基于径基函数神经网络的精馏塔自适应控制

Adaptive Control of Distillation Columns Based on RBF Neural Networks

中文关键词  精馏塔  非线性  RBF神经网络  逆动态模型  自适应控制  RLS算法

英文关键词  distillation column  nonlinear  RBF nural networks  inverse dynamic model  adaptive control  RLS algorithm

中文摘要

      精馏塔是化工过程中最常用，最重要的操作单元，其本质的非线性及时变性使得对它的控制非常困难。本文提出了一种基于径基函数（RBF）网络的自适应控制方案。该方案简捷、可靠，具有很强的鲁棒性和抗干扰性能。将该方案应用在工业脱乙烷塔的控制中得到了令人满意的结果。

英文摘要

      Disillation columns are the most usual and important operating units in the process of chemical engineering. They are non-linear and time-varying, and these characteristics make the design of the control scheme very difficult. This paper proposed an adaptive control strategy based on radial basis function (RBF) neural network. The control scheme is simple, relizble and possesses strong robustness and disturbance rejection. Fairly good control results were obtained when the control scheme was applied to a distillation column.