{"title":"A New Particle Swarm Optimization with Bat Algorithm Parameter-Based MPPT for Photovoltaic Systems under Partial Shading Conditions","authors":"M. Alshareef","doi":"10.24846/v31i4y202206","DOIUrl":"https://doi.org/10.24846/v31i4y202206","url":null,"abstract":"","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43700618","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}
Aurimas Petrovas, R. Baušys, E. Zavadskas, F. Smarandache
{"title":"Generation of Creative Game Scene Patterns by the Neutrosophic Genetic CoCoSo Method","authors":"Aurimas Petrovas, R. Baušys, E. Zavadskas, F. Smarandache","doi":"10.24846/v31i4y202201","DOIUrl":"https://doi.org/10.24846/v31i4y202201","url":null,"abstract":"","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43195415","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}
M. Sarfraz, Zhixiao Ye, D. Banciu, Florin Dragan, L. Ivașcu
{"title":"Intertwining Digitalization and Sustainable Performance via the Mediating Role of Digital Transformation and the Moderating Role of FinTech Behavior Adoption","authors":"M. Sarfraz, Zhixiao Ye, D. Banciu, Florin Dragan, L. Ivașcu","doi":"10.24846/v31i4y202204","DOIUrl":"https://doi.org/10.24846/v31i4y202204","url":null,"abstract":"","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44232339","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}
{"title":"Optimization of Multimodal Trait Prediction Using Particle Swarm Optimization","authors":"Milić Vukojičić, M. Veinovic","doi":"10.24846/v31i4y202203","DOIUrl":"https://doi.org/10.24846/v31i4y202203","url":null,"abstract":"","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":"127 3-4","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41297882","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}
{"title":"HBSBoost: A Hybrid Balancing Technique for Defaulting Enterprise Recognition","authors":"Marui Du, Zuoquan Zhang","doi":"10.24846/v31i4y202207","DOIUrl":"https://doi.org/10.24846/v31i4y202207","url":null,"abstract":"","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48712345","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}
{"title":"An Optimized Method for Solving Membership-based Neutrosophic Linear Programming Problems","authors":"A. Nafei, C. Huang, S. Azizi, Shuanfa Chen","doi":"10.24846/v31i4y202205","DOIUrl":"https://doi.org/10.24846/v31i4y202205","url":null,"abstract":"","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46553713","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}
Ouail Mjahed, Salah El Hadaj, E. E. El Guarmah, Soukaina Mjahed
: Recently, in order to optimize artificial neural networks (ANNs), several bio-inspired metaheuristic algorithms have been successfully applied. Moreover, these hybrid ANNs were operated using no more than two or three metaheuristic algorithms at a time. Additionally, the classification field is so rich that some issues were not sufficiently addressed. The main contribution of this paper is related to the use of several ANN hybridizations at the same time, while taking into account the datasets for which the ANNs or their hybridizations have been rarely explored. Thus, seven hybridized ANNs with bio-inspired metaheuristic algorithms such as particle swarm optimization (PSO-ANN), genetic algorithm (GA-ANN), differential evolution (DE-ANN), cultural algorithm (CA-ANN), harmony search (HS-ANN), black hole algorithm (BH- ANN) and ant lion optimizer (ALO-ANN) were considered for classifying four kinds of datasets. After a back-propagation neural network (BPNN) was designed, the connection weights and biases of neurons were optimized by using the seven metaheuristic algorithms mentioned above. The four selected data types belong to different domains and differ with regard to the number of classes, variables and examples. As performance measurement is concerned; the efficiencies, purities and F-measure are analysed. For all simulation runs, it can be noticed that metaheuristic algorithms were able to reach optimal efficiencies and that all the PSO-ANN-based networks obtained higher values for efficiency. For this analysis, the dependence of the obtained results on certain metaheuristic parameters was taken into account.
{"title":"Bio-Inspired Hybridization of Artificial Neural Networks for Various Classification Tasks","authors":"Ouail Mjahed, Salah El Hadaj, E. E. El Guarmah, Soukaina Mjahed","doi":"10.24846/v31i3y202202","DOIUrl":"https://doi.org/10.24846/v31i3y202202","url":null,"abstract":": Recently, in order to optimize artificial neural networks (ANNs), several bio-inspired metaheuristic algorithms have been successfully applied. Moreover, these hybrid ANNs were operated using no more than two or three metaheuristic algorithms at a time. Additionally, the classification field is so rich that some issues were not sufficiently addressed. The main contribution of this paper is related to the use of several ANN hybridizations at the same time, while taking into account the datasets for which the ANNs or their hybridizations have been rarely explored. Thus, seven hybridized ANNs with bio-inspired metaheuristic algorithms such as particle swarm optimization (PSO-ANN), genetic algorithm (GA-ANN), differential evolution (DE-ANN), cultural algorithm (CA-ANN), harmony search (HS-ANN), black hole algorithm (BH- ANN) and ant lion optimizer (ALO-ANN) were considered for classifying four kinds of datasets. After a back-propagation neural network (BPNN) was designed, the connection weights and biases of neurons were optimized by using the seven metaheuristic algorithms mentioned above. The four selected data types belong to different domains and differ with regard to the number of classes, variables and examples. As performance measurement is concerned; the efficiencies, purities and F-measure are analysed. For all simulation runs, it can be noticed that metaheuristic algorithms were able to reach optimal efficiencies and that all the PSO-ANN-based networks obtained higher values for efficiency. For this analysis, the dependence of the obtained results on certain metaheuristic parameters was taken into account.","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46522841","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}
M. Asad, J. Gu, U. Farooq, V. Balas, M. Balas, G. Abbas
: Composite state convergence is a novel scheme applied for the bilateral control of a telerobotic system. The scheme offers an elegant design procedure and employs only three communication channels to establish synchronization between a single-master and a single-slave robotic system. This paper expands the capability of the composite state convergence scheme to accommodate any number of master and slave systems and proposes a disturbance observer-based composite state convergence architecture where k -master systems can cooperatively control l -slave systems in the presence of uncertainties. A systematic method is presented to compute the control gains while observer gains are determined in a standard way. To validate the proposed architecture, MATLAB simulations are performed on symmetric and asymmetric arrangements of single-degree-of-freedom teleoperation systems. Finally, experimental results are obtained using Quanser’s Qube-Servo systems in QUARC/Simulink environment.
{"title":"An Improved Composite State Convergence Scheme with Disturbance Compensation for Multilateral Teleoperation Systems","authors":"M. Asad, J. Gu, U. Farooq, V. Balas, M. Balas, G. Abbas","doi":"10.24846/v31i3y202204","DOIUrl":"https://doi.org/10.24846/v31i3y202204","url":null,"abstract":": Composite state convergence is a novel scheme applied for the bilateral control of a telerobotic system. The scheme offers an elegant design procedure and employs only three communication channels to establish synchronization between a single-master and a single-slave robotic system. This paper expands the capability of the composite state convergence scheme to accommodate any number of master and slave systems and proposes a disturbance observer-based composite state convergence architecture where k -master systems can cooperatively control l -slave systems in the presence of uncertainties. A systematic method is presented to compute the control gains while observer gains are determined in a standard way. To validate the proposed architecture, MATLAB simulations are performed on symmetric and asymmetric arrangements of single-degree-of-freedom teleoperation systems. Finally, experimental results are obtained using Quanser’s Qube-Servo systems in QUARC/Simulink environment.","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42111070","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}
: The occurrence of failures in the control surfaces of an aircraft may become a serious threat to the safety of both aircraft and passengers. That is, using fault-tolerant control (FTC) is vital for such critical systems. The nonlinear progressive accommodation (NPA) is a FTC strategy that consists in solving the State-dependant Riccati Equation (SDRE) in an iterative way. The aim of this work is to study the efficiency of the NPA, in the case of a non-classical stabilization problem and a different modelling of a nonlinear (NL) system, affected by a total actuator failure. That is, a modified NPA strategy is proposed by combining the SDRE control and a feed-forward compensator, derived from the Forward-Propagation-Riccati-Equation (FPRE). The system considered in this paper is a full NL model of a DC-8 aircraft with coupled dynamics. The modelling of the aircraft as well as the simulation of the healthy, affected and accommodated system are presented. The proposed NPA method allows the aircraft to achieve a trajectory-following mission despite the complete failure of its actuator. Most importantly, by preserving the system’s stability, the developed approach can be considered as a good alternative to the use of redundant actuators in aircraft.
{"title":"Nonlinear Accommodation of a DC-8 Aircraft Affected by a Complete Loss of a Control Surface","authors":"Hajer Mlayeh, K. Ben Othman","doi":"10.24846/v31i3y202210","DOIUrl":"https://doi.org/10.24846/v31i3y202210","url":null,"abstract":": The occurrence of failures in the control surfaces of an aircraft may become a serious threat to the safety of both aircraft and passengers. That is, using fault-tolerant control (FTC) is vital for such critical systems. The nonlinear progressive accommodation (NPA) is a FTC strategy that consists in solving the State-dependant Riccati Equation (SDRE) in an iterative way. The aim of this work is to study the efficiency of the NPA, in the case of a non-classical stabilization problem and a different modelling of a nonlinear (NL) system, affected by a total actuator failure. That is, a modified NPA strategy is proposed by combining the SDRE control and a feed-forward compensator, derived from the Forward-Propagation-Riccati-Equation (FPRE). The system considered in this paper is a full NL model of a DC-8 aircraft with coupled dynamics. The modelling of the aircraft as well as the simulation of the healthy, affected and accommodated system are presented. The proposed NPA method allows the aircraft to achieve a trajectory-following mission despite the complete failure of its actuator. Most importantly, by preserving the system’s stability, the developed approach can be considered as a good alternative to the use of redundant actuators in aircraft.","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44307533","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}
C. Cioaca, V. Popescu, V. Prisacariu, S. Pop, Cristian Vidan
: The main purpose of this paper is to present a pilot configuration management system, namely QuadFlexArch, necessary for the planning of ISTAR military missions performed with unmanned aerial systems (UASs). The creation of this system started due to an operational need identified during the modernization of the Phoenix 30 quad-rotor vertical take-off and landing (VTOL) UAS. QuadFlexArch has been designed so as to allow being constantly updated according to the most recent operational requirements, associated with the latest UASs, but also with the new validated and available technical solutions. The model adopted for the design and development of the configuration management system allows the identification and evaluation of UAS by testing the key performance parameters (the noise level, thrust, torque, power, speed for the motor-propeller assembly, ESC signal and the reconfiguration time for a certain mission), the determination of the flight autonomy and data integration into a decision support platform designed in the Delphi programming language. The obtained result is in the form of a hierarchy of technical solutions available for optimal mission planning.
{"title":"UAS Flexible Configuration for Optimum Performance in ISTAR Military Missions","authors":"C. Cioaca, V. Popescu, V. Prisacariu, S. Pop, Cristian Vidan","doi":"10.24846/v31i3y202211","DOIUrl":"https://doi.org/10.24846/v31i3y202211","url":null,"abstract":": The main purpose of this paper is to present a pilot configuration management system, namely QuadFlexArch, necessary for the planning of ISTAR military missions performed with unmanned aerial systems (UASs). The creation of this system started due to an operational need identified during the modernization of the Phoenix 30 quad-rotor vertical take-off and landing (VTOL) UAS. QuadFlexArch has been designed so as to allow being constantly updated according to the most recent operational requirements, associated with the latest UASs, but also with the new validated and available technical solutions. The model adopted for the design and development of the configuration management system allows the identification and evaluation of UAS by testing the key performance parameters (the noise level, thrust, torque, power, speed for the motor-propeller assembly, ESC signal and the reconfiguration time for a certain mission), the determination of the flight autonomy and data integration into a decision support platform designed in the Delphi programming language. The obtained result is in the form of a hierarchy of technical solutions available for optimal mission planning.","PeriodicalId":49466,"journal":{"name":"Studies in Informatics and Control","volume":" ","pages":""},"PeriodicalIF":1.6,"publicationDate":"2022-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41877461","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}
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