Pub Date : 2022-07-08DOI: 10.1109/CONECCT55679.2022.9865713
Alireza Keyanfar, Liyana Meh, Reihaneh Rabbani
Housing is not a static artifact and contributes to the physical and psychological state of the residents. The impact of the housing effect depends on the residents' quality of life and satisfaction. A review of housing journals indicates that optimal housing is not accessible for most low-income households due to the lack of financial support for tenants due to the landlords' absolute power, dwellers with physical or mental disabilities, and elderlies. Therefore, preferably, they look for a home that is as satisfying as possible. If unavoidable, a housing relocation might bring the housing situation more in line with their preferences. This paper proposes ways to obtain adaptive housing responsive to users' preferences using intelligent technologies to optimize the residents' quality of life. The work shows that implementing sensors for managing a healthy environment, smart carpet as an interface between the environment and the ventilation system, facial emotion recognition, intelligent weather detection, smart curtains, mobile apps, and adjusting interior lighting and color-changing may be valuable to offer a comfortable, user-friendly home environment and facilitates the house choosing for the user by considering their personalities and behavior patterns.
{"title":"Application of intelligence in solving architectural problems in the field of housing","authors":"Alireza Keyanfar, Liyana Meh, Reihaneh Rabbani","doi":"10.1109/CONECCT55679.2022.9865713","DOIUrl":"https://doi.org/10.1109/CONECCT55679.2022.9865713","url":null,"abstract":"Housing is not a static artifact and contributes to the physical and psychological state of the residents. The impact of the housing effect depends on the residents' quality of life and satisfaction. A review of housing journals indicates that optimal housing is not accessible for most low-income households due to the lack of financial support for tenants due to the landlords' absolute power, dwellers with physical or mental disabilities, and elderlies. Therefore, preferably, they look for a home that is as satisfying as possible. If unavoidable, a housing relocation might bring the housing situation more in line with their preferences. This paper proposes ways to obtain adaptive housing responsive to users' preferences using intelligent technologies to optimize the residents' quality of life. The work shows that implementing sensors for managing a healthy environment, smart carpet as an interface between the environment and the ventilation system, facial emotion recognition, intelligent weather detection, smart curtains, mobile apps, and adjusting interior lighting and color-changing may be valuable to offer a comfortable, user-friendly home environment and facilitates the house choosing for the user by considering their personalities and behavior patterns.","PeriodicalId":380005,"journal":{"name":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125627682","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 : 2022-07-08DOI: 10.1109/CONECCT55679.2022.9865720
G. Thiagarajan, Deepan Vetrivel, Sanjeev Gurugopinath
Matrix decomposition methods such as the Cholesky and the QR decomposition arise in several applications in signal processing for multiple-input, multiple-output (MIMO) communication systems. The computational complexity of regular Cholesky and QR solvers is known to be $mathcal{O}left( {{N^3}} right)$. To reduce this, several recursive algorithms at both column- and block-levels have been proposed in the literature. In this paper, we utilize one such recursive structure in Cholesky and QR decompositions for matrices with entries from the field of complex numbers, which results in a level of complexity reduction. The use of the considered techniques is discussed in the context of a MIMO decoder. In particular, the utility of proposed methods is illustrated in a MIMO successive interference cancellation based detector. Simulation results are provided to substantiate the performance of a detector under two different antenna and receiver configurations.
{"title":"Recursive Matrix Decomposition Methods and Applications in Wireless Communication","authors":"G. Thiagarajan, Deepan Vetrivel, Sanjeev Gurugopinath","doi":"10.1109/CONECCT55679.2022.9865720","DOIUrl":"https://doi.org/10.1109/CONECCT55679.2022.9865720","url":null,"abstract":"Matrix decomposition methods such as the Cholesky and the QR decomposition arise in several applications in signal processing for multiple-input, multiple-output (MIMO) communication systems. The computational complexity of regular Cholesky and QR solvers is known to be $mathcal{O}left( {{N^3}} right)$. To reduce this, several recursive algorithms at both column- and block-levels have been proposed in the literature. In this paper, we utilize one such recursive structure in Cholesky and QR decompositions for matrices with entries from the field of complex numbers, which results in a level of complexity reduction. The use of the considered techniques is discussed in the context of a MIMO decoder. In particular, the utility of proposed methods is illustrated in a MIMO successive interference cancellation based detector. Simulation results are provided to substantiate the performance of a detector under two different antenna and receiver configurations.","PeriodicalId":380005,"journal":{"name":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134261127","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 : 2022-07-08DOI: 10.1109/CONECCT55679.2022.9865709
A. Chandra, G. Singh, V. Pant
Due to the integration of distributed generation (DG), fault level of the microgrid changes significantly. The fault current behaves dynamically and inhibits the activities of conventional protection algorithms. To address this serious issue for protection, a simple and fast protection algorithm, based on Empirical Mode Decomposition (EMD) and Hilbert Transform (HT) is proposed in this paper for the protection of grid-connected 14 BUS looped microgrid system. This scheme estimates the energy difference of current signals retrieved from both ends of the feeder. Further, the fault detection signal is generated from the Hilbert spectral energy difference. Nonetheless, for the comparative analysis of the performance of proposed EMD based fault detection technique, Variational Mode Decomposition (VMD) is also performed. Further high resistance fault cases are also examined to verify effectiveness of this proposed scheme. As this technique is essentially reckoning on the energy difference of current signals, it does not suffer from the difficulties associated with dynamic current behaviour of a microgrid. This proposed system is simulated in PSCAD simulation software and the programming for signal analysis is performed in MATLAB.
{"title":"Fault Detection of Grid-Connected Looped Microgrid based on Estimated Energy Difference Signal","authors":"A. Chandra, G. Singh, V. Pant","doi":"10.1109/CONECCT55679.2022.9865709","DOIUrl":"https://doi.org/10.1109/CONECCT55679.2022.9865709","url":null,"abstract":"Due to the integration of distributed generation (DG), fault level of the microgrid changes significantly. The fault current behaves dynamically and inhibits the activities of conventional protection algorithms. To address this serious issue for protection, a simple and fast protection algorithm, based on Empirical Mode Decomposition (EMD) and Hilbert Transform (HT) is proposed in this paper for the protection of grid-connected 14 BUS looped microgrid system. This scheme estimates the energy difference of current signals retrieved from both ends of the feeder. Further, the fault detection signal is generated from the Hilbert spectral energy difference. Nonetheless, for the comparative analysis of the performance of proposed EMD based fault detection technique, Variational Mode Decomposition (VMD) is also performed. Further high resistance fault cases are also examined to verify effectiveness of this proposed scheme. As this technique is essentially reckoning on the energy difference of current signals, it does not suffer from the difficulties associated with dynamic current behaviour of a microgrid. This proposed system is simulated in PSCAD simulation software and the programming for signal analysis is performed in MATLAB.","PeriodicalId":380005,"journal":{"name":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133364544","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 : 2022-07-08DOI: 10.1109/CONECCT55679.2022.9865820
Rachit Mayur Shah, B. Sainath, Akshansh Gupta
Tasks such as image classification, object detection, to mention a few, play an important role in computer vision. Numerous algorithms have been developed to improve the performance of such tasks for benchmark datasets. Although advanced algorithms offer state-of-the-art performance on such tasks, it is also important to analyze their algorithmic feasibility over the time to make it practical for end-user applications. This paper analyzes two such groups of algorithms, namely, Convolutional Neural Networks (CNN) based algorithms with You Only Look Once (YOLO) in terms of speed and accuracy.
图像分类、目标检测等任务在计算机视觉中发挥着重要作用。已经开发了许多算法来改进基准数据集的这些任务的性能。虽然先进的算法在这些任务上提供了最先进的性能，但随着时间的推移分析它们的算法可行性也很重要，以使其对最终用户应用程序具有实用性。本文从速度和准确性两方面分析了两组这样的算法，即基于卷积神经网络(CNN)的You Only Look Once (YOLO)算法。
{"title":"Comparative Performance Study of CNN-based Algorithms and YOLO","authors":"Rachit Mayur Shah, B. Sainath, Akshansh Gupta","doi":"10.1109/CONECCT55679.2022.9865820","DOIUrl":"https://doi.org/10.1109/CONECCT55679.2022.9865820","url":null,"abstract":"Tasks such as image classification, object detection, to mention a few, play an important role in computer vision. Numerous algorithms have been developed to improve the performance of such tasks for benchmark datasets. Although advanced algorithms offer state-of-the-art performance on such tasks, it is also important to analyze their algorithmic feasibility over the time to make it practical for end-user applications. This paper analyzes two such groups of algorithms, namely, Convolutional Neural Networks (CNN) based algorithms with You Only Look Once (YOLO) in terms of speed and accuracy.","PeriodicalId":380005,"journal":{"name":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129073355","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 : 2022-07-08DOI: 10.1109/CONECCT55679.2022.9865747
Melih Aslan, Huseyin Baydar, V. Kılıç
This paper reports comb-shaped patch antennas with asymmetrical geometries having two and three arms on the sides. The proposed geometry is evolved from regular rectangular shaped patch antenna by removing certain parts of the radiator patch and shifting the arms on one side of the antenna. Systematic simulations were obtained with the designed antennas for different arm shifting distances, and changes in resonance behavior and far-field radiation pattern were investigated. Results show that as the arm shifting increases the first and second resonance frequencies of the antennas decrease. Also, it is observed that the radiation occurs with two symmetric beams at the second resonance frequency of the designed antennas with no shift between the arms. However, as the arm shifting is applied the beam on the side of the arms closer to the feeding line gets stronger, whereas the other beam weakens. Obtained plots indicate that the directivity of the antennas have a tendency to increase with the arm shifting while the side lobe level decreases. In addition, results show that the half power beam width of the antenna increases with arm shifting. The simulations were repeated for different arm thicknesses and the same observations were held.
{"title":"Comb-Shaped Patch Antenna Design Study with Shifted Arms and Asymmetric Architecture Enabling Controlled Resonance Change and Radiation Pattern","authors":"Melih Aslan, Huseyin Baydar, V. Kılıç","doi":"10.1109/CONECCT55679.2022.9865747","DOIUrl":"https://doi.org/10.1109/CONECCT55679.2022.9865747","url":null,"abstract":"This paper reports comb-shaped patch antennas with asymmetrical geometries having two and three arms on the sides. The proposed geometry is evolved from regular rectangular shaped patch antenna by removing certain parts of the radiator patch and shifting the arms on one side of the antenna. Systematic simulations were obtained with the designed antennas for different arm shifting distances, and changes in resonance behavior and far-field radiation pattern were investigated. Results show that as the arm shifting increases the first and second resonance frequencies of the antennas decrease. Also, it is observed that the radiation occurs with two symmetric beams at the second resonance frequency of the designed antennas with no shift between the arms. However, as the arm shifting is applied the beam on the side of the arms closer to the feeding line gets stronger, whereas the other beam weakens. Obtained plots indicate that the directivity of the antennas have a tendency to increase with the arm shifting while the side lobe level decreases. In addition, results show that the half power beam width of the antenna increases with arm shifting. The simulations were repeated for different arm thicknesses and the same observations were held.","PeriodicalId":380005,"journal":{"name":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134520677","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}
Opportunistic networks(OppNets) are a subset of mobile IoT networks in which no direct connection can be established between a message’s source and its destination node. Instead, routing occurs through a collection of intermediate mobile nodes. The lack of a direct connection, along with the mobile nature of the nodes makes routing in OppNets a challenge. This paper aims to utilize machine learning to automate the routing process in Opportunistic networks. The proposed model is a context-aware protocol called DBSCAN-R. DBSCAN-R utilizes DBSCAN(Density-Based Clustering of Application with Noise), an unsupervised soft clustering algorithm to make routing choices. Four dynamic network parameters are chosen to use as features for clustering in DBSCAN. DBSCAN-R outperforms 3 benchmark algorithms i.e Epidemic routing, ProPHET routing, and MaxProp routing when comparing the delivery success rate, average hop count, overhead ratio, and messages dropped.
机会网络(OppNets)是移动物联网网络的一个子集，在该网络中，消息的源节点和目标节点之间不能建立直接连接。相反，路由是通过一组中间移动节点进行的。缺乏直接连接以及节点的移动性使得OppNets中的路由成为一项挑战。本文旨在利用机器学习实现机会主义网络中路由过程的自动化。所提出的模型是一个名为DBSCAN-R的上下文感知协议。DBSCAN- r利用无监督软聚类算法DBSCAN(Density-Based Clustering of Application with Noise)进行路由选择。选择了四个动态网络参数作为DBSCAN中聚类的特征。在比较传递成功率、平均跳数、开销比和丢弃的消息时，DBSCAN-R优于3种基准算法，即Epidemic路由、ProPHET路由和MaxProp路由。
{"title":"DBSCAN-R: A Machine Learning Approach for Routing in Opportunistic Networks","authors":"Rohan Pillai, Rashmi Rao, Ch Rajendra prasad, Apoorva Rao Iragavarapu, Annapurna D","doi":"10.1109/CONECCT55679.2022.9865751","DOIUrl":"https://doi.org/10.1109/CONECCT55679.2022.9865751","url":null,"abstract":"Opportunistic networks(OppNets) are a subset of mobile IoT networks in which no direct connection can be established between a message’s source and its destination node. Instead, routing occurs through a collection of intermediate mobile nodes. The lack of a direct connection, along with the mobile nature of the nodes makes routing in OppNets a challenge. This paper aims to utilize machine learning to automate the routing process in Opportunistic networks. The proposed model is a context-aware protocol called DBSCAN-R. DBSCAN-R utilizes DBSCAN(Density-Based Clustering of Application with Noise), an unsupervised soft clustering algorithm to make routing choices. Four dynamic network parameters are chosen to use as features for clustering in DBSCAN. DBSCAN-R outperforms 3 benchmark algorithms i.e Epidemic routing, ProPHET routing, and MaxProp routing when comparing the delivery success rate, average hop count, overhead ratio, and messages dropped.","PeriodicalId":380005,"journal":{"name":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115994245","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 : 2022-07-08DOI: 10.1109/CONECCT55679.2022.9865745
V. Advaith, Anushka Shivkumar, B. S. Sowmya Lakshmi
Part-of-speech (POS) tagging is one of the vital Natural Language Processing (NLP) tasks that entails categorising words in a text (corpus) in accordance with a specific part of the speech, based on the word’s context. POS tagging for Indian Languages is not widely explored. Kannada is extremely inflectional and contains one of the most complex and richest collections of linguistic traits. Hence, developing a POS tagger for a resource-poor language such as Kannada is difficult The morphological complexity of Hindi becomes a challenge despite there having been numerous attempts of building a POS tagger for the language. The proposed work deals with the development of a POS tagger for both Kannada and Hindi by employing Machine Learning (ML) and Deep Learning (DL) algorithms. The results obtained are based on experiments conducted on a corpus consisting of around 3 lakh unique words for Kannada and Hindi combined. The 17 POS tags have been taken from the BIS tag set.
{"title":"Parts of Speech Tagging for Kannada and Hindi Languages using ML and DL models","authors":"V. Advaith, Anushka Shivkumar, B. S. Sowmya Lakshmi","doi":"10.1109/CONECCT55679.2022.9865745","DOIUrl":"https://doi.org/10.1109/CONECCT55679.2022.9865745","url":null,"abstract":"Part-of-speech (POS) tagging is one of the vital Natural Language Processing (NLP) tasks that entails categorising words in a text (corpus) in accordance with a specific part of the speech, based on the word’s context. POS tagging for Indian Languages is not widely explored. Kannada is extremely inflectional and contains one of the most complex and richest collections of linguistic traits. Hence, developing a POS tagger for a resource-poor language such as Kannada is difficult The morphological complexity of Hindi becomes a challenge despite there having been numerous attempts of building a POS tagger for the language. The proposed work deals with the development of a POS tagger for both Kannada and Hindi by employing Machine Learning (ML) and Deep Learning (DL) algorithms. The results obtained are based on experiments conducted on a corpus consisting of around 3 lakh unique words for Kannada and Hindi combined. The 17 POS tags have been taken from the BIS tag set.","PeriodicalId":380005,"journal":{"name":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"146 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123341228","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}
There’s been an increase in attempts to control the surge in pollution levels due to extensive exploitation of conventional fossil fuels. These efforts have fueled research for alternative green solutions. Lithium-ion batteries are immensely beneficial for energy storage system. They are extremely advantageous in the automobile industry, particularly as a source to power Electric Vehicles (EVs). Lithium-ion batteries are also vital for powering consumer electronics. The State of Charge (SOC) measurement is used to calculate the remaining usage time of batteries, is one of the most pertinent metric. The goal of current research has been to develop accurate State of Charge (SOC) prediction algorithms. All existing methods require significant amount of superior-quality curated dataset. However, battery researchers have minimal access to commercial battery datasets and therefore must rely on open-access public datasets that lack the required heterogeneity to generate generalised SOC algorithms. To resolve this issue of lack of data, we introduce a Sample Convolution and Interaction Networks (SCINet) to produce resilient synthetic battery data. The code implementation can be found on: https://github.com/vinayakrajurs/Sample-Convolution-Interaction-Syntheic-Data
{"title":"Synthetic Data Generation using Resilient Sample Convolution and Interactive Learning Approach","authors":"Vinayak Raj Urs, Vageesh Maiya, Janamejaya Channegowda, Chaitanya Lingaraj","doi":"10.1109/CONECCT55679.2022.9865732","DOIUrl":"https://doi.org/10.1109/CONECCT55679.2022.9865732","url":null,"abstract":"There’s been an increase in attempts to control the surge in pollution levels due to extensive exploitation of conventional fossil fuels. These efforts have fueled research for alternative green solutions. Lithium-ion batteries are immensely beneficial for energy storage system. They are extremely advantageous in the automobile industry, particularly as a source to power Electric Vehicles (EVs). Lithium-ion batteries are also vital for powering consumer electronics. The State of Charge (SOC) measurement is used to calculate the remaining usage time of batteries, is one of the most pertinent metric. The goal of current research has been to develop accurate State of Charge (SOC) prediction algorithms. All existing methods require significant amount of superior-quality curated dataset. However, battery researchers have minimal access to commercial battery datasets and therefore must rely on open-access public datasets that lack the required heterogeneity to generate generalised SOC algorithms. To resolve this issue of lack of data, we introduce a Sample Convolution and Interaction Networks (SCINet) to produce resilient synthetic battery data. The code implementation can be found on: https://github.com/vinayakrajurs/Sample-Convolution-Interaction-Syntheic-Data","PeriodicalId":380005,"journal":{"name":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125154233","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 : 2022-07-08DOI: 10.1109/CONECCT55679.2022.9865832
Partha Roy, Susanta Ray
The objective of this paper is to develop a state space affine model of a permanent magnet synchronous motor (PMSM) to facilitate its behavioral study for different sets of parameters. The modeling is done in step-by-step manner with clear-cut explanation. First the two-axis d-q model is built. Then the model is transformed into state-space using affine transformation. The dynamic behavior of the dimensionless state-space variables is studied thereupon. A special investigation shows the probability of the chaotic behavior of the motor. The simulation results in MATLAB® environment demonstrate the effectiveness of the appraisals of this analysis.
{"title":"Development of Non-linear State-space Affine Model of PMSM and Analysis of Its Dynamic Behavior Encompassing the Possibility of Chaos","authors":"Partha Roy, Susanta Ray","doi":"10.1109/CONECCT55679.2022.9865832","DOIUrl":"https://doi.org/10.1109/CONECCT55679.2022.9865832","url":null,"abstract":"The objective of this paper is to develop a state space affine model of a permanent magnet synchronous motor (PMSM) to facilitate its behavioral study for different sets of parameters. The modeling is done in step-by-step manner with clear-cut explanation. First the two-axis d-q model is built. Then the model is transformed into state-space using affine transformation. The dynamic behavior of the dimensionless state-space variables is studied thereupon. A special investigation shows the probability of the chaotic behavior of the motor. The simulation results in MATLAB® environment demonstrate the effectiveness of the appraisals of this analysis.","PeriodicalId":380005,"journal":{"name":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130631165","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 : 2022-07-08DOI: 10.1109/CONECCT55679.2022.9865761
Jamal Pasha, S. Karpagavalli
Autonomous companion robots have shown to be particularly beneficial for gathering information in areas where people are restricted. Controlling them is often a challenge ng feat due to the environment's ambiguity and the nonlinear dynamics of the grounds. Despite the fact that a variety of controller designs are feasible, and some are documented in the literature, it is unknown which designs are best suited for a certain context. In this paper, we attempted to design a robot that can be adapted for usage in any environment by making only skeleton alterations, we designed the controller with integrating Neural network nodes with Q-learning algorithm to regulate movement of the robot using LIDAR samples. With military applications in consideration, we implemented encryptors to send and receive data, and we distributed all dumps to the controller to ensure that we only needed to be connected when delivering data to the owner. As all this requires high processing speed and storage, we recommend using ESP32-S2 for its high clock speed.
{"title":"Spydobot-AI Based autonomous spider like robot for spying","authors":"Jamal Pasha, S. Karpagavalli","doi":"10.1109/CONECCT55679.2022.9865761","DOIUrl":"https://doi.org/10.1109/CONECCT55679.2022.9865761","url":null,"abstract":"Autonomous companion robots have shown to be particularly beneficial for gathering information in areas where people are restricted. Controlling them is often a challenge ng feat due to the environment's ambiguity and the nonlinear dynamics of the grounds. Despite the fact that a variety of controller designs are feasible, and some are documented in the literature, it is unknown which designs are best suited for a certain context. In this paper, we attempted to design a robot that can be adapted for usage in any environment by making only skeleton alterations, we designed the controller with integrating Neural network nodes with Q-learning algorithm to regulate movement of the robot using LIDAR samples. With military applications in consideration, we implemented encryptors to send and receive data, and we distributed all dumps to the controller to ensure that we only needed to be connected when delivering data to the owner. As all this requires high processing speed and storage, we recommend using ESP32-S2 for its high clock speed.","PeriodicalId":380005,"journal":{"name":"2022 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130886207","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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