基于通用学习网络的预估控制

利用通用学习网络具有所有节点互连，任意两节点之间可以有多重连接，且连接允许有任意延迟时间的特点，对典型非线性、大滞后系统进行了辨识．结合PID控制器对pH中和过程实现了高精度的预估控制．通过与传统的Smith预估控制的比较，证明该网络能有效地应用于大滞后系统，利用该网络进行系统辨识是对未知对象模型控制的一种有效新方法．

Predictive Control Based on the Universal Learning Network

A universal learning network (ULN), of which the nodes are connected with one another and there are multiple branches with arbitrary time delays between any two nodes, is used to identify the typical nonlinear and long time delay system. Integrating ULN with a PID controller, this paper achieves an exact predictive control for pH neutralization process. Compared with the traditional Smith predictive control method, the ULN can be effectively used in nonlinear and long time delay systems and it is a new and effective method for controlling unknown object models.