Pub Date : 2010-06-21DOI: 10.1109/AIS.2010.5547022
E. Pereira, J. Sousa
We discuss the problem of dynamic reallocation of vehicles among teams of Unmanned Air Vehicles (UAV) executing concurrently. Each team addresses a task that consists of a sequence of subtasks to be executed in an adversary environment, where the vehicles face the risk of becoming inoperative. Our approach consists on separating the problem into a planning procedure followed by an optimal control problem, which is solved using stochastic dynamic programming (DP). We consider mixed-initiative interactions, where human operators are able to tune parameters of the problem according to their experience. The main goal of execution control is to balance the performance of teams in order to increase the success of the overall mission.
{"title":"Reallocations in teams of UAVs using dynamic programming and mixed initiative interactions","authors":"E. Pereira, J. Sousa","doi":"10.1109/AIS.2010.5547022","DOIUrl":"https://doi.org/10.1109/AIS.2010.5547022","url":null,"abstract":"We discuss the problem of dynamic reallocation of vehicles among teams of Unmanned Air Vehicles (UAV) executing concurrently. Each team addresses a task that consists of a sequence of subtasks to be executed in an adversary environment, where the vehicles face the risk of becoming inoperative. Our approach consists on separating the problem into a planning procedure followed by an optimal control problem, which is solved using stochastic dynamic programming (DP). We consider mixed-initiative interactions, where human operators are able to tune parameters of the problem according to their experience. The main goal of execution control is to balance the performance of teams in order to increase the success of the overall mission.","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"1 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79774230","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 : 2010-06-21DOI: 10.1109/AIS.2010.5547039
Chao Chen, D. Zhang, Lei Zhang, Yongqiang Zhao
Segmentation of fingerprint image is the first step of fingerprint recognition, and it plays an essential role which helps to preserve genuine and reduce false minutiae and further aids the performance of Automatic Fingerprint Identification System (AFIS). The problem of segmentation has been thoroughly studied but never been completely solved. During this paper, we propose a novel representation of fingerprint image with the added polari-metric information which is captured by Stokes Imaging System, and followed by a simple yet efficient segmentation of fingerprint image based on the polarimetric variance (Polvar). Polarimetric characteristic is another distinguishable feature beside intense that reflecting light carries, and it provides potential way to enhance the contrast between background and foreground, and between ridges and valleys as well. And therefore, there is a possibility to achieve a satisfactory segmentation results. Non-overlapping block Polvar feature is utilized to accelerate computation, and moreover the segmentation results that are based on other common used features are compared, that is block energy, block coherence, block cluster degree. Experimental results show that our proposed novel method is much efficient than the other features and simultaneously achieve higher accuracy especially it well segments the case of remaining ridges from previously scanned finger. Segmentation results are evaluated both visually by human inspire and quantitatively.
{"title":"Segmentation of fingerprint image by using polarimetric feature","authors":"Chao Chen, D. Zhang, Lei Zhang, Yongqiang Zhao","doi":"10.1109/AIS.2010.5547039","DOIUrl":"https://doi.org/10.1109/AIS.2010.5547039","url":null,"abstract":"Segmentation of fingerprint image is the first step of fingerprint recognition, and it plays an essential role which helps to preserve genuine and reduce false minutiae and further aids the performance of Automatic Fingerprint Identification System (AFIS). The problem of segmentation has been thoroughly studied but never been completely solved. During this paper, we propose a novel representation of fingerprint image with the added polari-metric information which is captured by Stokes Imaging System, and followed by a simple yet efficient segmentation of fingerprint image based on the polarimetric variance (Polvar). Polarimetric characteristic is another distinguishable feature beside intense that reflecting light carries, and it provides potential way to enhance the contrast between background and foreground, and between ridges and valleys as well. And therefore, there is a possibility to achieve a satisfactory segmentation results. Non-overlapping block Polvar feature is utilized to accelerate computation, and moreover the segmentation results that are based on other common used features are compared, that is block energy, block coherence, block cluster degree. Experimental results show that our proposed novel method is much efficient than the other features and simultaneously achieve higher accuracy especially it well segments the case of remaining ridges from previously scanned finger. Segmentation results are evaluated both visually by human inspire and quantitatively.","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"1 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83033634","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 : 2010-06-21DOI: 10.1109/AIS.2010.5547018
K. Belghith, F. Kabanza, L. Hartman
In this paper we describe a new randomized path-planning approach presenting two novel features that are useful in various complex real-world applications. First, it handles zones in the robot workspace with different degrees of desirability. Given the random quality of paths that are calculated by traditional randomized approaches, this provides a mean to specify a sampling strategy that controls the search process to generate better paths by simply annotating regions in the free workspace with degrees of desirability. Second, our approach can efficiently re-compute paths in dynamic environments where obstacles and zones can change shape or move concurrently with the robot. The new path planner is implemented within an automated planning application for generating 3D tasks demonstrations involving a teleoperated robot arm on the International Space Station (ISS). A typical task demonstration involves moving the robot arm from one configuration to another. Our objective is to automatically plan the position of cameras to film the arm in a manner that conveys the best awareness of the robot trajectory to the user. For a given task, the robot trajectory is generated using the new path planner. The latter not only computes collision free paths but also takes into account the limited direct view of the ISS, the lighting conditions and other safety constraints about operating the robot. A suitable camera planning system is then used to find the best sequence of camera shots following the robot on its path.
{"title":"Using a randomized path planner to generate 3D task demonstrations of robot operations","authors":"K. Belghith, F. Kabanza, L. Hartman","doi":"10.1109/AIS.2010.5547018","DOIUrl":"https://doi.org/10.1109/AIS.2010.5547018","url":null,"abstract":"In this paper we describe a new randomized path-planning approach presenting two novel features that are useful in various complex real-world applications. First, it handles zones in the robot workspace with different degrees of desirability. Given the random quality of paths that are calculated by traditional randomized approaches, this provides a mean to specify a sampling strategy that controls the search process to generate better paths by simply annotating regions in the free workspace with degrees of desirability. Second, our approach can efficiently re-compute paths in dynamic environments where obstacles and zones can change shape or move concurrently with the robot. The new path planner is implemented within an automated planning application for generating 3D tasks demonstrations involving a teleoperated robot arm on the International Space Station (ISS). A typical task demonstration involves moving the robot arm from one configuration to another. Our objective is to automatically plan the position of cameras to film the arm in a manner that conveys the best awareness of the robot trajectory to the user. For a given task, the robot trajectory is generated using the new path planner. The latter not only computes collision free paths but also takes into account the limited direct view of the ISS, the lighting conditions and other safety constraints about operating the robot. A suitable camera planning system is then used to find the best sequence of camera shots following the robot on its path.","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"28 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78740193","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 : 2010-06-21DOI: 10.1109/AIS.2010.5547045
C. Papaodysseus, P. Rousopoulos, Dimitris Arabadjis, Fivi Panopoulou, M. Panagopoulos
In this paper a new approach is presented for automatic writer identification. The approach is applied to the identification of the writer of ancient Greek inscriptions that in turn may offer precise and objective dating of the inscriptions content. Such a dating is crucial for the correct history writing. The methodology is based on the idea of creating an ideal representative of each alphabet symbol in each inscription, via proper fitting of all realizations of the specific symbol in this inscription. Next, geometric features for the ideal representative for each alphabet symbol are defined and extracted and corresponding statistical processing follows based on the computation of the mean value and variance of these characteristics. The decision for writer identification is made via pair-wise, feature based comparisons of the ideal representatives of the inscriptions. Each comparison is implemented by means of multiple statistical tests and an introduced maximum likelihood approach. The system was applied to 33 Athenian inscriptions of classical era which were correctly attributed to 8 different hands, namely with 100% success rate.
{"title":"Handwriting automatic classification: Application to ancient Greek inscriptions","authors":"C. Papaodysseus, P. Rousopoulos, Dimitris Arabadjis, Fivi Panopoulou, M. Panagopoulos","doi":"10.1109/AIS.2010.5547045","DOIUrl":"https://doi.org/10.1109/AIS.2010.5547045","url":null,"abstract":"In this paper a new approach is presented for automatic writer identification. The approach is applied to the identification of the writer of ancient Greek inscriptions that in turn may offer precise and objective dating of the inscriptions content. Such a dating is crucial for the correct history writing. The methodology is based on the idea of creating an ideal representative of each alphabet symbol in each inscription, via proper fitting of all realizations of the specific symbol in this inscription. Next, geometric features for the ideal representative for each alphabet symbol are defined and extracted and corresponding statistical processing follows based on the computation of the mean value and variance of these characteristics. The decision for writer identification is made via pair-wise, feature based comparisons of the ideal representatives of the inscriptions. Each comparison is implemented by means of multiple statistical tests and an introduced maximum likelihood approach. The system was applied to 33 Athenian inscriptions of classical era which were correctly attributed to 8 different hands, namely with 100% success rate.","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"79 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79892656","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 : 2010-06-21DOI: 10.1109/AIS.2010.5547050
Bob Zhang, F. Karray
The optic disc (OD) and fovea are important anatomical features in retinal images. Its detections are crucial for developing an automated screening program. This paper proposes a method to automatically detect the OD and fovea in fundus images in three stages: OD vessel candidate detection, OD vessel candidate matching, and fovea detection. The first stage is achieved with multi-scale Gaussian filtering, scale production, and double thresholding to initially extract the vessels' directional map. The map is then thinned before another threshold is applied to remove pixels with low intensities. This result forms the OD vessel candidates. In the second stage, a Vessels' Directional Matched Filter (VDMF) of various dimensions is applied to the candidates to be matched, and the pixel with the smallest difference designated the OD center. Finally, the fovea is detected as the pixel with lowest intensity in a window either to the left or right of the OD center. We tested the proposed method on a subset of a new database consisting of 139 images from a diabetic retinopathy (DR) screening programme. The OD center and fovea were successfully detected with accuracies of 96.4% (134/139) and 98.1% (105/107) respectively.
{"title":"Optic disc and fovea detection via multi-scale matched filters and a vessels' directional matched filter","authors":"Bob Zhang, F. Karray","doi":"10.1109/AIS.2010.5547050","DOIUrl":"https://doi.org/10.1109/AIS.2010.5547050","url":null,"abstract":"The optic disc (OD) and fovea are important anatomical features in retinal images. Its detections are crucial for developing an automated screening program. This paper proposes a method to automatically detect the OD and fovea in fundus images in three stages: OD vessel candidate detection, OD vessel candidate matching, and fovea detection. The first stage is achieved with multi-scale Gaussian filtering, scale production, and double thresholding to initially extract the vessels' directional map. The map is then thinned before another threshold is applied to remove pixels with low intensities. This result forms the OD vessel candidates. In the second stage, a Vessels' Directional Matched Filter (VDMF) of various dimensions is applied to the candidates to be matched, and the pixel with the smallest difference designated the OD center. Finally, the fovea is detected as the pixel with lowest intensity in a window either to the left or right of the OD center. We tested the proposed method on a subset of a new database consisting of 139 images from a diabetic retinopathy (DR) screening programme. The OD center and fovea were successfully detected with accuracies of 96.4% (134/139) and 98.1% (105/107) respectively.","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"64 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80338816","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 : 2010-06-21DOI: 10.2316/Journal.201.2011.4.201-2292
C. Cocaud, A. Jnifene
This paper presents the implementation of an environment mapping technique based on a probabilistic quadtree which records the location of static and dynamic obstacles, as well as the certainty over each obstacle's estimated position. The quadtree-based map is updated online (i.e. near-real time) based on multi-sensor feeds originating from one to three X80 mobile robots operating simultaneously. The probabilistic quadtree map is part of a guidance and navigation control system which combines a Genetic Algorithm-based global path planner and a Potential Field local controller. The centralized map is shared by all mobile robots although each robot has an independent controller. Performance of the proposed method for this guidance and navigation control system is demonstrated experimentally with the Dr. Robot's ™ wireless X80 mobile robots.
{"title":"Environment mapping using probabilistic quadtree for the guidance and control of autonomous mobile robots","authors":"C. Cocaud, A. Jnifene","doi":"10.2316/Journal.201.2011.4.201-2292","DOIUrl":"https://doi.org/10.2316/Journal.201.2011.4.201-2292","url":null,"abstract":"This paper presents the implementation of an environment mapping technique based on a probabilistic quadtree which records the location of static and dynamic obstacles, as well as the certainty over each obstacle's estimated position. The quadtree-based map is updated online (i.e. near-real time) based on multi-sensor feeds originating from one to three X80 mobile robots operating simultaneously. The probabilistic quadtree map is part of a guidance and navigation control system which combines a Genetic Algorithm-based global path planner and a Potential Field local controller. The centralized map is shared by all mobile robots although each robot has an independent controller. Performance of the proposed method for this guidance and navigation control system is demonstrated experimentally with the Dr. Robot's ™ wireless X80 mobile robots.","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"27 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82294421","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 : 2010-06-21DOI: 10.1109/AIS.2010.5547053
Arvind Dorai, K. Ponnambalam
Epilepsy is a serious neurological disorder characterized by recurrent unprovoked seizures due to abnormal or excessive neuronal activity in the brain. An estimated 50 million people around the world suffer from this condition, and it is classified as the second most serious neurological disease known to humanity, after stroke. With early and accurate detection of seizures, doctors can gain valuable time to administer medications and other such anti-seizure countermeasures to help reduce the damaging effects of this crippling disorder. The time-varying dynamics and high inter-individual variability make early prediction of the seizure state a challenging task. Many studies have shown that EEG signals do have valuable information that, if correctly analyzed, could help in the prediction of seizures in epileptic patients before their occurrence. Several mathematical transforms have been analyzed for its correlation with seizure onset prediction, and a series of experiments were done to certify their strengths. New algorithms are presented to help clarify, monitor, and cross-validate the classification of EEG signals to predict the ictal (i.e. seizure) states, specifically the preictal, interictal, and postictal states in the brain. These new methods show promising results in detecting the presence of a preictal phase prior to the ictal state.
{"title":"Automated epileptic seizure onset detection","authors":"Arvind Dorai, K. Ponnambalam","doi":"10.1109/AIS.2010.5547053","DOIUrl":"https://doi.org/10.1109/AIS.2010.5547053","url":null,"abstract":"Epilepsy is a serious neurological disorder characterized by recurrent unprovoked seizures due to abnormal or excessive neuronal activity in the brain. An estimated 50 million people around the world suffer from this condition, and it is classified as the second most serious neurological disease known to humanity, after stroke. With early and accurate detection of seizures, doctors can gain valuable time to administer medications and other such anti-seizure countermeasures to help reduce the damaging effects of this crippling disorder. The time-varying dynamics and high inter-individual variability make early prediction of the seizure state a challenging task. Many studies have shown that EEG signals do have valuable information that, if correctly analyzed, could help in the prediction of seizures in epileptic patients before their occurrence. Several mathematical transforms have been analyzed for its correlation with seizure onset prediction, and a series of experiments were done to certify their strengths. New algorithms are presented to help clarify, monitor, and cross-validate the classification of EEG signals to predict the ictal (i.e. seizure) states, specifically the preictal, interictal, and postictal states in the brain. These new methods show promising results in detecting the presence of a preictal phase prior to the ictal state.","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"46 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78818378","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 : 2010-06-21DOI: 10.1109/AIS.2010.5547033
J. Silva, J. Sousa
The problem of path following for autonomous vehicles under adversarial behavior is considered. The objective is to keep the cross-track error to the reference path inside a given tolerance interval. The adversarial behavior models system uncertainty and unknown or poorly estimated bounded disturbances. The first step to that objective is the computation of an invariant set, namely the maximal set of states that the vehicle may enter while ensuring that the cross-track error will never exceed the tolerance interval. This is done through dynamic programming. Two modes of operation are then considered: when the vehicle is inside the invariant set, the objective is to stay inside it while minimizing a combination of the actuation effort and cross-track error; otherwise, the objective becomes to reach the invariant set in minimum time. Each mode corresponds to a different optimal control problem which is dealt independently; thus, each mode has a corresponding control law. We discuss efficient ways of computing and implementing those control laws on currently available computational systems. For the purpose of the dynamic programming approach, the autonomous vehicles are modeled as an unicycle. Simulations with a six degree of freedom nonlinear model of an autonomous submarine are performed in order to illustrate the robustness of the control strategy.
{"title":"A dynamic programming approach for the control of autonomous vehicles on planar motion","authors":"J. Silva, J. Sousa","doi":"10.1109/AIS.2010.5547033","DOIUrl":"https://doi.org/10.1109/AIS.2010.5547033","url":null,"abstract":"The problem of path following for autonomous vehicles under adversarial behavior is considered. The objective is to keep the cross-track error to the reference path inside a given tolerance interval. The adversarial behavior models system uncertainty and unknown or poorly estimated bounded disturbances. The first step to that objective is the computation of an invariant set, namely the maximal set of states that the vehicle may enter while ensuring that the cross-track error will never exceed the tolerance interval. This is done through dynamic programming. Two modes of operation are then considered: when the vehicle is inside the invariant set, the objective is to stay inside it while minimizing a combination of the actuation effort and cross-track error; otherwise, the objective becomes to reach the invariant set in minimum time. Each mode corresponds to a different optimal control problem which is dealt independently; thus, each mode has a corresponding control law. We discuss efficient ways of computing and implementing those control laws on currently available computational systems. For the purpose of the dynamic programming approach, the autonomous vehicles are modeled as an unicycle. Simulations with a six degree of freedom nonlinear model of an autonomous submarine are performed in order to illustrate the robustness of the control strategy.","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"76 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87053248","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 : 2010-06-21DOI: 10.1109/AIS.2010.5547046
Qin Li, Jinghua Wang, J. You, Bob Zhang, F. Karray
Nowadays large populations worldwide are suffering from eye diseases such as astigmatism, myopia, and hyperopia which are caused by ophthalmologically refractive errors. This paper presents an effective approach to computer aided diagnosis of such eye diseases due to ophthalmologically refractive errors. The proposed system consists of two major steps: (1) image segmentation and geometrical feature extraction; (2) group sparse representation based classification. Although image segmentation seems relatively easy and straight forward, it is a challenge task to achieve high accuracy of segmentation for images at poor quality caused by distortion during image digitization. To avoid misclassifications by incomplete information, we propose group sparse representation-based classification scheme to classify low-dimensional data which are partially corrupted. The experimental results demonstrate the feasibility of the new classification scheme with good performance for potential medical applications.
{"title":"Refractive error detection via group sparse representation","authors":"Qin Li, Jinghua Wang, J. You, Bob Zhang, F. Karray","doi":"10.1109/AIS.2010.5547046","DOIUrl":"https://doi.org/10.1109/AIS.2010.5547046","url":null,"abstract":"Nowadays large populations worldwide are suffering from eye diseases such as astigmatism, myopia, and hyperopia which are caused by ophthalmologically refractive errors. This paper presents an effective approach to computer aided diagnosis of such eye diseases due to ophthalmologically refractive errors. The proposed system consists of two major steps: (1) image segmentation and geometrical feature extraction; (2) group sparse representation based classification. Although image segmentation seems relatively easy and straight forward, it is a challenge task to achieve high accuracy of segmentation for images at poor quality caused by distortion during image digitization. To avoid misclassifications by incomplete information, we propose group sparse representation-based classification scheme to classify low-dimensional data which are partially corrupted. The experimental results demonstrate the feasibility of the new classification scheme with good performance for potential medical applications.","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"70 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73491276","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 : 2010-06-21DOI: 10.1109/AIS.2010.5547030
P. Zbranek, L. Veselý
The main idea presented in this paper is to use interval analysis technique on state estimation of nonlinear dynamic system, in this concrete case the PMSM (Permanent Magnet Synchronous Machine). PMSM drives offers in comparison to other drives several advantages but it is necessary to have knowledge of actual rotor position and actual speed of rotation for precise control. Measurement of these state variables is technically or financially unnecessarily consumptive. These data are usually obtained by state observers, in most cases by extended Kalman filter or his modifications. Unfortunately, in many cases this is insufficient. That is why other methods of state estimation are being researched. One of these methods is interval analysis in which results are not points, but intervals. Advantage of this is that these intervals are guaranteed.
{"title":"Nonlinear state estimation using interval computation in PMSM state observer simulation","authors":"P. Zbranek, L. Veselý","doi":"10.1109/AIS.2010.5547030","DOIUrl":"https://doi.org/10.1109/AIS.2010.5547030","url":null,"abstract":"The main idea presented in this paper is to use interval analysis technique on state estimation of nonlinear dynamic system, in this concrete case the PMSM (Permanent Magnet Synchronous Machine). PMSM drives offers in comparison to other drives several advantages but it is necessary to have knowledge of actual rotor position and actual speed of rotation for precise control. Measurement of these state variables is technically or financially unnecessarily consumptive. These data are usually obtained by state observers, in most cases by extended Kalman filter or his modifications. Unfortunately, in many cases this is insufficient. That is why other methods of state estimation are being researched. One of these methods is interval analysis in which results are not points, but intervals. Advantage of this is that these intervals are guaranteed.","PeriodicalId":71187,"journal":{"name":"自主智能系统(英文)","volume":"42 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2010-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75196974","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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