2009 IEEE International Conference on Fuzzy Systems最新文献

Design and simulation of a hybrid controller for a multi-input multi-output magnetic suspension system 多输入多输出磁悬浮系统混合控制器的设计与仿真

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2015-01-06 DOI: 10.1109/FUZZY.2009.5277404

S. Abuelenin

{"title":"Design and simulation of a hybrid controller for a multi-input multi-output magnetic suspension system","authors":"S. Abuelenin","doi":"10.1109/FUZZY.2009.5277404","DOIUrl":"https://doi.org/10.1109/FUZZY.2009.5277404","url":null,"abstract":"In this paper we present a Fuzzy Logic control approach designed to stabilize a multi-input multi-output magnetic suspension system. The system has four cubic floaters and four actuators that apply magnetic forces on the floaters, the suspension is performed by changing the voltages applied on the actuators, hence changing their currents, producing vertical magnetic forces that balance with the gravitational force. A fuzzy logic controller is used to control each actuator; the system is nonlinear and sensitive to initial conditions. Another fuzzy logic controller is used as a supervisory controller in order to increase the dynamic range of the system, enabling it to stabilize the floaters when the initial displacements are relatively big. Another design consideration was to keep the four floaters in the same plane as much as possible, to perform that task, a PD controller was set to modulate the currents of the four actuators in order to minimize an error signal measuring the relative vertical displacement of all the four floaters. Simulation results show that the designed control scheme stabilized the system for the design constrains.","PeriodicalId":117895,"journal":{"name":"2009 IEEE International Conference on Fuzzy Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2015-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130874482","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

A novel multi-level quantization scheme for discrete particle swarm optimization 一种新的离散粒子群优化多级量化方案

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277306

Hwachang Song, Ryan B. Diolata, Y. Joo

引用次数: 3

A novel cluster validity criterion for fuzzy C-regression models 一种新的模糊c回归模型聚类效度准则

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277386

C. Kung, J. Su, Yi-Fen Nieh

引用次数: 7

Linguistic rulesets extracted from a quantifier-based fuzzy classification system 基于量词模糊分类系统的语言规则集提取

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277081

K. Rasmani, J. Garibaldi, Qiang Shen, Ian O. Ellis

引用次数: 1

An improved flush material belt weigh feeder system via fuzzy logic controller and adaptive neural networks 采用模糊逻辑控制器和自适应神经网络设计了一种改进的冲料带式称重给料系统

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277428

Tsung-Ying Sun, Ming-Chin Yang, Shang-Jeng Tsai, Jyun-Sian He

{"title":"An improved flush material belt weigh feeder system via fuzzy logic controller and adaptive neural networks","authors":"Tsung-Ying Sun, Ming-Chin Yang, Shang-Jeng Tsai, Jyun-Sian He","doi":"10.1109/FUZZY.2009.5277428","DOIUrl":"https://doi.org/10.1109/FUZZY.2009.5277428","url":null,"abstract":"The Flush Material Belt Weigh Feeder (FMBWF) has used in many material handling plants. The stability and the performance of the layer control system will affect the quality of the production. In general, the behavior of the flush material on the BWF is non-linear, time-lag, and disturbance character. The layer of the flush material on the belt is hard to be stably controlled especially the occurrence of unstable situation in flush material or the prefeeder feeding rate and the variation of the set point value of the FMBWF. This paper focuses on the performance improvement of the FMBWF via adopted a fuzzy controller under the situation of the Flow Rate Set Value (FRSV) variation. The proposed fuzzy controller is utilized instead of the original feed forward compensation function to deal with the problems of the temporary unstable situation. This paper offers the simulation result comparison of the set point value variations between the BWF for the original and the proposed control system. The simulation results are distinct better than the original control system. The influence of the variations of the set point value can be successfully evaluated by the Fuzzy controller and adjusted the Proportional Actuator immediately. Finally the proposed control system remains convergence with smooth and stable. Therefore, the accuracy, stability and the performance of the control system are improved.","PeriodicalId":117895,"journal":{"name":"2009 IEEE International Conference on Fuzzy Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115027501","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

Hybrid SVM-GPs learning for modeling of molecular autoregulatory feedback loop systems with outliers 带有异常值的分子自调节反馈回路系统建模的混合SVM-GPs学习

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277426

Jin-Tsong Jeng, Chen-Chia Chuang, Sheng-Lun Jheng

引用次数: 0

Relaxed stabilization conditions of T-S fuzzy systems using piecewise lyapunov function based switching fuzzy controller 基于分段李雅普诺夫函数的切换模糊控制器的T-S模糊系统松弛镇定条件

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277097

Ying-Jen Chen, H. Ohtake, Kazuo Tanaka, Wen-June Wang, Hua O. Wang

引用次数: 3

The geometric interval type-2 fuzzy logic approach in robotic mobile issue 机器人移动问题的几何区间2型模糊逻辑方法

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277307

N. Baklouti, A. Alimi

引用次数: 21

Networked control systems design via fuzzy logic method 基于模糊逻辑方法的网络化控制系统设计

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277101

Song-Shyong Chen

引用次数: 2

Triplet of FCM classifiers FCM分类器的三元组

2009 IEEE International Conference on Fuzzy Systems Pub Date : 2009-10-02 DOI: 10.1109/FUZZY.2009.5277336

H. Ichihashi, A. Notsu, Katsuhiro Honda

{"title":"Triplet of FCM classifiers","authors":"H. Ichihashi, A. Notsu, Katsuhiro Honda","doi":"10.1109/FUZZY.2009.5277336","DOIUrl":"https://doi.org/10.1109/FUZZY.2009.5277336","url":null,"abstract":"This paper proposes an additional version of the fuzzy c-means based classifier (FCMC). The classifier FCMC-R treats relational data instead of object data. FCMCs use covariance structures to represent flexible shapes of clusters. Despite its effectiveness, the intense computation of covariance matrices is an impediment for classifying a set of high-dimensional feature data. In order to tackle with this problem, we proposed a way of directly handling high-dimensional data, i.e., FCMC-H. The third type of the FCM classifier is the relational classifier FCMC-R, which is derived from FCMC-H. The relational data represented by a relational matrix are based on dissimilarities or distances between object data. The triplets, i.e., FCMC, FCMC-H, and FCMC-R are equivalent when the dimensionality of feature vectors is not very high and the dissimilarity is represented by Euclidean distances. The randomized test set performance of FCMC on the sets of object data from UCI repository is comparable to that of the support vector machine (SVM) classifier. The performances of the triplet in terms of 100 times three way data splits (3-WDS) procedure are compared. The triplet surpasses the k-nearest neighbor (k-NN) classifier, which is a well established and very popular relational classifier.","PeriodicalId":117895,"journal":{"name":"2009 IEEE International Conference on Fuzzy Systems","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114828305","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