2010 Chinese Control and Decision Conference最新文献_第6页

Exponential stability of BAM type Cohen-Grossberg neural networks with delays on time scales 具有时滞的BAM型Cohen-Grossberg神经网络的指数稳定性

2010 Chinese Control and Decision Conference Pub Date : 2010-05-26 DOI: 10.1109/CCDC.2010.5498803

Chaolong Zhang, Qiru Wang, Fengjian Yang, Jianfu Yang

引用次数: 0

Adaptive calibration algorithm of three axial magnetic fluxgate sensor using support vector regression 基于支持向量回归的三轴磁通门传感器自适应标定算法

2010 Chinese Control and Decision Conference Pub Date : 2010-05-26 DOI: 10.1109/CCDC.2010.5498387

Jun Shi

引用次数: 6

Tribological properties prediction of brake lining for automobiles based on BP neural network 基于BP神经网络的汽车刹车片摩擦学性能预测

2010 Chinese Control and Decision Conference Pub Date : 2010-05-26 DOI: 10.1109/CCDC.2010.5498739

Yan Yin, Jiusheng Bao, Lei Yang

{"title":"Tribological properties prediction of brake lining for automobiles based on BP neural network","authors":"Yan Yin, Jiusheng Bao, Lei Yang","doi":"10.1109/CCDC.2010.5498739","DOIUrl":"https://doi.org/10.1109/CCDC.2010.5498739","url":null,"abstract":"By many tribological experiments of brake lining for automobiles, the original experimental data were firstly obtained, which contains the influencing rules of braking conditions on tribological performance. Based on the artificial neural network technology and the experimental data specimens, the BP neural network model was established to predict the tribological properties. Three parameters of braking conditions (braking pressure, sliding velocity and surface temperature) were selected as input vectors, and two parameters of tribological performance (friction coefficient and wear rate) were selected as output vectors. By contrast of prediction values and experimental results, it is found that the neural network can predict properly the influencing rules of braking conditions on tribological performance. What is more, the neural network has quite favorable ability for predicting of friction coefficient. While it has bad ability for predicting of wear rate, especially when the pressure, velocity and temperature are high. As a whole, this paper has proved that it is feasible and valuable to use neural network for predicting tribological properties of friction materials.","PeriodicalId":227938,"journal":{"name":"2010 Chinese Control and Decision Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116471294","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

Exponential stabilizability for a class of the singular distributed parameter control systems 一类奇异分布参数控制系统的指数稳定性

2010 Chinese Control and Decision Conference Pub Date : 2010-05-26 DOI: 10.1109/CCDC.2010.5498928

Shaojie Li, Jiangshu Wang

引用次数: 10

Consensus of second-order multi-agent systems under communication delay 通信延迟下二阶多智能体系统的一致性

2010 Chinese Control and Decision Conference Pub Date : 2010-05-26 DOI: 10.1109/CCDC.2010.5498912

Chenglin Liu, Fei Liu

引用次数: 3

Extending LaSalle's invariance principle to impulsive switched systems with an application to hybrid epidemic dynamics 将LaSalle不变性原理推广到脉冲切换系统并在混合流行病动力学中的应用

2010 Chinese Control and Decision Conference Pub Date : 2010-05-26 DOI: 10.1109/CCDC.2010.5499107

Jun Liu, Xinzhi Liu, W. Xie

引用次数: 5

Parameter optimization for turbine DEH control system based on Improved Genetic Algorithm 基于改进遗传算法的汽轮机DEH控制系统参数优化

2010 Chinese Control and Decision Conference Pub Date : 2010-05-26 DOI: 10.1109/CCDC.2010.5498598

Na Li, Lixia Lv

引用次数: 7

Non-fragile control for a class of uncertain time-delay switched fuzzy systems 一类不确定时滞切换模糊系统的非脆弱控制

2010 Chinese Control and Decision Conference Pub Date : 2010-05-26 DOI: 10.1109/CCDC.2010.5498199

Yingying Ye, Hong Yang, Le Zhang

引用次数: 1

New sliding mode control of building structure using RBF neural networks 基于RBF神经网络的建筑结构滑模控制新方法

2010 Chinese Control and Decision Conference Pub Date : 2010-05-26 DOI: 10.1109/CCDC.2010.5498707

Zhijun Li, Z. Deng, Zhiping Gu

{"title":"New sliding mode control of building structure using RBF neural networks","authors":"Zhijun Li, Z. Deng, Zhiping Gu","doi":"10.1109/CCDC.2010.5498707","DOIUrl":"https://doi.org/10.1109/CCDC.2010.5498707","url":null,"abstract":"The undue chattering effect is the major disadvantage of conventional sliding mode controllers. In this study, based on the advantage of RBF neural network control method, a new adaptive sliding mode control method, which is one of the active control algorithms, has been applied for seismically-excited building structures. The undue chattering effect, the major disadvantage of conventional sliding mode controller, has been avoided by introducing the new control method. First, we build the motion equation and design the switching surfaces. Next, based on the RBF neural network control algorithm, we adjust the control gain parameter and then design the neurocontroller. For numerical applications, a three-storey shear building model subjected to ground excitations has been considered. The ground accelerations recorded in two different earthquake events have been used to evaluate the effectiveness of the control algorithm for varied disturbances. The simulation results show preliminarily that our new adaptive sliding mode control method is quite effective: not only can it reduce the peak-response of the ground motion, but also it can keep the chattering effect sufficiently low.","PeriodicalId":227938,"journal":{"name":"2010 Chinese Control and Decision Conference","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124137834","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

Robust fault detection dynamic observer design for LTI systems LTI系统鲁棒故障检测动态观测器设计

2010 Chinese Control and Decision Conference Pub Date : 2010-05-26 DOI: 10.1109/CCDC.2010.5498164

Xiukun Wei, L. Lihua, Guo-qiang Cai, Yong Qin, L. Jia

引用次数: 6