Pub Date : 2000-09-01DOI: 10.1109/ISIC.1999.796642
S. Ge, Chao Wang
In this paper, the adaptive backstepping with tuning functions method is used for the control of uncertain Chua's circuits with all the key parameters unknown. First, we show that several Chua's circuits of different types including Chua's oscillator, Chua's circuit with cubic nonlinearity, and Murali-Lakshmanan-Chua circuit, can all be transformed into a class of nonlinear systems in the so-called non-autonomous "strict-feedback" form. Next, an adaptive backstepping with tuning functions method is extended to the non-autonomous "strict-feedback" system, and then used to control the output of the Chua's circuit to asymptotically track an arbitrarily given reference signal generated from a known, bounded and smooth nonlinear reference model. Both global stability and asymptotic tracking of the closed-loop system are guaranteed. Simulation results are presented to show the effectiveness of the approach.
{"title":"Adaptive control of uncertain Chua's circuits","authors":"S. Ge, Chao Wang","doi":"10.1109/ISIC.1999.796642","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796642","url":null,"abstract":"In this paper, the adaptive backstepping with tuning functions method is used for the control of uncertain Chua's circuits with all the key parameters unknown. First, we show that several Chua's circuits of different types including Chua's oscillator, Chua's circuit with cubic nonlinearity, and Murali-Lakshmanan-Chua circuit, can all be transformed into a class of nonlinear systems in the so-called non-autonomous \"strict-feedback\" form. Next, an adaptive backstepping with tuning functions method is extended to the non-autonomous \"strict-feedback\" system, and then used to control the output of the Chua's circuit to asymptotically track an arbitrarily given reference signal generated from a known, bounded and smooth nonlinear reference model. Both global stability and asymptotic tracking of the closed-loop system are guaranteed. Simulation results are presented to show the effectiveness of the approach.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2000-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115909461","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 : 1999-12-01DOI: 10.1109/ISIC.1999.796628
D. Liu, H. Patiño
Addresses the problem of generating autonomously an optimal control action sequence for ship steering control based on adaptive critic designs. The principal objective is to autonomously design an optimal controller that steers the center of the ship through a number of gates in a particular order using a minimum amount of time. In general, the steering of mobile vehicles depends on the interactions between a vehicle and its supporting medium. Nautical ships present particularly long time delays in response to rudder movements (control actions). Planning for the future encounters with gates should be part of the current control decision, since the ship's position and orientation as it moves through one gate greatly affect the ease of navigation through successive gates. The proposed adaptive critic design-based controller learns to guide the ship through a set of gates autonomously. The simulation results show the performance of the proposed approach.
{"title":"Adaptive critic designs for self-learning ship steering control","authors":"D. Liu, H. Patiño","doi":"10.1109/ISIC.1999.796628","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796628","url":null,"abstract":"Addresses the problem of generating autonomously an optimal control action sequence for ship steering control based on adaptive critic designs. The principal objective is to autonomously design an optimal controller that steers the center of the ship through a number of gates in a particular order using a minimum amount of time. In general, the steering of mobile vehicles depends on the interactions between a vehicle and its supporting medium. Nautical ships present particularly long time delays in response to rudder movements (control actions). Planning for the future encounters with gates should be part of the current control decision, since the ship's position and orientation as it moves through one gate greatly affect the ease of navigation through successive gates. The proposed adaptive critic design-based controller learns to guide the ship through a set of gates autonomously. The simulation results show the performance of the proposed approach.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127323036","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 : 1999-12-01DOI: 10.1109/ISIC.1999.796657
Y. Yam, Hung T. Nguyen, V. Kreinovich
One of the main problems of fuzzy control is that the number of rules which are necessary to represent a given control strategy with a given accuracy, grows exponentially with the increase in accuracy. As a result, for reasonable accuracy and a reasonable number of input variables, a great number of rules is sometimes needed. In this paper, we start to solve this problem by pointing out that traditional one-step fuzzy rule bases, in which expert rules directly express control in terms of the input, are often a simplification of the actual multi-step expert reasoning. We show that a natural formalization of such expert reasoning leads to a universal approximation result in which the number of control rules does not increase with the increase in accuracy. Thus, this multi-resolution approach looks like a promising solution to the rule base explosion problem.
{"title":"Multi-resolution techniques in the rules-based intelligent control systems: a universal approximation result","authors":"Y. Yam, Hung T. Nguyen, V. Kreinovich","doi":"10.1109/ISIC.1999.796657","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796657","url":null,"abstract":"One of the main problems of fuzzy control is that the number of rules which are necessary to represent a given control strategy with a given accuracy, grows exponentially with the increase in accuracy. As a result, for reasonable accuracy and a reasonable number of input variables, a great number of rules is sometimes needed. In this paper, we start to solve this problem by pointing out that traditional one-step fuzzy rule bases, in which expert rules directly express control in terms of the input, are often a simplification of the actual multi-step expert reasoning. We show that a natural formalization of such expert reasoning leads to a universal approximation result in which the number of control rules does not increase with the increase in accuracy. Thus, this multi-resolution approach looks like a promising solution to the rule base explosion problem.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126482233","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 : 1999-12-01DOI: 10.1109/ISIC.1999.796656
R. Osegueda, Y. Mendoza, O. Kosheleva, V. Kreinovich
Thorough testing of a huge aerospace structures results in a large amount of data, and long processing time. To decrease the processing time, we use a "multi-resolution" technique, in which we first separate the data into data corresponding to different vibration modes, and then combine these data together. We show how a general methodology for choosing the optimal uncertainty representation can be used to find the optimal uncertainty representations for this particular problem. Namely, we show that the problem of finding the best approximation to the probability of detection (POD) curve can be solved similarly to the problem of finding the best activation function in neural networks. A similar approach can be used in detecting faults in medical images.
{"title":"Multi-resolution methods in non-destructive testing of aerospace structures and in medicine","authors":"R. Osegueda, Y. Mendoza, O. Kosheleva, V. Kreinovich","doi":"10.1109/ISIC.1999.796656","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796656","url":null,"abstract":"Thorough testing of a huge aerospace structures results in a large amount of data, and long processing time. To decrease the processing time, we use a \"multi-resolution\" technique, in which we first separate the data into data corresponding to different vibration modes, and then combine these data together. We show how a general methodology for choosing the optimal uncertainty representation can be used to find the optimal uncertainty representations for this particular problem. Namely, we show that the problem of finding the best approximation to the probability of detection (POD) curve can be solved similarly to the problem of finding the best activation function in neural networks. A similar approach can be used in detecting faults in medical images.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115498463","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 : 1999-09-15DOI: 10.1109/ISIC.1999.796634
S.-H. Lee, J.-T. Lim
Stability of switched systems with impulse effects is considered. Using the concepts of minimum holding time and redundancy, we establish sufficient conditions for stability, asymptotic stability, and exponential stability in the sense of Lyapunov. The presented results are more practical than the existing stability analyses that introduce multiple Lyapunov functions.
{"title":"Stability analysis of switched systems with impulse effects","authors":"S.-H. Lee, J.-T. Lim","doi":"10.1109/ISIC.1999.796634","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796634","url":null,"abstract":"Stability of switched systems with impulse effects is considered. Using the concepts of minimum holding time and redundancy, we establish sufficient conditions for stability, asymptotic stability, and exponential stability in the sense of Lyapunov. The presented results are more practical than the existing stability analyses that introduce multiple Lyapunov functions.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116304178","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 : 1999-09-15DOI: 10.1109/ISIC.1999.796627
M. Lairi, G. Bloch
The paper is concerned with the determination of a minimal structure of a one hidden layer perceptron for system identification and control. Structural identification is a key issue in neural modeling. Decreasing the size of a neural network is a way to avoid overfitting and bad generalization and leads moreover to simpler models which are required for real time applications, particularly in control. A learning algorithm and a pruning method both based on criteria robust to outliers are presented. Their performances are illustrated on a real example, the inverse model identification of a maglev system, which is nonlinear, dynamical and fast. This inverse model is used in a feedforward neural control scheme. Very satisfactory approximation performances are obtained for a network with very few parameters.
{"title":"A neural network with minimal structure for maglev system modeling and control","authors":"M. Lairi, G. Bloch","doi":"10.1109/ISIC.1999.796627","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796627","url":null,"abstract":"The paper is concerned with the determination of a minimal structure of a one hidden layer perceptron for system identification and control. Structural identification is a key issue in neural modeling. Decreasing the size of a neural network is a way to avoid overfitting and bad generalization and leads moreover to simpler models which are required for real time applications, particularly in control. A learning algorithm and a pruning method both based on criteria robust to outliers are presented. Their performances are illustrated on a real example, the inverse model identification of a maglev system, which is nonlinear, dynamical and fast. This inverse model is used in a feedforward neural control scheme. Very satisfactory approximation performances are obtained for a network with very few parameters.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1999-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120956927","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.1999.796652
M. Polycarpou
The paper presents a robust fault diagnosis scheme for detecting and accommodating faults occurring in a class of nonlinear multi-input multi-output dynamical systems. Changes in the system dynamics due to a fault are modeled as nonlinear functions of the control input and state variables. The fault function can model slowly developing (incipient) or abrupt faults, with each component of the fault vector being represented by a separate time profile. The stability of the robust fault accommodation scheme is established using Lyapunov redesign methods.
{"title":"Fault accommodation of a class of nonlinear dynamical systems using a learning approach","authors":"M. Polycarpou","doi":"10.1109/ISIC.1999.796652","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796652","url":null,"abstract":"The paper presents a robust fault diagnosis scheme for detecting and accommodating faults occurring in a class of nonlinear multi-input multi-output dynamical systems. Changes in the system dynamics due to a fault are modeled as nonlinear functions of the control input and state variables. The fault function can model slowly developing (incipient) or abrupt faults, with each component of the fault vector being represented by a separate time profile. The stability of the robust fault accommodation scheme is established using Lyapunov redesign methods.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"08 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":"124836299","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.1999.796647
C. Ament, G. Goch
To guarantee a constant quality of manufactured products, it is necessary to optimize the process parameters immediately when a failure of the workpiece quality has been observed. Since this relationship of measurement and process parameters is complex and nonlinear in most cases, this feedback loop is closed manually by an experienced operator in general. In the paper the concept of a fuzzy model based quality control is introduced, which allows automated feedback. Based on a process model, the controller is able to interpret the measurement and to adjust the process parameters. To overcome the problem, that a complex process model has to be developed first, a learning approach is presented. As membership functions radial basis functions are used to approximate the control law, and the model parameters are recursively determined by Kalman filtering. The method is applied to control workpiece geometry and surface roughness in a turning process.
{"title":"A learning fuzzy control approach to improve manufacturing quality","authors":"C. Ament, G. Goch","doi":"10.1109/ISIC.1999.796647","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796647","url":null,"abstract":"To guarantee a constant quality of manufactured products, it is necessary to optimize the process parameters immediately when a failure of the workpiece quality has been observed. Since this relationship of measurement and process parameters is complex and nonlinear in most cases, this feedback loop is closed manually by an experienced operator in general. In the paper the concept of a fuzzy model based quality control is introduced, which allows automated feedback. Based on a process model, the controller is able to interpret the measurement and to adjust the process parameters. To overcome the problem, that a complex process model has to be developed first, a learning approach is presented. As membership functions radial basis functions are used to approximate the control law, and the model parameters are recursively determined by Kalman filtering. The method is applied to control workpiece geometry and surface roughness in a turning process.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"20 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":"115071041","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.1999.796639
Hui Liu, Danwei W. Wang
Due to the high nonlinear property, the convergence of neural network based closed-loop system are very difficult to analyze. In the paper, we adopt cerebellar model articulation controller (CMAC) as an iterative learning controller, the convergence of the closed-loop system is analyzed based on the iterative learning control theory. Simulation results verify the analysis.
{"title":"Convergence of CMAC network learning control for a class of nonlinear dynamic system","authors":"Hui Liu, Danwei W. Wang","doi":"10.1109/ISIC.1999.796639","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796639","url":null,"abstract":"Due to the high nonlinear property, the convergence of neural network based closed-loop system are very difficult to analyze. In the paper, we adopt cerebellar model articulation controller (CMAC) as an iterative learning controller, the convergence of the closed-loop system is analyzed based on the iterative learning control theory. Simulation results verify the analysis.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"87 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":"122828819","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.1999.796666
Z. Butler, A. Rizzi, R. Hollis
A variety of mobile robot tasks require complete coverage of an initially unknown environment, either as the entire task or as a way to generate a complete map for use during further missions. This is a problem known as sensor-based coverage, in which the robot's sensing is used to plan a path that reaches every point in the environment. A new algorithm, CC/sub R/, is presented here which works for robots with only contact sensing that operate in environments with rectilinear boundaries and obstacles. This algorithm uses a high-level rule-based feedback structure to direct coverage rather than a script in order to facilitate future extensions to a team of independent robots. The outline of a completeness proof of CC/sub R/ is also presented, which shows that it produces coverage of any of a large class of rectilinear environments. Implementation of CC/sub R/ in simulation is discussed, as well as the results of testing in a variety of world geometries and potential extensions to the algorithm.
{"title":"Contact sensor-based coverage of rectilinear environments","authors":"Z. Butler, A. Rizzi, R. Hollis","doi":"10.1109/ISIC.1999.796666","DOIUrl":"https://doi.org/10.1109/ISIC.1999.796666","url":null,"abstract":"A variety of mobile robot tasks require complete coverage of an initially unknown environment, either as the entire task or as a way to generate a complete map for use during further missions. This is a problem known as sensor-based coverage, in which the robot's sensing is used to plan a path that reaches every point in the environment. A new algorithm, CC/sub R/, is presented here which works for robots with only contact sensing that operate in environments with rectilinear boundaries and obstacles. This algorithm uses a high-level rule-based feedback structure to direct coverage rather than a script in order to facilitate future extensions to a team of independent robots. The outline of a completeness proof of CC/sub R/ is also presented, which shows that it produces coverage of any of a large class of rectilinear environments. Implementation of CC/sub R/ in simulation is discussed, as well as the results of testing in a variety of world geometries and potential extensions to the algorithm.","PeriodicalId":300130,"journal":{"name":"Proceedings of the 1999 IEEE International Symposium on Intelligent Control Intelligent Systems and Semiotics (Cat. No.99CH37014)","volume":"25 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":"128616943","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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