| 基于支持向量机的激光焊接过程辨识与控制 |
| |
| 引用本文： | 邹伟,刘玉生.基于支持向量机的激光焊接过程辨识与控制[J].计算机仿真,2008,25(12). |
| |
| 作者姓名： | 邹伟 刘玉生 |
| |
| 作者单位： | 四川大学电气信息学院,四川,成都,610065 |
| |
| 基金项目： | 国家自然科学基金国际合作项目
|
| |
| 摘 要： | 激光焊接过程数学模型足一个较强非线性的数学模型,通常的线性辨识方法无法得到它精确的数学模型.支持向量机作为一种新的机器学习方法,具有较强的非线性拟合能力,应用支持向量机非线性系统回归建模方法,辨识出具有典型非线性特性的焊接过程模型,并采用预测控制算法对焊接过程进行控制.实验证明,支持向量机对非线性系统具有很好的拟合效果,基于支持向量机的预测控制具有较好的非线性控制效果.
|
| 关 键 词： | 支持向量机 辨识 预测控制 非线性 拟合 |
Application of Support Vector Machine to Welding Model Identification and Control |
| |
| ZOU Wei,LIU Yu-sheng.Application of Support Vector Machine to Welding Model Identification and Control[J].Computer Simulation,2008,25(12). |
| |
| Authors: | ZOU Wei LIU Yu-sheng |
| |
| Affiliation: | ZOU Wei,LIU Yu-sheng(School of Electrics , Information Technology,Sichuan University,Chengdu Sichuan 610065,China) |
| |
| Abstract: | Mathematical model of Laser Welding Process is a stronger nonlinear mathematical model and the usual identification methods for linear system can't get accurate model. As a new machine learning method, Support vector machine(SVM) has a stronger ability of nonlinear fitting. The paper applies the method of Support Vector Regression (SVR) to nonlinear systems identification and get welding model of representative nonlinear characteristics. which is controlled by using predictive control algorithm. The simulat... |
| |
| Keywords: | Support vector machines(SVM) Identification Predictive control Nonlinear Fitting |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
|
