摘要
从工业过程实际应用要求出发,研究开发了基于模糊逻辑系统的小脑模型关节控制器神经网络算法。仿真研究表明,该算法提高了传统小脑模型关节控制器的平滑能力和泛化能力,可以很好地应用于工业过程的软测量中。经现场的长期应用实施,证实了该热值软测量系统具有较高的准确性,充分显示了燃料气系统热值变化的特征,对裂解炉炉管出口温度的稳定控制起到了极大作用。
A new neural algorithm based on fuzzy Cerebella Model Articulation Controller (CMAC) is researched for the application of industry process. By the computer simulation, it is proved that the generalization and smoothing ability of CMAC can be improved compared with the traditional CMAC. Based on the algorithm, the enthalpy soft sensing system is built, which has high veracity confirmed by long time applications in industry plant. The system can demonstrate the change of cracking fuel gas enthalpy adequately, and take effect in the control system of average coils output temperature of cracking furnaces.
基金
国家自然科学基金资助项目(60074027)
上海市教育发展基金会曙光计划项目(2000SG18)
国家863/CIMS主题资助项目(2001AA411230)。~~
