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A design of analog CMOS fuzzy inference circuits using OTAs 基于ota的模拟CMOS模糊推理电路设计
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324192
T. Inoue, K. Tsukano
{"title":"A design of analog CMOS fuzzy inference circuits using OTAs","authors":"T. Inoue, K. Tsukano","doi":"10.1109/IFIS.1993.324192","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324192","url":null,"abstract":"A design of analog CMOS fuzzy operational circuits (a membership function circuit, a maximum circuit, a minimum circuit and a defuzzifier circuit) based on operational transconductance amplifiers (OTAs) is presented. SPICE simulations are given to show their operation speed and accuracy under the assumption that the standard 5 /spl mu/m CMOS design is used. As an application, a 3/spl times/3 singleton fuzzy controller is synthesized using the proposed circuits. The simulation of this controller showed that the operation speed of the order of 1 MFLIPS (fuzzy logical inference per second) is easily realizable.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125389853","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
Aircraft model-following control simulation with a fuzzy optimizer 基于模糊优化器的飞机模型跟踪控制仿真
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324181
S. Swanson
{"title":"Aircraft model-following control simulation with a fuzzy optimizer","authors":"S. Swanson","doi":"10.1109/IFIS.1993.324181","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324181","url":null,"abstract":"A software model of NASA's Shuttle Training Aircraft is used to model-follow a Boeing 747. A classical linear control system is used to perform the model-following. In addition a fuzzy optimizer is created which modifies the gains of a classical control system to enhance performance. The fuzzy optimizer uses the past performance of the control system as input and outputs chances to the gains.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123710868","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
Automatic generation of membership function and fuzzy rule using inductive reasoning 利用归纳推理自动生成隶属函数和模糊规则
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324207
C.J. Kim, B. Russell
{"title":"Automatic generation of membership function and fuzzy rule using inductive reasoning","authors":"C.J. Kim, B. Russell","doi":"10.1109/IFIS.1993.324207","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324207","url":null,"abstract":"This paper discusses the automatic generation of membership function and fuzzy rule. The generation of them are accomplished by utilizing the essential characteristic of the inductive reasoning which derives a general consensus from the particular. The induction is performed by the entropy minimization principle which clusters most optimally the parameters corresponding to the output classes. The rule derivation also provide the average probability of each step of rule, which is no other than the rule weight. The generation scheme is illustrated for practical use.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133945777","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 logic based collision avoidance for a mobile robot 基于模糊逻辑的移动机器人避碰
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1017/S0263574700016866
Angelo Martinez, E. Tunstel, M. Jamshidi
{"title":"Fuzzy logic based collision avoidance for a mobile robot","authors":"Angelo Martinez, E. Tunstel, M. Jamshidi","doi":"10.1017/S0263574700016866","DOIUrl":"https://doi.org/10.1017/S0263574700016866","url":null,"abstract":"Navigation and collision avoidance are major areas of research in mobile robotics that involve varying degrees of uncertainty. In general, the problem consists of achieving sensor based motion control of a mobile robot among obstacles in structured and/or unstructured environments with collision-free motion as the proirity. A fuzzy logic based intelligent control strategy has been developed here to computationally implement the approximate reasoning necessary for handling the uncertainty inherent in the collision avoidance problem.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114153438","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: 59
Analytical structure of a two-input two-output fuzzy controller 一种双输入双输出模糊控制器的解析结构
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324201
H. Ying
{"title":"Analytical structure of a two-input two-output fuzzy controller","authors":"H. Ying","doi":"10.1109/IFIS.1993.324201","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324201","url":null,"abstract":"This study investigates the analytical structure of a two-input two-output fuzzy controller which employs triangular-shaped input fuzzy sets, trapezoidal-shaped output fuzzy sets, linear control rules, probabilistic AND fuzzy logic, Lukasiewcz OR fuzzy logic, Mamdani's minimum inference method and a center of gravity defuzzification algorithm. The structure of the fuzzy controller is proven to be the sum of global 4D multilevel relays and local nonlinear proportional-integral (PI) controllers with variable gains continuously changing with process outputs. The global multilevel relays play a major role in determining control action of the fuzzy controller while the local PI controllers locally fine tune the control action of the relays. As the number of control rules approaches /spl infin/, each global 4D multilevel relay becomes the sum of two global linear PI controllers while the local PI controllers disappear.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123600192","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
Toward an automated design station for fuzzy controller application development 面向模糊控制器应用开发的自动化设计工作站
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324211
T. Janabi, L. Sultan
{"title":"Toward an automated design station for fuzzy controller application development","authors":"T. Janabi, L. Sultan","doi":"10.1109/IFIS.1993.324211","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324211","url":null,"abstract":"This paper outlines the feature of a new development station for automated design of fuzzy controller application. The station supports such functions as automated knowledge base (KB) generation and tuning. The station represents the new generation of tools to support rapid design and development of fuzzy controller application.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129174351","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: 0
A neural-fuzzy system for the protein folding problem 蛋白质折叠问题的神经模糊系统
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324216
W. Daugherity
{"title":"A neural-fuzzy system for the protein folding problem","authors":"W. Daugherity","doi":"10.1109/IFIS.1993.324216","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324216","url":null,"abstract":"While artificial neural networks and fuzzy systems have both been used as universal approximators, the two approaches have different advantages. For example, neural networks are good at classification and learning, while fuzzy systems can perform inference. To take advantage of such complementary strengths, various hybrid neural-fuzzy systems have been devised. The research reported here involves a new combination of neural and fuzzy systems developed for the protein folding problem, that is, how to estimate the number of topological hydrophobic contacts in the (unknown) most stable conformation of a given sequence of monomer residues. Fuzzy meta-rules are used to generate a series of neural networks for longer and longer input monomer sequences.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131726586","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: 0
From min-max robust control to fuzzy logic control 从最小-最大鲁棒控制到模糊逻辑控制
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324199
K. Liu, F. L. Lewis
{"title":"From min-max robust control to fuzzy logic control","authors":"K. Liu, F. L. Lewis","doi":"10.1109/IFIS.1993.324199","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324199","url":null,"abstract":"The robust control of dynamical systems with bounded uncertainties is a challenging topic from either the theoretical or the practical point of view. The classical robust control, especially the so-called min-max control, may cause the whole dynamical system unstable due to its discontinuity. On the other hand, the fuzzy logic control, partially owe its success to the centroid defuzzification technique, makes the control signal always continuous and smooth while maintaining the merit of the min-max robust control. This paper deals with the transformation from min-max control to fuzzy logic control and discusses its implementation.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125940101","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
Design of a two-level fuzzy controller for a reactive miniature mobile robot 响应式微型移动机器人的两级模糊控制器设计
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324183
Marjorie Skubic, S. Graves, J. Mollenhauer
{"title":"Design of a two-level fuzzy controller for a reactive miniature mobile robot","authors":"Marjorie Skubic, S. Graves, J. Mollenhauer","doi":"10.1109/IFIS.1993.324183","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324183","url":null,"abstract":"This paper describes the design and implementation of the fuzzy control system for a small, reactive mobile robot which operates in an unknown, unpredictable, and dynamic environment. A modular, two-level fuzzy controller is used for navigation, obstacle avoidance, and target tracking. The fuzzy controller provides the mechanism for fusing noisy sensor data from multiple sensors which may present conflicting information. Competing behaviors of target tracking and obstacle avoidance are combined in a way that serves both functions, thereby resulting in an emergent intelligent behavior of the robot controller. The efficiency of the two-level fuzzy controller is demonstrated by implementing the system on a small mobile robot with two onboard processors and limited memory (2K per processor).<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133019120","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
Neural and heuristic job allocation planner for AGVs 基于神经网络和启发式的agv作业分配规划
Third International Conference on Industrial Fuzzy Control and Intelligent Systems Pub Date : 1993-12-01 DOI: 10.1109/IFIS.1993.324219
A. J. Bostel, W. Gan, V. Sagar, C. H. See
{"title":"Neural and heuristic job allocation planner for AGVs","authors":"A. J. Bostel, W. Gan, V. Sagar, C. H. See","doi":"10.1109/IFIS.1993.324219","DOIUrl":"https://doi.org/10.1109/IFIS.1993.324219","url":null,"abstract":"Automated guided vehicles (AGVs) are automatic load carriers that transfer objects from one location to another in a factory environment. Due to the increasing complexity of factory floor environments coupled with the need for increased flexibility in AGV systems, it is becoming increasingly important to be able to dynamically alter both the AGV job queue and the AGV path. In this paper, a new method based on an artificial neural network model is presented for evaluating the best job assignment so as to achieve better system efficiency.<<ETX>>","PeriodicalId":408138,"journal":{"name":"Third International Conference on Industrial Fuzzy Control and Intelligent Systems","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1993-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115564176","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
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