{"title":"Maximizing the Efficiency of Automation Solutions with Automation 360: Approaches for Developing Subtasks and Retry Framework","authors":"Sai Madhur Potturu","doi":"10.4236/ica.2023.142002","DOIUrl":"https://doi.org/10.4236/ica.2023.142002","url":null,"abstract":"","PeriodicalId":62904,"journal":{"name":"智能控制与自动化(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70627245","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":"Data-Driven Model Identification and Control of the Inertial Systems","authors":"I. Cojuhari","doi":"10.4236/ica.2023.141001","DOIUrl":"https://doi.org/10.4236/ica.2023.141001","url":null,"abstract":"","PeriodicalId":62904,"journal":{"name":"智能控制与自动化(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70627350","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":"Blockchain-Based Islamic Marriage Certification with the Supremacy of Web 3.0","authors":"Md. Al-Sajiduzzaman Akand, Sarwar Azmain Reza, Amatul Bushra Akhi","doi":"10.4236/ica.2022.134004","DOIUrl":"https://doi.org/10.4236/ica.2022.134004","url":null,"abstract":"","PeriodicalId":62904,"journal":{"name":"智能控制与自动化(英文)","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70627141","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":"Artificial Intelligence Trends and Ethics: Issues and Alternatives for Investors","authors":"Yoser Gadhoum","doi":"10.4236/ica.2022.131001","DOIUrl":"https://doi.org/10.4236/ica.2022.131001","url":null,"abstract":"","PeriodicalId":62904,"journal":{"name":"智能控制与自动化(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70627288","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}
Iterative Learning Control is an effective way of controlling the errors which act directly on the repetitive system. The stability of the system is the main objective in designing. The Small Gain Theorem is used in the design process of State Feedback ILC. The feedback controller along with the Iterative Learning Control adds an advantage in producing a system with minimal error. The past error and current error feedback Iterative control system are studied with reference to the region of disturbance at the output. This paper mainly focuses on comparing the region of disturbance at the output end. The past error feed forward and current error feedback systems are developed on the singular values. Hence, we use the singular values to set an output disturbance limit for the past error and current error feedback ILC system. Thus, we obtain a result of past error feed forward performing better than the current error feedback system. This implies greater region of disturbance suppression to past error feed forward than the other.
{"title":"Using Singular Value to Set Output Disturbance Limits to Feedback ILC Control","authors":"Rashid Alzuabi, A. Alotaibi, Humoud A. Alqattan","doi":"10.4236/ica.2022.132002","DOIUrl":"https://doi.org/10.4236/ica.2022.132002","url":null,"abstract":"Iterative Learning Control is an effective way of controlling the errors which act directly on the repetitive system. The stability of the system is the main objective in designing. The Small Gain Theorem is used in the design process of State Feedback ILC. The feedback controller along with the Iterative Learning Control adds an advantage in producing a system with minimal error. The past error and current error feedback Iterative control system are studied with reference to the region of disturbance at the output. This paper mainly focuses on comparing the region of disturbance at the output end. The past error feed forward and current error feedback systems are developed on the singular values. Hence, we use the singular values to set an output disturbance limit for the past error and current error feedback ILC system. Thus, we obtain a result of past error feed forward performing better than the current error feedback system. This implies greater region of disturbance suppression to past error feed forward than the other.","PeriodicalId":62904,"journal":{"name":"智能控制与自动化(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70626989","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}
Iterative learning control is a controlling tool developed to overcome periodic disturbances acting on repetitive systems. State-feedback ILC controller was designed based on the use of the small gain theorem. Stability conditions were reported in the case of past error and current error feedback schemes based on Singular values. Disturbances acting on the load of the system were reported for the case of past error feedforward only which kept the investigation of the current error feedback as an open question. This paper develops a comparison between the past error feedforward and current error feedback schemes disturbance conditions in singular values. As a result, the conditions found highly support the use of the past error over the current error feedback.
{"title":"Load Disturbance Conditions for Current Error Feedback and Past Error Feedforward State-Feedback Iterative Learning Control","authors":"A. Alotaibi, Asmaa Alkandri, M. A. Alsubaie","doi":"10.4236/ICA.2021.122004","DOIUrl":"https://doi.org/10.4236/ICA.2021.122004","url":null,"abstract":"Iterative \u0000learning control is a controlling tool developed to overcome periodic \u0000disturbances acting on repetitive systems. State-feedback ILC controller was \u0000designed based on the use of the small gain theorem. Stability conditions were \u0000reported in the case of past error and current error feedback schemes based on \u0000Singular values. Disturbances acting on the load of the system were reported for the case of \u0000past error feedforward only which kept the investigation of the current error \u0000feedback as an open question. This paper develops a comparison between the past \u0000error feedforward and current error feedback schemes disturbance conditions in \u0000singular values. As a result, the conditions found highly support the use of \u0000the past error over the current error feedback.","PeriodicalId":62904,"journal":{"name":"智能控制与自动化(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49548617","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}
The purpose of this review is to apply geometric frameworks in identification problems. In contrast to the qualitative theory of dynamical systems (DSQT), the chaos and catastrophes, researches on the application of geometric frameworks have not been performed in identification problems. The direct transfer of DSQT ideas is inefficient through the peculiarities of identification systems. In this paper, the attempt is made based on the latest researches in this field. A methodology for the synthesis of geometric frameworks (GF) is proposed, which reflects features of nonlinear systems. Methods based on GF analysis are developed for the decision-making on properties and structure of nonlinear systems. The problem solution of structural identifiability is obtained for nonlinear systems under uncertainty.
{"title":"Geometrical Frameworks in Identification Problem","authors":"N. Karabutov","doi":"10.4236/ICA.2021.122002","DOIUrl":"https://doi.org/10.4236/ICA.2021.122002","url":null,"abstract":"The purpose of this review \u0000is to apply geometric frameworks in identification problems. In contrast to the \u0000qualitative theory of dynamical systems (DSQT), the chaos and catastrophes, \u0000researches on the application of geometric frameworks have not been performed in \u0000identification problems. The direct transfer of DSQT ideas is inefficient through \u0000the peculiarities of identification systems. In this paper, the attempt is made based on the \u0000latest researches in this field. A methodology for the synthesis of geometric \u0000frameworks (GF) is proposed, which reflects \u0000features of nonlinear systems. Methods based on GF analysis are developed for the \u0000decision-making on properties and structure of nonlinear systems. The problem \u0000solution of structural identifiability is obtained for nonlinear systems under uncertainty.","PeriodicalId":62904,"journal":{"name":"智能控制与自动化(英文)","volume":"12 1","pages":"17-43"},"PeriodicalIF":0.0,"publicationDate":"2021-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49620524","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}
In the last decade, a few valuable types of research have been conducted to discriminate fractured zones from non-fractured ones. In this paper, petrophysical and image logs of eight wells were utilized to detect fractured zones. Decision tree, random forest, support vector machine, and deep learning were four classifiers applied over petrophysical logs and image logs for both training and testing. The output of classifiers was fused by ordered weighted averaging data fusion to achieve more reliable, accurate, and general results. Accuracy of close to 99% has been achieved. This study reports a significant improvement compared to the existing work that has an accuracy of close to 80%.
{"title":"Applied Machine Learning Methods for Detecting Fractured Zones by Using Petrophysical Logs","authors":"H. Azizi, Hassanzadeh Reza","doi":"10.4236/ICA.2021.122003","DOIUrl":"https://doi.org/10.4236/ICA.2021.122003","url":null,"abstract":"In the last decade, a few \u0000valuable types of research have been conducted to discriminate fractured zones \u0000from non-fractured ones. In this paper, petrophysical and image logs of eight \u0000wells were utilized to detect fractured zones. Decision tree, random forest, \u0000support vector machine, and deep learning were four classifiers applied over \u0000petrophysical logs and image logs for both training and testing. The output of \u0000classifiers was fused by ordered weighted averaging data fusion to achieve more \u0000reliable, accurate, and general results. Accuracy of close to 99% has been \u0000achieved. This study reports a significant improvement compared to the existing \u0000work that has an accuracy of close to 80%.","PeriodicalId":62904,"journal":{"name":"智能控制与自动化(英文)","volume":"12 1","pages":"44-64"},"PeriodicalIF":0.0,"publicationDate":"2021-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46620475","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":"Automated Smart Utilization of Background Lights and Daylight for Green Building Efficient and Economic Indoor Lighting Intensity Control","authors":"Muhammad M. A. S. Mahmoud","doi":"10.4236/ICA.2021.121001","DOIUrl":"https://doi.org/10.4236/ICA.2021.121001","url":null,"abstract":"","PeriodicalId":62904,"journal":{"name":"智能控制与自动化(英文)","volume":"69 1","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70626448","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}
Nizar J. Alkhateeb, H. Ebraheem, Ebraheem Sultan, Bassam M. Alrahsed
{"title":"Adaptive Backstepping Compensation of Drives with Sandwiched Deadzone Nonlinearity","authors":"Nizar J. Alkhateeb, H. Ebraheem, Ebraheem Sultan, Bassam M. Alrahsed","doi":"10.4236/ica.2021.123005","DOIUrl":"https://doi.org/10.4236/ica.2021.123005","url":null,"abstract":"","PeriodicalId":62904,"journal":{"name":"智能控制与自动化(英文)","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"70626582","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：