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

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The formulation of a simple fuzzy model tuning predictive controller for MIMO systems MIMO系统的简单模糊模型整定预测控制器的建立
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343664
T. Yamazaki
{"title":"The formulation of a simple fuzzy model tuning predictive controller for MIMO systems","authors":"T. Yamazaki","doi":"10.1109/FUZZY.1994.343664","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343664","url":null,"abstract":"The author (1993) studied a model rule form that describes the cause-effect relation between past control actions and process responses, in which the control actions are defined by three fuzzy variables, long past, medium past and short past actions, in order to formulate a simple fuzzy model tuning predictive controller (FMTPC) for SISO systems. In this paper, the formulation of a simple FMTPC for MIMO systems is investigated by applying the same representation of control actions as for SISO systems, the rule form of partial pairings of input and output relation, and fuzzy linear functions for the calculation of model output. The model representation proposed is in analogy with the way human operators perceive their past control actions and resulting process responses linguistically. Due to these treatments, the whole process of controller design has been simplified considerably without sacrificing controller performance, and consequently a controller applicable for practical uses has been realized.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"9 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":"130264193","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
Custom design of a hardware fuzzy logic controller 自定义设计一个硬件模糊逻辑控制器
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343560
D. Hung
{"title":"Custom design of a hardware fuzzy logic controller","authors":"D. Hung","doi":"10.1109/FUZZY.1994.343560","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343560","url":null,"abstract":"The paper describes a custom designed hardware fuzzy logic controller (FLC) for high speed real-time control applications. With a pipelined parallel architecture, the FLC can operate at very high speeds. The FLC can also gain the ability of online adaptation by connecting itself to a supervisory microprocessor so that its performance can be constantly monitored and its knowledge base can be updated at run time. A two inputs, one output prototype of the PLC has been implemented with a Xilinx XC4008-6 FPGA and a separate EPROM. With the FLC's control unit operating at a clock speed of 20 MHz, the FLC can produce 9 million control actions per second.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"34 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":"133963223","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: 14
Design of adaptive fuzzy sliding mode for nonlinear system control 非线性系统自适应模糊滑模控制设计
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343693
Sinn-Cheng Lin, Yung-Yaw Chen
{"title":"Design of adaptive fuzzy sliding mode for nonlinear system control","authors":"Sinn-Cheng Lin, Yung-Yaw Chen","doi":"10.1109/FUZZY.1994.343693","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343693","url":null,"abstract":"An adaptive fuzzy sliding mode controller (AFSMC) is proposed. The parameters of the membership functions in the fuzzy rule base are changed according to some adaptive algorithm for the purpose of controlling the system state to hit a user-defined sliding surface and then slide along it. The initial IF-THEN rules in the AFSMC can be randomly selected or roughly given by human experts, and then automatically tuned by a direct adaptive law. Therefore, the reduction of the expertise dependency in the design procedure of fuzzy logic control is called the rule tolerance property. By applying the AFSMC to control a nonlinear unstable inverted pendulum system, the simulation results showed the expected approximation sliding property, and the dynamic behavior of control system can be determined by the sliding surface.<<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":"131498598","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: 63
Definition and formulation of backward-reasoning with fuzzy if... then... rules 模糊后向推理的定义与表述然后……规则
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343849
T. Arnould, S. Tano
{"title":"Definition and formulation of backward-reasoning with fuzzy if... then... rules","authors":"T. Arnould, S. Tano","doi":"10.1109/FUZZY.1994.343849","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343849","url":null,"abstract":"The importance and efficiency of backward-reasoning in classical reasoning has been stressed a long time ago, especially in the case of expert systems and decision support systems. However, its extension to fuzzy reasoning has never been considered. In this paper, the authors propose a definition and formulation of backward-reasoning with fuzzy \"if... then...\" rules based on the generalized modus ponens and show how this reasoning scheme can practically be applied in various situations.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"152 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":"127577080","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
A fuzzy-based approach to numeric constraint networks 一种基于模糊的数值约束网络方法
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343572
K. Kim, P. Cho
{"title":"A fuzzy-based approach to numeric constraint networks","authors":"K. Kim, P. Cho","doi":"10.1109/FUZZY.1994.343572","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343572","url":null,"abstract":"Current numeric constraint propagation systems accepting exact numeric values or intervals have a limitation on representing the preference among values. To represent and handle the preference on the values, the notion of fuzzy numeric constraint networks is introduced. After defining the notion of fuzzy consistency, we show that fuzzy consistency can be represented by an extension of interval consistency. Using this relation, we propose a propagation algorithm for solving fuzzy numeric constraint networks.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"9 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":"127637030","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
Learn to produce fuzzy control rules with UCL 学习用UCL生成模糊控制规则
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343623
Lin Xiaozhong, Liu Zemin
{"title":"Learn to produce fuzzy control rules with UCL","authors":"Lin Xiaozhong, Liu Zemin","doi":"10.1109/FUZZY.1994.343623","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343623","url":null,"abstract":"Bart Kosko (1990) has proposed a method to produce fuzzy control rules using unsupervised competitive learning (UCL). But experiments show that some problems are waiting for further study. This paper discusses two of those problems. (1) How to partition the universe of discourse of the fuzzy variables in the rules. (2) How to determine the rules according to the clustering results. This paper presents two new methods to solve these two problems. Their effectiveness was proved by the simulation results from an inverted pendulum system.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"1 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":"131094824","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: 2
A variable-structure fuzzy logic controller with run-time adaptation 一种具有运行时适应性的变结构模糊控制器
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343869
S.M. Smith
{"title":"A variable-structure fuzzy logic controller with run-time adaptation","authors":"S.M. Smith","doi":"10.1109/FUZZY.1994.343869","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343869","url":null,"abstract":"The design of a variable structure fuzzy logic controller for minimum-time set-point control is presented. The controller architecture is extended to accommodate runtime adaptation. This innovative approach combines the quick response of bang-bang like control with the stable convergence properties of more conservative linear control to produce a robust high performance controller. The controller is based on a Takagi-Sugeno-Kang format but the controller is warped during each step response to change its structure. The warping is done through scaling of the controller inputs and outputs. An online scheme for finding the best values for the scaling is presented.<<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":"133399206","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: 7
Membership function-based fuzzy model and its applications to multivariable nonlinear model-predictive control 基于隶属函数的模糊模型及其在多变量非线性模型预测控制中的应用
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343932
Renhong Zhao, Rakesh Govind
{"title":"Membership function-based fuzzy model and its applications to multivariable nonlinear model-predictive control","authors":"Renhong Zhao, Rakesh Govind","doi":"10.1109/FUZZY.1994.343932","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343932","url":null,"abstract":"The nonlinear processes in direct digital control systems can be modeled by the membership function-based fuzzy models proposed in this paper. The two-dimensional membership functions used by this paper are identified by using limited process response data. Instead of using membership functions to represent the belonging to a set this paper uses the membership functions to represent the gradual deviation from the known states. The membership function-based fuzzy models are effective nonlinear models which can be used for multivariable nonlinear predictive control in which the process interaction is used to enhance the control action rather than being decoupled like in linear control.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"51 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":"115881734","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
A tuning method for fuzzy inference with fuzzy input and fuzzy output 一种具有模糊输入和模糊输出的模糊推理调谐方法
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343852
T. Oyama, S. Tano, T. Arnould
{"title":"A tuning method for fuzzy inference with fuzzy input and fuzzy output","authors":"T. Oyama, S. Tano, T. Arnould","doi":"10.1109/FUZZY.1994.343852","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343852","url":null,"abstract":"Most studies on tuning of fuzzy inference are concerned with numerical inputs and outputs only, and very few research has been done on tuning of fuzzy inference with fuzzy inputs and outputs. Moreover, in many cases the object of tuning are fuzzy predicates only, apart from the other factors intervening in fuzzy inference. In this paper the authors propose a method to tune the fuzzy inference when inputs and outputs are given as fuzzy sets. This method is similar to backpropagation and tunes the parameters of aggregation operators, implication functions and combination functions as well as the fuzzy predicates which appear in the nodes of the network representing the calculation process of the fuzzy inference. Some results of tuning simulation are also shown.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"25 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":"124552452","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 logic for vehicle climate control 汽车气候控制的模糊逻辑
Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference Pub Date : 1994-06-26 DOI: 10.1109/FUZZY.1994.343729
Leighton Ira Davis, T. Sieja, R. W. Matteson, G. A. Dage, R. Ames
{"title":"Fuzzy logic for vehicle climate control","authors":"Leighton Ira Davis, T. Sieja, R. W. Matteson, G. A. Dage, R. Ames","doi":"10.1109/FUZZY.1994.343729","DOIUrl":"https://doi.org/10.1109/FUZZY.1994.343729","url":null,"abstract":"Typical automobile automatic climate control systems use linear proportional control to maintain a comfortable interior environment. In the process of refining these systems, we have found two significant limitations of linear proportional control when viewed from the standpoint of an occupant's subjective comfort: 1) there are certain control situations in any HVAC (Heating, Ventilation, and Air Conditioning) system that are inherently nonlinear; and 2) it is not possible to realize occupant comfort merely by maintaining proximity to a desired temperature. In this paper, we describe a fuzzy logic control system which addresses these limitations by including rules that provide nonlinear compensation, and by allowing the control to be expressed in the same heuristic terms that an occupant would use in describing the level of comfort.<<ETX>>","PeriodicalId":153967,"journal":{"name":"Proceedings of 1994 IEEE 3rd International Fuzzy Systems Conference","volume":"30 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":"114788995","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: 25
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