摘要
本文根据火电单元机组负荷控制系统被控对象的具体特点及神经元的学习功能，分别设计了以锅炉跟随为基础和以汽机跟随为基础的两种基于自适应神经元模型的负荷控制系统。仿真计算表明，控制系统中的学习参数均能很快地收敛到平衡值，且两种控制系统均具有良好的控制品质。
Utilizing the learning ability of adaptive neural model and according to the features of the controlled plant, this paper successfully designs two load control systems for a thermal power unit, which are based on boiler following and turbine following modes respectively. The results of simulations show that the control parameters can quickly converge to their equilibrium values, and both load control systems of thermal power unit have good control performance.
出处
《中国电机工程学报》
EI
CSCD
北大核心
1995年第1期1-7,共7页
Proceedings of the CSEE
基金
国家自然科学基金
关键词
火电单元机组
负荷控制系统
神经元模型
thermal power unit load control system neural model self-learning
