分层递阶控制系统体系结构的Hopfield网络模型

Hopfield Neural Network Model for Hierarchic Control Architecture

在分析了分散控制、分布式控制和分层递阶控制系统体系结构的基础上，提出了分层递阶控制系统体系结构的Hopfield网络模型，指出这一模型可以用常规的DCS系统和现场总线控制系统来实现，并能实现其混合形式。通过比较发现这两种控制系统各有优缺点，DCS适用于大型递阶控制系统，而FCS适用于小型递阶控制系统，当FCS用于大型递阶控制系统时，必须采用物理上的递阶结构形式。

After analyzing the decentralized control and distributed control and hierarchic control system architecture, the Hopfield neural network model for hierarchic control architecture is proposed. It is pointed out that the model can be implemented with the normal DCS and field bus control system(FCS). And the composed structure of the decentralized control and distributed control and hierarchic control can also be implemented with them. Comparing the DCS with the FCS, the DCS is feasible for large scale control system, and the FCS is feasible for smaller hierarchic control system. When the FCS is employed to a large scale system, the hierarchic structure in physic must be used to build the system.