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Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference最新文献

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Synthesis and analysis of fuzzy logic finite state machine models 模糊逻辑有限状态机模型的综合与分析
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343685
J. Grantner, M. Patyra
{"title":"Synthesis and analysis of fuzzy logic finite state machine models","authors":"J. Grantner, M. Patyra","doi":"10.1109/FUZZY.1994.343685","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343685","url":null,"abstract":"A common drawback of most linguistic models is that they are essentially static, time is not a parameter in describing the behavior of the process model, or they are unable to respond to a specific sequence of changes at the inputs of the system. Dynamic linguistic models can be implemented by fuzzy automata. Of the feasible solutions, at present, fuzzy logic RISC processors and fuzzy logic finite state machines (ASIC) seem to be most promising. The latter approach is taken into consideration. In this paper the model of the fuzzy-state-fuzzy-output (FSFO) finite state machine (FSM) is discussed in detail. The state membership function (SMF) is introduced and the FSFO FSM implementation by means of crisp-state-fuzzy-output (CSFO) FSM using SMF is proposed. The multivariable model and inference scheme are suggested based on CSFO and FSFO FSM.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121210326","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}
引用次数: 35
Goal-driven reasoning for fuzzy knowledge-based systems using a Petri net formalism 基于Petri网的模糊知识系统目标驱动推理
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343522
Alberto Bugarín-Diz, S. Barro
{"title":"Goal-driven reasoning for fuzzy knowledge-based systems using a Petri net formalism","authors":"Alberto Bugarín-Diz, S. Barro","doi":"10.1109/FUZZY.1994.343522","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343522","url":null,"abstract":"In this paper we describe a goal-driven reasoning algorithm over fuzzy knowledge bases. The approach to the problem permits characterizing the chaining between rules without requiring a complete identification between the propositions. The certainty degree of the rules is implemented by means of linguistic truth values and we include different considerations on the goals. A simple and adequate description of the process is achieved through the use of a Petri net formalism for the representation and manipulation of fuzzy knowledge bases.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114367544","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}
引用次数: 4
Real-time control using tactile feedback and fuzzy logic 实时控制采用触觉反馈和模糊逻辑
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343620
B. Hutchings, R. J. Petersen
{"title":"Real-time control using tactile feedback and fuzzy logic","authors":"B. Hutchings, R. J. Petersen","doi":"10.1109/FUZZY.1994.343620","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343620","url":null,"abstract":"Tactile sensors are a class of robotic sensors capable of measuring contact interaction between a robotic gripper and a grasped object. Tactile sensors are an important source of dynamic information for real-time gripper control during manipulation tasks. To be effective, this dynamic information must be used as part of a real-time control scheme because many of the conditions indicated by the tactile sensor require immediate attention (typically in milliseconds or less). One important application of dynamic tactile data is the tracking of objects in real time. This paper discusses a tracking system that was implemented to prove the feasibility of using a tactile sensor and fuzzy logic to track objects in real time. The system as implemented used a tactile sensor, an X-Y table, a personal computer and custom fuzzy-logic software. It successfully tracked objects at speeds in excess of 1 ms/sup -1/.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116317369","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}
引用次数: 3
Reliability structure functions based upon fuzzy numbers 基于模糊数的可靠性结构函数
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343525
V. Cutello, J. Montero
{"title":"Reliability structure functions based upon fuzzy numbers","authors":"V. Cutello, J. Montero","doi":"10.1109/FUZZY.1994.343525","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343525","url":null,"abstract":"The main aim of this paper is to establish a basis for reliability structure functions where the space of states for the system and its components is assumed to be a family of fuzzy numbers. A particular non-probabilistic uncertainty can be modeled in this way, generalizing classical crisp binary and multistate models in reliability theory. The importance of an underlying order relation defined on the given family of fuzzy numbers is also stressed.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125602411","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}
引用次数: 1
Fuzzy sliding mode control of nonlinear system 非线性系统的模糊滑模控制
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343938
Chen-Sheng Ting, T.-H.S. Li, Fan-Chu Kung
{"title":"Fuzzy sliding mode control of nonlinear system","authors":"Chen-Sheng Ting, T.-H.S. Li, Fan-Chu Kung","doi":"10.1109/FUZZY.1994.343938","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343938","url":null,"abstract":"The unmodeled dynamics of a nonlinear control system is studied by using a fuzzy control approach. Based on variable structure system (VSS) theory, this paper presents two fuzzy control schemes. As the upper bound of system uncertainty is known, it can be used as a clue to form fuzzy control logic. The full inference provides an estimation for the unknown upper bound. Examples are given to illustrate the application of the proposed methods.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121746041","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}
引用次数: 12
Fuzzy logic and behavior control strategy for autonomous mobile robot mapping 自主移动机器人映射的模糊逻辑和行为控制策略
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343732
E. Tunstel, M. Jamshidi
{"title":"Fuzzy logic and behavior control strategy for autonomous mobile robot mapping","authors":"E. Tunstel, M. Jamshidi","doi":"10.1109/FUZZY.1994.343732","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343732","url":null,"abstract":"In support of research efforts to develop reactive mobile robots capable of autonomous navigation, we are concentrating on providing human reasoning capabilities as a resource for intelligence and integrating the world mapping and navigation tasks. The underlying philosophy is that an autonomous mobile robot should be able to make a map of its environment as it navigates through that environment. Fuzzy logic control and behavior-based navigation are proposed as means to implement this philosophy. Fuzzy logic provides the approximate reasoning necessary for handling the uncertainty inherent in mobile robot navigation. By decomposing the problem into simpler tasks we can develop mobile robots that exhibit a sufficient level of intelligence for performing navigation and mapping. In this paper, we discuss a strategy for incorporating fuzzy reasoning into the framework of reactive behavior control systems for autonomous mapping.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115940083","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}
引用次数: 28
Importance of membership functions: a comparative study on different learning methods for fuzzy inference systems 隶属函数的重要性:模糊推理系统不同学习方法的比较研究
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343588
Ahmad Lotfi, A. Tsoi
{"title":"Importance of membership functions: a comparative study on different learning methods for fuzzy inference systems","authors":"Ahmad Lotfi, A. Tsoi","doi":"10.1109/FUZZY.1994.343588","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343588","url":null,"abstract":"This paper investigates different adaptive structures for fuzzy inference systems. We examine the effect of membership functions on reasoning process when the number of rules is fixed. Three commonly used membership function shapes have been employed in this study. It has been shown that membership functions have the dominant effect on reasoning process rather than number of rules or inference mechanism. We compare our adaptive membership function scheme with two already proposed by others.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115896830","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}
引用次数: 27
A comparison of PID and fuzzy control of a model car 模型车PID控制与模糊控制的比较
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343846
J. Pereira, J. Bowles
{"title":"A comparison of PID and fuzzy control of a model car","authors":"J. Pereira, J. Bowles","doi":"10.1109/FUZZY.1994.343846","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343846","url":null,"abstract":"This paper demonstrates the usefulness of fuzzy logic in control system applications over conventional methods with the help of an experimental model. It makes comparisons between conventional proportional, integrative plus derivative (PID) controllers and other control techniques with the aid of an intelligent drive system for a model car. It also demonstrates the ease in switching from a conventional system to its fuzzy counterpart and shows why fuzzy logic has revolutionized the way control systems are implemented.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115974208","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}
引用次数: 11
Fuzzy control with fuzzy inputs: the need for new rule semantics 带有模糊输入的模糊控制:需要新的规则语义
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343717
D. Driankov, Rainer Palm, H. Hellendoorn
{"title":"Fuzzy control with fuzzy inputs: the need for new rule semantics","authors":"D. Driankov, Rainer Palm, H. Hellendoorn","doi":"10.1109/FUZZY.1994.343717","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343717","url":null,"abstract":"The standard computation taking place in a fuzzy logic controller proceeds from crisp inputs and via the consecutive steps of fuzzification, inference, and defuzzification computes a crisp control output. However, this computational practice simplifies to an extent the actual developments taking place in the closed loop. In reality, the knowledge about the current values of the controller input is very often available via sensory measurements. In this case, one has to take into account the negative side effects that come up with the use of sensors, in particular the presence of noisy measurements. In the paper the authors consider one particular way of dealing with noisy controller inputs, namely transforming the noise-distribution into a fuzzy set and then feeding back the so obtained fuzzy signal to the controller input. Adopting this approach requires that the shape of the input fuzzy signal should be reflected as much as possible in the output fuzzy signal so that important noise characteristics are preserved. In the paper the authors describe the requirements on the shape of the fuzzy output signal given a certain fuzzy input signal and show that the existing semantics for fuzzy IF-THEN rules do not satisfy these requirements. The authors propose new semantics for such rules which together with max-min composition produces the desired results.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132394616","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}
引用次数: 16
Alternative membership function for sequential fuzzy clustering 序列模糊聚类的备选隶属函数
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343578
J. Sum, L. Chan
{"title":"Alternative membership function for sequential fuzzy clustering","authors":"J. Sum, L. Chan","doi":"10.1109/FUZZY.1994.343578","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343578","url":null,"abstract":"This paper presents an alternative membership function for fuzzy c-mean. According to this membership function and Bezdek's definition, we derive two sequential algorithms for fuzzy c-mean. Both of them are stochastic gradient descent algorithms which minimize Bezdek's objective functional. Analytical result indicates that both algorithms are actually compatible with each other. The convergence properties of both algorithms are studied. As the update equations are so simple, these sequential algorithms are embedded into neural network to form a class of fuzzy neural network analogue to unsupervised type neural network such that competitive learning is a special case.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132397732","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}
引用次数: 5
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