Pub Date : 2012-12-01DOI: 10.1109/ICARCV.2012.6485350
R. Levy, S. Arogeti, Danwei W. Wang
In this paper, we integrate information from a hybrid bond graph (HBG) model and discrete event systems (DES) into a fault diagnosis method for hybrid systems. In a pure HBG framework, mode change detection and isolation is handled by the mode change signature and the mode change signature matrix. In a DES approach, discrete states and faults are traced based on observable events and diagnosers. The integration of the two approaches is based on a new diagnoser that is driven by both, observable events and consistency indicators generated by continuous residuals. The proposed method allows not only to effectively trace the system mode, but also to decide whether this mode is faulty or normal. The new method is presented along with a theoretical example.
{"title":"Mode tracking and diagnosis of hybrid systems, an integrated approach","authors":"R. Levy, S. Arogeti, Danwei W. Wang","doi":"10.1109/ICARCV.2012.6485350","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485350","url":null,"abstract":"In this paper, we integrate information from a hybrid bond graph (HBG) model and discrete event systems (DES) into a fault diagnosis method for hybrid systems. In a pure HBG framework, mode change detection and isolation is handled by the mode change signature and the mode change signature matrix. In a DES approach, discrete states and faults are traced based on observable events and diagnosers. The integration of the two approaches is based on a new diagnoser that is driven by both, observable events and consistency indicators generated by continuous residuals. The proposed method allows not only to effectively trace the system mode, but also to decide whether this mode is faulty or normal. The new method is presented along with a theoretical example.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114202657","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 : 2012-12-01DOI: 10.1109/ICARCV.2012.6485322
Wu Jiayun, L. Bin
The detection of object regions based on local saliency has been with great interest in computer vision for its potential contributions to applications, such as recognition, because objects of interest could be contained in salient regions. However, regions are extracted from local salient locations by simple procedures without the global inference, resulting in poor segmentation of possible objects. In this paper, a two-strategy has been proposed to introduce local saliency into foreground subtraction, a color grouping method. By using only color information and no prior higher level knowledge about objects and scenes, multiple foreground regions are extracted simultaneously according to visual attention based salient locations. The prominence score is defined to further evaluate these regions for their possibility to contain objects of interest.
{"title":"A color grouping method for detection of object regions based on local saliency","authors":"Wu Jiayun, L. Bin","doi":"10.1109/ICARCV.2012.6485322","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485322","url":null,"abstract":"The detection of object regions based on local saliency has been with great interest in computer vision for its potential contributions to applications, such as recognition, because objects of interest could be contained in salient regions. However, regions are extracted from local salient locations by simple procedures without the global inference, resulting in poor segmentation of possible objects. In this paper, a two-strategy has been proposed to introduce local saliency into foreground subtraction, a color grouping method. By using only color information and no prior higher level knowledge about objects and scenes, multiple foreground regions are extracted simultaneously according to visual attention based salient locations. The prominence score is defined to further evaluate these regions for their possibility to contain objects of interest.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"23 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120911377","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 : 2012-12-01DOI: 10.1109/ICARCV.2012.6485280
Peng Cui, M. Fu
A distributed steady-state estimator is presented for linear interconnected systems. Stability of the distributed estimator is investigated. Sufficient conditions of stability are deduced based on the state and observation models. Some examples are provided to illustrate the relationship between the stability of the estimator and that of the original dynamics.
{"title":"Stability analysis of a distributed state estimator for linear systems","authors":"Peng Cui, M. Fu","doi":"10.1109/ICARCV.2012.6485280","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485280","url":null,"abstract":"A distributed steady-state estimator is presented for linear interconnected systems. Stability of the distributed estimator is investigated. Sufficient conditions of stability are deduced based on the state and observation models. Some examples are provided to illustrate the relationship between the stability of the estimator and that of the original dynamics.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116197997","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 : 2012-12-01DOI: 10.1109/ICARCV.2012.6485300
Jared Le Cras, J. Paxman
Underground mining environments pose many unique challenges to the task of creating extensive, survey quality 3D maps. The extreme characteristics of such environments require a modular mapping solution which has no dependency on Global Positioning Systems (GPS), physical odometry, a priori information or motion model simplification. These restrictions rule out many existing 3D mapping approaches. This work examines a hybrid approach to mapping, fusing omnidirectional vision and 3D range data to produce an automatically registered, accurate and dense 3D map. A series of discrete 3D laser scans are registered through a combination of vision based bearing-only localization and scan matching with the Iterative Closest Point (ICP) algorithm. Depth information provided by the laser scans is used to correctly scale the bearing-only feature map, which in turn supplies an initial pose estimate for a registration algorithm to build the 3D map and correct localization drift. The resulting extensive maps require no external instrumentation or a priori information. Preliminary testing demonstrated the ability of the hybrid system to produce a highly accurate 3D map of an extensive indoor space.
{"title":"A modular hybrid SLAM for the 3D mapping of large scale environments","authors":"Jared Le Cras, J. Paxman","doi":"10.1109/ICARCV.2012.6485300","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485300","url":null,"abstract":"Underground mining environments pose many unique challenges to the task of creating extensive, survey quality 3D maps. The extreme characteristics of such environments require a modular mapping solution which has no dependency on Global Positioning Systems (GPS), physical odometry, a priori information or motion model simplification. These restrictions rule out many existing 3D mapping approaches. This work examines a hybrid approach to mapping, fusing omnidirectional vision and 3D range data to produce an automatically registered, accurate and dense 3D map. A series of discrete 3D laser scans are registered through a combination of vision based bearing-only localization and scan matching with the Iterative Closest Point (ICP) algorithm. Depth information provided by the laser scans is used to correctly scale the bearing-only feature map, which in turn supplies an initial pose estimate for a registration algorithm to build the 3D map and correct localization drift. The resulting extensive maps require no external instrumentation or a priori information. Preliminary testing demonstrated the ability of the hybrid system to produce a highly accurate 3D map of an extensive indoor space.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115968646","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 : 2012-12-01DOI: 10.1109/ICARCV.2012.6485398
A. Delprado, R. Eaton
Algorithms to detect and track objects within an image have traditionally had large processing times and so have been used in an offline context. With computer power consistently increasing these algorithms are now able to be adapted to run within a realtime context. This paper proposes an algorithm to run line and circle detections with minimal computation time by tracking objects primarily for use with control systems. A particular case study is made with the Ball and Beam apparatus. Comparisons will be made with existing Hough Transform methods for the validity of the method and processing time.
{"title":"An efficient single Vote Hough tracking algorithm","authors":"A. Delprado, R. Eaton","doi":"10.1109/ICARCV.2012.6485398","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485398","url":null,"abstract":"Algorithms to detect and track objects within an image have traditionally had large processing times and so have been used in an offline context. With computer power consistently increasing these algorithms are now able to be adapted to run within a realtime context. This paper proposes an algorithm to run line and circle detections with minimal computation time by tracking objects primarily for use with control systems. A particular case study is made with the Ball and Beam apparatus. Comparisons will be made with existing Hough Transform methods for the validity of the method and processing time.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121206169","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 : 2012-12-01DOI: 10.1109/ICARCV.2012.6485367
Bei Chen, Y. Niu, Yuanyuan Zou
This work considers the problem of sliding mode control for stochastic systems with Markovian jumping parameters, in which the packet dropout may happen when the state information is transmitted from the sensor to the controller. By means of an estimator for loss signals, an integral-like sliding function is constructed. And then, a sliding mode controller involving in dropout probability is designed such that the effect of packet losses can be effectively attenuated. Moreover, the analysis on both the stability of sliding mode dynamics and the reachability of sliding surface are made. Finally, the numerical simulation results are given.
{"title":"Sliding mode control for networked systems with Markovian jumping parameters","authors":"Bei Chen, Y. Niu, Yuanyuan Zou","doi":"10.1109/ICARCV.2012.6485367","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485367","url":null,"abstract":"This work considers the problem of sliding mode control for stochastic systems with Markovian jumping parameters, in which the packet dropout may happen when the state information is transmitted from the sensor to the controller. By means of an estimator for loss signals, an integral-like sliding function is constructed. And then, a sliding mode controller involving in dropout probability is designed such that the effect of packet losses can be effectively attenuated. Moreover, the analysis on both the stability of sliding mode dynamics and the reachability of sliding surface are made. Finally, the numerical simulation results are given.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121817879","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}
Recently, safe diagnosability of discrete event systems (DESs) was investigated in the literature. This paper addresses the issue of safe diagnosability for fuzzy discrete event systems (FDESs). We formalize the notion of safe diagnosability for fuzzy automata, where the observability of fuzzy events is defined to be fuzzy instead of crisp. A safe diagnosable fuzzy automaton is required that not only faults can be detected with a certain degree but also fault detection must be completed before any forbidden string in the failed mode of system is executed. A fuzzy automaton called the recognizer is introduced to distinguish the forbidden strings from the illegal language. Then a safe diagnoser is constructed to perform safe diagnosis of FDESs. In particular, a necessary and sufficient condition of safe diagnosability for FDESs is derived, which extends the main results of safe diagnosability from crisp DESs to the setting of FDESs. Some illustrative examples are provided.
{"title":"Safe diagnosability of fuzzy discrete-event systems","authors":"Fuchun Liu, Qiansheng Zhang, Xuesong Chen, Renwei Huang","doi":"10.1109/ICARCV.2012.6485167","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485167","url":null,"abstract":"Recently, safe diagnosability of discrete event systems (DESs) was investigated in the literature. This paper addresses the issue of safe diagnosability for fuzzy discrete event systems (FDESs). We formalize the notion of safe diagnosability for fuzzy automata, where the observability of fuzzy events is defined to be fuzzy instead of crisp. A safe diagnosable fuzzy automaton is required that not only faults can be detected with a certain degree but also fault detection must be completed before any forbidden string in the failed mode of system is executed. A fuzzy automaton called the recognizer is introduced to distinguish the forbidden strings from the illegal language. Then a safe diagnoser is constructed to perform safe diagnosis of FDESs. In particular, a necessary and sufficient condition of safe diagnosability for FDESs is derived, which extends the main results of safe diagnosability from crisp DESs to the setting of FDESs. Some illustrative examples are provided.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125195700","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 : 2012-12-01DOI: 10.1109/ICARCV.2012.6485249
Wei Zhou, X. Ye
Nonlinear backstepping adaptive controller is proposed for the design of parallel DC-DC buck converters with uncertainties of load and power disturbance. Global asymptotic stability of the system is proved by Lyapunov stability theory. The relationship between the control elements and circuit parameters is determined by simulation analysis. The simulation results demonstrate the effectiveness of the presented method.
{"title":"Adaptive control of parallel DC-DC buck converters with uncertain parameters","authors":"Wei Zhou, X. Ye","doi":"10.1109/ICARCV.2012.6485249","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485249","url":null,"abstract":"Nonlinear backstepping adaptive controller is proposed for the design of parallel DC-DC buck converters with uncertainties of load and power disturbance. Global asymptotic stability of the system is proved by Lyapunov stability theory. The relationship between the control elements and circuit parameters is determined by simulation analysis. The simulation results demonstrate the effectiveness of the presented method.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122522981","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 : 2012-12-01DOI: 10.1109/ICARCV.2012.6485405
Zhan Li, Zhicheng Li, Huijun Gao, H. Karimi
In this note, we study the problems of stability analysis and H∞ controller synthesis of discrete-time switched systems with time-varying delay. The system under consideration is firstly transformed into an interconnection system. Based on the system transformation and the scaled small gain theorem, the asymptotic stability of the original system is examined via the version of the bounded realness of the transformed forward system. The aim of the proposed approach is to reduce conservatism, which is made possible by a precise approximation of the time-varying delay and the input-output approach. The proposed stability condition is demonstrated to be much less conservative than most existing results. Moreover, the problem of H∞ controller synthesis involving convex optimization is further solved based on the stability condition, whose effectiveness are also illustrated via numerical examples.
{"title":"Further results on H∞ control of switched linear time-delay systems","authors":"Zhan Li, Zhicheng Li, Huijun Gao, H. Karimi","doi":"10.1109/ICARCV.2012.6485405","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485405","url":null,"abstract":"In this note, we study the problems of stability analysis and H∞ controller synthesis of discrete-time switched systems with time-varying delay. The system under consideration is firstly transformed into an interconnection system. Based on the system transformation and the scaled small gain theorem, the asymptotic stability of the original system is examined via the version of the bounded realness of the transformed forward system. The aim of the proposed approach is to reduce conservatism, which is made possible by a precise approximation of the time-varying delay and the input-output approach. The proposed stability condition is demonstrated to be much less conservative than most existing results. Moreover, the problem of H∞ controller synthesis involving convex optimization is further solved based on the stability condition, whose effectiveness are also illustrated via numerical examples.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115135299","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 : 2012-12-01DOI: 10.1109/ICARCV.2012.6485320
Sheng Wang, Qiang Wu, Xiangjian He, Min Xu
In this paper, we study the impact of learning an Adaboost classifier with small sample set (i.e., with fewer training examples). In particular, we make use of car localization as an underlying application, because car localization can be widely used to various real world applications. In order to evaluate the performance of Adaboost learning with a few examples, we simply apply Adaboost learning to a recently proposed feature descriptor - Locally Adaptive Regression Kernel (LARK). As a type of state-of-the-art feature descriptor, LARK is robust against illumination changes and noises. More importantly, we use LARK because its spatial property is also favorable for our purpose (i.e., each patch in the LARK descriptor corresponds to one unique pixel in the original image). In addition to learning a detector from the entire training dataset, we also split the original training dataset into several sub-groups and then we train one detector for each sub-group. We compare those features associated using the detector of each sub-group with that of the detector learnt with the entire training dataset and propose improvements based on the comparison results. Our experimental results indicate that the Adaboost learning is only successful on a small dataset when those learnt features simultaneously satisfy two conditions that: 1. features are learnt from the Region of Interest (ROI), and 2. features are sufficiently far away from each other.
{"title":"On splitting dataset: Boosting Locally Adaptive Regression Kernels for car localization","authors":"Sheng Wang, Qiang Wu, Xiangjian He, Min Xu","doi":"10.1109/ICARCV.2012.6485320","DOIUrl":"https://doi.org/10.1109/ICARCV.2012.6485320","url":null,"abstract":"In this paper, we study the impact of learning an Adaboost classifier with small sample set (i.e., with fewer training examples). In particular, we make use of car localization as an underlying application, because car localization can be widely used to various real world applications. In order to evaluate the performance of Adaboost learning with a few examples, we simply apply Adaboost learning to a recently proposed feature descriptor - Locally Adaptive Regression Kernel (LARK). As a type of state-of-the-art feature descriptor, LARK is robust against illumination changes and noises. More importantly, we use LARK because its spatial property is also favorable for our purpose (i.e., each patch in the LARK descriptor corresponds to one unique pixel in the original image). In addition to learning a detector from the entire training dataset, we also split the original training dataset into several sub-groups and then we train one detector for each sub-group. We compare those features associated using the detector of each sub-group with that of the detector learnt with the entire training dataset and propose improvements based on the comparison results. Our experimental results indicate that the Adaboost learning is only successful on a small dataset when those learnt features simultaneously satisfy two conditions that: 1. features are learnt from the Region of Interest (ROI), and 2. features are sufficiently far away from each other.","PeriodicalId":441236,"journal":{"name":"2012 12th International Conference on Control Automation Robotics & Vision (ICARCV)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133920488","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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