Pub Date : 2011-03-14DOI: 10.1109/ICIT.2011.5754350
A. Kebairi, M. Becherif, M. El Bagdouri, S. Cai
This paper deals with the modeling, identification and control of the Pierburg mechatronic actuator. This actuator is used in the BMW M57 diesel engine to control all the air which are charged and entered in the vehicle engine. The actuator static characteristics are exploited to model the system dynamics. Then, the obtained model from the identification procedure is used to design a nonlinear control based on the backstepping and Lyapunov theory. Simulation and experimental results are presented.
{"title":"Modeling and backstepping-based control of an electromechanical actuator","authors":"A. Kebairi, M. Becherif, M. El Bagdouri, S. Cai","doi":"10.1109/ICIT.2011.5754350","DOIUrl":"https://doi.org/10.1109/ICIT.2011.5754350","url":null,"abstract":"This paper deals with the modeling, identification and control of the Pierburg mechatronic actuator. This actuator is used in the BMW M57 diesel engine to control all the air which are charged and entered in the vehicle engine. The actuator static characteristics are exploited to model the system dynamics. Then, the obtained model from the identification procedure is used to design a nonlinear control based on the backstepping and Lyapunov theory. Simulation and experimental results are presented.","PeriodicalId":356868,"journal":{"name":"2011 IEEE International Conference on Industrial Technology","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127909656","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 : 2011-03-14DOI: 10.1109/ICIT.2011.5754358
Fei Xu, Liming Shi
High speed maglev maintenance vehicle (MMV) is propelled by multiple in-wheel-induction-motors drive system (IWIM). This paper analyses the characteristics of multiple IWIM drive system for MMV. An electromechanical simulation platform is developed in our Lab. Adaptive flux observer is applied to provide speed sensor-less vector control for multiple IWIM drive system. The influences of different wheel radius, motor parameters and control schemes are simulated by setting different coefficient of radius and motor parameters. It shows that radius difference may seriously cause speed and traction force difference, and motor parameter difference may deteriorate dynamical performance. The coordinating motor control can improve the performance of multi-motors with less hard and software increase.
{"title":"Characteristics analysis of multiple in-wheel-induction-motors drive system","authors":"Fei Xu, Liming Shi","doi":"10.1109/ICIT.2011.5754358","DOIUrl":"https://doi.org/10.1109/ICIT.2011.5754358","url":null,"abstract":"High speed maglev maintenance vehicle (MMV) is propelled by multiple in-wheel-induction-motors drive system (IWIM). This paper analyses the characteristics of multiple IWIM drive system for MMV. An electromechanical simulation platform is developed in our Lab. Adaptive flux observer is applied to provide speed sensor-less vector control for multiple IWIM drive system. The influences of different wheel radius, motor parameters and control schemes are simulated by setting different coefficient of radius and motor parameters. It shows that radius difference may seriously cause speed and traction force difference, and motor parameter difference may deteriorate dynamical performance. The coordinating motor control can improve the performance of multi-motors with less hard and software increase.","PeriodicalId":356868,"journal":{"name":"2011 IEEE International Conference on Industrial Technology","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133359801","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 : 2011-03-14DOI: 10.1109/ICIT.2011.5754349
Hiroshi Matsuki, Y. Fujimoto
This study aims to replicate knowledge of operation for water supply system. The proposed method is able to extract knowledge of operation of experienced operators, and regenerate a plan of operation by using support vector regression. The proposed method can contribute to compensating for reduction of experienced operators.
{"title":"Knowledge acquisition from in-operation data for water supply system","authors":"Hiroshi Matsuki, Y. Fujimoto","doi":"10.1109/ICIT.2011.5754349","DOIUrl":"https://doi.org/10.1109/ICIT.2011.5754349","url":null,"abstract":"This study aims to replicate knowledge of operation for water supply system. The proposed method is able to extract knowledge of operation of experienced operators, and regenerate a plan of operation by using support vector regression. The proposed method can contribute to compensating for reduction of experienced operators.","PeriodicalId":356868,"journal":{"name":"2011 IEEE International Conference on Industrial Technology","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131880213","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 : 2011-03-14DOI: 10.1109/ICIT.2011.5754392
Ismail H. Akyuz, S. Kizir, Z. Bingul
In this paper, a single-link flexible joint robot is designed, fabricated and controlled. Three different fuzzy logic controllers (FLCs) were used to remove link vibrations and to obtain accurate trajectory tracking of link end-point. The input variables of the first and the second FLCs are motor rotation angle error and its derivative, and end-effector deflection error and derivative of deflection error, respectively. The outputs of these controllers are inputs of the third FLC producing the control signal of the flexible joint system. All of the FLCs were embedded in ds1103 real time control board. In the step response experiments, the error of motor rotation angle was obtained less than 0.12 degree and there was no steady-state error in the end-effector deflection. In the different trajectory-tracking experiments with the same FLC structure, small errors and phase shift in the system variables were occurred. Also, parameters of flexible arm were changed to test robustness of the FLC. It is seen that FLC are very robust to internal and external disturbances. Considering the all results of the experiments, FLC shows efficient performance in flexible robot arm.
{"title":"Fuzzy logic control of single-link flexible joint manipulator","authors":"Ismail H. Akyuz, S. Kizir, Z. Bingul","doi":"10.1109/ICIT.2011.5754392","DOIUrl":"https://doi.org/10.1109/ICIT.2011.5754392","url":null,"abstract":"In this paper, a single-link flexible joint robot is designed, fabricated and controlled. Three different fuzzy logic controllers (FLCs) were used to remove link vibrations and to obtain accurate trajectory tracking of link end-point. The input variables of the first and the second FLCs are motor rotation angle error and its derivative, and end-effector deflection error and derivative of deflection error, respectively. The outputs of these controllers are inputs of the third FLC producing the control signal of the flexible joint system. All of the FLCs were embedded in ds1103 real time control board. In the step response experiments, the error of motor rotation angle was obtained less than 0.12 degree and there was no steady-state error in the end-effector deflection. In the different trajectory-tracking experiments with the same FLC structure, small errors and phase shift in the system variables were occurred. Also, parameters of flexible arm were changed to test robustness of the FLC. It is seen that FLC are very robust to internal and external disturbances. Considering the all results of the experiments, FLC shows efficient performance in flexible robot arm.","PeriodicalId":356868,"journal":{"name":"2011 IEEE International Conference on Industrial Technology","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132258656","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 : 2011-03-14DOI: 10.1109/ICIT.2011.5754336
B. Wilamowski
In the presentation major difficulties of designing neural networks are shown. It turn out that popular MLP (Multi Layer Perceptron) networks in most cases produces far from satisfactory results. Also, popular EBP (Error Back Propagation) algorithm is very slow and often is not capable to train best neural network architectures. Very powerful and fast LM (Levenberg- Marquardt) algorithm was unfortunately implemented only for MLP networks. Also, because a necessity of the inversion of the matrix, which size is proportional to number of patterns, the LM algorithm can be used only for small problems. However, the major frustration with neural networks occurs when too large neural networks are used and it is being trained with too small number of training patterns. Indeed, such networks, with excessive number of neurons, can be trained to very small errors, but these networks will respond very poorly for new patterns, which were not used for training. The most of frustrations with neural network can be eliminated when smaller, more effective, architectures are used and trained by newly developed NBN (Neuron-by-Neuron) algorithm.
{"title":"How to not get frustrated with neural networks","authors":"B. Wilamowski","doi":"10.1109/ICIT.2011.5754336","DOIUrl":"https://doi.org/10.1109/ICIT.2011.5754336","url":null,"abstract":"In the presentation major difficulties of designing neural networks are shown. It turn out that popular MLP (Multi Layer Perceptron) networks in most cases produces far from satisfactory results. Also, popular EBP (Error Back Propagation) algorithm is very slow and often is not capable to train best neural network architectures. Very powerful and fast LM (Levenberg- Marquardt) algorithm was unfortunately implemented only for MLP networks. Also, because a necessity of the inversion of the matrix, which size is proportional to number of patterns, the LM algorithm can be used only for small problems. However, the major frustration with neural networks occurs when too large neural networks are used and it is being trained with too small number of training patterns. Indeed, such networks, with excessive number of neurons, can be trained to very small errors, but these networks will respond very poorly for new patterns, which were not used for training. The most of frustrations with neural network can be eliminated when smaller, more effective, architectures are used and trained by newly developed NBN (Neuron-by-Neuron) algorithm.","PeriodicalId":356868,"journal":{"name":"2011 IEEE International Conference on Industrial Technology","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129533033","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 : 2011-03-14DOI: 10.1109/ICIT.2011.5754394
T. Nagai, S. Aramaki, V. Moshnyaga
Industrial robots have been recently introduced into the assembly line of consumer products. To assemble a product, goal coordinates must be specified for the robot. Because this task is quite difficult and time-consuming, we propose computing the values of goal coordinates from an object model of target design. In this paper, we define a model capable of managing information necessary for assembling parts by a robot. The effectiveness of the model is verified by using an experimental system.
{"title":"The design object model for robotic assembly of mechanical components","authors":"T. Nagai, S. Aramaki, V. Moshnyaga","doi":"10.1109/ICIT.2011.5754394","DOIUrl":"https://doi.org/10.1109/ICIT.2011.5754394","url":null,"abstract":"Industrial robots have been recently introduced into the assembly line of consumer products. To assemble a product, goal coordinates must be specified for the robot. Because this task is quite difficult and time-consuming, we propose computing the values of goal coordinates from an object model of target design. In this paper, we define a model capable of managing information necessary for assembling parts by a robot. The effectiveness of the model is verified by using an experimental system.","PeriodicalId":356868,"journal":{"name":"2011 IEEE International Conference on Industrial Technology","volume":"519 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134405982","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 : 2011-03-14DOI: 10.1109/ICIT.2011.5754412
Md Atiqur Rahman Ahad, J. Tan, Hyoungseop Kim, S. Ishikawa
Researches on action understanding and analysis are very crucial for various applications in computer vision. However, these face numerous challenges to represent and recognize different complex actions. This paper presents a noble spatio-temporal 3D (XYT) method for recognizing various complex activities, with a blend of local and global feature-based approach for motion representation. We incorporate SURF (Speeded-Up Robust Features), which is a scale- and rotation-invariant interest point detector and descriptor. Based on the interest points, optical flow-based directional motion history and energy images are developed. In this approach, the flow-based motion vectors are split into four different channels. From these channels, the corresponding four directional templates are computed. 56-D feature vector is calculated according to the Hu invariants for each action. k-nearest neighbor classification scheme is employed for recognition. We employ leave-one-out cross-validation method for partitioning scheme. We apply our method to outdoor dataset and we achieve satisfactory recognition results. We compare our method with some of other approaches and show that our method outperforms them.
{"title":"SURF-based spatio-temporal history image method for action representation","authors":"Md Atiqur Rahman Ahad, J. Tan, Hyoungseop Kim, S. Ishikawa","doi":"10.1109/ICIT.2011.5754412","DOIUrl":"https://doi.org/10.1109/ICIT.2011.5754412","url":null,"abstract":"Researches on action understanding and analysis are very crucial for various applications in computer vision. However, these face numerous challenges to represent and recognize different complex actions. This paper presents a noble spatio-temporal 3D (XYT) method for recognizing various complex activities, with a blend of local and global feature-based approach for motion representation. We incorporate SURF (Speeded-Up Robust Features), which is a scale- and rotation-invariant interest point detector and descriptor. Based on the interest points, optical flow-based directional motion history and energy images are developed. In this approach, the flow-based motion vectors are split into four different channels. From these channels, the corresponding four directional templates are computed. 56-D feature vector is calculated according to the Hu invariants for each action. k-nearest neighbor classification scheme is employed for recognition. We employ leave-one-out cross-validation method for partitioning scheme. We apply our method to outdoor dataset and we achieve satisfactory recognition results. We compare our method with some of other approaches and show that our method outperforms them.","PeriodicalId":356868,"journal":{"name":"2011 IEEE International Conference on Industrial Technology","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133996781","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 : 2011-03-14DOI: 10.1109/ICIT.2011.5754377
C. Singh, K. Poddar
This paper presents the implementation aspects of an automated data acquisition system for low speed air-intake studies on aircraft models. The system has been developed at National Wind Tunnel Facility (NWTF), Indian Institute of Technology (IIT) Kanpur, (India) using virtual instrumentation technique and PXI (PCI eXtension for Instrumentation) architecture which enhances the productivity and reduces the cost through easy-to-integrate application software and PXI modular hardware. The application software of the system called virtual instrument has been developed using LabVIEW-based graphical development environment which enables the test engineer to configure the system easily to carry out air-intake studies for various intake aircraft configurations. The PXI architecture used for the system is very versatile and meets the specific needs of measurement and control applications by adding an integrated trigger bus and reference clock for multi-board synchronization. The system presented in this work has been used successfully for air-intake studies on various configurations of intake aircraft models.
{"title":"Development of an automated data acquisition system for low speed air-intake studies","authors":"C. Singh, K. Poddar","doi":"10.1109/ICIT.2011.5754377","DOIUrl":"https://doi.org/10.1109/ICIT.2011.5754377","url":null,"abstract":"This paper presents the implementation aspects of an automated data acquisition system for low speed air-intake studies on aircraft models. The system has been developed at National Wind Tunnel Facility (NWTF), Indian Institute of Technology (IIT) Kanpur, (India) using virtual instrumentation technique and PXI (PCI eXtension for Instrumentation) architecture which enhances the productivity and reduces the cost through easy-to-integrate application software and PXI modular hardware. The application software of the system called virtual instrument has been developed using LabVIEW-based graphical development environment which enables the test engineer to configure the system easily to carry out air-intake studies for various intake aircraft configurations. The PXI architecture used for the system is very versatile and meets the specific needs of measurement and control applications by adding an integrated trigger bus and reference clock for multi-board synchronization. The system presented in this work has been used successfully for air-intake studies on various configurations of intake aircraft models.","PeriodicalId":356868,"journal":{"name":"2011 IEEE International Conference on Industrial Technology","volume":"762 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133522951","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 : 2011-03-14DOI: 10.1109/ICIT.2011.5754398
G. Deshpande, Xiaoping Hu
In this paper we investigated the nonlinear sources of neurophysiologic changes in the motor cortex due to peripheral fatigue using functional magnetic resonance imaging (fMRI). The changes in nonlinearity was tracked from pre- to post-fatigue resting state using patterns of singularities in the complex plane. A significant decrease in nonlinearity with an accompanying decrease in determinism was observed post fatigue. The possible contributing factors for such a change include decreased excitability of cortical neurons and/or changes in neurovascular coupling. The dynamical changes of nonlinearity during the task showed a decrease in nonlinearity in the initial phase of the task followed by a partial recovery that continued into the post-fatigue resting state. This observation not only proves the hypothesis that cortical effects of fatigue extend beyond the fatiguing task, but also strengthens the possibility of changes in the nonlinearity of neurovascular coupling as a result of fatigue. Subsequently the source of nonlinearity was characterized using a polynomial differential equation model. We found that the nonlinearity is primarily driven by a square relation and to some extent by a logarithmic relation. Also, the magnitude of the coefficients contributing to these nonlinearities decrease post-fatigue confirming the earlier observation.
{"title":"Fatigue-induced changes in brain nonlinearity inferred by nonparametric and differential equation models of fMRI","authors":"G. Deshpande, Xiaoping Hu","doi":"10.1109/ICIT.2011.5754398","DOIUrl":"https://doi.org/10.1109/ICIT.2011.5754398","url":null,"abstract":"In this paper we investigated the nonlinear sources of neurophysiologic changes in the motor cortex due to peripheral fatigue using functional magnetic resonance imaging (fMRI). The changes in nonlinearity was tracked from pre- to post-fatigue resting state using patterns of singularities in the complex plane. A significant decrease in nonlinearity with an accompanying decrease in determinism was observed post fatigue. The possible contributing factors for such a change include decreased excitability of cortical neurons and/or changes in neurovascular coupling. The dynamical changes of nonlinearity during the task showed a decrease in nonlinearity in the initial phase of the task followed by a partial recovery that continued into the post-fatigue resting state. This observation not only proves the hypothesis that cortical effects of fatigue extend beyond the fatiguing task, but also strengthens the possibility of changes in the nonlinearity of neurovascular coupling as a result of fatigue. Subsequently the source of nonlinearity was characterized using a polynomial differential equation model. We found that the nonlinearity is primarily driven by a square relation and to some extent by a logarithmic relation. Also, the magnitude of the coefficients contributing to these nonlinearities decrease post-fatigue confirming the earlier observation.","PeriodicalId":356868,"journal":{"name":"2011 IEEE International Conference on Industrial Technology","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123271285","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 : 2011-03-14DOI: 10.1109/ICIT.2011.5754402
Duong-Van Nguyen, L. Kuhnert, Tao Jiang, S. Thamke, K. Kuhnert
Recently, there are many autonomous navigation applications done in outdoor environment. However, safe navigation is still a daunting challenge in terrain containing vegetation. Thus, a study on vegetation detection for outdoor automobile navigation is investigated in this work. At the early state of our research, we focused on the segmentation of LADAR data into two classes by using local three-dimensional point cloud statistics. The classes are: scatter to represent vegetation such as tall grasses, bushes and tree canopy, surface to capture solid objects like ground surface, rocks or tree trunks. However, the only use of 3D features would never result a real robust vegetation detection system because of lacking color information. We, hence, propose a 2D-3D combination approach which can utilize the complement of three-dimensional point distribution and color descriptor. Firstly, 3D point cloud is segmented into regions of homogeneous distance. The local point distribution is then analyzed for each region to extract scatter features. Secondly, a coarse 2D-3D calibration needs to be implemented in order to map the regions to the corresponding color image. Then, color descriptors are studied and applied to each region and considered as color features. Those all scatter and color features will be trained by Support Vector Machine to generate vegetation classifier. Finally, we will show the out-performance of this approach in comparison with more conventional approaches.
{"title":"Vegetation detection for outdoor automobile guidance","authors":"Duong-Van Nguyen, L. Kuhnert, Tao Jiang, S. Thamke, K. Kuhnert","doi":"10.1109/ICIT.2011.5754402","DOIUrl":"https://doi.org/10.1109/ICIT.2011.5754402","url":null,"abstract":"Recently, there are many autonomous navigation applications done in outdoor environment. However, safe navigation is still a daunting challenge in terrain containing vegetation. Thus, a study on vegetation detection for outdoor automobile navigation is investigated in this work. At the early state of our research, we focused on the segmentation of LADAR data into two classes by using local three-dimensional point cloud statistics. The classes are: scatter to represent vegetation such as tall grasses, bushes and tree canopy, surface to capture solid objects like ground surface, rocks or tree trunks. However, the only use of 3D features would never result a real robust vegetation detection system because of lacking color information. We, hence, propose a 2D-3D combination approach which can utilize the complement of three-dimensional point distribution and color descriptor. Firstly, 3D point cloud is segmented into regions of homogeneous distance. The local point distribution is then analyzed for each region to extract scatter features. Secondly, a coarse 2D-3D calibration needs to be implemented in order to map the regions to the corresponding color image. Then, color descriptors are studied and applied to each region and considered as color features. Those all scatter and color features will be trained by Support Vector Machine to generate vegetation classifier. Finally, we will show the out-performance of this approach in comparison with more conventional approaches.","PeriodicalId":356868,"journal":{"name":"2011 IEEE International Conference on Industrial Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129570027","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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