SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504)最新文献

Genetic identification of dynamical systems with static nonlinearities 静态非线性动力系统的遗传辨识

SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504) Pub Date : 2001-06-27 DOI: 10.1109/SMCIA.2001.936730

M. Dotoli, G. Maione, D. Naso, B. Turchiano

引用次数: 29

Neural network analysis of Doppler-broadened neutron absorption resonance data 多普勒加宽中子吸收共振数据的神经网络分析

SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504) Pub Date : 2001-06-25 DOI: 10.1109/SMCIA.2001.936732

J.R. Thomas, M. Embrechts, R.M. Stringfield, R. M. Wheat

引用次数: 4

Immune network simulation of reactive control of a robot arm manipulator 机器人手臂机械臂无功控制的免疫网络仿真

SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504) Pub Date : 2001-06-25 DOI: 10.1109/SMCIA.2001.936733

Hossam Meshref, H. Vanlandingham

{"title":"Immune network simulation of reactive control of a robot arm manipulator","authors":"Hossam Meshref, H. Vanlandingham","doi":"10.1109/SMCIA.2001.936733","DOIUrl":"https://doi.org/10.1109/SMCIA.2001.936733","url":null,"abstract":"The field of robotics is an important application area for artificial immune systems. We can make use of the immune system properties to control and to identify complex or even unknown systems. Much research has been done in studying the dynamics of the autonomous mobile robot with particular interest in obstacle avoidance and/or trajectory following. Our research is concerned with robot arm manipulator trajectory planning which is based on sensor-based reactive control. In order to control a robot, it must be kinematically analyzed and the result of this analysis entered into the controller of the robot. Kinematics analysis starts with calculating the forward kinematics solution (FKS). The FKS is a prerequisite for obtaining the inverse kinematics solution (IKS) that is entered into the robot controller and forms the basis of the remote control of the robot. While calculating the IKS, there are many possible poses that links of that manipulator can take to reach the designated point in the robot space. An important question, when a manipulator is dealing with a real dynamically changing environment, is what is the best pose that will get to the target point in the shortest time. We use one of the features of the immune system to build a network of manipulator joints that will interact together to reach the desired target point within the shortest time. The use of an artificial immune network simulator in this research is to play the role of prediction for robot behavior in the new environment.","PeriodicalId":104202,"journal":{"name":"SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121678101","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: 9

Organizing an online soft computing conference: a case study 组织一次在线软计算会议:一个案例研究

SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504) Pub Date : 2001-06-25 DOI: 10.1109/SMCIA.2001.936722

J. Martikainen, J. Tanskanen, Xiao-Zhi Gao, S. Ovaska

引用次数: 0

Fast fuzzy neural network for fault diagnosis of rotational machine parts using general parameter learning and adaptation 基于通用参数学习和自适应的快速模糊神经网络用于旋转机械零件故障诊断

SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504) Pub Date : 2001-06-25 DOI: 10.1109/SMCIA.2001.936734

S. Satoh, M. S. Shaikh, Y. Dote

{"title":"Fast fuzzy neural network for fault diagnosis of rotational machine parts using general parameter learning and adaptation","authors":"S. Satoh, M. S. Shaikh, Y. Dote","doi":"10.1109/SMCIA.2001.936734","DOIUrl":"https://doi.org/10.1109/SMCIA.2001.936734","url":null,"abstract":"We compare empirically the performance of nonlinear radial basis function neural networks (RBFN) and time delay neural networks (TDNN) in accuracy and speed for fault detection in rotational machine parts. We use the advantageous general parameter (GP) approach for initializing the weights of the RBFN model in the beginning of the offline system identification phase, as well as for fine-tuning the modeling accuracy of RBFN. The GP-RBFN scheme is adaptive but still computationally efficient due to the single adaptive parameter and its simple learning rule. The fault measure is the moving average of a general parameter. In order to verify the performance of the proposed schemes, they are applied to fault detection of automobile transmission gears. As the acoustic time series is slightly nonlinear, the RBFN gives high-speed fault detection, but detection accuracy is not so high. To overcome this problem a TDNN is developed that achieves more accurate fault detection although it needs more computational time. A fault is detected through regression lines. Both methods are empirically compared in speed and accuracy for fault detection of automobile transmission gears.","PeriodicalId":104202,"journal":{"name":"SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2001-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124229915","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

Modeling evolutionary supervisors for multi-agent manufacturing control with discrete event formalism 基于离散事件形式的多智能体制造控制演化监督模型

SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504) Pub Date : 2001-06-25 DOI: 10.1109/SMCIA.2001.936737

G. Maione, D. Naso

引用次数: 1

Genetic algorithm solution of Vigenere alphabetic codes Vigenere字母编码的遗传算法求解

SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504) Pub Date : 2001-06-25 DOI: 10.1109/SMCIA.2001.936729

C. F. Jones, M. Christman

引用次数: 5

Robust generation mix under uncertain environments in electric power systems 电力系统不确定环境下的鲁棒发电组合

SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504) Pub Date : 2001-06-25 DOI: 10.1109/SMCIA.2001.936725

K. Yasuda, M. Tsunematsu

引用次数: 0

A non-linear tunable PI block for improvement of closed-loop control response 用于改善闭环控制响应的非线性可调PI块

SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504) Pub Date : 2001-06-25 DOI: 10.1109/SMCIA.2001.936738

E. Dummermuth

引用次数: 0

Combining off-line and on-line information in process study using the self-organizing map (SOM) 利用自组织图(SOM)将过程研究中的离线和在线信息相结合

SMCia/01. Proceedings of the 2001 IEEE Mountain Workshop on Soft Computing in Industrial Applications (Cat. No.01EX504) Pub Date : 2001-06-25 DOI: 10.1109/SMCIA.2001.936731

S. Laine

引用次数: 4