":"Continuous manufacturing represents a flow production method in which the processed materials are in continuous movement between the interconnected operating units involved in the production process. This method has been adopted in many industries, e.g., electrical components, automotive or food production due to increased needs and higher quality of the resulting products. Continuous manufacturing is a first step towards transforming industrial processes into cyber-physical systems (CPSs). In case of pharma industry, recent studies revealed the benefits of transforming batch production into continuous manufacturing, related to product quality, lower fabrication costs and reduced production times. Among the advantages of continuous manufacturing, regardless of industry, is an increase in efficiency, enabled by maximum automation through the interconnection of operation units. As such, this paper proposes a control strategy based on Linear Quadratic Regulator (LQR) with Integral action (LQI) for the production of pharmaceutical tablets. Moreover, the control architecture has been extended by using an observer to estimate the unknown states of the system. The simulation results obtained on a Matlab/Simulink-based pilot plant and the performance analysis prove that this method is suitable for the dry granulation process.","PeriodicalId":220845,"journal":{"name":"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115487502","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}
Pub Date : 2022-10-19DOI: 10.1109/ICSTCC55426.2022.9931890
A. Florea, F. Stoican, C. Buiu, C. Oara
3D/6D pose estimation is a novel research area, part of the larger robotics sensing domain, focused on extracting 3D position and 3D rotation information using affordable hardware such as RGB-D or Stereoscopic depth cameras. Most estimators rely internally on a machine learning model for either the object detection phase or the entire 6D pose estimation loop. Thus, a custom machine learning (ML) model and dataset must be constructed and trained respectively in order to achieve the stated goal. The majority of the 3D/6D pose estimation models focus on standardized datasets so a custom dataset must also be created for each model. This article explores the benefits and challenges of artificially generated datasets on one 3D pose estimation model and the ML model transfer learning process. An accuracy test is conducted using real hardware.
{"title":"3D Pose Estimation of Custom Objects Using Synthetic Datasets","authors":"A. Florea, F. Stoican, C. Buiu, C. Oara","doi":"10.1109/ICSTCC55426.2022.9931890","DOIUrl":"https://doi.org/10.1109/ICSTCC55426.2022.9931890","url":null,"abstract":"3D/6D pose estimation is a novel research area, part of the larger robotics sensing domain, focused on extracting 3D position and 3D rotation information using affordable hardware such as RGB-D or Stereoscopic depth cameras. Most estimators rely internally on a machine learning model for either the object detection phase or the entire 6D pose estimation loop. Thus, a custom machine learning (ML) model and dataset must be constructed and trained respectively in order to achieve the stated goal. The majority of the 3D/6D pose estimation models focus on standardized datasets so a custom dataset must also be created for each model. This article explores the benefits and challenges of artificially generated datasets on one 3D pose estimation model and the ML model transfer learning process. An accuracy test is conducted using real hardware.","PeriodicalId":220845,"journal":{"name":"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124405154","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}
Pub Date : 2022-10-19DOI: 10.1109/ICSTCC55426.2022.9931827
V. Mînzu, Iulian Arama, C. Vlad
This paper proposes a practical method to diminish the computational complexity of the controllers using predictions based on the Evolutionary Algorithm (EA). It is the case of Receding Horizon Control structures whose Controller can integrate an EA to generate the optimal predictions. In a previous paper, the authors proposed the control range adaptation to diminish the computational complexity. An additional technique called control range tuning is proposed in this paper.
{"title":"Predictions based on Evolutionary Algorithms – Implementation Aspects regarding the Control Variables' Domain","authors":"V. Mînzu, Iulian Arama, C. Vlad","doi":"10.1109/ICSTCC55426.2022.9931827","DOIUrl":"https://doi.org/10.1109/ICSTCC55426.2022.9931827","url":null,"abstract":"This paper proposes a practical method to diminish the computational complexity of the controllers using predictions based on the Evolutionary Algorithm (EA). It is the case of Receding Horizon Control structures whose Controller can integrate an EA to generate the optimal predictions. In a previous paper, the authors proposed the control range adaptation to diminish the computational complexity. An additional technique called control range tuning is proposed in this paper.","PeriodicalId":220845,"journal":{"name":"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124808600","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}
Pub Date : 2022-10-19DOI: 10.1109/ICSTCC55426.2022.9931868
Lukas Pröhl, Ricus Husmann, Vinzenz Birr, H. Aschemann
This paper deals with the implementation and an assessment of loop-closing techniques for an EKF-SLAM. Here, especially the minimization of uncertainties of the vehicle pose and of the global map are in the scope of interest. Therefore, different approaches of loop-closing are integrated in the framework of an extended Kalman Filter implementation for the SLAM problem. In particular, the detection of a loop closure as well as its impact on the accuracies of both robot pose and global map will be presented. Experimental results are obtained from a Turtlebot3 robot operating in a lab environment.
{"title":"Investigation of Camera-Based Loop-Closing Techniques for EKF-SLAM","authors":"Lukas Pröhl, Ricus Husmann, Vinzenz Birr, H. Aschemann","doi":"10.1109/ICSTCC55426.2022.9931868","DOIUrl":"https://doi.org/10.1109/ICSTCC55426.2022.9931868","url":null,"abstract":"This paper deals with the implementation and an assessment of loop-closing techniques for an EKF-SLAM. Here, especially the minimization of uncertainties of the vehicle pose and of the global map are in the scope of interest. Therefore, different approaches of loop-closing are integrated in the framework of an extended Kalman Filter implementation for the SLAM problem. In particular, the detection of a loop closure as well as its impact on the accuracies of both robot pose and global map will be presented. Experimental results are obtained from a Turtlebot3 robot operating in a lab environment.","PeriodicalId":220845,"journal":{"name":"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124874332","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}
Pub Date : 2022-10-19DOI: 10.1109/ICSTCC55426.2022.9931814
Alexandru-Costin Băroiu, G. Ene
Still in the inception of Web 3.0, the present study stands as an important incursion into the future of the Internet and displays how different technologies, Social Media and Cryptocurrencies, can influence each other and the world around them in these new, exciting, times. This paper seeks to find if there is a relationship between Twitter Sentiment and Bitcoin price. To this end, data is collected and preprocessed to construct a dataset consisting of two time series, one for Twitter Sentiment regarding Bitcoin and one for Bitcoin Price. The relationship between the two is studied through a Vector Autoregressive model. The results show that each exerts influence on the other. Twitter Sentiment is quicker to absorb the information, while Bitcoin Price takes longer to intake the most recent events. Future avenues of study are identified, with topic analysis of Bitcoin discourse being highlighted due to its potential to unlock new knowledge.
{"title":"Twitter Sentiment and Bitcoin Price – Is there a connection?","authors":"Alexandru-Costin Băroiu, G. Ene","doi":"10.1109/ICSTCC55426.2022.9931814","DOIUrl":"https://doi.org/10.1109/ICSTCC55426.2022.9931814","url":null,"abstract":"Still in the inception of Web 3.0, the present study stands as an important incursion into the future of the Internet and displays how different technologies, Social Media and Cryptocurrencies, can influence each other and the world around them in these new, exciting, times. This paper seeks to find if there is a relationship between Twitter Sentiment and Bitcoin price. To this end, data is collected and preprocessed to construct a dataset consisting of two time series, one for Twitter Sentiment regarding Bitcoin and one for Bitcoin Price. The relationship between the two is studied through a Vector Autoregressive model. The results show that each exerts influence on the other. Twitter Sentiment is quicker to absorb the information, while Bitcoin Price takes longer to intake the most recent events. Future avenues of study are identified, with topic analysis of Bitcoin discourse being highlighted due to its potential to unlock new knowledge.","PeriodicalId":220845,"journal":{"name":"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125148717","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}
Pub Date : 2022-10-19DOI: 10.1109/ICSTCC55426.2022.9931835
J. Hidalgo, H. Meneses, O. Arrieta, R. Vilanova
This paper shows the development process of a web application for desktop and mobile computers, designed to incor-porate a tuning service for PI/PID controllers for processes whose dynamics were identified through a model with a single fractional parameter. Such application relies on a client-server model based on cloud computing, which allows offloading the computation from the restricted resources, and software dependencies in the mobile environment to a remote server in which tuning and simulation are executed in a shorter time. The model to reach such communication in order to achieve optimal performance of the overall system is also presented.
{"title":"Web Application for PI/PID Controllers Tuning Using a Fractional-Order Process Model","authors":"J. Hidalgo, H. Meneses, O. Arrieta, R. Vilanova","doi":"10.1109/ICSTCC55426.2022.9931835","DOIUrl":"https://doi.org/10.1109/ICSTCC55426.2022.9931835","url":null,"abstract":"This paper shows the development process of a web application for desktop and mobile computers, designed to incor-porate a tuning service for PI/PID controllers for processes whose dynamics were identified through a model with a single fractional parameter. Such application relies on a client-server model based on cloud computing, which allows offloading the computation from the restricted resources, and software dependencies in the mobile environment to a remote server in which tuning and simulation are executed in a shorter time. The model to reach such communication in order to achieve optimal performance of the overall system is also presented.","PeriodicalId":220845,"journal":{"name":"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"475 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123392105","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}
Pub Date : 2022-10-19DOI: 10.1109/ICSTCC55426.2022.9931829
N. Haloui, M. Abbas-Turki, T. Rodet
This contribution presents a methodology to detect material deterioration in periodic systems using model identification. To detect the failure, the relation between the model's parameters and failure's characteristics are analyzed. Thus, a robust and an efficient algorithm is proposed to detect failures. The algorithm leads to a residual parameter to identify anomaly, which allows an intuitive failure detection. The convexity of criterion, the variation of parameters within interval and the residual's expression allow to use optimisation algorithm or step evaluation of criterion, where the last procedure allows to simplify the implementation of the algorithm and aims to online utilization. The proposed approach is applied to gearbox system, where the classical analysis cannot bring clear information about deterioration. The efficiency of the proposed method is as well proved and the application is used to benchmark the algorithm's parameters.
{"title":"Robust fault detection for gearbox failure","authors":"N. Haloui, M. Abbas-Turki, T. Rodet","doi":"10.1109/ICSTCC55426.2022.9931829","DOIUrl":"https://doi.org/10.1109/ICSTCC55426.2022.9931829","url":null,"abstract":"This contribution presents a methodology to detect material deterioration in periodic systems using model identification. To detect the failure, the relation between the model's parameters and failure's characteristics are analyzed. Thus, a robust and an efficient algorithm is proposed to detect failures. The algorithm leads to a residual parameter to identify anomaly, which allows an intuitive failure detection. The convexity of criterion, the variation of parameters within interval and the residual's expression allow to use optimisation algorithm or step evaluation of criterion, where the last procedure allows to simplify the implementation of the algorithm and aims to online utilization. The proposed approach is applied to gearbox system, where the classical analysis cannot bring clear information about deterioration. The efficiency of the proposed method is as well proved and the application is used to benchmark the algorithm's parameters.","PeriodicalId":220845,"journal":{"name":"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116512526","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}
Pub Date : 2022-10-19DOI: 10.1109/ICSTCC55426.2022.9931777
I. Santín, R. Vilanova, C. Pedret, M. Meneses, O. Arrieta
Wastewater treatment plants are necessary to improve the quality of wastewater before it is discharged into the receiving environment, but they have the disadvantage of generating nitrous oxide emissions during the biological treatment, which is a potent Greenhouse Gas (GHG). This is a serious drawback as the reduction of greenhouse gas emissions due to anthropogenic causes is one of the main challenges to face with reference to climate change effects. In this paper we examine one potential way to reduce nitrous oxide emissions by reducing the dissolved oxygen to minimum levels. To achieve this objective, the present work proposes to use the internal recirculation flow rate of the biological treatment. This is a rather forgotten manipulated variable that, as it is intended to show, may have potential side effects to complement already existing control actions. Therefore, this additional regulation is added to a usual control strategy in wastewater treatment plants, which achieves satisfactory results in water quality and in operational costs but with high nitrous oxide emissions. The Benchmark Simulation Model No.2 Gas (BSM2G) is used as working scenario, which includes the two main nitrous oxide emission pathways: heterotrophic denitrification and ammonia oxidizing bacteria denitrification.
{"title":"Complementary Control Actions for Greenhouse Gas Emissions Reduction in Wastewater Treatment Plant Operation","authors":"I. Santín, R. Vilanova, C. Pedret, M. Meneses, O. Arrieta","doi":"10.1109/ICSTCC55426.2022.9931777","DOIUrl":"https://doi.org/10.1109/ICSTCC55426.2022.9931777","url":null,"abstract":"Wastewater treatment plants are necessary to improve the quality of wastewater before it is discharged into the receiving environment, but they have the disadvantage of generating nitrous oxide emissions during the biological treatment, which is a potent Greenhouse Gas (GHG). This is a serious drawback as the reduction of greenhouse gas emissions due to anthropogenic causes is one of the main challenges to face with reference to climate change effects. In this paper we examine one potential way to reduce nitrous oxide emissions by reducing the dissolved oxygen to minimum levels. To achieve this objective, the present work proposes to use the internal recirculation flow rate of the biological treatment. This is a rather forgotten manipulated variable that, as it is intended to show, may have potential side effects to complement already existing control actions. Therefore, this additional regulation is added to a usual control strategy in wastewater treatment plants, which achieves satisfactory results in water quality and in operational costs but with high nitrous oxide emissions. The Benchmark Simulation Model No.2 Gas (BSM2G) is used as working scenario, which includes the two main nitrous oxide emission pathways: heterotrophic denitrification and ammonia oxidizing bacteria denitrification.","PeriodicalId":220845,"journal":{"name":"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114712456","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}
Pub Date : 2022-10-19DOI: 10.1109/ICSTCC55426.2022.9931779
Mohammad Zain, A. H. Ali, S. M. Hamza, S. J. Arif
Studying and analysing earthquake signals, in some depth, is an important aspect of engineering, geophysics, and disaster management. At present seismic vibration analysis involves large-scale setups that require a considerable investment. Shake tables, underwater explosions, colliding large masses with shock absorbers, are all expensive, complex, and non-mobile processes of generating seismic vibrations. In the backdrop of the above, the purpose of the present study is rather modest, viz. to examine and suggest a viable and reliable low-cost technology with a portable method for producing seismic vibrations and foreshocks. To achieve the objective, a novel algorithm is devised, tested, and implemented employing a synchro, stepper motor, and microcontroller. The results were verified by using a technique that uses changes in the rotating magnetic field to measure velocity with high accuracy. The findings from the aforesaid method are quite accurate in comparison to the reference data. The analysis of the measurements performed in the frequency domain with MATLAB is in good concurrence with the benchmarked data. The present study provides an alternative and more economical method to analyse shockwaves and any seismic activity that takes place in the surrounding areas.
{"title":"Microcontroller Based Low Cost Seismic Vibration Generating System","authors":"Mohammad Zain, A. H. Ali, S. M. Hamza, S. J. Arif","doi":"10.1109/ICSTCC55426.2022.9931779","DOIUrl":"https://doi.org/10.1109/ICSTCC55426.2022.9931779","url":null,"abstract":"Studying and analysing earthquake signals, in some depth, is an important aspect of engineering, geophysics, and disaster management. At present seismic vibration analysis involves large-scale setups that require a considerable investment. Shake tables, underwater explosions, colliding large masses with shock absorbers, are all expensive, complex, and non-mobile processes of generating seismic vibrations. In the backdrop of the above, the purpose of the present study is rather modest, viz. to examine and suggest a viable and reliable low-cost technology with a portable method for producing seismic vibrations and foreshocks. To achieve the objective, a novel algorithm is devised, tested, and implemented employing a synchro, stepper motor, and microcontroller. The results were verified by using a technique that uses changes in the rotating magnetic field to measure velocity with high accuracy. The findings from the aforesaid method are quite accurate in comparison to the reference data. The analysis of the measurements performed in the frequency domain with MATLAB is in good concurrence with the benchmarked data. The present study provides an alternative and more economical method to analyse shockwaves and any seismic activity that takes place in the surrounding areas.","PeriodicalId":220845,"journal":{"name":"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131797257","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}
Pub Date : 2022-10-19DOI: 10.1109/ICSTCC55426.2022.9931784
Sabin Rosioru, G. Stamatescu, Iulia Stamatescu, I. Fagarasan, D. Popescu
Advanced manufacturing systems increasingly rely on intelligent algorithms to discriminate, model and predict system behaviours that lead to increased productivity. Edge intelligence allows the industrial systems to collect, compute and act based on process data while reducing the latency and cost associated to an hierarchical control system in which complex decisions are generated in the upper layers of the automation hierarchy. Greater local computing capabilities allow the online operation of such algorithms while accounting for increased performance requirements and lower sampling periods of the control loops. In this work we present the concept of a cognitive robotic cell that collects, stores and processes data in situ for enabling the control of a robotic arm in a production setting. The main features that characterise the robotic cell are embedded computing, open interfaces, and standards-based industrial communication with hardware peripherals and digital twin models for validation. An application of part classification is presented that uses the YOLOv4 image processing algorithm for real-time and online assessment that guides the control of an ABB IRB120C robotic arm. Results illustrate the feasibility and robustness of the approach in a real application. Quantitative evaluation underlines the performance of the implemented system.
{"title":"Deep Learning based Parts Classification in a Cognitive Robotic Cell System","authors":"Sabin Rosioru, G. Stamatescu, Iulia Stamatescu, I. Fagarasan, D. Popescu","doi":"10.1109/ICSTCC55426.2022.9931784","DOIUrl":"https://doi.org/10.1109/ICSTCC55426.2022.9931784","url":null,"abstract":"Advanced manufacturing systems increasingly rely on intelligent algorithms to discriminate, model and predict system behaviours that lead to increased productivity. Edge intelligence allows the industrial systems to collect, compute and act based on process data while reducing the latency and cost associated to an hierarchical control system in which complex decisions are generated in the upper layers of the automation hierarchy. Greater local computing capabilities allow the online operation of such algorithms while accounting for increased performance requirements and lower sampling periods of the control loops. In this work we present the concept of a cognitive robotic cell that collects, stores and processes data in situ for enabling the control of a robotic arm in a production setting. The main features that characterise the robotic cell are embedded computing, open interfaces, and standards-based industrial communication with hardware peripherals and digital twin models for validation. An application of part classification is presented that uses the YOLOv4 image processing algorithm for real-time and online assessment that guides the control of an ABB IRB120C robotic arm. Results illustrate the feasibility and robustness of the approach in a real application. Quantitative evaluation underlines the performance of the implemented system.","PeriodicalId":220845,"journal":{"name":"2022 26th International Conference on System Theory, Control and Computing (ICSTCC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115460286","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}
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