Pub Date : 1995-08-27DOI: 10.1109/ISIC.1995.525066
W. Kalkhoff
This paper describes a new approach to modelling robot systems by a large number of cooperating agents solving a robot task. On the one hand the agent model submits to use results of the distributed artificial intelligence (DAI), on the other hand, typical aspects of robot systems must be integrated. Therefore, an agent model will be presented serving the special requirements of robot systems and offering many advantages like robustness, high efficiency, and the chance of integrating reactive and deliberative behavior. The agent model also enables the use of different programming paradigms, ranging from complex over hierarchical to object-oriented agents. Finally, a typical set of agents is presented, forming a multi-layered, distributed and reactive (MDR) robot task-level transformer.
{"title":"Agent-oriented robot task transformation","authors":"W. Kalkhoff","doi":"10.1109/ISIC.1995.525066","DOIUrl":"https://doi.org/10.1109/ISIC.1995.525066","url":null,"abstract":"This paper describes a new approach to modelling robot systems by a large number of cooperating agents solving a robot task. On the one hand the agent model submits to use results of the distributed artificial intelligence (DAI), on the other hand, typical aspects of robot systems must be integrated. Therefore, an agent model will be presented serving the special requirements of robot systems and offering many advantages like robustness, high efficiency, and the chance of integrating reactive and deliberative behavior. The agent model also enables the use of different programming paradigms, ranging from complex over hierarchical to object-oriented agents. Finally, a typical set of agents is presented, forming a multi-layered, distributed and reactive (MDR) robot task-level transformer.","PeriodicalId":219623,"journal":{"name":"Proceedings of Tenth International Symposium on Intelligent Control","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115103030","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 : 1995-08-27DOI: 10.1109/ISIC.1995.525102
Y. Cho, R. Rajamani
This paper addresses the issue of state estimation from limited sensor measurements in the presence of parameter uncertainty. An adaptive nonlinear observer is suggested for Lipschitz nonlinear systems and the stability of this observer is shown to be related to finding solutions to a quadratic inequality involving two variables. A coordinate transformation is used to reformulate this inequality as a linear matrix inequality. A systematic algorithm is presented which checks for feasibility of a solution to the quadratic inequality and yields an observer whenever the solution is feasible. The state estimates then are guaranteed to converge to zero asymptotically. The convergence of the parameters, however, is determined by a persistence-of-excitation type constraint.
{"title":"A systematic approach to adaptive observer synthesis for nonlinear systems","authors":"Y. Cho, R. Rajamani","doi":"10.1109/ISIC.1995.525102","DOIUrl":"https://doi.org/10.1109/ISIC.1995.525102","url":null,"abstract":"This paper addresses the issue of state estimation from limited sensor measurements in the presence of parameter uncertainty. An adaptive nonlinear observer is suggested for Lipschitz nonlinear systems and the stability of this observer is shown to be related to finding solutions to a quadratic inequality involving two variables. A coordinate transformation is used to reformulate this inequality as a linear matrix inequality. A systematic algorithm is presented which checks for feasibility of a solution to the quadratic inequality and yields an observer whenever the solution is feasible. The state estimates then are guaranteed to converge to zero asymptotically. The convergence of the parameters, however, is determined by a persistence-of-excitation type constraint.","PeriodicalId":219623,"journal":{"name":"Proceedings of Tenth International Symposium on Intelligent Control","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123065693","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 : 1995-08-27DOI: 10.1109/ISIC.1995.525105
W. K. Lennon, K. Passino
There exist several problems in the control of brake systems including the development of control logic for antilock braking systems (ABS) and "base-braking." Here, we study the base-braking control problem where we seek to develop a controller that can ensure that the braking torque commanded by the driver will be achieved. In particular, we develop a "fuzzy model reference learning controller" and a "genetic model reference adaptive controller", and investigate their effectiveness in reducing the effects of variations in the process due to temperature.
{"title":"Intelligent control for brake systems","authors":"W. K. Lennon, K. Passino","doi":"10.1109/ISIC.1995.525105","DOIUrl":"https://doi.org/10.1109/ISIC.1995.525105","url":null,"abstract":"There exist several problems in the control of brake systems including the development of control logic for antilock braking systems (ABS) and \"base-braking.\" Here, we study the base-braking control problem where we seek to develop a controller that can ensure that the braking torque commanded by the driver will be achieved. In particular, we develop a \"fuzzy model reference learning controller\" and a \"genetic model reference adaptive controller\", and investigate their effectiveness in reducing the effects of variations in the process due to temperature.","PeriodicalId":219623,"journal":{"name":"Proceedings of Tenth International Symposium on Intelligent Control","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123703896","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 : 1995-08-27DOI: 10.1109/ISIC.1995.525117
P. Spacek, A. El Moudni, S. Zerhouni, M. Ferney
One can consider a system of production to be a dynamic system. Moreover, it is interesting to describe the system by equations in which state vector, input and output vectors appear. This can help when carrying out synthesis of the system. The Petri net representation of a system allows one to define three vectors mentioned above. If the corresponding Petri net is an event graph (i.e. each place has exactly one input and one output transition), it is possible to apply a mathematical model for this system. The model is known in literature as max algebra or max-plus algebra R/sub max/=(R/spl cup.
{"title":"Max-plus algebra for discrete event systems-some links to structural controllability and structural observability","authors":"P. Spacek, A. El Moudni, S. Zerhouni, M. Ferney","doi":"10.1109/ISIC.1995.525117","DOIUrl":"https://doi.org/10.1109/ISIC.1995.525117","url":null,"abstract":"One can consider a system of production to be a dynamic system. Moreover, it is interesting to describe the system by equations in which state vector, input and output vectors appear. This can help when carrying out synthesis of the system. The Petri net representation of a system allows one to define three vectors mentioned above. If the corresponding Petri net is an event graph (i.e. each place has exactly one input and one output transition), it is possible to apply a mathematical model for this system. The model is known in literature as max algebra or max-plus algebra R/sub max/=(R/spl cup.","PeriodicalId":219623,"journal":{"name":"Proceedings of Tenth International Symposium on Intelligent Control","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128548367","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 : 1995-08-27DOI: 10.1109/ISIC.1995.525115
E. Stella, G. Cicirelli, F.P. Lovergine, A. Distante
This paper describes a position estimation technique based on the fusion of data obtained by two independent subsystems in a mobile robot navigation context. The first subsystem is a self-location one composed of an onboard camera, an onboard image processing unit and artificial landmarks; the second one is a dead-reckoning subsystem based on odometry. The robot navigation system integrates the position estimation obtained by the vision subsystem with the position estimated by odometry using a Kalman filter framework.
{"title":"Position estimation for a mobile robot using data fusion","authors":"E. Stella, G. Cicirelli, F.P. Lovergine, A. Distante","doi":"10.1109/ISIC.1995.525115","DOIUrl":"https://doi.org/10.1109/ISIC.1995.525115","url":null,"abstract":"This paper describes a position estimation technique based on the fusion of data obtained by two independent subsystems in a mobile robot navigation context. The first subsystem is a self-location one composed of an onboard camera, an onboard image processing unit and artificial landmarks; the second one is a dead-reckoning subsystem based on odometry. The robot navigation system integrates the position estimation obtained by the vision subsystem with the position estimated by odometry using a Kalman filter framework.","PeriodicalId":219623,"journal":{"name":"Proceedings of Tenth International Symposium on Intelligent Control","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124654649","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 : 1995-08-27DOI: 10.1109/ISIC.1995.525029
D. Hyland
This paper discusses the adaptive neural control (ANC) architecture for online system identification and adaptive control. We describe the basic architecture and summarize the test results obtained to-date.
{"title":"Adaptive neural control for flexible aerospace systems: progress and prospects","authors":"D. Hyland","doi":"10.1109/ISIC.1995.525029","DOIUrl":"https://doi.org/10.1109/ISIC.1995.525029","url":null,"abstract":"This paper discusses the adaptive neural control (ANC) architecture for online system identification and adaptive control. We describe the basic architecture and summarize the test results obtained to-date.","PeriodicalId":219623,"journal":{"name":"Proceedings of Tenth International Symposium on Intelligent Control","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129735401","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 : 1995-08-27DOI: 10.1109/ISIC.1995.525110
J. T. Spooner, Kevin M. Passinot
Recently, stable direct and indirect adaptive controllers have been presented which use Takagi-Sugeno fuzzy systems, conventional fuzzy systems, or a class of neural networks to provide asymptotic tracking of a reference signal for a class of continuous-time nonlinear plants with poorly understood dynamics. The indirect adaptive scheme allows for the inclusion of a priori knowledge about the plant dynamics in terms of exact mathematical equations or linguistics while the direct adaptive scheme allows for the incorporation of such a priori knowledge in specifying the controller. In this paper, the performance of these indirect and direct adaptive schemes is demonstrated through the longitudinal control of an automobile in an automated highway system.
{"title":"Stable adaptive fuzzy control for an automated highway system","authors":"J. T. Spooner, Kevin M. Passinot","doi":"10.1109/ISIC.1995.525110","DOIUrl":"https://doi.org/10.1109/ISIC.1995.525110","url":null,"abstract":"Recently, stable direct and indirect adaptive controllers have been presented which use Takagi-Sugeno fuzzy systems, conventional fuzzy systems, or a class of neural networks to provide asymptotic tracking of a reference signal for a class of continuous-time nonlinear plants with poorly understood dynamics. The indirect adaptive scheme allows for the inclusion of a priori knowledge about the plant dynamics in terms of exact mathematical equations or linguistics while the direct adaptive scheme allows for the incorporation of such a priori knowledge in specifying the controller. In this paper, the performance of these indirect and direct adaptive schemes is demonstrated through the longitudinal control of an automobile in an automated highway system.","PeriodicalId":219623,"journal":{"name":"Proceedings of Tenth International Symposium on Intelligent Control","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124137364","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 : 1995-08-27DOI: 10.1109/ISIC.1995.525093
R. Colbaugh, E. Barany
This paper considers the problem of characterizing the stability properties of the equilibria of an important class of recurrent neural networks. Sufficient conditions are given under which the neural network possesses a unique globally asymptotically stable equilibrium point for each external input. These conditions are less restrictive than those previously obtained and are easily checked, so that incorporating them in existing neural network design procedures should increase the flexibility and reduce the complexity of this synthesis process. Results are provided for both continuous-time and discrete-time networks.
{"title":"Stability analysis for a class of neural networks","authors":"R. Colbaugh, E. Barany","doi":"10.1109/ISIC.1995.525093","DOIUrl":"https://doi.org/10.1109/ISIC.1995.525093","url":null,"abstract":"This paper considers the problem of characterizing the stability properties of the equilibria of an important class of recurrent neural networks. Sufficient conditions are given under which the neural network possesses a unique globally asymptotically stable equilibrium point for each external input. These conditions are less restrictive than those previously obtained and are easily checked, so that incorporating them in existing neural network design procedures should increase the flexibility and reduce the complexity of this synthesis process. Results are provided for both continuous-time and discrete-time networks.","PeriodicalId":219623,"journal":{"name":"Proceedings of Tenth International Symposium on Intelligent Control","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121720128","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 : 1995-08-27DOI: 10.1109/ISIC.1995.525118
Xiaojun Yang, M. Lemmon, P. Antsaklis
This paper summarizes preliminary results on the implementation and convergence of an inductive learning algorithm used to identify optimal logical DES controllers. The algorithm is a modification of Angluin's L* procedure. It uses queries to an equivalence oracle and incomplete membership oracle to learn a minimal deterministic finite automaton consistent with the supremal controllable sublanguage of a known specification language and unknown plant. This paper shows how the proposed algorithm is implemented, provides results on the procedure's convergence properties, and presents an example illustrating its use.
{"title":"Inductive inference of optimal controllers for uncertain logical discrete event systems","authors":"Xiaojun Yang, M. Lemmon, P. Antsaklis","doi":"10.1109/ISIC.1995.525118","DOIUrl":"https://doi.org/10.1109/ISIC.1995.525118","url":null,"abstract":"This paper summarizes preliminary results on the implementation and convergence of an inductive learning algorithm used to identify optimal logical DES controllers. The algorithm is a modification of Angluin's L* procedure. It uses queries to an equivalence oracle and incomplete membership oracle to learn a minimal deterministic finite automaton consistent with the supremal controllable sublanguage of a known specification language and unknown plant. This paper shows how the proposed algorithm is implemented, provides results on the procedure's convergence properties, and presents an example illustrating its use.","PeriodicalId":219623,"journal":{"name":"Proceedings of Tenth International Symposium on Intelligent Control","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129975699","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 : 1995-08-27DOI: 10.1109/ISIC.1995.525089
S. Jagannathan, M. W. Vandegrift, F. Lewis
This paper demonstrates tracking control of a class of unknown nonlinear dynamical systems using a discrete-time fuzzy logic controller (FLC). Designing a discrete-time FLC is significant because almost all FLCs are implemented on digital computers. A repeatable design algorithm and a stability proof are presented for an adaptive fuzzy logic controller that uses basis vectors based on the fuzzy system, unlike most standard adaptive control approaches which use basis vectors depending on the unknown plant (e.g. a tediously computed "regression matrix"). The authors select an e-modification sort of approach to adapt the fuzzy system parameters. Using this adaptive fuzzy logic controller, the authors prove uniform ultimate boundedness of the closed-loop signals and that the controller achieves tracking. In fact, the fuzzy system designed is a model-free universal fuzzy controller that works for any system in the given class of systems.
{"title":"Adaptive fuzzy logic control of discrete-time dynamical systems","authors":"S. Jagannathan, M. W. Vandegrift, F. Lewis","doi":"10.1109/ISIC.1995.525089","DOIUrl":"https://doi.org/10.1109/ISIC.1995.525089","url":null,"abstract":"This paper demonstrates tracking control of a class of unknown nonlinear dynamical systems using a discrete-time fuzzy logic controller (FLC). Designing a discrete-time FLC is significant because almost all FLCs are implemented on digital computers. A repeatable design algorithm and a stability proof are presented for an adaptive fuzzy logic controller that uses basis vectors based on the fuzzy system, unlike most standard adaptive control approaches which use basis vectors depending on the unknown plant (e.g. a tediously computed \"regression matrix\"). The authors select an e-modification sort of approach to adapt the fuzzy system parameters. Using this adaptive fuzzy logic controller, the authors prove uniform ultimate boundedness of the closed-loop signals and that the controller achieves tracking. In fact, the fuzzy system designed is a model-free universal fuzzy controller that works for any system in the given class of systems.","PeriodicalId":219623,"journal":{"name":"Proceedings of Tenth International Symposium on Intelligent Control","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134358301","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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