Pub Date : 2008-09-30DOI: 10.1109/ISIC.2008.4635965
Siming Zhao, T. Kalmár-Nagy
We propose a smooth uni-cyclic pursuit control law in order to avoid controller discontinuity. The local stability of all the equilibria are characterized. Global bifurcation analysis of three different cases are carried out based on phase portraits of a 2-dimensional system. Numerics agree well with the theoretical results.
{"title":"Nonlinear dynamics of uni-cyclic pursuit","authors":"Siming Zhao, T. Kalmár-Nagy","doi":"10.1109/ISIC.2008.4635965","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635965","url":null,"abstract":"We propose a smooth uni-cyclic pursuit control law in order to avoid controller discontinuity. The local stability of all the equilibria are characterized. Global bifurcation analysis of three different cases are carried out based on phase portraits of a 2-dimensional system. Numerics agree well with the theoretical results.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128597534","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635938
Wenjie Dong, J. Farrell
This paper considers the optimal control of unknown nonlinear systems. To deal with the uncertainties in the system, a locally weighted learning observer (LWLO) is proposed. Using the functions approximated within the LWLO, analytic optimal controllers are proposed in the sense of pointwise min-norm. To show effectiveness of the proposed controllers, numerical simulations are presented.
{"title":"Optimal Regulation of Unknown Nonlinear Systems Based on Locally Weighted Learning","authors":"Wenjie Dong, J. Farrell","doi":"10.1109/ISIC.2008.4635938","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635938","url":null,"abstract":"This paper considers the optimal control of unknown nonlinear systems. To deal with the uncertainties in the system, a locally weighted learning observer (LWLO) is proposed. Using the functions approximated within the LWLO, analytic optimal controllers are proposed in the sense of pointwise min-norm. To show effectiveness of the proposed controllers, numerical simulations are presented.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133242642","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635970
N. Gans, G. Hu, W. Dixon
A novel visual servo controller is developed in this paper that simultaneously regulates both the camera pose and image errors. This Lyapunov-based controller stabilizes both the entire image and pose error simultaneously. Furthermore, the controller uses adaptive depth estimation to eliminate the need to measure depth or obtain knowledge of the scene.
{"title":"Simultaneous Stability of Image and Pose Error in Visual Servo Control","authors":"N. Gans, G. Hu, W. Dixon","doi":"10.1109/ISIC.2008.4635970","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635970","url":null,"abstract":"A novel visual servo controller is developed in this paper that simultaneously regulates both the camera pose and image errors. This Lyapunov-based controller stabilizes both the entire image and pose error simultaneously. Furthermore, the controller uses adaptive depth estimation to eliminate the need to measure depth or obtain knowledge of the scene.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"2013 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127433257","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635942
Yongli Wang, Shuning Wang, J. Khan, Yudong Chen
The main difficulty for standard continuous piecewise linear neural networks (SCPLNN) approximation is how to partition the definitional domain into several simplices, which is called a triangulation. In this paper, we firstly propose a method of triangulation to perform SCPLNN approximation. Our scheme starts with an initial, coarse triangulation of the given data and subdivides simplex until the error of the SCPLNN approximation is smaller than some tolerance. Then SCPLNN based on triangulation is identified. The proposed method involving triangulation and identification of SCPLNN is shown to be useful in approximating nonlinear systems. In addition, for each simplex, the local inverse model can easily be calculated for each local model of SCPLNN is linear. From control perspective, we exploit the advantage of the piecewise linear property of SCPLNN and design controllers for each approximate model. The validity of this control scheme using inverse of the local linear model is tested by using a NARX model.
{"title":"Approximation and Inverse Control of Nonlinear System using Standard Continuous Piecewise Linear Neural Networks","authors":"Yongli Wang, Shuning Wang, J. Khan, Yudong Chen","doi":"10.1109/ISIC.2008.4635942","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635942","url":null,"abstract":"The main difficulty for standard continuous piecewise linear neural networks (SCPLNN) approximation is how to partition the definitional domain into several simplices, which is called a triangulation. In this paper, we firstly propose a method of triangulation to perform SCPLNN approximation. Our scheme starts with an initial, coarse triangulation of the given data and subdivides simplex until the error of the SCPLNN approximation is smaller than some tolerance. Then SCPLNN based on triangulation is identified. The proposed method involving triangulation and identification of SCPLNN is shown to be useful in approximating nonlinear systems. In addition, for each simplex, the local inverse model can easily be calculated for each local model of SCPLNN is linear. From control perspective, we exploit the advantage of the piecewise linear property of SCPLNN and design controllers for each approximate model. The validity of this control scheme using inverse of the local linear model is tested by using a NARX model.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132404767","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635926
K. Baheti
The National Science Foundation (NSF) is focusing on "transformative" research and on encouraging "high risk" at the cutting edge instead of "sure thing" projects that promise only incremental advances. The goal of the session is to bring together university and industry researchers and students attending the 2008 MSC and inform them about the NSF funding priorities. Specific focus includes grant opportunities for academic liaison with industry (GOALI) to synergize university-industry partnerships. The session include the following presentations that share their perspectives on industry-university collaborations.
{"title":"NSF Grant Opportunities for Industry-University Collaborations","authors":"K. Baheti","doi":"10.1109/ISIC.2008.4635926","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635926","url":null,"abstract":"The National Science Foundation (NSF) is focusing on \"transformative\" research and on encouraging \"high risk\" at the cutting edge instead of \"sure thing\" projects that promise only incremental advances. The goal of the session is to bring together university and industry researchers and students attending the 2008 MSC and inform them about the NSF funding priorities. Specific focus includes grant opportunities for academic liaison with industry (GOALI) to synergize university-industry partnerships. The session include the following presentations that share their perspectives on industry-university collaborations.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131180622","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635960
Tengfei Liu, Cong Wang, D. Hill
Recently, a deterministic learning theory was proposed for identification and rapid pattern recognition of uncertain nonlinear dynamical systems. In this paper, we investigate deterministic learning of discrete-time nonlinear systems. For periodic or recurrent dynamical patterns, the persistent excitation (PE) condition can be satisfied by a regression subvector constructed from the neurons near the sequence. With the satisfaction of the PE condition, it is shown that the internal dynamics of an uncertain discrete-time nonlinear system can be accurately learned along the state sequence. Using the learned knowledge, a rapid pattern recognition mechanism can be implemented, in which synchronous errors are taken as the measure of similarity of the dynamical patterns generated from different systems. Compared with the methods based on signal processing, this approach appears to need less time-domain information for recognition and is more effective for high speed applications. Simulation is included to show the effectiveness of the approach.
{"title":"Deterministic Learning and Rapid Dynamical Pattern Recognition of Discrete-Time Systems","authors":"Tengfei Liu, Cong Wang, D. Hill","doi":"10.1109/ISIC.2008.4635960","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635960","url":null,"abstract":"Recently, a deterministic learning theory was proposed for identification and rapid pattern recognition of uncertain nonlinear dynamical systems. In this paper, we investigate deterministic learning of discrete-time nonlinear systems. For periodic or recurrent dynamical patterns, the persistent excitation (PE) condition can be satisfied by a regression subvector constructed from the neurons near the sequence. With the satisfaction of the PE condition, it is shown that the internal dynamics of an uncertain discrete-time nonlinear system can be accurately learned along the state sequence. Using the learned knowledge, a rapid pattern recognition mechanism can be implemented, in which synchronous errors are taken as the measure of similarity of the dynamical patterns generated from different systems. Compared with the methods based on signal processing, this approach appears to need less time-domain information for recognition and is more effective for high speed applications. Simulation is included to show the effectiveness of the approach.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"97 12","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113960706","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635959
Yongqi Liang, Chongzhao Han
This paper is about maneuver estimation of semi-ballistic reentry vehicle (SBRV). It is the first time that maneuvers of this kind of vehicle are researched in the field of tracking. Firstly, based on 3-dimensional maneuvering model, maneuvers of SBRV are analyzed. Secondly, according to characteristics of SBRV, IMM filter is chosen. With the given rule for model-set, a series of model-sets are designed for tracking of this kind of reentry vehicle (RV). Then, simulations are given to check the effectiveness of the newly designed model-sets. Characteristics of each model-set and the generalized model-set for SBRV are given at last.
{"title":"Tracking of Semi-ballistic Reentry Vehicle","authors":"Yongqi Liang, Chongzhao Han","doi":"10.1109/ISIC.2008.4635959","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635959","url":null,"abstract":"This paper is about maneuver estimation of semi-ballistic reentry vehicle (SBRV). It is the first time that maneuvers of this kind of vehicle are researched in the field of tracking. Firstly, based on 3-dimensional maneuvering model, maneuvers of SBRV are analyzed. Secondly, according to characteristics of SBRV, IMM filter is chosen. With the given rule for model-set, a series of model-sets are designed for tracking of this kind of reentry vehicle (RV). Then, simulations are given to check the effectiveness of the newly designed model-sets. Characteristics of each model-set and the generalized model-set for SBRV are given at last.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122000262","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635943
A. Ibeas, P. Balaguer, R. Vilanova, C. Pedret
In this paper, an intelligent adaptive multi-model based control scheme is proposed to obtain the lowest-order model for a system under control by means of adaptation and switching between multiple models. The multi-model scheme is composed of three models of increasing consecutive orders operating in parallel along with a switching mechanism between them. The switching policy selects on-line the necessary order of the nominal model required to achieve the desired degree of performance of the closed-loop depending on the reference signal selection. In this way, the order selection is performed automatically in real-time by comparing the actual behaviour of the system with the desired performance for the closed-loop. The estimation of the parameters of the model is performed by an adaptive algorithm integrating a so-called multi-estimation scheme. This architecture leads to a simple procedure to on-line select the appropriate order of the nominal model required for a certain control application with assessment of a prescribed level of closed-loop performance.
{"title":"On-Line Model Selection Techniques By Using Multiple Models And Supervision Algorithms","authors":"A. Ibeas, P. Balaguer, R. Vilanova, C. Pedret","doi":"10.1109/ISIC.2008.4635943","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635943","url":null,"abstract":"In this paper, an intelligent adaptive multi-model based control scheme is proposed to obtain the lowest-order model for a system under control by means of adaptation and switching between multiple models. The multi-model scheme is composed of three models of increasing consecutive orders operating in parallel along with a switching mechanism between them. The switching policy selects on-line the necessary order of the nominal model required to achieve the desired degree of performance of the closed-loop depending on the reference signal selection. In this way, the order selection is performed automatically in real-time by comparing the actual behaviour of the system with the desired performance for the closed-loop. The estimation of the parameters of the model is performed by an adaptive algorithm integrating a so-called multi-estimation scheme. This architecture leads to a simple procedure to on-line select the appropriate order of the nominal model required for a certain control application with assessment of a prescribed level of closed-loop performance.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116903617","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635957
Tung Le, C. Hadjicostis
In this paper, we analyze the performance of belief propagation max-product algorithms when used to solve the multiple fault diagnosis (MFD) problem. The MFD problem is described by a bipartite diagnosis graph (BDG) which consists of a set of components, a set of alarms, and a set of connections (or causal dependencies) between them, along with a set of parameters that describe the prior probabilities for component, alarm and connection failures. Given the alarm observations, our goal is to find the status of the components that has the maximum a posteriori (MAP) probability. By using properties of the max-product algorithm (MPA) and the sequential max-product algorithm (SMPA), we are able to analyze in this paper the performance of both algorithms with respect to the MAP solution (in terms of the probability of erroneous diagnosis). Our theoretical analysis indicates that the upper bounds in this paper are up to several orders of magnitude better than existing bounds, especially when the smallest loop size is an odd number. We also provide examples which demonstrate that our theoretical upper bounds match very well with simulation results.
{"title":"Improved Performance Bounds on Max-Product Algorithms for Multiple Fault Diagnosis in Graphs with Loops","authors":"Tung Le, C. Hadjicostis","doi":"10.1109/ISIC.2008.4635957","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635957","url":null,"abstract":"In this paper, we analyze the performance of belief propagation max-product algorithms when used to solve the multiple fault diagnosis (MFD) problem. The MFD problem is described by a bipartite diagnosis graph (BDG) which consists of a set of components, a set of alarms, and a set of connections (or causal dependencies) between them, along with a set of parameters that describe the prior probabilities for component, alarm and connection failures. Given the alarm observations, our goal is to find the status of the components that has the maximum a posteriori (MAP) probability. By using properties of the max-product algorithm (MPA) and the sequential max-product algorithm (SMPA), we are able to analyze in this paper the performance of both algorithms with respect to the MAP solution (in terms of the probability of erroneous diagnosis). Our theoretical analysis indicates that the upper bounds in this paper are up to several orders of magnitude better than existing bounds, especially when the smallest loop size is an odd number. We also provide examples which demonstrate that our theoretical upper bounds match very well with simulation results.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128663851","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 : 2008-09-30DOI: 10.1109/ISIC.2008.4635936
Heesu Roh, J. Han, Jungwoo Lee, Kwangwoo Lee, Soosung Lee, Daegeun Seo
In order to effectively manipulate indoor mobile robots, it is important to localize their positions precisely. Although a number of different ways using ultrasonic beacons have been developed, these methods are restricted to a relatively small area because all the beacons should be localized before any actual measurement. In this paper, a new methodology is developed to improve the accuracy of the auto-calibration process in the localization method. The new three-point-extraction algorithm is used in conjunction with existing trilateration and auto-calibration algorithms to compose a new localization method. Validity of the new algorithm is verified through experiments for two and three triangular areas, where the localized path error is confirmed to be significantly small in average. In addition, the path error turns out not to accumulate to a considerable extent. The result enables the robot to autonomously localize its path by recognizing the accurate positions of newly appearing beacons.
{"title":"Development of a New Localization Method for Mobile Robots","authors":"Heesu Roh, J. Han, Jungwoo Lee, Kwangwoo Lee, Soosung Lee, Daegeun Seo","doi":"10.1109/ISIC.2008.4635936","DOIUrl":"https://doi.org/10.1109/ISIC.2008.4635936","url":null,"abstract":"In order to effectively manipulate indoor mobile robots, it is important to localize their positions precisely. Although a number of different ways using ultrasonic beacons have been developed, these methods are restricted to a relatively small area because all the beacons should be localized before any actual measurement. In this paper, a new methodology is developed to improve the accuracy of the auto-calibration process in the localization method. The new three-point-extraction algorithm is used in conjunction with existing trilateration and auto-calibration algorithms to compose a new localization method. Validity of the new algorithm is verified through experiments for two and three triangular areas, where the localized path error is confirmed to be significantly small in average. In addition, the path error turns out not to accumulate to a considerable extent. The result enables the robot to autonomously localize its path by recognizing the accurate positions of newly appearing beacons.","PeriodicalId":342070,"journal":{"name":"2008 IEEE International Symposium on Intelligent Control","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133813664","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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