多变量PID型神经元网络控制系统及在除氧器水位解耦控制中的仿真研究

The Control System of Multi-variable PID Neural Network and Its Application in Deaerator Water Level Control

介绍了多变量PID型神经元网络控制系统.给出了网络的结构和学习算法,说明了系统参数选取方法,分析了除氧器水位控制的特点.仿真结果表明,该控制系统对多变量强耦合的除氧器水位控制对象具有良好的解耦性能和自学习控制特性.

The control system of multi-variable PID neural network is introduced. Its structure and learning algorithm are given; the methods of its parameter selection are explained ; the characteristics of deaerator water level control system is analyzed. The simulation results prove that the control system has perfect decouple and self-learning control performance for multi-variable strong-coupled time-varying deaerator water level control system.