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

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Fuzzy inputs 模糊输入
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1995-03-20 DOI: 10.1109/FUZZY.1994.343831
R. Palm, Dimiter Driankov
{"title":"Fuzzy inputs","authors":"R. Palm, Dimiter Driankov","doi":"10.1109/FUZZY.1994.343831","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343831","url":null,"abstract":"Deals with fuzzy signals at the input of a fuzzy controller. Commonly, almost all theoretical considerations and practical applications of fuzzy control deal with crisp signals fed to the input of the controller. In order to take into account side-effects arising with the use of sensory information, such as noise or spatial distribution of a signal, it is of interest to show how the control loop behaves in the presence of fuzzy signals. In this paper, some useful operations on fuzzy sets are first described, especially time-varying membership functions and their derivatives. On this basis, sliding mode control and a related fuzzy control strategy are applied to fuzzy signals. In this context, stability and robustness are discussed. Simulation results compare the method of using inputs with the fuzzy input approach.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1995-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114781178","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: 43
A self-tuning fuzzy logic controller for temperature control of superheated steam 一种用于过热蒸汽温度控制的自整定模糊控制器
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343927
Pekka Isomursu, T. Rauma
{"title":"A self-tuning fuzzy logic controller for temperature control of superheated steam","authors":"Pekka Isomursu, T. Rauma","doi":"10.1109/FUZZY.1994.343927","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343927","url":null,"abstract":"We first introduce a non-adaptive fuzzy logic controller (FLC) for the control of live steam temperature in a coal-fired power plant. For further enhancing performance, we introduce a self-tuning method for the FLC that modifies the scaling factor of one FLC output. To make the FLC more portable to other similar plants and more robust we add another self-tuning mechanism that runs online and modifies the membership functions of the fuzzy rule set. We have used the meta-rule approach in the tuning mechanisms. The performance of the FLC is compared to a cascade PI controller.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"37 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":"117276596","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: 32
Parking control based on predictive fuzzy control 基于预测模糊控制的停车控制
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343618
S. Yasunobu, Y. Murai
{"title":"Parking control based on predictive fuzzy control","authors":"S. Yasunobu, Y. Murai","doi":"10.1109/FUZZY.1994.343618","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343618","url":null,"abstract":"The car is operated by the drive knowledge of the driver who knows the dynamic characteristic of the car well. To achieve the control based on this drive knowledge, a car operation system was constructed of fuzzy control scheme that consisted of two hierarchies of state evaluate fuzzy control and predictive fuzzy control. The computer simulation of the parking control was executed by using this system. It was confirmed that the proposal method is effective.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"44 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":"121005430","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: 33
Fuzzy-based grasp-force-adaptation for multifingered robot hands 基于模糊的多指机械手抓取力自适应
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343911
Th. Dorsam, S. Fatikow, I. Streit
{"title":"Fuzzy-based grasp-force-adaptation for multifingered robot hands","authors":"Th. Dorsam, S. Fatikow, I. Streit","doi":"10.1109/FUZZY.1994.343911","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343911","url":null,"abstract":"A fuzzy logic approach for the online grasp-force-adaptation, which can be used for the control of fine manipulating with a multifingered robot hand, will be presented in this paper. The kernel of this approach consists of decision making logic which expresses the a-priory knowledge about the force behaviour inside the friction cones and the necessary reactions, regarding the criterion for grip stability. For the software realisation of the fuzzy control approach a Fuzzy-C Development System supporting the entire development process was used. Two corresponding fuzzy controllers have been designed: A finger controller and a grasp controller. During fine manipulations of an object the fuzzy controller interacts with an underlying conventional controller that receives, after defuzzyfication, the adapted force values which were applied. A computer based simulation system was developed to analyse the capabilities of the designed fuzzy controllers.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"37 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":"121067607","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: 19
Calligraphic robot by fuzzy logic 模糊逻辑书写机器人
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343934
S. Masui, T. Terano
{"title":"Calligraphic robot by fuzzy logic","authors":"S. Masui, T. Terano","doi":"10.1109/FUZZY.1994.343934","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343934","url":null,"abstract":"The robot suggested here is constructed so as to have a basic knowledge of generating Kanji. The most essential features of Kanji are extracted from typical copies and represented as fuzzy rules. This is difficult work. Another problem is to realize writing motion by the robot arm. Calligraphy requires very delicate operation of the writing brush. The results are effected sensitively by the touch, speed and control of the writing brush. But a more important factor of evaluation is the balance or harmony of the whole Kanji. The rules of precise writing motion or the sensuous evaluation are represented by natural language and is only achieved by use of fuzzy logic.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"61 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":"127208240","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
Depth estimation from image defocus using fuzzy logic 基于模糊逻辑的图像离焦深度估计
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343711
C. Swain, A. Peters, K. Kawamura
{"title":"Depth estimation from image defocus using fuzzy logic","authors":"C. Swain, A. Peters, K. Kawamura","doi":"10.1109/FUZZY.1994.343711","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343711","url":null,"abstract":"A method for improving the accuracy of depth-from-defocus is presented. Fuzzy logic is combined with a depth-from-defocus technique to correct for uncertainty and imprecision in depth estimation. Two inputs to the fuzzy algorithm are the focus quality and the focal error. Focus quality is a measure of the amount of defocus in an image. Focal error is the difference in focus between corresponding points in images with different apertures. The output is the depth estimation for objects in images that may be either blurred or in focus. Experiments show that fuzzy logic significantly improves depth estimation compared to the nonfuzzy depth-from-defocus method. The estimation error using fuzzy logic is less than 1.5% over an object distance from 7 to 11 feet. Therefore, this method improves the accuracy of the depth-from-defocus method, while maintaining simplicity. This method was implemented using a standard camera lens and an ANDROX imaging board.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"2013 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":"127381639","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: 10
Consistency checking based on high level fuzzy Petri nets 基于高级模糊Petri网的一致性检验
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343550
H. Scarpelli, F. Gomide
{"title":"Consistency checking based on high level fuzzy Petri nets","authors":"H. Scarpelli, F. Gomide","doi":"10.1109/FUZZY.1994.343550","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343550","url":null,"abstract":"The problem of verifying the integrity of fuzzy knowledge bases is discussed. An approach to find potential inconsistencies in fuzzy rule based systems is described. The approach models the knowledge base as a high level fuzzy Petri net and uses the structural properties of the net for verification. Basic notions on approximate reasoning and high level fuzzy Petri nets are also given. The method used for consistency checking is briefly reviewed. Procedures for discovering potential inconsistencies at both local and global levels are described.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"15 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":"125971733","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: 6
Support logic for feature representation, pattern recognition and machine learning 支持特征表示、模式识别和机器学习的逻辑
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343749
J. Baldwin, R. Gooch, T. Martin
{"title":"Support logic for feature representation, pattern recognition and machine learning","authors":"J. Baldwin, R. Gooch, T. Martin","doi":"10.1109/FUZZY.1994.343749","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343749","url":null,"abstract":"The formalism of support logic provides a framework for deductive inference, with mathematically sound and consistent treatment of uncertainty and evidence which is aggregated through the reasoning process. The authors apply support logic programming to pattern recognition. Initially, a pattern classifier is constructed by encoding expert knowledge of the problem domain into rules of support logic. Fuzzy sets allow the general properties of features to be described precisely. Semantic unification provides an alternative to the usual metric-based similarity criteria. The validity of the approach is established by cross-validating the support logic classifier against models from alternative paradigms. The authors then attempt to circumvent the requirement for a domain expert, and assess the extent to which data-driven learning processes can be used to automatically derive components of the support logic classifier.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"103 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":"123589182","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
Impact of fuzzy normal forms on knowledge representation 模糊范式对知识表示的影响
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343540
I. Turksen
{"title":"Impact of fuzzy normal forms on knowledge representation","authors":"I. Turksen","doi":"10.1109/FUZZY.1994.343540","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343540","url":null,"abstract":"Fuzzy normal forms can be generated with an application of \"Normal Form Generation Algorithm\" on fuzzy truth tables. This takes place at the third level of knowledge representation, i.e., propositional level. It is shown that at least three distinct sets of normal forms can be generated depending on the axioms one is willing to impose on the propositional fuzzy set and logic theories. All are conjunctive-disjunctive and complement based De Morgan logics with the following three classes of axioms that identify each general class of fuzzy normal forms in order of least to most restrictive set of axioms in the following sense: 1) boundary and monotonicity; 2) boundary, monotonicity, associativity and commutativity; and 3) boundary, monotonicity, associativity, commutativity and idempotency.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"90 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":"126859098","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 approach in model-based object recognition 基于模型的物体识别中的模糊方法
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343586
D. Popovic, N. Liang
{"title":"Fuzzy approach in model-based object recognition","authors":"D. Popovic, N. Liang","doi":"10.1109/FUZZY.1994.343586","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343586","url":null,"abstract":"A fuzzy logic approach to pattern recognition is proposed along with the corresponding model-based problem solving algorithm suitable for recognition in intelligent robotics, where a good visual orientation is required for space orientation of a working robot. For simplified pattern recognition the angle-of-sight signature is used to represent the features of the object image. The features, defined in this way, are then used for building a reference model base. In addition, the membership function of the reference modes was defined in order to structure the demarcation rule base. Finally using the model base built and the rule-based algorithm proposed, the stored image of the \"seen\" object is classified as pertaining to the reference one or not. Some simulation results are included.<<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":"115015215","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: 6
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