Pub Date : 2017-07-21DOI: 10.1109/ICSSE.2017.8030869
Tuan-Anh Vu, L. Pham, T. K. Huynh, Synh Viet-Uyen Ha
Vehicle detection and classification is an essential application in traffic surveillance system (TSS). However, recognizing moving vehicle at nighttime is more challenging because of either poorly (lack of street lights) or brightly illuminations and chaos traffic of motorbikes. Adding to this is various type of vehicles travels on the same road which falsifies the pairing results. So, this research proposes an algorithm for vehicle detection and classification at nighttime surveillance scenes which consists of headlight segmentation, headlight detection, headlight tracking and pairing and vehicle classification (two-wheeled and four-wheeled vehicles). First, bright objects are segmented by using the luminance and color variations. Then, the candidate headlights are detected and validated through the characteristics of the headlights such as area, centroid, rims, and shape. Afterward, we present a way to tracking and pairing the headlights by calculating the area ratio, spatial information on the vertical and horizontal of a headlight. Finally, the vehicle is classified into two-wheeled and four-wheeled vehicles. The novelty of our work is that headlights are validated and paired using trajectory tracing technique. The evaluation results are promising for a detection rate of 81.19% in nighttime scenes.
{"title":"Nighttime vehicle detection and classification via headlights trajectories matching","authors":"Tuan-Anh Vu, L. Pham, T. K. Huynh, Synh Viet-Uyen Ha","doi":"10.1109/ICSSE.2017.8030869","DOIUrl":"https://doi.org/10.1109/ICSSE.2017.8030869","url":null,"abstract":"Vehicle detection and classification is an essential application in traffic surveillance system (TSS). However, recognizing moving vehicle at nighttime is more challenging because of either poorly (lack of street lights) or brightly illuminations and chaos traffic of motorbikes. Adding to this is various type of vehicles travels on the same road which falsifies the pairing results. So, this research proposes an algorithm for vehicle detection and classification at nighttime surveillance scenes which consists of headlight segmentation, headlight detection, headlight tracking and pairing and vehicle classification (two-wheeled and four-wheeled vehicles). First, bright objects are segmented by using the luminance and color variations. Then, the candidate headlights are detected and validated through the characteristics of the headlights such as area, centroid, rims, and shape. Afterward, we present a way to tracking and pairing the headlights by calculating the area ratio, spatial information on the vertical and horizontal of a headlight. Finally, the vehicle is classified into two-wheeled and four-wheeled vehicles. The novelty of our work is that headlights are validated and paired using trajectory tracing technique. The evaluation results are promising for a detection rate of 81.19% in nighttime scenes.","PeriodicalId":296191,"journal":{"name":"2017 International Conference on System Science and Engineering (ICSSE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115443524","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 : 2017-07-21DOI: 10.1109/ICSSE.2017.8030909
N. Binh, Nguyen Anh Tung, Dao Phuong Nam, Cao Thanh Trung
The issue of nonlinear model predictive control has always been a topic of much concern. We will propose a new approach to robust nonlinear model predictive control to class of nonlinear model system with input constraint under state-dependent disturbances. The considered class of model is separated into linear part at current state, nonlinear part and state-dependent disturbances which are assumed to have their bound. The state-feedback control law is obtained by that solving optimization problem of upper bound of infinite horizon cost function with input constraint via LMIs. In this paper, in order to guarantee robust stability, the proposed approach must generates feasible regions which ensures the existence of a solution and stable region bounded by that. Moreover, these regions are able to contract after every sampling time to proof the robust stability of the system. The simulation results demonstrate the good performance of the proposed approach to RNMPC.
{"title":"An approach robust nonlinear model predictive control with state-dependent disturbances via linear matrix inequalities","authors":"N. Binh, Nguyen Anh Tung, Dao Phuong Nam, Cao Thanh Trung","doi":"10.1109/ICSSE.2017.8030909","DOIUrl":"https://doi.org/10.1109/ICSSE.2017.8030909","url":null,"abstract":"The issue of nonlinear model predictive control has always been a topic of much concern. We will propose a new approach to robust nonlinear model predictive control to class of nonlinear model system with input constraint under state-dependent disturbances. The considered class of model is separated into linear part at current state, nonlinear part and state-dependent disturbances which are assumed to have their bound. The state-feedback control law is obtained by that solving optimization problem of upper bound of infinite horizon cost function with input constraint via LMIs. In this paper, in order to guarantee robust stability, the proposed approach must generates feasible regions which ensures the existence of a solution and stable region bounded by that. Moreover, these regions are able to contract after every sampling time to proof the robust stability of the system. The simulation results demonstrate the good performance of the proposed approach to RNMPC.","PeriodicalId":296191,"journal":{"name":"2017 International Conference on System Science and Engineering (ICSSE)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127308540","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 : 2017-07-21DOI: 10.1109/ICSSE.2017.8030892
N. Dinh, Nguyen Hong Viet, L. A. Nguyen, Hong Toan Dinh, Nguyen Tran Hiep, Pham Trung Dung, T. Ngo, Xuan-Tung Truong
In this paper, we propose an extended navigation framework for autonomous mobile robots in dynamic environments using a reinforcement learning algorithm. The main idea of the proposed algorithm is to provide the mobile robots the relative position and motion of the surrounding objects to the robots, and the safety constraints such as minimum distance from the robots to the obstacles, and a learning model. We then distribute the mobile robots into a dynamic environment. The mobile robots will automatically learn to adapt to the environment by their own experienced through the trial-and-error interaction with the surrounding environment. When the learning phase is completed, the mobile robots equipped with our proposed framework are able to navigate autonomously and safely in the dynamic environment. The simulation results in a simulated environment shows that, our proposed navigation framework is capable of driving the mobile robots to avoid dynamic obstacles and catch up dynamic targets, providing the safety for the surrounding objects and the mobile robots.
{"title":"An extended navigation framework for autonomous mobile robot in dynamic environments using reinforcement learning algorithm","authors":"N. Dinh, Nguyen Hong Viet, L. A. Nguyen, Hong Toan Dinh, Nguyen Tran Hiep, Pham Trung Dung, T. Ngo, Xuan-Tung Truong","doi":"10.1109/ICSSE.2017.8030892","DOIUrl":"https://doi.org/10.1109/ICSSE.2017.8030892","url":null,"abstract":"In this paper, we propose an extended navigation framework for autonomous mobile robots in dynamic environments using a reinforcement learning algorithm. The main idea of the proposed algorithm is to provide the mobile robots the relative position and motion of the surrounding objects to the robots, and the safety constraints such as minimum distance from the robots to the obstacles, and a learning model. We then distribute the mobile robots into a dynamic environment. The mobile robots will automatically learn to adapt to the environment by their own experienced through the trial-and-error interaction with the surrounding environment. When the learning phase is completed, the mobile robots equipped with our proposed framework are able to navigate autonomously and safely in the dynamic environment. The simulation results in a simulated environment shows that, our proposed navigation framework is capable of driving the mobile robots to avoid dynamic obstacles and catch up dynamic targets, providing the safety for the surrounding objects and the mobile robots.","PeriodicalId":296191,"journal":{"name":"2017 International Conference on System Science and Engineering (ICSSE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130655070","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 : 2017-07-21DOI: 10.1109/ICSSE.2017.8030937
G. Gateau, P. Q. Dung, M. Cousineau, P. Do, Huu Nhan Le
This paper presents the implementation of a decentralized modulation for the control of multilevel converters requiring phase-shifted carriers. Contrary to the principle using a “master” controller providing a set of interleaved carriers, the proposed method uses local interconnections between different independent elementary controllers allowing them to self-align their own carrier regardless the number of actives cells.
{"title":"Digital implementation of decentralized control for multilevel converter","authors":"G. Gateau, P. Q. Dung, M. Cousineau, P. Do, Huu Nhan Le","doi":"10.1109/ICSSE.2017.8030937","DOIUrl":"https://doi.org/10.1109/ICSSE.2017.8030937","url":null,"abstract":"This paper presents the implementation of a decentralized modulation for the control of multilevel converters requiring phase-shifted carriers. Contrary to the principle using a “master” controller providing a set of interleaved carriers, the proposed method uses local interconnections between different independent elementary controllers allowing them to self-align their own carrier regardless the number of actives cells.","PeriodicalId":296191,"journal":{"name":"2017 International Conference on System Science and Engineering (ICSSE)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133193692","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 : 2017-07-21DOI: 10.1109/ICSSE.2017.8030867
Nguyen Thanh Van, T. N. Thinh, Le Thanh Sach
Recently, anomaly-based intrusion detection techniques are valuable methodology to detect both known as well as unknown/new attacks, so they can cope with the diversity of the attacks and the constantly changing nature of network attacks. There are many problems need to be considered in anomaly-based network intrusion detection system (NIDS), such as ability to adapt to dynamic network environments, unavailability of labeled data, false positive rate. This paper, we use Deep learning techniques to implement an anomaly-based NIDS. These techniques show the sensitive power of generative models with good classification, capabilities to deduce part of its knowledge from incomplete data and the adaptability. Our experiments with KDDCup99 network traffic connections show that our work is effective to exact detect in anomaly-based NIDS and classify intrusions into five groups with the accuracy based on network data sources.
{"title":"An anomaly-based network intrusion detection system using Deep learning","authors":"Nguyen Thanh Van, T. N. Thinh, Le Thanh Sach","doi":"10.1109/ICSSE.2017.8030867","DOIUrl":"https://doi.org/10.1109/ICSSE.2017.8030867","url":null,"abstract":"Recently, anomaly-based intrusion detection techniques are valuable methodology to detect both known as well as unknown/new attacks, so they can cope with the diversity of the attacks and the constantly changing nature of network attacks. There are many problems need to be considered in anomaly-based network intrusion detection system (NIDS), such as ability to adapt to dynamic network environments, unavailability of labeled data, false positive rate. This paper, we use Deep learning techniques to implement an anomaly-based NIDS. These techniques show the sensitive power of generative models with good classification, capabilities to deduce part of its knowledge from incomplete data and the adaptability. Our experiments with KDDCup99 network traffic connections show that our work is effective to exact detect in anomaly-based NIDS and classify intrusions into five groups with the accuracy based on network data sources.","PeriodicalId":296191,"journal":{"name":"2017 International Conference on System Science and Engineering (ICSSE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125588502","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 : 2017-07-21DOI: 10.1109/ICSSE.2017.8030924
Nguyen Anh Tung, N. Binh, Tran Hoang Anh, Dao Phuong Nam, Nguyen Minh Dong
Teleoperation is a human control system enabling humans to interact with the remote environment through a dual robot system which includes a master robot and a slave robot operating in two different places. Wave variables and scattering approaches were proposed in [1],[2] with constant time delay, [3],[4] with varying time delays. This paper develops them based on different wave variables and new passivity control to guarantee the stability of the whole system against varying time delays without assumption that absolute derivative of time delays is smaller than one. The validity of the control law is based on passivity theory. In addition, force controller design is considered for increasing transparency of system. The simulation results demonstrate the good performance of the proposed controller for position synchronization.
{"title":"Synchronization control of Bilateral Teleoperation systems by using wave variable method under varying time delay","authors":"Nguyen Anh Tung, N. Binh, Tran Hoang Anh, Dao Phuong Nam, Nguyen Minh Dong","doi":"10.1109/ICSSE.2017.8030924","DOIUrl":"https://doi.org/10.1109/ICSSE.2017.8030924","url":null,"abstract":"Teleoperation is a human control system enabling humans to interact with the remote environment through a dual robot system which includes a master robot and a slave robot operating in two different places. Wave variables and scattering approaches were proposed in [1],[2] with constant time delay, [3],[4] with varying time delays. This paper develops them based on different wave variables and new passivity control to guarantee the stability of the whole system against varying time delays without assumption that absolute derivative of time delays is smaller than one. The validity of the control law is based on passivity theory. In addition, force controller design is considered for increasing transparency of system. The simulation results demonstrate the good performance of the proposed controller for position synchronization.","PeriodicalId":296191,"journal":{"name":"2017 International Conference on System Science and Engineering (ICSSE)","volume":"188 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133889788","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 : 2017-07-21DOI: 10.1109/ICSSE.2017.8030934
Yao-Yu Jhuang, Tong Lin, T. D. Nguyen, Shao-I Chu, Bing-Hong Liu, Van-Trung Pham
Nowadays, the problem of using minimum number of time slots for data aggregation such that sensors can work without data collision for data transmissions has received a great deal of attention in Wireless Sensor Network (WRSN). It is worth mentioning that there exists many approaches that are tried to reduce the number of time slots for data aggregation in WSNs. However, most of previous works are fallen into reducing time slots in certain circle. In this paper, we investigate the problem of Reducing Data Aggregation Time without Data Collision (RDATDC) problem and first propose a new overlap circle technique, which is termed the Overlap-Circle-based algorithm (OCBA), to solve the RDATDC problem. Simulation results show that the OCBA has better performance than other method.
{"title":"A new overlap circle technique for Reducing Data Aggregation Time in Wireless Sensor Networks","authors":"Yao-Yu Jhuang, Tong Lin, T. D. Nguyen, Shao-I Chu, Bing-Hong Liu, Van-Trung Pham","doi":"10.1109/ICSSE.2017.8030934","DOIUrl":"https://doi.org/10.1109/ICSSE.2017.8030934","url":null,"abstract":"Nowadays, the problem of using minimum number of time slots for data aggregation such that sensors can work without data collision for data transmissions has received a great deal of attention in Wireless Sensor Network (WRSN). It is worth mentioning that there exists many approaches that are tried to reduce the number of time slots for data aggregation in WSNs. However, most of previous works are fallen into reducing time slots in certain circle. In this paper, we investigate the problem of Reducing Data Aggregation Time without Data Collision (RDATDC) problem and first propose a new overlap circle technique, which is termed the Overlap-Circle-based algorithm (OCBA), to solve the RDATDC problem. Simulation results show that the OCBA has better performance than other method.","PeriodicalId":296191,"journal":{"name":"2017 International Conference on System Science and Engineering (ICSSE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132537311","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 : 2017-07-01DOI: 10.1109/ICSSE.2017.8030889
H. Pham, NamHoai Nguyen, P. D. Nguyen
The work represents a dynamic programming and piecewise linearization based control strategy for a perturbed discrete-time nonlinear system. Firstly, the perturbed discrete-time nonlinear system is linearized at each sampling time. The origin system is approximated by infinite number of the linearized models. Then, the disturbances are estimated under the assumption of slow variations in input and state during a sampling period. Finally, a controller based on the dynamic programming method is designed. The proposed control strategy is applied to control a boiler-turbine system and compared to the other method with the usage of numerical simulation. The simulation results show that the proposed method gives better performance in term of overshoot and smoothness of control signals and it can be applied to other plants in industry.
{"title":"Dynamic programming based control for perturbed discrete time nonlinear systems","authors":"H. Pham, NamHoai Nguyen, P. D. Nguyen","doi":"10.1109/ICSSE.2017.8030889","DOIUrl":"https://doi.org/10.1109/ICSSE.2017.8030889","url":null,"abstract":"The work represents a dynamic programming and piecewise linearization based control strategy for a perturbed discrete-time nonlinear system. Firstly, the perturbed discrete-time nonlinear system is linearized at each sampling time. The origin system is approximated by infinite number of the linearized models. Then, the disturbances are estimated under the assumption of slow variations in input and state during a sampling period. Finally, a controller based on the dynamic programming method is designed. The proposed control strategy is applied to control a boiler-turbine system and compared to the other method with the usage of numerical simulation. The simulation results show that the proposed method gives better performance in term of overshoot and smoothness of control signals and it can be applied to other plants in industry.","PeriodicalId":296191,"journal":{"name":"2017 International Conference on System Science and Engineering (ICSSE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115290290","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 : 2017-07-01DOI: 10.1109/ICSSE.2017.8030836
The Chien Hoang, H. Dang, V. Nguyen
In this paper, we propose a Kinect-based virtual training system for rehabilitation system. The system is aimed to assist patients after stroke or with spiral cord injuries who consequently have movement disorders to perform rehabilitation exercises at home. Movements of patients is capture and their skeletons are tracked by means of Kinect sensor. Patient's movements are then compared to the prerecorded movements of virtual coach/trainer.
{"title":"Kinect-based virtual training system for rehabilitation","authors":"The Chien Hoang, H. Dang, V. Nguyen","doi":"10.1109/ICSSE.2017.8030836","DOIUrl":"https://doi.org/10.1109/ICSSE.2017.8030836","url":null,"abstract":"In this paper, we propose a Kinect-based virtual training system for rehabilitation system. The system is aimed to assist patients after stroke or with spiral cord injuries who consequently have movement disorders to perform rehabilitation exercises at home. Movements of patients is capture and their skeletons are tracked by means of Kinect sensor. Patient's movements are then compared to the prerecorded movements of virtual coach/trainer.","PeriodicalId":296191,"journal":{"name":"2017 International Conference on System Science and Engineering (ICSSE)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123423687","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 : 2017-07-01DOI: 10.1109/ICSSE.2017.8030921
Nguyen Vinh Quan, Ng M Tam, N. Nhờ, Duong Hoai Nghia
A stator-flux-oriented vector controller of induction motor is often used in the controllers due to less depending on parameters of the motors, the parameters of the motors are nonlinear and time-varying solution conditions slip control will be applied by the brilliant advantages of stability control is slipping sustainable and as soon as the system noise. On the other hand, when the parameters of nonlinear objects changes over time, the problems keep constant speed when the load changes are difficult to implement, therefore the neural network is used to identify the speed of machines are needed to increase the stability control system. This article presents a new method of designing sliding mode controller based on radial basic function network (RBF) for three-phase asynchronous motors based a stator-flux-oriented vector controller. Two sliding controllers are designed independently for stator-flux-vector estimation and torque, in which magnetic flux is estimated and the speed of the motor is identified by RBF network, combined seven - level cascade inverter with a reduction common-mode algorithm applied to increase the stability for the controller. Simulations and experiments using Matlab / Simulink for 1-hp induction motor drive, typed 150-rad/s squirrel cage rotor, the results present velocity followed setting values at the frequency change from the lowest 50-rad/s to 150 rad highest/s, the system is still stable when the stator is changed stator resistance and rotor resistance up to 1.5 times the original value.
{"title":"Sliding mode control of a three phase induction motor based on RBF neural network","authors":"Nguyen Vinh Quan, Ng M Tam, N. Nhờ, Duong Hoai Nghia","doi":"10.1109/ICSSE.2017.8030921","DOIUrl":"https://doi.org/10.1109/ICSSE.2017.8030921","url":null,"abstract":"A stator-flux-oriented vector controller of induction motor is often used in the controllers due to less depending on parameters of the motors, the parameters of the motors are nonlinear and time-varying solution conditions slip control will be applied by the brilliant advantages of stability control is slipping sustainable and as soon as the system noise. On the other hand, when the parameters of nonlinear objects changes over time, the problems keep constant speed when the load changes are difficult to implement, therefore the neural network is used to identify the speed of machines are needed to increase the stability control system. This article presents a new method of designing sliding mode controller based on radial basic function network (RBF) for three-phase asynchronous motors based a stator-flux-oriented vector controller. Two sliding controllers are designed independently for stator-flux-vector estimation and torque, in which magnetic flux is estimated and the speed of the motor is identified by RBF network, combined seven - level cascade inverter with a reduction common-mode algorithm applied to increase the stability for the controller. Simulations and experiments using Matlab / Simulink for 1-hp induction motor drive, typed 150-rad/s squirrel cage rotor, the results present velocity followed setting values at the frequency change from the lowest 50-rad/s to 150 rad highest/s, the system is still stable when the stator is changed stator resistance and rotor resistance up to 1.5 times the original value.","PeriodicalId":296191,"journal":{"name":"2017 International Conference on System Science and Engineering (ICSSE)","volume":"21 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122837041","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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