基于支持向量机的质量控制软测量建模

在具体研究支持向量机理论的基础上，提出了一种基于支持向量机的软测量控制方法。针对工业过程变量无法在线测量和大滞后的问题，建立了相应的支持向量机回归模型，将此方法用于合成反应器的质量控制中,实现了输出值的在线预估，并分析了参数调整和核函数的选择对建模的影响，得到了泛化良好的模型仿真结果。

Soft-sensor modeling of quality control based on support vector machine

On the basis of studying Support Vector Machine (SVM) theory, a soft-sensor controlling method based on Support Vector Machine wass presented. In order to solve the problem of getting the important parameter that is hard to be measured online and has long time-delay, a soft-sensor controlling method based on support vector machine was presented. In the control process, modeling techniques have been studied intensively, and then RBF kernel function was chosen to establish an exact support vector machine model. On the background of quality control in a company, the online estimate of output value was realized. Under the circumstance of changing and choosing different parameters and through a lot of research and simulation, a relatively better generalization result model was established.