上海交通大学学报(自然版) ›› 2017, Vol. 51 ›› Issue (10): 1252-1259.doi: 10.16183/j.cnki.jsjtu.2017.10.015
孔小兵1,范昌2,刘向杰1
出版日期:
2017-10-31
发布日期:
2017-10-31
基金资助:
KONG Xiaobing1,2,FAN Chang2,LIU Xiangjie1
Online:
2017-10-31
Published:
2017-10-31
Supported by:
摘要: 针对超超临界直流锅炉主汽温控制系统,提出一种基于模糊神经网络模型的分布式监督预测控制(DSPC)策略.在各子系统原有的调节层结构的基础上,增加监督层,将中间点温度和各级过热器出口温度设定值的调整问题转化为在线优化问题.子系统监督层目标函数考虑相关联子系统的性能指标,通过相邻子系统监督层的信息交换和迭代优化,实现各级子系统的协同配合.针对负荷扰动情况进行仿真实验,结果验证了所提出方法的有效性.
中图分类号:
孔小兵1,范昌2,刘向杰1. 超超临界机组主汽温分布式监督预测控制[J]. 上海交通大学学报(自然版), 2017, 51(10): 1252-1259.
KONG Xiaobing1,2,FAN Chang2,LIU Xiangjie1. Distributed Supervisory Predictive Control of
Main Steam Temperature for UltraSupercritical Unit[J]. Journal of Shanghai Jiaotong University, 2017, 51(10): 1252-1259.
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