Pub Date : 1900-01-01DOI: 10.1109/ISIC.1999.796696
P. Keller
The electronic nose draws its inspiration from biology. Both the electronic nose and the biological olfactory system consist of an array of chemical sensing elements and a pattern recognition system. This paper reviews the basic concepts of electronic noses and their relationship to biological olfaction. Different approaches to chemical data analysis including statistical methods, standard artificial neural network approaches, and those based on advanced biological models of the olfaction are described. Finally, a prototype system is reviewed.
{"title":"Mimicking biology: applications of cognitive systems to electronic noses","authors":"P. Keller","doi":"10.1109/ISIC.1999.796696","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796696","url":null,"abstract":"The electronic nose draws its inspiration from biology. Both the electronic nose and the biological olfactory system consist of an array of chemical sensing elements and a pattern recognition system. This paper reviews the basic concepts of electronic noses and their relationship to biological olfaction. Different approaches to chemical data analysis including statistical methods, standard artificial neural network approaches, and those based on advanced biological models of the olfaction are described. Finally, a prototype system is reviewed.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124487333","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 : 1900-01-01DOI: 10.1109/ISIC.1999.796638
Jizhong Xiao, Q. Song, Danwei W. Wang
This paper presents an iterative learning controller using neural network (NN) for the robot trajectory tracking control. The basic control configuration is briefly presented and a new weight-tuning algorithm of NN is proposed with a dead-zone technique. Theoretical proof is given which shows that our modified algorithm guarantees the convergence of NN estimation error in the presence of disturbance. The simulation study demonstrates that the proposed weight-tuning algorithm is robust and less sensitive to noise compared to the standard backpropagation algorithm in identifying the robot inverse dynamics. Moreover, the simulation results also shows that the proposed NN learning control scheme can greatly reduce tracking errors as the iteration number increases.
{"title":"A learning control scheme based on neural networks for repeatable robot trajectory tracking","authors":"Jizhong Xiao, Q. Song, Danwei W. Wang","doi":"10.1109/ISIC.1999.796638","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796638","url":null,"abstract":"This paper presents an iterative learning controller using neural network (NN) for the robot trajectory tracking control. The basic control configuration is briefly presented and a new weight-tuning algorithm of NN is proposed with a dead-zone technique. Theoretical proof is given which shows that our modified algorithm guarantees the convergence of NN estimation error in the presence of disturbance. The simulation study demonstrates that the proposed weight-tuning algorithm is robust and less sensitive to noise compared to the standard backpropagation algorithm in identifying the robot inverse dynamics. Moreover, the simulation results also shows that the proposed NN learning control scheme can greatly reduce tracking errors as the iteration number increases.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"227 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124503331","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 : 1900-01-01DOI: 10.1109/ISIC.1999.796622
A. Favela
We introduce some analysis tools for a class of continuous-linear hybrid systems. The continuous-linear term is used in the sense of system theory and it is in this sense that continuous-linear hybrid automata are defined. Using the defined automaton representation, we provide an analytical formulation of the system dynamic behavior. With the analysis results, dynamic properties for reachability and limit cycle analysis purposes are established. Finally, a coupled hybrid case is conducted.
{"title":"Hybrid automata models in continuous-linear hybrid systems analysis","authors":"A. Favela","doi":"10.1109/ISIC.1999.796622","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796622","url":null,"abstract":"We introduce some analysis tools for a class of continuous-linear hybrid systems. The continuous-linear term is used in the sense of system theory and it is in this sense that continuous-linear hybrid automata are defined. Using the defined automaton representation, we provide an analytical formulation of the system dynamic behavior. With the analysis results, dynamic properties for reachability and limit cycle analysis purposes are established. Finally, a coupled hybrid case is conducted.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121128413","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 : 1900-01-01DOI: 10.1109/ISIC.1999.796694
Chrystopher L. Nehaniv
Shannon and Weaver (1963) formalized the notion of information transmission rate and capacity for pre-existing channels. Wittgenstein (1968) insisted that linguistic meaning be defined in terms of use in language games. Peirce (1965) realized the importance of sign, signified, and interpretant in processes of semiosis. In particular, the connection between sign and signified does not take place in a platonic vacuum but is situated, embodied, embedded, and must be mediated by an interpretant. We introduce a rigorous mathematical notion of meaning, as (1) agent- and observer- perceptible information in interaction games between an agent and its environment or between an agent and other agents, that is (2) useful for satisfying homeostatic and other drives, needs, goals or intentions. With this framework it is possible to address issues of sensor- and actuator- design, origins, evolution, and maintenance for biological and artificial systems. Moreover, correspondences between channels of meaning are exploited by biological entities in predicting the behavior or reading the intent of others, as in predator-prey and social interaction. Social learning, imitation, communication of experience also develop and can be developed on this substrate of shared meaning.
{"title":"Meaning for observers and agents","authors":"Chrystopher L. Nehaniv","doi":"10.1109/ISIC.1999.796694","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796694","url":null,"abstract":"Shannon and Weaver (1963) formalized the notion of information transmission rate and capacity for pre-existing channels. Wittgenstein (1968) insisted that linguistic meaning be defined in terms of use in language games. Peirce (1965) realized the importance of sign, signified, and interpretant in processes of semiosis. In particular, the connection between sign and signified does not take place in a platonic vacuum but is situated, embodied, embedded, and must be mediated by an interpretant. We introduce a rigorous mathematical notion of meaning, as (1) agent- and observer- perceptible information in interaction games between an agent and its environment or between an agent and other agents, that is (2) useful for satisfying homeostatic and other drives, needs, goals or intentions. With this framework it is possible to address issues of sensor- and actuator- design, origins, evolution, and maintenance for biological and artificial systems. Moreover, correspondences between channels of meaning are exploited by biological entities in predicting the behavior or reading the intent of others, as in predator-prey and social interaction. Social learning, imitation, communication of experience also develop and can be developed on this substrate of shared meaning.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"294 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132791497","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 : 1900-01-01DOI: 10.1109/ISIC.1999.796651
M. Baglietto, T. Parisini, R. Zoppoli
There are many situations, in engineering and economic systems, where several decision makers (DMs), sharing different information patterns, cooperate to the accomplishment of a common goal. We address an approximate technique consisting in constraining the control functions to have a fixed structure (we chose feedforward neural networks). We are then able to obtain solutions that approximate the optimal ones within any desired degree of accuracy under very general conditions. Such a technique has proved to be effective in non-LQG classical optimal control and in team problems not solvable analytically.
{"title":"Neural approximators for the solution of decentralized optimal control problems","authors":"M. Baglietto, T. Parisini, R. Zoppoli","doi":"10.1109/ISIC.1999.796651","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796651","url":null,"abstract":"There are many situations, in engineering and economic systems, where several decision makers (DMs), sharing different information patterns, cooperate to the accomplishment of a common goal. We address an approximate technique consisting in constraining the control functions to have a fixed structure (we chose feedforward neural networks). We are then able to obtain solutions that approximate the optimal ones within any desired degree of accuracy under very general conditions. Such a technique has proved to be effective in non-LQG classical optimal control and in team problems not solvable analytically.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130194355","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 : 1900-01-01DOI: 10.1109/ISIC.1999.796678
Mingxuan Sun, Danwei W. Wang
In this paper, a sampled-data iterative learning control (ILC) method is proposed for a class of nonlinear continuous-time systems with higher-order relative degree. The learning control does not require differentiation of tracking error. As the sampling period is set to be small enough, a sufficient condition is derived to guarantee the convergence of the learning process. This method can be applied to a more general class of nonlinear continuous-time systems that the most existing ILC methods fail to work.
{"title":"Sampled-data iterative learning control for a class of nonlinear systems","authors":"Mingxuan Sun, Danwei W. Wang","doi":"10.1109/ISIC.1999.796678","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796678","url":null,"abstract":"In this paper, a sampled-data iterative learning control (ILC) method is proposed for a class of nonlinear continuous-time systems with higher-order relative degree. The learning control does not require differentiation of tracking error. As the sampling period is set to be small enough, a sufficient condition is derived to guarantee the convergence of the learning process. This method can be applied to a more general class of nonlinear continuous-time systems that the most existing ILC methods fail to work.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130598502","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 : 1900-01-01DOI: 10.1109/ISIC.1999.796625
Yonghong Tan, Xuanju Dang, A. van Cauwenberghe
A nonlinear PID controller is proposed to handle some nonlinear process control problems. In this scheme, the controller uses the system error, the integral of the system error, and the derivative of the system error as its inputs but the mapping from the inputs to the output is nonlinear. The corresponding nonlinear mapping may be specified based on the control requirement. The NPIDC strategy is realized using neural networks. For online training of the neural network based NPIDC, a PID gradient descent optimizing algorithm with momentum term is proposed. Then, the convergent characteristic of the algorithm is presented. Finally, a simulation study of applying the neural NPIDC strategy to a continuous-stirred-tank-reactor and a van de Vusse reactor is illustrated.
针对一些非线性过程控制问题，提出了一种非线性PID控制器。在该方案中，控制器使用系统误差、系统误差的积分和系统误差的导数作为其输入，但从输入到输出的映射是非线性的。可根据控制要求指定相应的非线性映射。NPIDC策略采用神经网络实现。针对基于NPIDC的神经网络在线训练问题，提出了一种带动量项的PID梯度下降优化算法。然后，给出了该算法的收敛特性。最后，对连续搅拌罐式反应器和van de Vusse反应器进行了神经网络NPIDC策略的仿真研究。
{"title":"A neural network based nonlinear PID controller using PID gradient training","authors":"Yonghong Tan, Xuanju Dang, A. van Cauwenberghe","doi":"10.1109/ISIC.1999.796625","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796625","url":null,"abstract":"A nonlinear PID controller is proposed to handle some nonlinear process control problems. In this scheme, the controller uses the system error, the integral of the system error, and the derivative of the system error as its inputs but the mapping from the inputs to the output is nonlinear. The corresponding nonlinear mapping may be specified based on the control requirement. The NPIDC strategy is realized using neural networks. For online training of the neural network based NPIDC, a PID gradient descent optimizing algorithm with momentum term is proposed. Then, the convergent characteristic of the algorithm is presented. Finally, a simulation study of applying the neural NPIDC strategy to a continuous-stirred-tank-reactor and a van de Vusse reactor is illustrated.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122389210","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 : 1900-01-01DOI: 10.1109/ISIC.1999.796698
T. El-Fouly, N. Zerhouni, M. Ferney, A. El Moudni
This paper presents an analysis of the dynamic behavior of manufacturing systems, as a basis for the control study. In this paper we present the special case of an open manufacturing line as an example. We present an analysis as well as an algorithm for minimizing the overall evolution time of a manufacturing line. The objective is to study the effect of changing the flow rate of the pieces arriving to the line on the overall performance of the manufacturing line (settling time, throughput) during the transient and the stationary regions.
{"title":"Analysis of manufacturing lines using a phase space algorithm","authors":"T. El-Fouly, N. Zerhouni, M. Ferney, A. El Moudni","doi":"10.1109/ISIC.1999.796698","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796698","url":null,"abstract":"This paper presents an analysis of the dynamic behavior of manufacturing systems, as a basis for the control study. In this paper we present the special case of an open manufacturing line as an example. We present an analysis as well as an algorithm for minimizing the overall evolution time of a manufacturing line. The objective is to study the effect of changing the flow rate of the pieces arriving to the line on the overall performance of the manufacturing line (settling time, throughput) during the transient and the stationary regions.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124159270","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 : 1900-01-01DOI: 10.1109/ISIC.1999.796680
Dongming Wang, L. Acar
This document introduces the concept of type-2 fuzzy sets and compares the type-2 fuzzy set preliminaries with the ordinary type-1 fuzzy set. Two theorems are proved: the first one helps to generate the general form of the type-2 operations, the second provides an approach to transfer the type-1 fuzzy uncertainties to the type-2 system.
{"title":"An analysis of type-1 and type-2 fuzzy logic systems","authors":"Dongming Wang, L. Acar","doi":"10.1109/ISIC.1999.796680","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796680","url":null,"abstract":"This document introduces the concept of type-2 fuzzy sets and compares the type-2 fuzzy set preliminaries with the ordinary type-1 fuzzy set. Two theorems are proved: the first one helps to generate the general form of the type-2 operations, the second provides an approach to transfer the type-1 fuzzy uncertainties to the type-2 system.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130676314","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 : 1900-01-01DOI: 10.1109/ISIC.1999.796646
H. Fadel, L. Holloway
The behavior of manufacturing systems with discrete I/O signals can be characterized by the timing and sequencing of changes (events) in these I/O. In this paper, we present a method to monitor these signals to alarm when faulty sequencing or timing behavior occurs, and also to warn when the timing starts to deviate from its normal behavior. This is accomplished by using a combination of the time template monitoring technique and statistical process control (SPC).
{"title":"Using SPC and template monitoring method for fault detection and prediction in discrete event manufacturing systems","authors":"H. Fadel, L. Holloway","doi":"10.1109/ISIC.1999.796646","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796646","url":null,"abstract":"The behavior of manufacturing systems with discrete I/O signals can be characterized by the timing and sequencing of changes (events) in these I/O. In this paper, we present a method to monitor these signals to alarm when faulty sequencing or timing behavior occurs, and also to warn when the timing starts to deviate from its normal behavior. This is accomplished by using a combination of the time template monitoring technique and statistical process control (SPC).","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127472028","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：