固定床反应器基于RBF网络的推断控制

<正>一些研究者基于简化机理模型,讨论了固定床反应器的推断控制。然而,工业过程中有许多固定床反应器的机理模型尚难以建立,而且由于固定床反应器特性的复杂性,模型简化和状态估计器的设计等具有较大的困难。因此,基于“黑箱”模型研究固定床反应器的推断控制可能是一条十分有效的途径。Budman等人提出用部分最小二乘法(PLS)以改进回归模型的性能。他们对实验室固定床反应器,假设沿反应器轴向的十点温度可以测量,并据此建立回归模型,然而由于固定床反应器具有严重非线性和时变等特性,用PLS法建立估计器仍有局限性。另外,实际的固定床反应器可能只有少数几个温度可以测量。因此其面向应用的推断控制策略的研究有十分重要的意义。

INFERENTIAL CONTROL OF A FIXED BED REACTOR USING RBF NETWORK

In this paper, a new inlereiitial control strategy based on RBF network for a non adiabalie tubular fixed -bed reactor is presented. An on-line self learning inferential estimator based on RHF network is developed, and then a predictive control system with output of the estim nor as feedback variable is designed. It is shown via simulation, where a phthalic anhydride reactor is taken as a research plant, thai the estimator has the performance of on line self - learning ability and good accuracy. Moreover, the performance of the control system is satisfactory.