首页 | 本学科首页   官方微博 | 高级检索  
     

石灰窑温度智能控制系统设计
引用本文:汪发亮,吴彩林. 石灰窑温度智能控制系统设计[J]. 工矿自动化, 2012, 38(6): 80-83
作者姓名:汪发亮  吴彩林
作者单位:马鞍山职业技术学院自动化系,安徽马鞍山,243000
基金项目:2011年安徽省高等学校省级质量工程项目
摘    要:提出了一种石灰窑燃烧室温度智能控制系统的设计方案。该系统以下燃烧室温度为控制目标,以煤气流量为调节对象,通过模糊神经网络动态调整煤气流量设定值,采用粒子群优化算法对模糊神经网络的参数进行寻优,并采用最小二乘支持向量机逆控制系统对煤气流量进行跟踪控制,实现了对石灰窑下燃烧室温度的精确控制。仿真结果表明,该系统响应速度快,稳定性好,具有很好的抗干扰性和鲁棒性。

关 键 词:石灰窑  燃烧室  温度控制  模糊神经网络  粒子群优化算法  最小二乘支持向量机  逆控制

Design of Intelligent Temperature Control System of Limekiln
WANG Fa-liang , WU Cai-lin. Design of Intelligent Temperature Control System of Limekiln[J]. Industry and Automation, 2012, 38(6): 80-83
Authors:WANG Fa-liang    WU Cai-lin
Affiliation:(Automation Department of Maanshan Technical College,Maanshan 243000,China)
Abstract:The paper proposed a design scheme of intelligent temperature control system of combustion chamber of limekiln.The system takes temperature of lower combustion chamber as control objective and gas flow as adjusting object,uses fuzzy neural network to dynamically adjust setting value of gas flow,uses particle swarm optimization algorithm to achieve optimization of parameters of the fuzzy neural network,and uses inverse control system of the least squares support vector machine to track and control gas flow,and it achieves precise control of temperature of the combustion chamber of limekiln.The simulation result showed that the system has fast response,good stability,strong anti-interference ability and robustness.
Keywords:limekiln  combustion chamber  temperature control  fuzzy neural network  particle swarm optimization algorithm  least squares support vector machine  inverse control
本文献已被 CNKI 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号